1
|
Capalbo A, de Wert G, Mertes H, Klausner L, Coonen E, Spinella F, Van de Velde H, Viville S, Sermon K, Vermeulen N, Lencz T, Carmi S. Screening embryos for polygenic disease risk: a review of epidemiological, clinical, and ethical considerations. Hum Reprod Update 2024; 30:529-557. [PMID: 38805697 PMCID: PMC11369226 DOI: 10.1093/humupd/dmae012] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/10/2024] [Revised: 03/25/2024] [Indexed: 05/30/2024] Open
Abstract
BACKGROUND The genetic composition of embryos generated by in vitro fertilization (IVF) can be examined with preimplantation genetic testing (PGT). Until recently, PGT was limited to detecting single-gene, high-risk pathogenic variants, large structural variants, and aneuploidy. Recent advances have made genome-wide genotyping of IVF embryos feasible and affordable, raising the possibility of screening embryos for their risk of polygenic diseases such as breast cancer, hypertension, diabetes, or schizophrenia. Despite a heated debate around this new technology, called polygenic embryo screening (PES; also PGT-P), it is already available to IVF patients in some countries. Several articles have studied epidemiological, clinical, and ethical perspectives on PES; however, a comprehensive, principled review of this emerging field is missing. OBJECTIVE AND RATIONALE This review has four main goals. First, given the interdisciplinary nature of PES studies, we aim to provide a self-contained educational background about PES to reproductive specialists interested in the subject. Second, we provide a comprehensive and critical review of arguments for and against the introduction of PES, crystallizing and prioritizing the key issues. We also cover the attitudes of IVF patients, clinicians, and the public towards PES. Third, we distinguish between possible future groups of PES patients, highlighting the benefits and harms pertaining to each group. Finally, our review, which is supported by ESHRE, is intended to aid healthcare professionals and policymakers in decision-making regarding whether to introduce PES in the clinic, and if so, how, and to whom. SEARCH METHODS We searched for PubMed-indexed articles published between 1/1/2003 and 1/3/2024 using the terms 'polygenic embryo screening', 'polygenic preimplantation', and 'PGT-P'. We limited the review to primary research papers in English whose main focus was PES for medical conditions. We also included papers that did not appear in the search but were deemed relevant. OUTCOMES The main theoretical benefit of PES is a reduction in lifetime polygenic disease risk for children born after screening. The magnitude of the risk reduction has been predicted based on statistical modelling, simulations, and sibling pair analyses. Results based on all methods suggest that under the best-case scenario, large relative risk reductions are possible for one or more diseases. However, as these models abstract several practical limitations, the realized benefits may be smaller, particularly due to a limited number of embryos and unclear future accuracy of the risk estimates. PES may negatively impact patients and their future children, as well as society. The main personal harms are an unindicated IVF treatment, a possible reduction in IVF success rates, and patient confusion, incomplete counselling, and choice overload. The main possible societal harms include discarded embryos, an increasing demand for 'designer babies', overemphasis of the genetic determinants of disease, unequal access, and lower utility in people of non-European ancestries. Benefits and harms will vary across the main potential patient groups, comprising patients already requiring IVF, fertile people with a history of a severe polygenic disease, and fertile healthy people. In the United States, the attitudes of IVF patients and the public towards PES seem positive, while healthcare professionals are cautious, sceptical about clinical utility, and concerned about patient counselling. WIDER IMPLICATIONS The theoretical potential of PES to reduce risk across multiple polygenic diseases requires further research into its benefits and harms. Given the large number of practical limitations and possible harms, particularly unnecessary IVF treatments and discarded viable embryos, PES should be offered only within a research context before further clarity is achieved regarding its balance of benefits and harms. The gap in attitudes between healthcare professionals and the public needs to be narrowed by expanding public and patient education and providing resources for informative and unbiased genetic counselling.
Collapse
Affiliation(s)
- Antonio Capalbo
- Juno Genetics, Department of Reproductive Genetics, Rome, Italy
- Center for Advanced Studies and Technology (CAST), Department of Medical Genetics, “G. d’Annunzio” University of Chieti-Pescara, Chieti, Italy
| | - Guido de Wert
- Department of Health, Ethics & Society, CAPHRI-School for Public Health and Primary Care and GROW School for Oncology and Reproduction, Maastricht University, Maastricht, The Netherlands
| | - Heidi Mertes
- Department of Philosophy and Moral Sciences, Ghent University, Ghent, Belgium
- Department of Public Health and Primary Care, Ghent University, Ghent, Belgium
| | - Liraz Klausner
- Braun School of Public Health and Community Medicine, The Hebrew University of Jerusalem, Jerusalem, Israel
| | - Edith Coonen
- Departments of Clinical Genetics and Reproductive Medicine, Maastricht University Medical Centre, Maastricht, The Netherlands
- School for Oncology and Developmental Biology, GROW, Maastricht University, Maastricht, The Netherlands
| | - Francesca Spinella
- Eurofins GENOMA Group Srl, Molecular Genetics Laboratories, Department of Scientific Communication, Rome, Italy
| | - Hilde Van de Velde
- Research Group Genetics Reproduction and Development (GRAD), Vrije Universiteit Brussel, Brussel, Belgium
- Brussels IVF, UZ Brussel, Brussel, Belgium
| | - Stephane Viville
- Laboratoire de Génétique Médicale LGM, Institut de Génétique Médicale d’Alsace IGMA, INSERM UMR 1112, Université de Strasbourg, France
- Laboratoire de Diagnostic Génétique, Unité de Génétique de l’infertilité (UF3472), Hôpitaux Universitaires de Strasbourg, Strasbourg, France
| | - Karen Sermon
- Research Group Genetics Reproduction and Development (GRAD), Vrije Universiteit Brussel, Brussel, Belgium
| | | | - Todd Lencz
- Institute of Behavioral Science, Feinstein Institutes for Medical Research, Manhasset, NY, USA
- Departments of Psychiatry and Molecular Medicine, Zucker School of Medicine at Hofstra/Northwell, Hempstead, NY 11549, USA
| | - Shai Carmi
- Braun School of Public Health and Community Medicine, The Hebrew University of Jerusalem, Jerusalem, Israel
| |
Collapse
|
2
|
Hoffmann TJ, Graff RE, Madduri RK, Rodriguez AA, Cario CL, Feng K, Jiang Y, Wang A, Klein RJ, Pierce BL, Eggener S, Tong L, Blot W, Long J, Goss LB, Darst BF, Rebbeck T, Lachance J, Andrews C, Adebiyi AO, Adusei B, Aisuodionoe-Shadrach OI, Fernandez PW, Jalloh M, Janivara R, Chen WC, Mensah JE, Agalliu I, Berndt SI, Shelley JP, Schaffer K, Machiela MJ, Freedman ND, Huang WY, Li SA, Goodman PJ, Till C, Thompson I, Lilja H, Ranatunga DK, Presti J, Van Den Eeden SK, Chanock SJ, Mosley JD, Conti DV, Haiman CA, Justice AC, Kachuri L, Witte JS. Genome-wide association study of prostate-specific antigen levels in 392,522 men identifies new loci and improves cross-ancestry prediction. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2024:2023.10.27.23297676. [PMID: 37961155 PMCID: PMC10635224 DOI: 10.1101/2023.10.27.23297676] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/15/2023]
Abstract
We conducted a multi-ancestry genome-wide association study of prostate-specific antigen (PSA) levels in 296,754 men (211,342 European ancestry; 58,236 African ancestry; 23,546 Hispanic/Latino; 3,630 Asian ancestry; 96.5% of participants were from the Million Veteran Program). We identified 318 independent genome-wide significant (p≤5e-8) variants, 184 of which were novel. Most demonstrated evidence of replication in an independent cohort (n=95,768). Meta-analyzing discovery and replication (n=392,522) identified 447 variants, of which a further 111 were novel. Out-of-sample variance in PSA explained by our genome-wide polygenic risk scores ranged from 11.6%-16.6% in European ancestry, 5.5%-9.5% in African ancestry, 13.5%-18.2% in Hispanic/Latino, and 8.6%-15.3% in Asian ancestry, and decreased with increasing age. Mid-life genetically-adjusted PSA levels were more strongly associated with overall and aggressive prostate cancer than unadjusted PSA. Our study highlights how including proportionally more participants from underrepresented populations improves genetic prediction of PSA levels, offering potential to personalize prostate cancer screening.
Collapse
|
3
|
Sun YV, Liu C, Hui Q, Zhou JJ, Gaziano JM, Wilson PWF, Joseph J, Phillips LS. Identification and correction for collider bias in a genome-wide association study of diabetes-related heart failure. Am J Hum Genet 2024; 111:1481-1493. [PMID: 38897203 PMCID: PMC11267521 DOI: 10.1016/j.ajhg.2024.05.018] [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: 09/14/2023] [Revised: 05/20/2024] [Accepted: 05/21/2024] [Indexed: 06/21/2024] Open
Abstract
Type 2 diabetes (T2D) is a major risk factor for heart failure (HF) and has elevated incidence among individuals with HF. Since genetics and HF can independently influence T2D, collider bias may occur when T2D (i.e., collider) is controlled for by design or analysis. Thus, we conducted a genome-wide association study (GWAS) of diabetes-related HF with correction for collider bias. We first performed a GWAS of HF to identify genetic instrumental variables (GIVs) for HF and to enable bidirectional Mendelian randomization (MR) analysis between T2D and HF. We identified 61 genomic loci, significantly associated with all-cause HF in 114,275 individuals with HF and over 1.5 million controls of European ancestry. Using a two-sample bidirectional MR approach with 59 and 82 GIVs for HF and T2D, respectively, we estimated that T2D increased HF risk (odds ratio [OR] 1.07, 95% confidence interval [CI] 1.04-1.10), while HF also increased T2D risk (OR 1.60, 95% CI 1.36-1.88). Then we performed a GWAS of diabetes-related HF corrected for collider bias due to the study design of index cases. After removing the spurious association of TCF7L2 locus due to collider bias, we identified two genome-wide significant loci close to PITX2 (chromosome 4) and CDKN2B-AS1 (chromosome 9) associated with diabetes-related HF in the Million Veteran Program and replicated the associations in the UK Biobank. Our MR findings provide strong evidence that HF increases T2D risk. As a result, collider bias leads to spurious genetic associations of diabetes-related HF, which can be effectively corrected to identify true positive loci.
Collapse
Affiliation(s)
- Yan V Sun
- Atlanta VA Healthcare System, Decatur, GA, USA; Department of Epidemiology, Emory University Rollins School of Public Health, Atlanta, GA, USA.
| | - Chang Liu
- Department of Epidemiology, Emory University Rollins School of Public Health, Atlanta, GA, USA
| | - Qin Hui
- Atlanta VA Healthcare System, Decatur, GA, USA; Department of Epidemiology, Emory University Rollins School of Public Health, Atlanta, GA, USA
| | - Jin J Zhou
- Department of Medicine, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA; Department of Biostatistics, Fielding School of Public Health, University of California, Los Angeles, Los Angeles, CA, USA
| | - J Michael Gaziano
- Massachusetts Veterans Epidemiology Research and Information Center (MAVERIC), VA Boston Healthcare System, Boston, MA, USA; Division of Aging, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Peter W F Wilson
- Atlanta VA Healthcare System, Decatur, GA, USA; Emory University School of Medicine, Atlanta, GA, USA
| | - Jacob Joseph
- VA Providence Healthcare System, Providence, RI, USA; The Warren Alpert Medical School of Brown University, Providence, RI, USA
| | - Lawrence S Phillips
- Atlanta VA Healthcare System, Decatur, GA, USA; Emory University School of Medicine, Atlanta, GA, USA
| |
Collapse
|
4
|
van Rossen TM, van Beurden YH, Bogaards JA, Budding AE, Mulder CJJ, Vandenbroucke-Grauls CMJE. Fecal microbiota composition is a better predictor of recurrent Clostridioides difficile infection than clinical factors in a prospective, multicentre cohort study. BMC Infect Dis 2024; 24:687. [PMID: 38987677 PMCID: PMC11238444 DOI: 10.1186/s12879-024-09506-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/14/2023] [Accepted: 06/13/2024] [Indexed: 07/12/2024] Open
Abstract
INTRODUCTION Clostridioides difficile infection (CDI) is the most common cause of antibiotic-associated diarrhoea. Fidaxomicin and fecal microbiota transplantation (FMT) are effective, but expensive therapies to treat recurrent CDI (reCDI). Our objective was to develop a prediction model for reCDI based on the gut microbiota composition and clinical characteristics, to identify patients who could benefit from early treatment with fidaxomicin or FMT. METHODS Multicentre, prospective, observational study in adult patients diagnosed with a primary episode of CDI. Fecal samples and clinical data were collected prior to, and after 5 days of CDI treatment. Follow-up duration was 8 weeks. Microbiota composition was analysed by IS-pro, a bacterial profiling technique based on phylum- and species-specific differences in the 16-23 S interspace regions of ribosomal DNA. Bayesian additive regression trees (BART) and adaptive group-regularized logistic ridge regression (AGRR) were used to construct prediction models for reCDI. RESULTS 209 patients were included, of which 25% developed reCDI. Variables related to microbiota composition provided better prediction of reCDI and were preferentially selected over clinical factors in joint prediction models. Bacteroidetes abundance and diversity after start of CDI treatment, and the increase in Proteobacteria diversity relative to baseline, were the most robust predictors of reCDI. The sensitivity and specificity of a BART model including these factors were 95% and 78%, but these dropped to 67% and 62% in out-of-sample prediction. CONCLUSION Early microbiota response to CDI treatment is a better predictor of reCDI than clinical prognostic factors, but not yet sufficient enough to predict reCDI in daily practice.
Collapse
Affiliation(s)
- Tessel M van Rossen
- Department of Medical Microbiology & Infection Control, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands.
- Amsterdam Institute for Infection and Immunity, Amsterdam, The Netherlands.
- Department of Gastroenterology & Hepatology, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands.
- Amsterdam Gastroenterology Endocrinology Metabolism Institute, Amsterdam, The Netherlands.
| | - Yvette H van Beurden
- Department of Gastroenterology & Hepatology, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | - Johannes A Bogaards
- Amsterdam Institute for Infection and Immunity, Amsterdam, The Netherlands
- Department of Epidemiology and Data Science, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
- Amsterdam Public Health, Amsterdam, The Netherlands
| | | | - Chris J J Mulder
- Department of Gastroenterology & Hepatology, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
- Amsterdam Gastroenterology Endocrinology Metabolism Institute, Amsterdam, The Netherlands
| | - Christina M J E Vandenbroucke-Grauls
- Department of Medical Microbiology & Infection Control, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
- Amsterdam Institute for Infection and Immunity, Amsterdam, The Netherlands
- Department of Clinical Epidemiology, Aarhus University, Aarhus, Denmark
| |
Collapse
|
5
|
Liley J, Newnham M, Bleda M, Bunclark K, Auger W, Barbera JA, Bogaard H, Delcroix M, Fernandes TM, Howard L, Jenkins D, Lang I, Mayer E, Rhodes C, Simpson M, Southgate L, Trembath R, Wharton J, Wilkins MR, Gräf S, Morrell N, Zaba JP, Toshner M. Shared and Distinct Genomics of Chronic Thromboembolic Pulmonary Hypertension and Pulmonary Embolism. Am J Respir Crit Care Med 2024; 209:1477-1485. [PMID: 38470220 PMCID: PMC11208965 DOI: 10.1164/rccm.202307-1236oc] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/20/2023] [Accepted: 03/11/2024] [Indexed: 03/13/2024] Open
Abstract
Rationale: Chronic thromboembolic pulmonary hypertension involves the formation and nonresolution of thrombus, dysregulated inflammation, angiogenesis, and the development of a small-vessel vasculopathy. Objectives: We aimed to establish the genetic basis of chronic thromboembolic pulmonary hypertension to gain insight into its pathophysiological contributors. Methods: We conducted a genome-wide association study on 1,907 European cases and 10,363 European control subjects. We coanalyzed our results with existing results from genome-wide association studies on deep vein thrombosis, pulmonary embolism, and idiopathic pulmonary arterial hypertension. Measurements and Main Results: Our primary association study revealed genetic associations at the ABO, FGG, F11, MYH7B, and HLA-DRA loci. Through our coanalysis, we demonstrate further associations with chronic thromboembolic pulmonary hypertension at the F2, TSPAN15, SLC44A2, and F5 loci but find no statistically significant associations shared with idiopathic pulmonary arterial hypertension. Conclusions: Chronic thromboembolic pulmonary hypertension is a partially heritable polygenic disease, with related though distinct genetic associations with pulmonary embolism and deep vein thrombosis.
Collapse
Affiliation(s)
| | - Michael Newnham
- Institute of Applied Health Research, Birmingham, United Kingdom
| | - Marta Bleda
- Department of Medicine, University of Cambridge, Cambridge, United Kingdom
| | | | - William Auger
- University of California, San Diego, San Diego, California
| | - Joan Albert Barbera
- Hospital Clinic, Institut d’Investigacions Biomèdiques August Pi i Sunyer, Centro de Investigación Biomédica en Red Enfermedades Respiratorias, University of Barcelona, Barcelona, Spain
| | - Harm Bogaard
- Amsterdam University Medical Center, Amsterdam, the Netherlands
| | | | | | - Luke Howard
- Hammersmith Hospital, London, United Kingdom
| | | | - Irene Lang
- Vienna General Hospital, Medical University of Vienna, Vienna, Austria
| | | | | | | | | | | | - John Wharton
- St. George’s, University of London, London, United Kingdom
| | | | - Stefan Gräf
- Department of Medicine, University of Cambridge, Cambridge, United Kingdom
| | - Nicholas Morrell
- Department of Medicine, University of Cambridge, Cambridge, United Kingdom
| | | | - Mark Toshner
- Department of Medicine, University of Cambridge, Cambridge, United Kingdom
| |
Collapse
|
6
|
Chen JX, Li Y, Zhang YB, Wang Y, Zhou YF, Geng T, Liu G, Pan A, Liao YF. Nonlinear relationship between high-density lipoprotein cholesterol and cardiovascular disease: an observational and Mendelian randomization analysis. Metabolism 2024; 154:155817. [PMID: 38364900 DOI: 10.1016/j.metabol.2024.155817] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/24/2023] [Revised: 01/29/2024] [Accepted: 02/13/2024] [Indexed: 02/18/2024]
Abstract
BACKGROUND Clinical trials and Mendelian randomization (MR) studies reported null effects of high-density lipoprotein cholesterol (HDL-C) on risk of cardiovascular disease (CVD), which might have overlooked a nonlinear causal association. We aimed to investigate the dose-response relationship between circulating HDL-C concentrations and CVD in observational and MR frameworks. METHODS We included 348,636 participants (52,919 CVD cases and 295,717 non-cases) of European ancestry with genetic data from the UK Biobank (UKB) and acquired genome-wide association summary data for HDL-C of Europeans from the Global Lipids Genetics Consortium (GLGC). Observational analyses were conducted in the UKB. Stratified MR analyses were conducted combing genetic data for CVD from UKB and lipids from GLGC. RESULTS Observational analyses showed L-shaped associations of HDL-C with CVD, with no further risk reduction when HDL-C levels exceeded 70 mg/dL. Multivariable MR analyses across entire distribution of HDL-C found no association of HDL-C with CVD, after control of the pleiotropic effect on other lipids and unmeasured pleiotropism. However, in stratified MR analyses, significant inverse associations of HDL-C with CVD were observed in the stratum of participants with HDL-C ≤ 50 mg/dL (odds ratio per unit increase, 0.86; 95 % confidence interval, 0.79-0.94), while null associations were observed in any stratum above 50 mg/dL. CONCLUSIONS Our data suggest a potentially causal inverse association of HDL-C at low levels with CVD risks. These findings advance our knowledge about the role of HDL as a potential target in CVD prevention and therapy.
Collapse
Affiliation(s)
- Jun-Xiang Chen
- Department of Epidemiology and Biostatistics, Ministry of Education Key Laboratory of Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Yue Li
- Department of Epidemiology and Biostatistics, Ministry of Education Key Laboratory of Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Yan-Bo Zhang
- Department of Epidemiology and Population Health, Albert Einstein College of Medicine, Bronx, NY, USA
| | - Yi Wang
- Department of Epidemiology and Population Health, Albert Einstein College of Medicine, Bronx, NY, USA
| | - Yan-Feng Zhou
- Department of Social Medicine and Health Management, School of Public Health, Guangxi Medical University, Nanning, China; Key Laboratory of Emergency and Trauma of Ministry of Education, Hainan Medical University, Haikou, China
| | - Tingting Geng
- Department of Epidemiology and Biostatistics, Ministry of Education Key Laboratory of Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China; Department of Nutrition and Food Hygiene, School of Public Health, Institute of Nutrition, Fudan University, Shanghai, China
| | - Gang Liu
- Department of Nutrition and Food Hygiene, Hubei Key Laboratory of Food Nutrition and Safety, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
| | - An Pan
- Department of Epidemiology and Biostatistics, Ministry of Education Key Laboratory of Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
| | - Yun-Fei Liao
- Department of Endocrinology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
| |
Collapse
|
7
|
Sargurupremraj M, Soumaré A, Bis JC, Surakka I, Jürgenson T, Joly P, Knol MJ, Wang R, Yang Q, Satizabal CL, Gudjonsson A, Mishra A, Bouteloup V, Phuah CL, van Duijn CM, Cruchaga C, Dufouil C, Chêne G, Lopez OL, Psaty BM, Tzourio C, Amouyel P, Adams HH, Jacqmin-Gadda H, Ikram MA, Gudnason V, Milani L, Winsvold BS, Hveem K, Matthews PM, Longstreth WT, Seshadri S, Launer LJ, Debette S. Genetic Complexities of Cerebral Small Vessel Disease, Blood Pressure, and Dementia. JAMA Netw Open 2024; 7:e2412824. [PMID: 38776079 PMCID: PMC11112447 DOI: 10.1001/jamanetworkopen.2024.12824] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/05/2023] [Accepted: 03/21/2024] [Indexed: 05/25/2024] Open
Abstract
Importance Vascular disease is a treatable contributor to dementia risk, but the role of specific markers remains unclear, making prevention strategies uncertain. Objective To investigate the causal association between white matter hyperintensity (WMH) burden, clinical stroke, blood pressure (BP), and dementia risk, while accounting for potential epidemiologic biases. Design, Setting, and Participants This study first examined the association of genetically determined WMH burden, stroke, and BP levels with Alzheimer disease (AD) in a 2-sample mendelian randomization (2SMR) framework. Second, using population-based studies (1979-2018) with prospective dementia surveillance, the genetic association of WMH, stroke, and BP with incident all-cause dementia was examined. Data analysis was performed from July 26, 2020, through July 24, 2022. Exposures Genetically determined WMH burden and BP levels, as well as genetic liability to stroke derived from genome-wide association studies (GWASs) in European ancestry populations. Main Outcomes and Measures The association of genetic instruments for WMH, stroke, and BP with dementia was studied using GWASs of AD (defined clinically and additionally meta-analyzed including both clinically diagnosed AD and AD defined based on parental history [AD-meta]) for 2SMR and incident all-cause dementia for longitudinal analyses. Results In 2SMR (summary statistics-based) analyses using AD GWASs with up to 75 024 AD cases (mean [SD] age at AD onset, 75.5 [4.4] years; 56.9% women), larger WMH burden showed evidence for a causal association with increased risk of AD (odds ratio [OR], 1.43; 95% CI, 1.10-1.86; P = .007, per unit increase in WMH risk alleles) and AD-meta (OR, 1.19; 95% CI, 1.06-1.34; P = .008), after accounting for pulse pressure for the former. Blood pressure traits showed evidence for a protective association with AD, with evidence for confounding by shared genetic instruments. In the longitudinal (individual-level data) analyses involving 10 699 incident all-cause dementia cases (mean [SD] age at dementia diagnosis, 74.4 [9.1] years; 55.4% women), no significant association was observed between larger WMH burden and incident all-cause dementia (hazard ratio [HR], 1.02; 95% CI, 1.00-1.04; P = .07). Although all exposures were associated with mortality, with the strongest association observed for systolic BP (HR, 1.04; 95% CI, 1.03-1.06; P = 1.9 × 10-14), there was no evidence for selective survival bias during follow-up using illness-death models. In secondary analyses using polygenic scores, the association of genetic liability to stroke, but not genetically determined WMH, with dementia outcomes was attenuated after adjusting for interim stroke. Conclusions These findings suggest that WMH is a primary vascular factor associated with dementia risk, emphasizing its significance in preventive strategies for dementia. Future studies are warranted to examine whether this finding can be generalized to non-European populations.
Collapse
Affiliation(s)
- Muralidharan Sargurupremraj
- Bordeaux Population Health Research Center, University of Bordeaux, Inserm, UMR 1219, Bordeaux, France
- Glenn Biggs Institute for Alzheimer’s & Neurodegenerative Diseases, University of Texas Health Sciences Center, San Antonio
| | - Aicha Soumaré
- Bordeaux Population Health Research Center, University of Bordeaux, Inserm, UMR 1219, Bordeaux, France
| | - Joshua C. Bis
- Cardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle
| | - Ida Surakka
- Department of Internal Medicine, University of Michigan, Ann Arbor
| | - Tuuli Jürgenson
- Estonian Genome Centre, Institute of Genomics, University of Tartu, Tartu, Estonia
| | - Pierre Joly
- Bordeaux Population Health Research Center, University of Bordeaux, Inserm, UMR 1219, Bordeaux, France
| | - Maria J. Knol
- Department of Epidemiology, Erasmus MC University Medical Center, Rotterdam, the Netherlands
| | - Ruiqi Wang
- School of Public Health, Boston University and the National Heart, Lung, and Blood Institute Framingham Heart Study, Boston, Massachusetts
- Department of Neurology, Boston University School of Medicine, Boston, Massachusetts
| | - Qiong Yang
- School of Public Health, Boston University and the National Heart, Lung, and Blood Institute Framingham Heart Study, Boston, Massachusetts
- Department of Neurology, Boston University School of Medicine, Boston, Massachusetts
| | - Claudia L. Satizabal
- Glenn Biggs Institute for Alzheimer’s & Neurodegenerative Diseases, University of Texas Health Sciences Center, San Antonio
- School of Public Health, Boston University and the National Heart, Lung, and Blood Institute Framingham Heart Study, Boston, Massachusetts
- Department of Neurology, Boston University School of Medicine, Boston, Massachusetts
| | | | - Aniket Mishra
- Bordeaux Population Health Research Center, University of Bordeaux, Inserm, UMR 1219, Bordeaux, France
| | - Vincent Bouteloup
- Bordeaux Population Health Research Center, University of Bordeaux, Inserm, UMR 1219, Bordeaux, France
| | - Chia-Ling Phuah
- Department of Neurology, Washington University School of Medicine & Barnes-Jewish Hospital, St Louis, Missouri
- NeuroGenomics and Informatics Center, Washington University in St Louis, St Louis, Missouri
| | - Cornelia M. van Duijn
- Nuffield Department of Population Health, University of Oxford, Oxford, United Kingdom
| | - Carlos Cruchaga
- NeuroGenomics and Informatics Center, Washington University in St Louis, St Louis, Missouri
- Department of Psychiatry, Washington University School of Medicine, St Louis, Missouri
- Charles F. and Joanne Knight Alzheimer Disease Research Center, Washington University School of Medicine, St Louis, Missouri
| | - Carole Dufouil
- Bordeaux Population Health Research Center, University of Bordeaux, Inserm, UMR 1219, Bordeaux, France
| | - Geneviève Chêne
- Bordeaux Population Health Research Center, University of Bordeaux, Inserm, UMR 1219, Bordeaux, France
- Department of Public Health, CHU de Bordeaux, Bordeaux, France
| | - Oscar L. Lopez
- Department of Neurology, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania
- Department of Psychiatry, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania
| | - Bruce M. Psaty
- Cardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle
- Department of Epidemiology, University of Washington, Seattle
- Department of Health Systems and Population Health, University of Washington, Seattle
| | - Christophe Tzourio
- Bordeaux Population Health Research Center, University of Bordeaux, Inserm, UMR 1219, Bordeaux, France
- Department of Public Health, CHU de Bordeaux, Bordeaux, France
| | - Philippe Amouyel
- INSERM U1167, University of Lille, Institut Pasteur de Lille, Lille, France
- Department of Epidemiology and Public Health, CHRU de Lille, Lille, France
| | - Hieab H. Adams
- Department of Human Genetics, Radboud University Medical Center, Nijmegen, the Netherlands
- Latin American Brain Health (BrainLat), Universidad Adolfo Ibáñez, Santiago, Chile
| | - Hélène Jacqmin-Gadda
- Bordeaux Population Health Research Center, University of Bordeaux, Inserm, UMR 1219, Bordeaux, France
| | - Mohammad Arfan Ikram
- Department of Epidemiology, Erasmus MC University Medical Center, Rotterdam, the Netherlands
| | - Vilmundur Gudnason
- Icelandic Heart Association, Kopavogur, Iceland
- Faculty of Medicine, University of Iceland, Reykjavik, Iceland
| | - Lili Milani
- Estonian Genome Centre, Institute of Genomics, University of Tartu, Tartu, Estonia
| | - Bendik S. Winsvold
- Division of Clinical Neuroscience, Department of Research and Innovation, Oslo University Hospital, Oslo, Norway
- K. G. Jebsen Center for Genetic Epidemiology, Department of Public Health and Nursing, Faculty of Medicine and Health Sciences, Norwegian University of Science and Technology (NTNU), Trondheim, Norway
- Department of Neurology, Oslo University Hospital, Oslo, Norway
| | - Kristian Hveem
- K. G. Jebsen Center for Genetic Epidemiology, Department of Public Health and Nursing, Faculty of Medicine and Health Sciences, Norwegian University of Science and Technology (NTNU), Trondheim, Norway
- HUNT Research Centre, Department of Public Health and Nursing, Norwegian University of Science and Technology, Levanger, Norway
| | - Paul M. Matthews
- Department of Brain Sciences, Imperial College London, London, United Kingdom
- UK Dementia Research Institute, Imperial College London, London, United Kingdom
- Data Science Institute, Imperial College London, London, United Kingdom
| | - W. T. Longstreth
- Department of Epidemiology, University of Washington, Seattle
- Department of Neurology, University of Washington, Seattle
| | - Sudha Seshadri
- Glenn Biggs Institute for Alzheimer’s & Neurodegenerative Diseases, University of Texas Health Sciences Center, San Antonio
- School of Public Health, Boston University and the National Heart, Lung, and Blood Institute Framingham Heart Study, Boston, Massachusetts
- Department of Neurology, Boston University School of Medicine, Boston, Massachusetts
| | - Lenore J. Launer
- Laboratory of Epidemiology and Population Sciences, Intramural Research Program, National Institute on Aging, Bethesda, Maryland
| | - Stéphanie Debette
- Bordeaux Population Health Research Center, University of Bordeaux, Inserm, UMR 1219, Bordeaux, France
- School of Public Health, Boston University and the National Heart, Lung, and Blood Institute Framingham Heart Study, Boston, Massachusetts
- Institute for Neurodegenerative Diseases, Department of Neurology, Bordeaux University Hospital, Bordeaux, France
| |
Collapse
|
8
|
Lawton M, Ben-Shlomo Y, Gkatzionis A, Hu MT, Grosset D, Tilling K. Two sample Mendelian Randomisation using an outcome from a multilevel model of disease progression. Eur J Epidemiol 2024; 39:521-533. [PMID: 38281297 PMCID: PMC11219432 DOI: 10.1007/s10654-023-01093-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/27/2023] [Accepted: 12/21/2023] [Indexed: 01/30/2024]
Abstract
Identifying factors that are causes of disease progression, especially in neurodegenerative diseases, is of considerable interest. Disease progression can be described as a trajectory of outcome over time-for example, a linear trajectory having both an intercept (severity at time zero) and a slope (rate of change). A technique for identifying causal relationships between one exposure and one outcome in observational data whilst avoiding bias due to confounding is two sample Mendelian Randomisation (2SMR). We consider a multivariate approach to 2SMR using a multilevel model for disease progression to estimate the causal effect an exposure has on the intercept and slope. We carry out a simulation study comparing a naïve univariate 2SMR approach to a multivariate 2SMR approach with one exposure that effects both the intercept and slope of an outcome that changes linearly with time since diagnosis. The simulation study results, across six different scenarios, for both approaches were similar with no evidence against a non-zero bias and appropriate coverage of the 95% confidence intervals (for intercept 93.4-96.2% and the slope 94.5-96.0%). The multivariate approach gives a better joint coverage of both the intercept and slope effects. We also apply our method to two Parkinson's cohorts to examine the effect body mass index has on disease progression. There was no strong evidence that BMI affects disease progression, however the confidence intervals for both intercept and slope were wide.
Collapse
Affiliation(s)
- Michael Lawton
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK.
| | - Yoav Ben-Shlomo
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
| | - Apostolos Gkatzionis
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol, UK
| | - Michele T Hu
- Nuffield Department of Clinical Neurosciences, Oxford University and Oxford University Hospitals NHS Foundation Trust, Oxford, UK
| | - Donald Grosset
- School of Neuroscience and Psychology, University of Glasgow, Glasgow, UK
| | - Kate Tilling
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol, UK
| |
Collapse
|
9
|
Wang P, Lin Z, Xue H, Pan W. Collider bias correction for multiple covariates in GWAS using robust multivariable Mendelian randomization. PLoS Genet 2024; 20:e1011246. [PMID: 38648211 PMCID: PMC11065275 DOI: 10.1371/journal.pgen.1011246] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/05/2023] [Revised: 05/02/2024] [Accepted: 04/02/2024] [Indexed: 04/25/2024] Open
Abstract
Genome-wide association studies (GWAS) have identified many genetic loci associated with complex traits and diseases in the past 20 years. Multiple heritable covariates may be added into GWAS regression models to estimate direct effects of genetic variants on a focal trait, or to improve the power by accounting for environmental effects and other sources of trait variations. When one or more covariates are causally affected by both genetic variants and hidden confounders, adjusting for them in GWAS will produce biased estimation of SNP effects, known as collider bias. Several approaches have been developed to correct collider bias through estimating the bias by Mendelian randomization (MR). However, these methods work for only one covariate, some of which utilize MR methods with relatively strong assumptions, both of which may not hold in practice. In this paper, we extend the bias-correction approaches in two aspects: first we derive an analytical expression for the collider bias in the presence of multiple covariates, then we propose estimating the bias using a robust multivariable MR (MVMR) method based on constrained maximum likelihood (called MVMR-cML), allowing the presence of invalid instrumental variables (IVs) and correlated pleiotropy. We also established the estimation consistency and asymptotic normality of the new bias-corrected estimator. We conducted simulations to show that all methods mitigated collider bias under various scenarios. In real data analyses, we applied the methods to two GWAS examples, the first a GWAS of waist-hip ratio with adjustment for only one covariate, body-mass index (BMI), and the second a GWAS of BMI adjusting metabolomic principle components as multiple covariates, illustrating the effectiveness of bias correction.
Collapse
Affiliation(s)
- Peiyao Wang
- Division of Biostatistics and Health Data Science, University of Minnesota, Minneapolis, Minnesota, United States of America
| | - Zhaotong Lin
- Division of Biostatistics and Health Data Science, University of Minnesota, Minneapolis, Minnesota, United States of America
- Department of Statistics, Florida State University, Tallahassee, Florida, United States of America
| | - Haoran Xue
- Division of Biostatistics and Health Data Science, University of Minnesota, Minneapolis, Minnesota, United States of America
- Department of Biostatistics, City University of Hong Kong, Hong Kong, China
| | - Wei Pan
- Division of Biostatistics and Health Data Science, University of Minnesota, Minneapolis, Minnesota, United States of America
| |
Collapse
|
10
|
Sesé L, Borie R, Kannengiesser C, Cottin V, Israel-Biet D, Crestani B, Cadranel J, Chenivesse C, Boubaya M, Valeyre D, Annesi-Maesano I, Nunes H. Impact of Air Pollution and MUC5B Genotype on Survival in Idiopathic Pulmonary Fibrosis. Ann Am Thorac Soc 2024; 21:519-523. [PMID: 38096447 DOI: 10.1513/annalsats.202305-495rl] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/02/2024] Open
Affiliation(s)
- Lucile Sesé
- Hôpital Avicenne Bobigny, France
- Université Sorbonne Paris Nord Bobigny, France
| | - Raphaël Borie
- Hôpital Bichat Paris, France
- Université Paris Cité Paris, France
| | | | - Vincent Cottin
- Hôpital Louis Pradel Lyon, France
- Université Claude Bernard Lyon 1 Lyon, France
- Institut National de Recherche pour l'Agriculture et l'Environnement Paris, France
- OrphaLung, member of Respifil, ERN-LUNG Lyon, France
| | | | | | | | | | | | - Dominique Valeyre
- Hôpital Avicenne Bobigny, France
- Université Sorbonne Paris Nord Bobigny, France
| | | | - Hilario Nunes
- Université Sorbonne Paris Nord Bobigny, France
- Hôpital Avicenne Paris, France
| |
Collapse
|
11
|
Cai H, Zhang H, Liang J, Liu Z, Huang G. Genetic liability to frailty in relation to functional outcome after ischemic stroke. Int J Stroke 2024; 19:50-57. [PMID: 37542426 DOI: 10.1177/17474930231194676] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 08/07/2023]
Abstract
BACKGROUND Frailty appears to be associated with unfavorable prognosis after stroke in observational studies, but the causality remains largely unknown. AIMS The aim of this study is to investigate the potential causal effect of frailty on functional outcome at 3 months after ischemic stroke using the Mendelian randomization (MR) framework. METHODS Genetic instruments for frailty index were identified in a genome-wide association study meta-analysis including 175,226 individuals of European descent. Corresponding genetic association estimates for functional outcome after ischemic stroke at 90 days were taken from the Genetic of Ischemic Stroke Functional Outcome (GISCOME) network of 6021 patients. We performed inverse-variance weighted MR as the main analyses, followed by several alternate methods and sensitivity analyses. RESULTS In univariable MR, we found evidence that genetically predicted higher frailty index (odds ratio (OR) = 5.12; 95% confidence interval (CI) = 1.31-20.09; p = 0.019) was associated with worse functional outcome (modified Rankin Scale score ⩾3) after ischemic stroke. In further multivariable MR adjusting for potential confounding traits including body mass index, C-reactive protein, inflammatory bowel disease, and smoking initiation, the overall patterns between genetic liability to frailty and poor functional outcome status remained. Sensitivity analyses with complementary methods and with model unadjusted for baseline stroke severity (OR = 4.19; 95% CI = 1.26-13.90; p = 0.019) yielded broadly concordant results. CONCLUSIONS The present MR study suggested a possible causal effect of frailty on poor functional outcome after ischemic stroke. Frailty might represent a potential target for intervention to improve recovery after ischemic stroke.
Collapse
Affiliation(s)
- Huan Cai
- Department of Rehabilitation Medicine, Zhongshan City People's Hospital, Zhongshan, China
| | - Hao Zhang
- Department of Neurology, Affiliated Hangzhou First People's Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Jialin Liang
- Department of Endocrinology and Metabolism, Zhongshan City People's Hospital, Zhongshan, China
| | - Zhonghua Liu
- Department of Rehabilitation Medicine, Zhongshan City People's Hospital, Zhongshan, China
| | - Guozhi Huang
- Department of Rehabilitation Medicine, Zhujiang Hospital, Southern Medical University, Guangzhou, China
- School of Rehabilitation Medicine, Southern Medical University, Guangzhou, China
| |
Collapse
|
12
|
Kachuri L, Guerra GA, Wendt GA, Hansen HM, Molinaro AM, Bracci P, McCoy L, Rice T, Wiencke JK, Eckel-Passow JE, Jenkins RB, Wrensch M, Francis SS. Genetic predisposition to altered blood cell homeostasis is associated with glioma risk and survival. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2023:2023.10.15.23296448. [PMID: 37905116 PMCID: PMC10614986 DOI: 10.1101/2023.10.15.23296448] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/02/2023]
Abstract
Glioma is a highly fatal brain tumor comprised of molecular subtypes with distinct clinical trajectories. Observational studies have suggested that variability in immune response may play a role in glioma etiology. However, their findings have been inconsistent and susceptible to reverse causation due to treatment effects and the immunosuppressive nature of glioma. We applied genetic variants associated (p<5×10-8) with blood cell traits to a meta-analysis of 3418 glioma cases and 8156 controls. Genetically predicted increase in the platelet to lymphocyte ratio (PLR) was associated with an increased risk of glioma (odds ratio (OR)=1.25, p=0.005), especially in IDH-mutant (IDHmut OR=1.38, p=0.007) and IDHmut 1p/19q non-codeleted (IDHmut-noncodel OR=1.53, p=0.004) tumors. However, reduced glioma risk was observed for higher counts of lymphocytes (IDHmut-noncodel OR=0.70, p=0.004) and neutrophils (IDHmut OR=0.69, p=0.019; IDHmut-noncodel OR=0.60, p=0.009), which may reflect genetic predisposition to enhanced immune-surveillance. In contrast to susceptibility, there was no association with survival in IDHmut-noncodel; however, in IDHmut 1p/19q co-deleted tumors, we observed higher mortality with increasing genetically predicted counts of lymphocytes (hazard ratio (HR)=1.65, 95% CI: 1.24-2.20), neutrophils (HR=1.49, 1.13-1.97), and eosinophils (HR=1.59, 1.18-2.14). Polygenic scores for blood cell traits were also associated with tumor immune microenvironment features, with heterogeneity by IDH status observed for 17 signatures related to interferon signaling, PD-1 expression, and T-cell/Cytotoxic responses. In summary, we identified novel, immune-mediated susceptibility mechanisms for glioma with potential disease management implications.
Collapse
Affiliation(s)
- Linda Kachuri
- Department of Epidemiology & Population Health, Stanford University School of Medicine, Stanford, CA
- Stanford Cancer Institute, Stanford University School of Medicine, Stanford, CA
| | - Geno A. Guerra
- Department of Neurological Surgery, University of California San Francisco, San Francisco, CA
- Department of Epidemiology & Biostatistics, University of California San Francisco, San Francisco, CA
| | - George A. Wendt
- Department of Neurological Surgery, University of California San Francisco, San Francisco, CA
| | - Helen M. Hansen
- Department of Neurological Surgery, University of California San Francisco, San Francisco, CA
| | - Annette M. Molinaro
- Department of Neurological Surgery, University of California San Francisco, San Francisco, CA
- Department of Epidemiology & Biostatistics, University of California San Francisco, San Francisco, CA
| | - Paige Bracci
- Department of Epidemiology & Biostatistics, University of California San Francisco, San Francisco, CA
| | - Lucie McCoy
- Department of Neurological Surgery, University of California San Francisco, San Francisco, CA
| | - Terri Rice
- Department of Neurological Surgery, University of California San Francisco, San Francisco, CA
| | - John K. Wiencke
- Department of Neurological Surgery, University of California San Francisco, San Francisco, CA
- Weill Institute for Neurosciences, University of California San Francisco, San Francisco, US
| | | | - Robert B. Jenkins
- Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, Minnesota, USA
| | - Margaret Wrensch
- Department of Neurological Surgery, University of California San Francisco, San Francisco, CA
| | - Stephen S. Francis
- Department of Neurological Surgery, University of California San Francisco, San Francisco, CA
- Department of Epidemiology & Biostatistics, University of California San Francisco, San Francisco, CA
- Weill Institute for Neurosciences, University of California San Francisco, San Francisco, US
| |
Collapse
|
13
|
Cai S, Allen RJ, Wain LV, Dudbridge F. Reassessing the association of MUC5B with survival in idiopathic pulmonary fibrosis. Ann Hum Genet 2023; 87:248-253. [PMID: 37537942 PMCID: PMC10952500 DOI: 10.1111/ahg.12522] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/09/2023] [Revised: 07/18/2023] [Accepted: 07/23/2023] [Indexed: 08/05/2023]
Abstract
A variant in the mucin 5B gene (MUC5B) is strongly associated with the risk of idiopathic pulmonary fibrosis. However, the same variant is associated with increased survival time. Previous work suggested that this may be explained by index event bias, with the true effect being to decrease survival. Here, we reassessed this claim using more recent methods and datasets. We found that the statistical assumptions of the previous analysis did not hold, and instead, we applied recent methods of corrected weighted least squares, MR-RAPS and Slope-hunter to both the previous data and an updated consortium meta-analysis. However, these analyses did not yield robust evidence for increased or decreased survival. In simulations of a true effect of decreased survival, we did not observe any realistic scenario in which index event bias led to an observed effect of increased survival. We therefore regard as unsafe the claim that MUC5B has a true effect of decreased survival. Alternative explanations should be sought to explain the observed association with increased survival.
Collapse
Affiliation(s)
- Siyang Cai
- Department of Population Health SciencesUniversity of LeicesterLeicesterUK
| | - Richard J. Allen
- Department of Population Health SciencesUniversity of LeicesterLeicesterUK
| | - Louise V. Wain
- Department of Population Health SciencesUniversity of LeicesterLeicesterUK
| | - Frank Dudbridge
- Department of Population Health SciencesUniversity of LeicesterLeicesterUK
| |
Collapse
|
14
|
Karampitsakos T, Juan-Guardela BM, Tzouvelekis A, Herazo-Maya JD. Precision medicine advances in idiopathic pulmonary fibrosis. EBioMedicine 2023; 95:104766. [PMID: 37625268 PMCID: PMC10469771 DOI: 10.1016/j.ebiom.2023.104766] [Citation(s) in RCA: 49] [Impact Index Per Article: 49.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/31/2023] [Revised: 07/07/2023] [Accepted: 08/07/2023] [Indexed: 08/27/2023] Open
Abstract
Idiopathic pulmonary fibrosis (IPF) is a highly heterogeneous, unpredictable and ultimately lethal chronic lung disease. Over the last decade, two anti-fibrotic agents have been shown to slow disease progression, however, both drugs are administered uniformly with minimal consideration of disease severity and inter-individual molecular, genetic, and genomic differences. Advances in biological understanding of disease endotyping and the emergence of precision medicine have shown that "a one-size-fits-all approach" to the management of chronic lung diseases is no longer appropriate. While precision medicine approaches have revolutionized the management of other diseases such as lung cancer and asthma, the implementation of precision medicine in IPF clinical practice remains an unmet need despite several reports demonstrating a large number of diagnostic, prognostic and theragnostic biomarker candidates in IPF. This review article aims to summarize our current knowledge of precision medicine in IPF and highlight barriers to translate these research findings into clinical practice.
Collapse
Affiliation(s)
- Theodoros Karampitsakos
- Division of Pulmonary, Critical Care and Sleep Medicine, Ubben Center for Pulmonary Fibrosis Research, Department of Internal Medicine, Morsani College of Medicine, University of South Florida, Tampa, FL, USA
| | - Brenda M Juan-Guardela
- Division of Pulmonary, Critical Care and Sleep Medicine, Ubben Center for Pulmonary Fibrosis Research, Department of Internal Medicine, Morsani College of Medicine, University of South Florida, Tampa, FL, USA
| | | | - Jose D Herazo-Maya
- Division of Pulmonary, Critical Care and Sleep Medicine, Ubben Center for Pulmonary Fibrosis Research, Department of Internal Medicine, Morsani College of Medicine, University of South Florida, Tampa, FL, USA.
| |
Collapse
|
15
|
Sargurupremraj M, Soumare A, Bis JC, Surakka I, Jurgenson T, Joly P, Knol MJ, Wang R, Yang Q, Satizabal CL, Gudjonsson A, Mishra A, Bouteloup V, Phuah CL, van Duijn CM, Cruchaga C, Dufouil C, Chêne G, Lopez O, Psaty BM, Tzourio C, Amouyel P, Adams HH, Jacqmin-Gadda H, Ikram MA, Gudnason V, Milani L, Winsvold BS, Hveem K, Matthews PM, Longstreth WT, Seshadri S, Launer LJ, Debette S. Complexities of cerebral small vessel disease, blood pressure, and dementia relationship: new insights from genetics. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2023:2023.08.08.23293761. [PMID: 37790435 PMCID: PMC10543241 DOI: 10.1101/2023.08.08.23293761] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 10/05/2023]
Abstract
Importance There is increasing recognition that vascular disease, which can be treated, is a key contributor to dementia risk. However, the contribution of specific markers of vascular disease is unclear and, as a consequence, optimal prevention strategies remain unclear. Objective To disentangle the causal relation of several key vascular traits to dementia risk: (i) white matter hyperintensity (WMH) burden, a highly prevalent imaging marker of covert cerebral small vessel disease (cSVD); (ii) clinical stroke; and (iii) blood pressure (BP), the leading risk factor for cSVD and stroke, for which efficient therapies exist. To account for potential epidemiological biases inherent to late-onset conditions like dementia. Design Setting and Participants This study first explored the association of genetically determined WMH, BP levels and stroke risk with AD using summary-level data from large genome-wide association studies (GWASs) in a two-sample Mendelian randomization (MR) framework. Second, leveraging individual-level data from large longitudinal population-based cohorts and biobanks with prospective dementia surveillance, the association of weighted genetic risk scores (wGRSs) for WMH, BP, and stroke with incident all-cause-dementia was explored using Cox-proportional hazard and multi-state models. The data analysis was performed from July 26, 2020, through July 24, 2022. Exposures Genetically determined levels of WMH volume and BP (systolic, diastolic and pulse blood pressures) and genetic liability to stroke. Main outcomes and measures The summary-level MR analyses focused on the outcomes from GWAS of clinically diagnosed AD (n-cases=21,982) and GWAS additionally including self-reported parental history of dementia as a proxy for AD diagnosis (ADmeta, n-cases=53,042). For the longitudinal analyses, individual-level data of 157,698 participants with 10,699 incident all-cause-dementia were studied, exploring AD, vascular or mixed dementia in secondary analyses. Results In the two-sample MR analyses, WMH showed strong evidence for a causal association with increased risk of ADmeta (OR, 1.16; 95%CI:1.05-1.28; P=.003) and AD (OR, 1.28; 95%CI:1.07-1.53; P=.008), after accounting for genetically determined pulse pressure for the latter. Genetically predicted BP traits showed evidence for a protective association with both clinically defined AD and ADmeta, with evidence for confounding by shared genetic instruments. In longitudinal analyses the wGRSs for WMH, but not BP or stroke, showed suggestive association with incident all-cause-dementia (HR, 1.02; 95%CI:1.00-1.04; P=.06). BP and stroke wGRSs were strongly associated with mortality but there was no evidence for selective survival bias during follow-up. In secondary analyses, polygenic scores with more liberal instrument definition showed association of both WMH and stroke with all-cause-dementia, AD, and vascular or mixed dementia; associations of stroke, but not WMH, with dementia outcomes were markedly attenuated after adjusting for interim stroke. Conclusion These findings provide converging evidence that WMH is a leading vascular contributor to dementia risk, which may better capture the brain damage caused by BP (and other etiologies) than BP itself and should be targeted in priority for dementia prevention in the population.
Collapse
Affiliation(s)
- Muralidharan Sargurupremraj
- University of Bordeaux, Inserm, Bordeaux Population Health Research Center, UMR 1219, Bordeaux, France
- Glenn Biggs Institute for Alzheimer's & Neurodegenerative Diseases, University of Texas Health Sciences Center, San Antonio, TX
| | - Aicha Soumare
- University of Bordeaux, Inserm, Bordeaux Population Health Research Center, UMR 1219, Bordeaux, France
| | - Joshua C Bis
- Cardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle, WA, USA
| | - Ida Surakka
- Department of Internal Medicine, University of Michigan, Ann Arbor, MI, USA
| | - Tuuli Jurgenson
- Estonian Genome Centre, Institute of Genomics, University of Tartu
| | - Pierre Joly
- University of Bordeaux, Inserm, Bordeaux Population Health Research Center, UMR 1219, Bordeaux, France
| | | | - Ruiqi Wang
- Boston University and the NHLBI's Framingham Heart Study, Boston, MA
- Department of Neurology, Boston University School of Medicine, Boston, MA, USA
| | - Qiong Yang
- Boston University and the NHLBI's Framingham Heart Study, Boston, MA
- Department of Neurology, Boston University School of Medicine, Boston, MA, USA
| | - Claudia L Satizabal
- Glenn Biggs Institute for Alzheimer's & Neurodegenerative Diseases, University of Texas Health Sciences Center, San Antonio, TX
- Boston University and the NHLBI's Framingham Heart Study, Boston, MA
- Department of Neurology, Boston University School of Medicine, Boston, MA, USA
| | | | - Aniket Mishra
- University of Bordeaux, Inserm, Bordeaux Population Health Research Center, UMR 1219, Bordeaux, France
| | - Vincent Bouteloup
- University of Bordeaux, Inserm, Bordeaux Population Health Research Center, UMR 1219, Bordeaux, France
| | - Chia-Ling Phuah
- Department of Neurology, Washington University School of Medicine & Barnes-Jewish Hospital, St. Louis, Missouri, USA
- NeuroGenomics and Informatics Center, Washington University in St Louis, Missouri, USA
| | | | - Carlos Cruchaga
- NeuroGenomics and Informatics Center, Washington University in St Louis, Missouri, USA
- Department of Psychiatry, Washington University School of Medicine, St. Louis, Missouri, USA
- The Charles F. and Joanne Knight Alzheimer's Disease Research Center, Washington University School of Medicine, St. Louis, Missouri, USA
| | - Carole Dufouil
- University of Bordeaux, Inserm, Bordeaux Population Health Research Center, UMR 1219, Bordeaux, France
| | - Geneviève Chêne
- University of Bordeaux, Inserm, Bordeaux Population Health Research Center, UMR 1219, Bordeaux, France
| | - Oscar Lopez
- Department of Neurology, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA
- Department of Psychiatry, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA
| | - Bruce M Psaty
- Cardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle, WA, USA
- Department of Epidemiology, University of Washington, Seattle, Washington, USA
- Department of Health Systems and Population Health, University of Washington, Seattle, WA, USA
| | - Christophe Tzourio
- University of Bordeaux, Inserm, Bordeaux Population Health Research Center, UMR 1219, Bordeaux, France
| | - Philippe Amouyel
- INSERM U1167, Lille, France
- Department of Epidemiology and Public Health, Pasteur Institute of Lille, France
| | | | - Hélène Jacqmin-Gadda
- University of Bordeaux, Inserm, Bordeaux Population Health Research Center, UMR 1219, Bordeaux, France
| | | | - Vilmundur Gudnason
- Icelandic Heart Association, 201 Kopavogur,Iceland
- University of Iceland, Faculty of Medicine, 101 Reykjavik , Iceland
| | - Lili Milani
- Estonian Genome Centre, Institute of Genomics, University of Tartu
| | - Bendik S Winsvold
- Department of Research and Innovation, Division of Clinical Neuroscience, Oslo University Hospital, Oslo, Norway
- K. G. Jebsen Center for Genetic Epidemiology, Department of Public Health and Nursing, Faculty of Medicine and Health Sciences, Norwegian University of Science and Technology (NTNU), Trondheim, Norway
- Department of Neurology, Oslo University Hospital, Oslo, Norway
| | - Kristian Hveem
- K. G. Jebsen Center for Genetic Epidemiology, Department of Public Health and Nursing, Faculty of Medicine and Health Sciences, Norwegian University of Science and Technology (NTNU), Trondheim, Norway
- HUNT Research Centre, Department of Public Health and Nursing, Norwegian University of Science and Technology, Levanger, Norway
| | - Paul M Matthews
- Department of Brain Sciences, Imperial College London, UK
- UK Dementia Research Institute, London, UK
- Data Science Institute, Imperial College London
| | - W T Longstreth
- Department of Neurology, University of Washington, Seattle, Washington, USA
- Department of Epidemiology, University of Washington, Seattle, Washington, USA
| | - Sudha Seshadri
- Glenn Biggs Institute for Alzheimer's & Neurodegenerative Diseases, University of Texas Health Sciences Center, San Antonio, TX
- Boston University and the NHLBI's Framingham Heart Study, Boston, MA
- Department of Neurology, Boston University School of Medicine, Boston, MA, USA
| | - Lenore J Launer
- Laboratory of Epidemiology and Population Sciences, Intramural Research Program, National Institute on Aging, Bethesda, MD, USA
| | - Stéphanie Debette
- University of Bordeaux, Inserm, Bordeaux Population Health Research Center, UMR 1219, Bordeaux, France
- Department of Neurology, Boston University School of Medicine, Boston, MA, USA
- Department of Neurology, Institute for Neurodegenerative Diseases, Bordeaux University Hospital, Bordeaux, France
| |
Collapse
|
16
|
Burgess S, Davey Smith G, Davies NM, Dudbridge F, Gill D, Glymour MM, Hartwig FP, Kutalik Z, Holmes MV, Minelli C, Morrison JV, Pan W, Relton CL, Theodoratou E. Guidelines for performing Mendelian randomization investigations: update for summer 2023. Wellcome Open Res 2023; 4:186. [PMID: 32760811 PMCID: PMC7384151 DOI: 10.12688/wellcomeopenres.15555.3] [Citation(s) in RCA: 180] [Impact Index Per Article: 180.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 07/19/2023] [Indexed: 08/08/2023] Open
Abstract
This paper provides guidelines for performing Mendelian randomization investigations. It is aimed at practitioners seeking to undertake analyses and write up their findings, and at journal editors and reviewers seeking to assess Mendelian randomization manuscripts. The guidelines are divided into ten sections: motivation and scope, data sources, choice of genetic variants, variant harmonization, primary analysis, supplementary and sensitivity analyses (one section on robust statistical methods and one on other approaches), extensions and additional analyses, data presentation, and interpretation. These guidelines will be updated based on feedback from the community and advances in the field. Updates will be made periodically as needed, and at least every 24 months.
Collapse
Affiliation(s)
- Stephen Burgess
- MRC Biostatistics Unit, University of Cambridge, Cambridge, UK
- BHF Cardiovascular Epidemiology Unit, University of Cambridge, Cambridge, UK
| | - George Davey Smith
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol, UK
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
| | - Neil M. Davies
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol, UK
- Division of Psychiatry, University College London, London, UK
- Department of Statistical Sciences, University College London, London, WC1E 6BT, UK
- K.G. Jebsen Center for Genetic Epidemiology, Department of Public Health and Nursing, NTNU, Norwegian University of Science and Technology, Trondheim, Norway
| | - Frank Dudbridge
- Department of Health Sciences, University of Leicester, Leicester, UK
| | - Dipender Gill
- Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, UK
| | - M. Maria Glymour
- Department of Epidemiology and Biostatistics, University of California, San Francisco, San Francisco, CA, USA
| | - Fernando P. Hartwig
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol, UK
- Postgraduate Program in Epidemiology, Federal University of Pelotas, Pelotas, Brazil
| | - Zoltán Kutalik
- Swiss Institute of Bioinformatics, Lausanne, Switzerland
- Department of Computational Biology, University of Lausanne, Lausanne, Switzerland
- University Center for Primary Care and Public Health (Unisanté), Lausanne, Switzerland
| | - Michael V. Holmes
- MRC Population Health Research Unit, Nuffield Department of Population Health, University of Oxford, Oxford, UK
- Clinical Trial Service Unit and Epidemiological Studies Unit, Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - Cosetta Minelli
- National Heart and Lung Institute, Imperial College London, London, UK
| | - Jean V. Morrison
- Department of Biostatistics, University of Michigan, Ann Arbor, MI, USA
| | - Wei Pan
- Division of Biostatistics, University of Minnesota, Minneapolis, MN, USA
| | - Caroline L. Relton
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol, UK
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
- London School of Hygiene & Tropical Medicine, Keppel Street, London, WC1E 7HT, UK
| | - Evropi Theodoratou
- Centre for Global Health, Usher Institute, University of Edinburgh, Edinburgh, UK
- Edinburgh Cancer Research Centre, Institute of Genetics and Cancer, The University of Edinburgh, Edinburgh, UK
| |
Collapse
|
17
|
Sha T, Wang Y, Zhang Y, Lane NE, Li C, Wei J, Zeng C, Lei G. Genetic Variants, Serum 25-Hydroxyvitamin D Levels, and Sarcopenia: A Mendelian Randomization Analysis. JAMA Netw Open 2023; 6:e2331558. [PMID: 37647062 PMCID: PMC10469287 DOI: 10.1001/jamanetworkopen.2023.31558] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/03/2023] [Accepted: 07/24/2023] [Indexed: 09/01/2023] Open
Abstract
Importance Vitamin D deficiency is commonly associated with sarcopenia; however, the latest International Clinical Practice Guidelines for Sarcopenia do not recommend vitamin D supplementation for sarcopenia owing to a lack of an apparent therapeutic effect on the indices of sarcopenia among participants with replete vitamin D concentration (ie, 25-hydroxyvitamin D [25(OH)D] level >20 ng/mL) from randomized clinical trials. While there is consensus in all vitamin D guidelines that serum levels of 25(OH)D less than 10 ng/mL should be corrected, approximately 30% of the world population's 25(OH)D levels range from 10 to 20 ng/mL, and it remains unclear whether such suboptimal levels can maintain optimal health, including sarcopenia risk. Objective To investigate the association of serum 25(OH)D level, especially suboptimal levels, with sarcopenia risk. Design, Setting, and Participants This genome-wide genetic association study was performed from August 2022 to February 2023 among the 295 489 unrelated European participants from the UK Biobank (2006-2010). Nonlinear and standard mendelian randomization analyses were used to examine the association of serum 25(OH)D concentration with sarcopenia risk. Exposures A weighted genetic risk score using 35 unrelated single-nucleotide variants from the UK Biobank and weights from the SUNLIGHT Consortium was selected as an instrumental variable for serum 25(OH)D concentration. Main Outcomes and Measures The primary outcome was sarcopenia, and the secondary outcomes consisted of grip strength, appendicular lean mass index, and gait speed. Results The final genetic analyses included 295 489 participants (mean [SD] age, 56.3 [8.1] years; 139 216 female [52.9%]). There was an L-shaped association between genetically predicted serum 25(OH)D concentration and sarcopenia risk. The risk of sarcopenia decreased rapidly as 25(OH)D concentration increased until 20 ng/mL and then leveled off. The odds ratio of sarcopenia for serum 25(OH)D level of 10 vs 20 ng/mL was 1.74 (95% CI, 1.17-2.59). Similar patterns were also observed when the association between serum 25(OH)D concentration and risks of each of the sarcopenia indices were evaluated. Conclusions and Relevance In this mendelian randomization genetic association study of adults in the UK Biobank, the findings supported a nonlinear association between suboptimal 25(OH)D levels and sarcopenia risk. Randomized clinical trials among participants with suboptimal 25(OH)D levels are required to verify the potential causality.
Collapse
Affiliation(s)
- Tingting Sha
- Department of Orthopaedics, Xiangya Hospital, Central South University, Changsha, China
- Hunan Key Laboratory of Joint Degeneration and Injury, Changsha, China
- Key Laboratory of Aging-related Bone and Joint Diseases Prevention and Treatment, Ministry of Education, Changsha, China
| | - Yilun Wang
- Department of Orthopaedics, Xiangya Hospital, Central South University, Changsha, China
- Hunan Key Laboratory of Joint Degeneration and Injury, Changsha, China
- Key Laboratory of Aging-related Bone and Joint Diseases Prevention and Treatment, Ministry of Education, Changsha, China
| | - Yuqing Zhang
- Division of Rheumatology, Allergy, and Immunology, Department of Medicine, Massachusetts General Hospital, Harvard Medical School, Boston
- The Mongan Institute, Massachusetts General Hospital, Harvard Medical School, Boston
| | - Nancy E. Lane
- Center for Musculoskeletal Health and Department of Medicine, University of California School of Medicine, Sacramento
| | - Changjun Li
- National Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Central South University, Changsha, China
- Department of Endocrinology, Endocrinology Research Center, Xiangya Hospital of Central South University, Changsha, China
| | - Jie Wei
- Hunan Key Laboratory of Joint Degeneration and Injury, Changsha, China
- Key Laboratory of Aging-related Bone and Joint Diseases Prevention and Treatment, Ministry of Education, Changsha, China
- Health Management Center, Xiangya Hospital, Central South University, Changsha, China
- Department of Epidemiology and Health Statistics, Xiangya School of Public Health, Central South University, Changsha, China
| | - Chao Zeng
- Department of Orthopaedics, Xiangya Hospital, Central South University, Changsha, China
- Hunan Key Laboratory of Joint Degeneration and Injury, Changsha, China
- Key Laboratory of Aging-related Bone and Joint Diseases Prevention and Treatment, Ministry of Education, Changsha, China
- National Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Central South University, Changsha, China
| | - Guanghua Lei
- Department of Orthopaedics, Xiangya Hospital, Central South University, Changsha, China
- Hunan Key Laboratory of Joint Degeneration and Injury, Changsha, China
- Key Laboratory of Aging-related Bone and Joint Diseases Prevention and Treatment, Ministry of Education, Changsha, China
- National Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Central South University, Changsha, China
| |
Collapse
|
18
|
Sood T, Perrot N, Chong M, Mohammadi-Shemirani P, Mushtaha M, Leong D, Rangarajan S, Hess S, Yusuf S, Gerstein HC, Paré G, Pigeyre M. Biomarkers Associated With Severe COVID-19 Among Populations With High Cardiometabolic Risk: A 2-Sample Mendelian Randomization Study. JAMA Netw Open 2023; 6:e2325914. [PMID: 37498601 PMCID: PMC10375306 DOI: 10.1001/jamanetworkopen.2023.25914] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 07/28/2023] Open
Abstract
Importance Cardiometabolic parameters are established risk factors for COVID-19 severity. The identification of causal or protective biomarkers for COVID-19 severity may facilitate the development of novel therapies. Objective To identify protein biomarkers that promote or reduce COVID-19 severity and that mediate the association of cardiometabolic risk factors with COVID-19 severity. Design, Setting, and Participants This genetic association study using 2-sample mendelian randomization (MR) was conducted in 2022 to investigate associations among cardiometabolic risk factors, circulating biomarkers, and COVID-19 hospitalization. Inputs for MR included genetic and proteomic data from 4147 participants with dysglycemia and cardiovascular risk factors collected through the Outcome Reduction With Initial Glargine Intervention (ORIGIN) trial. Genome-wide association study summary statistics were obtained from (1) 3 additional independent plasma proteome studies, (2) genetic consortia for selected cardiometabolic risk factors (including body mass index [BMI], type 2 diabetes, type 1 diabetes, and systolic blood pressure; all n >10 000), and (3) the COVID-19 Host Genetics Initiative (n = 5773 hospitalized and 15 497 nonhospitalized case participants with COVID-19). Data analysis was performed in July 2022. Exposures Genetically determined concentrations of 235 circulating proteins assayed with a multiplex biomarker panel from the ORIGIN trial for the initial analysis. Main Outcomes and Measures Hospitalization status of individuals from the COVID-19 Host Genetics Initiative with a positive COVID-19 test result. Results Among 235 biomarkers tested in samples totaling 22 101 individuals, MR analysis showed that higher kidney injury molecule-1 (KIM-1) levels reduced the likelihood of COVID-19 hospitalization (odds ratio [OR] per SD increase in KIM-1 levels, 0.86 [95% CI, 0.79-0.93]). A meta-analysis validated the protective association with no observed directional pleiotropy (OR per SD increase in KIM-1 levels, 0.91 [95% CI, 0.88-0.95]). Of the cardiometabolic risk factors studied, only BMI was associated with KIM-1 levels (0.17 SD increase in biomarker level per 1 kg/m2 [95% CI, 0.08-0.26]) and COVID-19 hospitalization (OR per 1-SD biomarker level, 1.33 [95% CI, 1.18-1.50]). Multivariable MR analysis also revealed that KIM-1 partially mitigated the association of BMI with COVID-19 hospitalization, reducing it by 10 percentage points (OR adjusted for KIM-1 level per 1 kg/m2, 1.23 [95% CI, 1.06-1.43]). Conclusions and Relevance In this genetic association study, KIM-1 was identified as a potential mitigator of COVID-19 severity, possibly attenuating the increased risk of COVID-19 hospitalization among individuals with high BMI. Further studies are required to better understand the underlying biological mechanisms.
Collapse
Affiliation(s)
- Tushar Sood
- Population Health Research Institute, Hamilton, Ontario, Canada
- Temerty Faculty of Medicine, University of Toronto, Toronto, Ontario, Canada
| | - Nicolas Perrot
- Population Health Research Institute, Hamilton, Ontario, Canada
- Department of Pathology and Molecular Medicine, McMaster University, Hamilton, Ontario, Canada
- Thrombosis and Atherosclerosis Research Institute, Hamilton, Ontario, Canada
| | - Michael Chong
- Population Health Research Institute, Hamilton, Ontario, Canada
- Department of Pathology and Molecular Medicine, McMaster University, Hamilton, Ontario, Canada
- Thrombosis and Atherosclerosis Research Institute, Hamilton, Ontario, Canada
| | - Pedrum Mohammadi-Shemirani
- Population Health Research Institute, Hamilton, Ontario, Canada
- Department of Pathology and Molecular Medicine, McMaster University, Hamilton, Ontario, Canada
- Thrombosis and Atherosclerosis Research Institute, Hamilton, Ontario, Canada
- Deep Genomics Inc, Toronto, Ontario, Canada
| | - Maha Mushtaha
- Population Health Research Institute, Hamilton, Ontario, Canada
| | - Darryl Leong
- Population Health Research Institute, Hamilton, Ontario, Canada
- Department of Medicine, McMaster University, Hamilton, Ontario, Canada
| | | | - Sibylle Hess
- Global Medical Diabetes, Sanofi, Frankfurt, Germany
| | - Salim Yusuf
- Population Health Research Institute, Hamilton, Ontario, Canada
- Department of Medicine, McMaster University, Hamilton, Ontario, Canada
| | - Hertzel C Gerstein
- Population Health Research Institute, Hamilton, Ontario, Canada
- Department of Medicine, McMaster University, Hamilton, Ontario, Canada
| | - Guillaume Paré
- Population Health Research Institute, Hamilton, Ontario, Canada
- Department of Pathology and Molecular Medicine, McMaster University, Hamilton, Ontario, Canada
- Thrombosis and Atherosclerosis Research Institute, Hamilton, Ontario, Canada
| | - Marie Pigeyre
- Population Health Research Institute, Hamilton, Ontario, Canada
- Department of Medicine, McMaster University, Hamilton, Ontario, Canada
| |
Collapse
|
19
|
Clayton GL, Gonçalves A, Soares, Goulding N, Borges MC, Holmes MV, Davey G, Smith, Tilling K, Lawlor DA, Carter AR. A framework for assessing selection and misclassification bias in mendelian randomisation studies: an illustrative example between body mass index and covid-19. BMJ 2023; 381:e072148. [PMID: 37336561 PMCID: PMC10277657 DOI: 10.1136/bmj-2022-072148] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 03/15/2023] [Indexed: 06/21/2023]
Affiliation(s)
- Gemma L Clayton
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol, UK
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
| | | | - Soares
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol, UK
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
| | - Neil Goulding
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol, UK
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
| | - Maria Carolina Borges
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol, UK
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
| | - Michael V Holmes
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol, UK
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
| | | | - Smith
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol, UK
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
- National Institute for Health Research Bristol Biomedical Research Centre, University Hospitals Bristol NHS Foundation Trust and University of Bristol, Bristol, UK
| | - Kate Tilling
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol, UK
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
- National Institute for Health Research Bristol Biomedical Research Centre, University Hospitals Bristol NHS Foundation Trust and University of Bristol, Bristol, UK
| | - Deborah A Lawlor
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol, UK
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
- National Institute for Health Research Bristol Biomedical Research Centre, University Hospitals Bristol NHS Foundation Trust and University of Bristol, Bristol, UK
| | - Alice R Carter
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol, UK
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
| |
Collapse
|
20
|
Kachuri L, Hoffmann TJ, Jiang Y, Berndt SI, Shelley JP, Schaffer KR, Machiela MJ, Freedman ND, Huang WY, Li SA, Easterlin R, Goodman PJ, Till C, Thompson I, Lilja H, Van Den Eeden SK, Chanock SJ, Haiman CA, Conti DV, Klein RJ, Mosley JD, Graff RE, Witte JS. Genetically adjusted PSA levels for prostate cancer screening. Nat Med 2023; 29:1412-1423. [PMID: 37264206 PMCID: PMC10287565 DOI: 10.1038/s41591-023-02277-9] [Citation(s) in RCA: 18] [Impact Index Per Article: 18.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/14/2022] [Accepted: 02/27/2023] [Indexed: 06/03/2023]
Abstract
Prostate-specific antigen (PSA) screening for prostate cancer remains controversial because it increases overdiagnosis and overtreatment of clinically insignificant tumors. Accounting for genetic determinants of constitutive, non-cancer-related PSA variation has potential to improve screening utility. In this study, we discovered 128 genome-wide significant associations (P < 5 × 10-8) in a multi-ancestry meta-analysis of 95,768 men and developed a PSA polygenic score (PGSPSA) that explains 9.61% of constitutive PSA variation. We found that, in men of European ancestry, using PGS-adjusted PSA would avoid up to 31% of negative prostate biopsies but also result in 12% fewer biopsies in patients with prostate cancer, mostly with Gleason score <7 tumors. Genetically adjusted PSA was more predictive of aggressive prostate cancer (odds ratio (OR) = 3.44, P = 6.2 × 10-14, area under the curve (AUC) = 0.755) than unadjusted PSA (OR = 3.31, P = 1.1 × 10-12, AUC = 0.738) in 106 cases and 23,667 controls. Compared to a prostate cancer PGS alone (AUC = 0.712), including genetically adjusted PSA improved detection of aggressive disease (AUC = 0.786, P = 7.2 × 10-4). Our findings highlight the potential utility of incorporating PGS for personalized biomarkers in prostate cancer screening.
Collapse
Affiliation(s)
- Linda Kachuri
- Department of Epidemiology & Biostatistics, University of California, San Francisco, San Francisco, CA, USA
- Department of Epidemiology & Population Health, Stanford University School of Medicine, Stanford, CA, USA
- Stanford Cancer Institute, Stanford University School of Medicine, Stanford, CA, USA
| | - Thomas J Hoffmann
- Department of Epidemiology & Biostatistics, University of California, San Francisco, San Francisco, CA, USA
- Institute of Human Genetics, University of California, San Francisco, San Francisco, CA, USA
| | - Yu Jiang
- Department of Epidemiology & Population Health, Stanford University School of Medicine, Stanford, CA, USA
| | - Sonja I Berndt
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, Rockville, MD, USA
| | - John P Shelley
- Department of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, TN, USA
| | | | - Mitchell J Machiela
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, Rockville, MD, USA
| | - Neal D Freedman
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, Rockville, MD, USA
| | - Wen-Yi Huang
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, Rockville, MD, USA
| | - Shengchao A Li
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, Rockville, MD, USA
| | - Ryder Easterlin
- Biological and Medical Informatics, University of California, San Francisco, San Francisco, CA, USA
| | | | - Cathee Till
- SWOG Statistics and Data Management Center, Fred Hutchinson Cancer Research Center, Seattle, WA, USA
| | - Ian Thompson
- CHRISTUS Santa Rosa Medical Center Hospital, San Antonio, TX, USA
| | - Hans Lilja
- Departments of Laboratory Medicine, Surgery and Medicine, Memorial Sloan Kettering Cancer Center, New York, NY, USA
- Department of Translational Medicine, Lund University, Skåne University Hospital, Malmö, Sweden
| | | | - Stephen J Chanock
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, Rockville, MD, USA
| | - Christopher A Haiman
- Center for Genetic Epidemiology, Department of Population and Preventive Health Sciences, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
- Norris Comprehensive Cancer Center, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
| | - David V Conti
- Center for Genetic Epidemiology, Department of Population and Preventive Health Sciences, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
- Norris Comprehensive Cancer Center, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
| | - Robert J Klein
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Jonathan D Mosley
- Department of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, TN, USA
- Department of Internal Medicine, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Rebecca E Graff
- Department of Epidemiology & Biostatistics, University of California, San Francisco, San Francisco, CA, USA.
| | - John S Witte
- Department of Epidemiology & Biostatistics, University of California, San Francisco, San Francisco, CA, USA.
- Department of Epidemiology & Population Health, Stanford University School of Medicine, Stanford, CA, USA.
- Stanford Cancer Institute, Stanford University School of Medicine, Stanford, CA, USA.
- Departments of Biomedical Data Science and Genetics, Stanford University, Stanford, CA, USA.
| |
Collapse
|
21
|
Kim JS, Manichaikul AW, Hoffman EA, Balte P, Anderson MR, Bernstein EJ, Madahar P, Oelsner EC, Kawut SM, Wysoczanski A, Laine AF, Adegunsoye A, Ma JZ, Taub MA, Mathias RA, Rich SS, Rotter JI, Noth I, Garcia CK, Barr RG, Podolanczuk AJ. MUC5B, telomere length and longitudinal quantitative interstitial lung changes: the MESA Lung Study. Thorax 2023; 78:566-573. [PMID: 36690926 PMCID: PMC9899287 DOI: 10.1136/thorax-2021-218139] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/26/2021] [Accepted: 07/11/2022] [Indexed: 02/06/2023]
Abstract
BACKGROUND The MUC5B promoter variant (rs35705950) and telomere length are linked to pulmonary fibrosis and CT-based qualitative assessments of interstitial abnormalities, but their associations with longitudinal quantitative changes of the lung interstitium among community-dwelling adults are unknown. METHODS We used data from participants in the Multi-Ethnic Study of Atherosclerosis with high-attenuation areas (HAAs, Examinations 1-6 (2000-2018)) and MUC5B genotype (n=4552) and telomere length (n=4488) assessments. HAA was defined as the per cent of imaged lung with attenuation of -600 to -250 Hounsfield units. We used linear mixed-effects models to examine associations of MUC5B risk allele (T) and telomere length with longitudinal changes in HAAs. Joint models were used to examine associations of longitudinal changes in HAAs with death and interstitial lung disease (ILD). RESULTS The MUC5B risk allele (T) was associated with an absolute change in HAAs of 2.60% (95% CI 0.36% to 4.86%) per 10 years overall. This association was stronger among those with a telomere length below an age-adjusted percentile of 5% (p value for interaction=0.008). A 1% increase in HAAs per year was associated with 7% increase in mortality risk (rate ratio (RR)=1.07, 95% CI 1.02 to 1.12) for overall death and 34% increase in ILD (RR=1.34, 95% CI 1.20 to 1.50). Longer baseline telomere length was cross-sectionally associated with less HAAs from baseline scans, but not with longitudinal changes in HAAs. CONCLUSIONS Longitudinal increases in HAAs were associated with the MUC5B risk allele and a higher risk of death and ILD.
Collapse
Affiliation(s)
- John S Kim
- Department of Medicine, University of Virginia School of Medicine, Charlottesville, Virginia, USA
- Department of Medicine, Columbia University Irving Medical Center, New York, New York, USA
| | - Ani W Manichaikul
- Department of Public Health Sciences, University of Virginia School of Medicine, Charlottesville, Virginia, USA
- Center for Public Health Genomics, University of Virginia School of Medicine, Charlottesville, Virginia, USA
| | - Eric A Hoffman
- Department of Radiology, University of Iowa, Iowa City, Iowa, USA
| | - Pallavi Balte
- Department of Medicine, Columbia University Irving Medical Center, New York, New York, USA
| | - Michaela R Anderson
- Department of Medicine, Columbia University Irving Medical Center, New York, New York, USA
| | - Elana J Bernstein
- Department of Medicine, Columbia University Irving Medical Center, New York, New York, USA
| | - Purnema Madahar
- Department of Medicine, Columbia University Irving Medical Center, New York, New York, USA
| | - Elizabeth C Oelsner
- Department of Medicine, Columbia University Irving Medical Center, New York, New York, USA
| | - Steven M Kawut
- Department of Medicine, Perelman School of Medicine University of Pennsylvania, Philadelphia, Pennsylvania, USA
- Department of Biostatistics and Epidemiology, Perelman School of Medicine University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Artur Wysoczanski
- Department of Medicine, Columbia University Irving Medical Center, New York, New York, USA
| | - Andrew F Laine
- Department of Biomedical Engineering, Columbia University, New York, New York, USA
| | | | - Jennie Z Ma
- Department of Public Health Sciences, University of Virginia School of Medicine, Charlottesville, Virginia, USA
| | - Margaret A Taub
- Department of Biostatistics, Johns Hopkins University Bloomberg School of Public Health, Baltimore, Maryland, USA
| | - Rasika A Mathias
- Department of Biostatistics, Johns Hopkins University Bloomberg School of Public Health, Baltimore, Maryland, USA
- Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA
| | - Stephen S Rich
- Department of Public Health Sciences, University of Virginia School of Medicine, Charlottesville, Virginia, USA
- Center for Public Health Genomics, University of Virginia School of Medicine, Charlottesville, Virginia, USA
| | - Jerome I Rotter
- Department of Pediatrics, Harbor-UCLA Medical Center, Torrance, California, USA
- The Institute for Translational Genomics and Population Sciences, The Lundquist Institute, Harbor-UCLA Medical Center, Torrance, California, USA
| | - Imre Noth
- Department of Medicine, University of Virginia School of Medicine, Charlottesville, Virginia, USA
| | - Christine Kim Garcia
- Department of Medicine, Columbia University Irving Medical Center, New York, New York, USA
| | - R Graham Barr
- Department of Medicine, Columbia University Irving Medical Center, New York, New York, USA
- Department of Epidemiology, Columbia University Mailman School of Public Health, New York, New York, USA
| | - Anna J Podolanczuk
- Division of Pulmonary and Critical Care, Weill Cornell Medical College, New York, New York, USA
| |
Collapse
|
22
|
Oldham JM, Allen RJ, Lorenzo-Salazar JM, Molyneaux PL, Ma SF, Joseph C, Kim JS, Guillen-Guio B, Hernández-Beeftink T, Kropski JA, Huang Y, Lee CT, Adegunsoye A, Pugashetti JV, Linderholm AL, Vo V, Strek ME, Jou J, Muñoz-Barrera A, Rubio-Rodriguez LA, Hubbard R, Hirani N, Whyte MKB, Hart S, Nicholson AG, Lancaster L, Parfrey H, Rassl D, Wallace W, Valenzi E, Zhang Y, Mychaleckyj J, Stockwell A, Kaminski N, Wolters PJ, Molina-Molina M, Banovich NE, Fahy WA, Martinez FJ, Hall IP, Tobin MD, Maher TM, Blackwell TS, Yaspan BL, Jenkins RG, Flores C, Wain LV, Noth I. PCSK6 and Survival in Idiopathic Pulmonary Fibrosis. Am J Respir Crit Care Med 2023; 207:1515-1524. [PMID: 36780644 PMCID: PMC10263132 DOI: 10.1164/rccm.202205-0845oc] [Citation(s) in RCA: 12] [Impact Index Per Article: 12.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/04/2022] [Accepted: 02/13/2023] [Indexed: 02/15/2023] Open
Abstract
Rationale: Idiopathic pulmonary fibrosis (IPF) is a devastating disease characterized by limited treatment options and high mortality. A better understanding of the molecular drivers of IPF progression is needed. Objectives: To identify and validate molecular determinants of IPF survival. Methods: A staged genome-wide association study was performed using paired genomic and survival data. Stage I cases were drawn from centers across the United States and Europe and stage II cases from Vanderbilt University. Cox proportional hazards regression was used to identify gene variants associated with differential transplantation-free survival (TFS). Stage I variants with nominal significance (P < 5 × 10-5) were advanced for stage II testing and meta-analyzed to identify those reaching genome-wide significance (P < 5 × 10-8). Downstream analyses were performed for genes and proteins associated with variants reaching genome-wide significance. Measurements and Main Results: After quality controls, 1,481 stage I cases and 397 stage II cases were included in the analysis. After filtering, 9,075,629 variants were tested in stage I, with 158 meeting advancement criteria. Four variants associated with TFS with consistent effect direction were identified in stage II, including one in an intron of PCSK6 (proprotein convertase subtilisin/kexin type 6) reaching genome-wide significance (hazard ratio, 4.11 [95% confidence interval, 2.54-6.67]; P = 9.45 × 10-9). PCSK6 protein was highly expressed in IPF lung parenchyma. PCSK6 lung staining intensity, peripheral blood gene expression, and plasma concentration were associated with reduced TFS. Conclusions: We identified four novel variants associated with IPF survival, including one in PCSK6 that reached genome-wide significance. Downstream analyses suggested that PCSK6 protein plays a potentially important role in IPF progression.
Collapse
Affiliation(s)
- Justin M. Oldham
- Division of Pulmonary and Critical Care Medicine, University of Michigan, Ann Arbor, Michigan
| | - Richard J. Allen
- Department of Health Sciences, University of Leicester, Leicester, United Kingdom
| | - Jose M. Lorenzo-Salazar
- Genomics Division, Instituto Tecnológico y de Energías Renovables, Santa Cruz de Tenerife, Spain
| | - Philip L. Molyneaux
- National Heart and Lung Institute, Imperial College London, London, United Kingdom
- Royal Brompton and Harefield Hospitals, Guy’s and St. Thomas’ NHS Foundation Trust, London, United Kingdom
| | - Shwu-Fan Ma
- Division of Pulmonary and Critical Care Medicine and
| | | | - John S. Kim
- Division of Pulmonary and Critical Care Medicine and
| | - Beatriz Guillen-Guio
- Department of Health Sciences, University of Leicester, Leicester, United Kingdom
- Research Unit, Hospital Universitario Nuestra Señora de Candelaria, Santa Cruz de Tenerife, Spain
| | - Tamara Hernández-Beeftink
- Research Unit, Hospital Universitario Nuestra Señora de Candelaria, Santa Cruz de Tenerife, Spain
- Research Unit, Hospital Universitario de Gran Canaria Dr. Negrin, Las Palmas de Gran Canaria, Spain
| | - Jonathan A. Kropski
- Division of Pulmonary and Critical Care Medicine, Vanderbilt University, Nashville, Tennessee
| | - Yong Huang
- Division of Pulmonary and Critical Care Medicine and
| | - Cathryn T. Lee
- Section of Pulmonary and Critical Care Medicine, University of Chicago, Chicago, Illinois
| | - Ayodeji Adegunsoye
- Section of Pulmonary and Critical Care Medicine, University of Chicago, Chicago, Illinois
| | - Janelle Vu Pugashetti
- Division of Pulmonary, Critical Care and Sleep Medicine, University of California, Davis, Davis, California
| | - Angela L. Linderholm
- Division of Pulmonary, Critical Care and Sleep Medicine, University of California, Davis, Davis, California
| | - Vivian Vo
- Division of Pulmonary, Critical Care and Sleep Medicine, University of California, Davis, Davis, California
| | - Mary E. Strek
- Section of Pulmonary and Critical Care Medicine, University of Chicago, Chicago, Illinois
| | - Jonathan Jou
- Department of Surgery, College of Medicine, University of Illinois, Peoria, Illinois
| | - Adrian Muñoz-Barrera
- Genomics Division, Instituto Tecnológico y de Energías Renovables, Santa Cruz de Tenerife, Spain
| | - Luis A. Rubio-Rodriguez
- Genomics Division, Instituto Tecnológico y de Energías Renovables, Santa Cruz de Tenerife, Spain
| | - Richard Hubbard
- Division of Epidemiology and Public Health, University of Nottingham, Nottingham, United Kingdom
- National Institute for Health Research, Nottingham Biomedical Research Centre, Nottingham University Hospitals NHS Trust, Nottingham, United Kingdom
| | - Nik Hirani
- Medical Research Council Centre for Inflammation Research, University of Edinburgh, Edinburgh, United Kingdom
| | - Moira K. B. Whyte
- Medical Research Council Centre for Inflammation Research, University of Edinburgh, Edinburgh, United Kingdom
| | - Simon Hart
- Respiratory Research Group, Hull York Medical School, Castle Hill Hospital, Cottingham, United Kingdom
| | - Andrew G. Nicholson
- National Heart and Lung Institute, Imperial College London, London, United Kingdom
- Royal Brompton and Harefield Hospitals, Guy’s and St. Thomas’ NHS Foundation Trust, London, United Kingdom
| | - Lisa Lancaster
- Division of Pulmonary and Critical Care Medicine, Vanderbilt University, Nashville, Tennessee
| | - Helen Parfrey
- Cambridge Interstitial Lung Disease Service, Royal Papworth Hospital, Cambridge, United Kingdom
| | - Doris Rassl
- Cambridge Interstitial Lung Disease Service, Royal Papworth Hospital, Cambridge, United Kingdom
| | - William Wallace
- Medical Research Council Centre for Inflammation Research, University of Edinburgh, Edinburgh, United Kingdom
| | - Eleanor Valenzi
- Division of Pulmonary, Allergy and Critical Care Medicine, University of Pittsburgh, Pittsburgh, Pennsylvania
| | - Yingze Zhang
- Division of Pulmonary, Allergy and Critical Care Medicine, University of Pittsburgh, Pittsburgh, Pennsylvania
| | - Josyf Mychaleckyj
- Center for Public Health Genomics, University of Virginia, Charlottesville, Virginia
| | | | - Naftali Kaminski
- Section of Pulmonary, Critical Care and Sleep Medicine, School of Medicine, Yale University, New Haven, Connecticut
| | - Paul J. Wolters
- Division of Pulmonary, Critical Care, Allergy and Sleep Medicine, University of California, San Francisco, San Francisco, California
| | - Maria Molina-Molina
- Servei de Pneumologia, Laboratori de Pneumologia Experimental, Instituto de Investigación Biomédica de Bellvitge, Campus de Bellvitge, Universitat de Barcelona, Barcelona, Spain
- Centro de Investigación Biomédica en Red de Enfermedades Respiratorias, Instituto de Salud Carlos III, Madrid, Spain
| | | | - William A. Fahy
- Discovery Medicine, GlaxoSmithKline, Stevenage, United Kingdom
| | | | - Ian P. Hall
- Division of Respiratory Medicine and
- National Institute for Health Research, Nottingham Biomedical Research Centre, Nottingham University Hospitals NHS Trust, Nottingham, United Kingdom
| | - Martin D. Tobin
- Department of Health Sciences, University of Leicester, Leicester, United Kingdom
- National Institute for Health Research, Leicester Respiratory Biomedical Research Centre, Glenfield Hospital, Leicester, United Kingdom
| | - Toby M. Maher
- National Heart and Lung Institute, Imperial College London, London, United Kingdom
- Division of Pulmonary and Critical Care Medicine, University of Southern California, Los Angeles, California; and
| | - Timothy S. Blackwell
- Division of Pulmonary and Critical Care Medicine, Vanderbilt University, Nashville, Tennessee
| | | | - R. Gisli Jenkins
- National Heart and Lung Institute, Imperial College London, London, United Kingdom
- Royal Brompton and Harefield Hospitals, Guy’s and St. Thomas’ NHS Foundation Trust, London, United Kingdom
| | - Carlos Flores
- Genomics Division, Instituto Tecnológico y de Energías Renovables, Santa Cruz de Tenerife, Spain
- Research Unit, Hospital Universitario Nuestra Señora de Candelaria, Santa Cruz de Tenerife, Spain
- Centro de Investigación Biomédica en Red de Enfermedades Respiratorias, Instituto de Salud Carlos III, Madrid, Spain
- Facultad de Ciencias de la Salud, Universidad Fernando Pessoa Canarias, Las Palmas de Gran Canaria, Spain
| | - Louise V. Wain
- Department of Health Sciences, University of Leicester, Leicester, United Kingdom
- National Institute for Health Research, Leicester Respiratory Biomedical Research Centre, Glenfield Hospital, Leicester, United Kingdom
| | - Imre Noth
- Division of Pulmonary and Critical Care Medicine and
| |
Collapse
|
23
|
Khramtsova EA, Wilson MA, Martin J, Winham SJ, He KY, Davis LK, Stranger BE. Quality control and analytic best practices for testing genetic models of sex differences in large populations. Cell 2023; 186:2044-2061. [PMID: 37172561 PMCID: PMC10266536 DOI: 10.1016/j.cell.2023.04.014] [Citation(s) in RCA: 10] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/26/2022] [Revised: 01/31/2023] [Accepted: 04/07/2023] [Indexed: 05/15/2023]
Abstract
Phenotypic sex-based differences exist for many complex traits. In other cases, phenotypes may be similar, but underlying biology may vary. Thus, sex-aware genetic analyses are becoming increasingly important for understanding the mechanisms driving these differences. To this end, we provide a guide outlining the current best practices for testing various models of sex-dependent genetic effects in complex traits and disease conditions, noting that this is an evolving field. Insights from sex-aware analyses will not only teach us about the biology of complex traits but also aid in achieving the goals of precision medicine and health equity for all.
Collapse
Affiliation(s)
- Ekaterina A Khramtsova
- Population Analytics and Insights, Data Science Analytics & Insights, Janssen R&D, Lower Gwynedd Township, PA, USA.
| | - Melissa A Wilson
- School of Life Sciences, Center for Evolution and Medicine, Biodesign Center for Mechanisms of Evolution, Arizona State University, Tempe, AZ 85282, USA
| | - Joanna Martin
- Centre for Neuropsychiatric Genetics and Genomics, Division of Psychological Medicine and Clinical Neurosciences, Cardiff University, Cardiff, UK
| | - Stacey J Winham
- Department of Quantitative Health Sciences, Division of Computational Biology, Mayo Clinic, Rochester, MN, USA
| | - Karen Y He
- Population Analytics and Insights, Data Science Analytics & Insights, Janssen R&D, Lower Gwynedd Township, PA, USA
| | - Lea K Davis
- Division of Genetic Medicine, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, USA; Department of Psychiatry and Behavioral Sciences, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Barbara E Stranger
- Center for Genetic Medicine, Department of Pharmacology, Northwestern University, Chicago, IL, USA.
| |
Collapse
|
24
|
Mavaddat N, Ficorella L, Carver T, Lee A, Cunningham AP, Lush M, Dennis J, Tischkowitz M, Downes K, Hu D, Hahnen E, Schmutzler RK, Stockley TL, Downs GS, Zhang T, Chiarelli AM, Bojesen SE, Liu C, Chung WK, Pardo M, Feliubadaló L, Balmaña J, Simard J, Antoniou AC, Easton DF. Incorporating Alternative Polygenic Risk Scores into the BOADICEA Breast Cancer Risk Prediction Model. Cancer Epidemiol Biomarkers Prev 2023; 32:422-427. [PMID: 36649146 PMCID: PMC9986688 DOI: 10.1158/1055-9965.epi-22-0756] [Citation(s) in RCA: 11] [Impact Index Per Article: 11.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/11/2022] [Revised: 11/09/2022] [Accepted: 01/10/2023] [Indexed: 01/18/2023] Open
Abstract
BACKGROUND The multifactorial risk prediction model BOADICEA enables identification of women at higher or lower risk of developing breast cancer. BOADICEA models genetic susceptibility in terms of the effects of rare variants in breast cancer susceptibility genes and a polygenic component, decomposed into an unmeasured and a measured component - the polygenic risk score (PRS). The current version was developed using a 313 SNP PRS. Here, we evaluated approaches to incorporating this PRS and alternative PRS in BOADICEA. METHODS The mean, SD, and proportion of the overall polygenic component explained by the PRS (α2) need to be estimated. $\alpha $ was estimated using logistic regression, where the age-specific log-OR is constrained to be a function of the age-dependent polygenic relative risk in BOADICEA; and using a retrospective likelihood (RL) approach that models, in addition, the unmeasured polygenic component. RESULTS Parameters were computed for 11 PRS, including 6 variations of the 313 SNP PRS used in clinical trials and implementation studies. The logistic regression approach underestimates $\alpha $, as compared with the RL estimates. The RL $\alpha $ estimates were very close to those obtained by assuming proportionality to the OR per 1 SD, with the constant of proportionality estimated using the 313 SNP PRS. Small variations in the SNPs included in the PRS can lead to large differences in the mean. CONCLUSIONS BOADICEA can be readily adapted to different PRS in a manner that maintains consistency of the model. IMPACT : The methods described facilitate comprehensive breast cancer risk assessment.
Collapse
Affiliation(s)
- Nasim Mavaddat
- Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge, Cambridge, United Kingdom
| | - Lorenzo Ficorella
- Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge, Cambridge, United Kingdom
| | - Tim Carver
- Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge, Cambridge, United Kingdom
| | - Andrew Lee
- Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge, Cambridge, United Kingdom
| | - Alex P. Cunningham
- Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge, Cambridge, United Kingdom
| | - Michael Lush
- Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge, Cambridge, United Kingdom
| | - Joe Dennis
- Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge, Cambridge, United Kingdom
| | - Marc Tischkowitz
- Department of Medical Genetics and National Institute for Health Research, Cambridge Biomedical Research Centre, The University of Cambridge, Cambridge, United Kingdom
| | - Kate Downes
- Cambridge Genomics Laboratory, Cambridge University Hospitals NHS Foundation Trust, Cambridge, United Kingdom
| | - Donglei Hu
- Division of General Internal Medicine, Department of Medicine, University of California San Francisco, San Francisco, California
| | - Eric Hahnen
- Center for Familial Breast and Ovarian Cancer, Faculty of Medicine and University Hospital Cologne, University of Cologne, Cologne, Germany
- Center for Integrated Oncology (CIO), Faculty of Medicine and University Hospital Cologne, University of Cologne, Cologne, Germany
| | - Rita K. Schmutzler
- Center for Familial Breast and Ovarian Cancer, Faculty of Medicine and University Hospital Cologne, University of Cologne, Cologne, Germany
- Center for Integrated Oncology (CIO), Faculty of Medicine and University Hospital Cologne, University of Cologne, Cologne, Germany
- Center for Molecular Medicine Cologne (CMMC), Faculty of Medicine and University Hospital Cologne, University of Cologne, Cologne, Germany
| | - Tracy L. Stockley
- Advanced Molecular Diagnostics Laboratory, Princess Margaret Cancer Centre, Toronto, Ontario, Canada
- Department of Laboratory Medicine and Pathobiology, The University of Toronto, Ontario, Canada
- Division of Clinical Laboratory Genetics, Laboratory Medicine Program, University Health Network, Toronto, Canada
| | - Gregory S. Downs
- Advanced Molecular Diagnostics Laboratory, Princess Margaret Cancer Centre, Toronto, Ontario, Canada
- Division of Clinical Laboratory Genetics, Laboratory Medicine Program, University Health Network, Toronto, Canada
| | - Tong Zhang
- Advanced Molecular Diagnostics Laboratory, Princess Margaret Cancer Centre, Toronto, Ontario, Canada
| | - Anna M. Chiarelli
- Dalla Lana School of Public Health, University of Toronto, Toronto, Ontario, Canada
- Ontario Health, Cancer Care Ontario, Toronto, Ontario, Canada
| | - Stig E. Bojesen
- Copenhagen General Population Study, Herlev and Gentofte Hospital, Copenhagen University Hospital, Herlev, Denmark
- Department of Clinical Biochemistry, Herlev and Gentofte Hospital, Copenhagen University Hospital, Herlev, Denmark
- Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Cong Liu
- Department of Biomedical Informatics, Columbia University Irving Medical Center, New York, New York
| | - Wendy K. Chung
- Departments of Pediatrics and Medicine, Columbia University, New York, New York
| | - Monica Pardo
- Hereditary Cancer Genetics Group, Vall d'Hebron Institut d'Oncologia, Barcelona, Spain
| | - Lidia Feliubadaló
- Hereditary Cancer Program, Catalan Institute of Oncology (ICO), L'Hospitalet de Llobregat, Spain
- Program in Molecular Mechanisms and Experimental Therapy in Oncology (Oncobell), IDIBELL, L'Hospitalet de Llobregat, Spain
- Centro de Investigación Biomédica en Red de Cáncer (CIBERONC), Madrid, Spain
| | - Judith Balmaña
- Hereditary Cancer Genetics Group, Vall d'Hebron Institut d'Oncologia, Barcelona, Spain
- Medical Oncology Department, University Hospital of Vall d'Hebron, Barcelona, Spain
| | - Jacques Simard
- Department of Molecular Medicine, Université Laval and CHU de Québec-Université Laval Research Center, Québec, Canada
| | - Antonis C. Antoniou
- Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge, Cambridge, United Kingdom
| | - Douglas F. Easton
- Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge, Cambridge, United Kingdom
- Centre for Cancer Genetic Epidemiology, Department of Oncology, University of Cambridge, Cambridge, United Kingdom
| |
Collapse
|
25
|
Zhou A, Hyppönen E. Vitamin D deficiency and C-reactive protein: a bidirectional Mendelian randomization study. Int J Epidemiol 2023; 52:260-271. [PMID: 35579027 PMCID: PMC9908047 DOI: 10.1093/ije/dyac087] [Citation(s) in RCA: 36] [Impact Index Per Article: 36.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/14/2021] [Accepted: 04/08/2022] [Indexed: 12/27/2022] Open
Abstract
BACKGROUND Low vitamin D status is often associated with systemic low-grade inflammation as reflected by elevated C-reactive protein (CRP) levels. We investigated the causality and direction of the association between vitamin D status and CRP using linear and non-linear Mendelian randomization (MR) analyses. METHODS MR analyses were conducted using data from 294 970 unrelated participants of White-British ancestry from the UK Biobank. Serum 25-hydroxyvitamin D [25(OH)D] and CRP concentrations were instrumented using 35 and 46 genome-wide significant variants, respectively. RESULTS In non-linear MR analysis, genetically predicted serum 25(OH)D had an L-shaped association with serum CRP, where CRP levels decreased sharply with increasing 25(OH)D concentration for participants within the deficiency range (<25 nmol/L) and levelled off at ∼50 nmol/L of 25(OH)D (Pnon-linear = 1.49E-4). Analyses using several pleiotropy-robust methods provided consistent results in stratified MR analyses, confirming the inverse association between 25(OH)D and CRP in the deficiency range (P = 1.10E-05) but not with higher concentrations. Neither linear or non-linear MR analysis supported a causal effect of serum CRP level on 25(OH)D concentration (Plinear = 0.32 and Pnon-linear = 0.76). CONCLUSION The observed association between 25(OH)D and CRP is likely to be caused by vitamin D deficiency. Correction of low vitamin D status may reduce chronic inflammation.
Collapse
Affiliation(s)
- Ang Zhou
- Australian Center for Precision Health, University of South Australia Cancer Research Institute, Adelaide, Australia
- South Australian Health and Medical Research Institute, Adelaide, Australia
| | - Elina Hyppönen
- Corresponding author. Australian Center for Precision Health, University of South Australia Cancer Research Institute, GPO Box 2471, Adelaide, SA 5001, Australia. E-mail:
| |
Collapse
|
26
|
Mitchell RE, Hartley AE, Walker VM, Gkatzionis A, Yarmolinsky J, Bell JA, Chong AHW, Paternoster L, Tilling K, Smith GD. Strategies to investigate and mitigate collider bias in genetic and Mendelian randomisation studies of disease progression. PLoS Genet 2023; 19:e1010596. [PMID: 36821633 PMCID: PMC9949638 DOI: 10.1371/journal.pgen.1010596] [Citation(s) in RCA: 11] [Impact Index Per Article: 11.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/24/2023] Open
Abstract
Genetic studies of disease progression can be used to identify factors that may influence survival or prognosis, which may differ from factors that influence on disease susceptibility. Studies of disease progression feed directly into therapeutics for disease, whereas studies of incidence inform prevention strategies. However, studies of disease progression are known to be affected by collider (also known as "index event") bias since the disease progression phenotype can only be observed for individuals who have the disease. This applies equally to observational and genetic studies, including genome-wide association studies and Mendelian randomisation (MR) analyses. In this paper, our aim is to review several statistical methods that can be used to detect and adjust for index event bias in studies of disease progression, and how they apply to genetic and MR studies using both individual- and summary-level data. Methods to detect the presence of index event bias include the use of negative controls, a comparison of associations between risk factors for incidence in individuals with and without the disease, and an inspection of Miami plots. Methods to adjust for the bias include inverse probability weighting (with individual-level data), or Slope-Hunter and Dudbridge et al.'s index event bias adjustment (when only summary-level data are available). We also outline two approaches for sensitivity analysis. We then illustrate how three methods to minimise bias can be used in practice with two applied examples. Our first example investigates the effects of blood lipid traits on mortality from coronary heart disease, while our second example investigates genetic associations with breast cancer mortality.
Collapse
Affiliation(s)
- Ruth E. Mitchell
- MRC Integrative Epidemiology Unit at the University of Bristol, Bristol, United Kingdom
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, United Kingdom
| | - April E. Hartley
- MRC Integrative Epidemiology Unit at the University of Bristol, Bristol, United Kingdom
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, United Kingdom
| | - Venexia M. Walker
- MRC Integrative Epidemiology Unit at the University of Bristol, Bristol, United Kingdom
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, United Kingdom
- Department of Surgery, University of Pennsylvania Perelman School of Medicine, Philadelphia, Pennsylvania, United States of America
| | - Apostolos Gkatzionis
- MRC Integrative Epidemiology Unit at the University of Bristol, Bristol, United Kingdom
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, United Kingdom
| | - James Yarmolinsky
- MRC Integrative Epidemiology Unit at the University of Bristol, Bristol, United Kingdom
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, United Kingdom
| | - Joshua A. Bell
- MRC Integrative Epidemiology Unit at the University of Bristol, Bristol, United Kingdom
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, United Kingdom
| | - Amanda H. W. Chong
- MRC Integrative Epidemiology Unit at the University of Bristol, Bristol, United Kingdom
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, United Kingdom
| | - Lavinia Paternoster
- MRC Integrative Epidemiology Unit at the University of Bristol, Bristol, United Kingdom
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, United Kingdom
| | - Kate Tilling
- MRC Integrative Epidemiology Unit at the University of Bristol, Bristol, United Kingdom
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, United Kingdom
| | - George Davey Smith
- MRC Integrative Epidemiology Unit at the University of Bristol, Bristol, United Kingdom
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, United Kingdom
| |
Collapse
|
27
|
Schooling CM, Zhao JV. Insights into Causal Cardiovascular Risk Factors from Mendelian Randomization. Curr Cardiol Rep 2023; 25:67-76. [PMID: 36640254 DOI: 10.1007/s11886-022-01829-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 11/07/2022] [Indexed: 01/15/2023]
Abstract
PURPOSE OF THE REVIEW This review summarizes major insights into causal risk factors for cardiovascular disease (CVD) by using Mendelian randomization (MR) to obtain unconfounded estimates, contextualized within its strengths and weaknesses. RECENT FINDINGS MR studies have confirmed the role of major CVD risk factors, including alcohol, smoking, adiposity, blood pressure, type 2 diabetes, lipids, and possibly inflammation, but added that the relation with alcohol is likely linear, confirmed the role of diastolic blood pressure, identified apolipoprotein B as the major target lipid, and foreshadowed results of some trials concerning anti-inflammatories. Identifying a healthy diet and the role of early life influences, such as birth weight, has proved more difficult. Use of MR has winnowed empirically driven hypotheses about CVD into a set of genetically validated targets of intervention. Greater inclusion of global diversity in genetic studies and the use of an overarching framework would enable even more informative MR studies.
Collapse
Affiliation(s)
- C M Schooling
- School of Public Health and Health Policy, City University of New York, 55 West 125th St, NY, 10027, New York, USA. .,School of Public Health, LKS Faculty of Medicine, The University of Hong Kong, Hong Kong SAR, China.
| | - J V Zhao
- School of Public Health, LKS Faculty of Medicine, The University of Hong Kong, Hong Kong SAR, China
| |
Collapse
|
28
|
Alonso-Gonzalez A, Tosco-Herrera E, Molina-Molina M, Flores C. Idiopathic pulmonary fibrosis and the role of genetics in the era of precision medicine. Front Med (Lausanne) 2023; 10:1152211. [PMID: 37181377 PMCID: PMC10172674 DOI: 10.3389/fmed.2023.1152211] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/27/2023] [Accepted: 04/03/2023] [Indexed: 05/16/2023] Open
Abstract
Idiopathic pulmonary fibrosis (IPF) is a chronic, rare progressive lung disease, characterized by lung scarring and the irreversible loss of lung function. Two anti-fibrotic drugs, nintedanib and pirfenidone, have been demonstrated to slow down disease progression, although IPF mortality remains a challenge and the patients die after a few years from diagnosis. Rare pathogenic variants in genes that are involved in the surfactant metabolism and telomere maintenance, among others, have a high penetrance and tend to co-segregate with the disease in families. Common recurrent variants in the population with modest effect sizes have been also associated with the disease risk and progression. Genome-wide association studies (GWAS) support at least 23 genetic risk loci, linking the disease pathogenesis with unexpected molecular pathways including cellular adhesion and signaling, wound healing, barrier function, airway clearance, and innate immunity and host defense, besides the surfactant metabolism and telomere biology. As the cost of high-throughput genomic technologies continuously decreases and new technologies and approaches arise, their widespread use by clinicians and researchers is efficiently contributing to a better understanding of the pathogenesis of progressive pulmonary fibrosis. Here we provide an overview of the genetic factors known to be involved in IPF pathogenesis and discuss how they will continue to further advance in this field. We also discuss how genomic technologies could help to further improve IPF diagnosis and prognosis as well as for assessing genetic risk in unaffected relatives. The development and validation of evidence-based guidelines for genetic-based screening of IPF will allow redefining and classifying this disease relying on molecular characteristics and contribute to the implementation of precision medicine approaches.
Collapse
Affiliation(s)
- Aitana Alonso-Gonzalez
- Unidad de Investigación, Hospital Universitario Nuestra Señora de Candelaria, Santa Cruz de Tenerife, Spain
- Universidad de Santiago de Compostela, Santiago de Compostela, Spain
| | - Eva Tosco-Herrera
- Unidad de Investigación, Hospital Universitario Nuestra Señora de Candelaria, Santa Cruz de Tenerife, Spain
| | - Maria Molina-Molina
- Servei de Pneumologia, Laboratori de Pneumologia Experimental, IDIBELL, Barcelona, Spain
- Campus de Bellvitge, Universitat de Barcelona, Barcelona, Spain
- CIBER de Enfermedades Respiratorias, Instituto de Salud Carlos III, Madrid, Spain
| | - Carlos Flores
- Unidad de Investigación, Hospital Universitario Nuestra Señora de Candelaria, Santa Cruz de Tenerife, Spain
- CIBER de Enfermedades Respiratorias, Instituto de Salud Carlos III, Madrid, Spain
- Genomics Division, Instituto Tecnológico y de Energías Renovables (ITER), Santa Cruz de Tenerife, Spain
- Facultad de Ciencias de la Salud, Universidad Fernando Pessoa Canarias, Las Palmas de Gran Canaria, Spain
- *Correspondence: Carlos Flores,
| |
Collapse
|
29
|
van der Vis JJ, Prasse A, Renzoni EA, Stock CJW, Caliskan C, Maher TM, Bonella F, Borie R, Crestani B, Petrek M, Wuyts WA, Wind AE, Molyneaux PL, Grutters JC, van Moorsel CHM. MUC5B rs35705950 minor allele associates with older age and better survival in idiopathic pulmonary fibrosis. Respirology 2022; 28:455-464. [PMID: 36571111 DOI: 10.1111/resp.14440] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/01/2022] [Accepted: 12/07/2022] [Indexed: 12/27/2022]
Abstract
BACKGROUND AND OBJECTIVE The minor T-allele of the MUC5B promoter polymorphism rs35705950 is strongly associated with idiopathic pulmonary fibrosis (IPF). However, conflicting results have been reported on the relationship between the MUC5B minor allele and survival and it is unknown whether a specific subgroup of IPF patients might benefit from MUC5B minor allele carriage. We investigated the association between MUC5B rs35705950, survival and patient characteristics in a real-world population of European IPF patients. METHODS In this retrospective study, 1751 patients with IPF from 8 European centres were included. MUC5B rs35705950 genotype, demographics, clinical characteristics at diagnosis and survival data were analysed. RESULTS In a multi-variate Cox proportional hazard model the MUC5B minor allele was a significant independent predictor of survival when adjusted for age, sex, high resolution computed tomography pattern, smoking behaviour and pulmonary function tests in IPF. MUC5B minor allele carriers were significantly older at diagnosis (p = 0.001). The percentage of MUC5B minor allele carriers increased significantly with age from 44% in patients aged <56 year, to 63% in patients aged >75. In IPF patients aged <56, the MUC5B minor allele was not associated with survival. In IPF patients aged ≥56, survival was significantly better for MUC5B minor allele carriers (45 months [CI: 42-49]) compared to non-carriers (29 months [CI: 26-33]; p = 4 × 10-12 ). CONCLUSION MUC5B minor allele carriage associates with a better median transplant-free survival of 16 months in the European IPF population aged over 56 years. MUC5B genotype status might aid disease prognostication in clinical management of IPF patients.
Collapse
Affiliation(s)
- Joanne J van der Vis
- St Antonius ILD Center of Excellence, Department of Pulmonology, St. Antonius Hospital, Nieuwegein, the Netherlands.,St Antonius ILD Center of Excellence, Department of Clinical Chemistry, St. Antonius Hospital, Nieuwegein, the Netherlands.,European Reference Network (ERN) ILD core Network center
| | - Antje Prasse
- European Reference Network (ERN) ILD core Network center.,Division of Pulmonology, Hannover Medical School & DZL BREATH, Hannover, Germany.,Fraunhofer Institute ITEM, Hannover, Germany
| | - Elisabetta A Renzoni
- Interstitial Lung Disease Unit, Royal Brompton and Harefield Clinical Group, Guy's and St Thomas' NHS Foundation Trust, London, UK.,Margaret Turner Warwick Centre for Fibrosing Lung Disease, National Heart and Lung Institute, Imperial College London, London, UK
| | - Carmel J W Stock
- Interstitial Lung Disease Unit, Royal Brompton and Harefield Clinical Group, Guy's and St Thomas' NHS Foundation Trust, London, UK.,Margaret Turner Warwick Centre for Fibrosing Lung Disease, National Heart and Lung Institute, Imperial College London, London, UK
| | - Canay Caliskan
- European Reference Network (ERN) ILD core Network center.,Division of Pulmonology, Hannover Medical School & DZL BREATH, Hannover, Germany
| | - Toby M Maher
- National Heart and Lung Institute, Imperial College London, London, UK.,Keck Medicine of University of Southern California, Los Angeles, California, USA
| | - Francesco Bonella
- European Reference Network (ERN) ILD core Network center.,Center for Interstitial and Rare Lung Diseases, Pneumology Department, Ruhrlandklinik University Hospital, University of Duisburg-Essen, Essen, Germany
| | - Raphael Borie
- European Reference Network (ERN) ILD core Network center.,Laboratoire d'excellence INFLAMEX, Inserm U1152, Paris, France.,Service de Pneumologie A, Hôpital Bichat, Paris, France
| | - Bruno Crestani
- European Reference Network (ERN) ILD core Network center.,Laboratoire d'excellence INFLAMEX, Inserm U1152, Paris, France.,Service de Pneumologie A, Hôpital Bichat, Paris, France
| | - Martin Petrek
- University Hospital Olomouc - Experimental Medicine, Olomouc, Czech Republic.,Faculty of Medicine and Dentistry Palacky University - Pathophysiology, Molecular and Translational Medicine, Olomouc, Czech Republic
| | - Wim A Wuyts
- European Reference Network (ERN) ILD core Network center.,Unit for Interstitial Lung Diseases, Department of Respiratory Medicine, University Hospitals, Leuven, Belgium
| | - Anne E Wind
- St Antonius ILD Center of Excellence, Department of Pulmonology, St. Antonius Hospital, Nieuwegein, the Netherlands.,European Reference Network (ERN) ILD core Network center
| | - Philip L Molyneaux
- Interstitial Lung Disease Unit, Royal Brompton and Harefield Clinical Group, Guy's and St Thomas' NHS Foundation Trust, London, UK.,National Heart and Lung Institute, Imperial College London, London, UK
| | - Jan C Grutters
- St Antonius ILD Center of Excellence, Department of Pulmonology, St. Antonius Hospital, Nieuwegein, the Netherlands.,European Reference Network (ERN) ILD core Network center.,Division of Heart and Lungs, University Medical Center Utrecht, Utrecht, the Netherlands
| | - Coline H M van Moorsel
- St Antonius ILD Center of Excellence, Department of Pulmonology, St. Antonius Hospital, Nieuwegein, the Netherlands.,European Reference Network (ERN) ILD core Network center.,Division of Heart and Lungs, University Medical Center Utrecht, Utrecht, the Netherlands
| |
Collapse
|
30
|
McDermott G, Gill R, Gagne S, Byrne S, Huang W, Cui J, Prisco L, Zaccardelli A, Martin L, Kronzer VL, Moll M, Cho MH, Shadick N, Dellaripa PF, Doyle T, Sparks JA. Associations of the MUC5B promoter variant with timing of interstitial lung disease and rheumatoid arthritis onset. Rheumatology (Oxford) 2022; 61:4915-4923. [PMID: 35289841 PMCID: PMC9707325 DOI: 10.1093/rheumatology/keac152] [Citation(s) in RCA: 12] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/15/2021] [Revised: 03/04/2022] [Indexed: 01/11/2023] Open
Abstract
OBJECTIVES To investigate the associations of the common MUC5B promoter variant with timing of RA-associated interstitial lung disease (RA-ILD) and RA onset. METHODS We identified patients with RA meeting 2010 ACR/EULAR criteria and available genotype information in the Mass General Brigham Biobank, a multihospital biospecimen and clinical data collection research study. We determined RA-ILD presence by reviewing all RA patients who had CT imaging, lung biopsy or autopsy results. We determined the dates of RA and RA-ILD diagnoses by manual records review. We examined the associations of the MUC5B promoter variant (G>T at rs35705950) with RA-ILD, RA-ILD occurring before or within 2 years of RA diagnosis and RA diagnosis at age >55 years. We used multivariable logistic regression to estimate odds ratios (ORs) for each outcome by MUC5B promoter variant status, adjusting for potential confounders including genetic ancestry and smoking. RESULTS We identified 1005 RA patients with available genotype data for rs35705950 (mean age 45 years, 79% female, 81% European ancestry). The MUC5B promoter variant was present in 155 (15.4%) and was associated with RA-ILD [multivariable OR 3.34 (95% CI 1.97, 5.60)], RA-ILD before or within 2 years of RA diagnosis [OR 4.01 (95% CI 1.78, 8.80)] and RA onset after age 55 years [OR 1.52 (95% CI 1.08, 2.12)]. CONCLUSIONS The common MUC5B promoter variant was associated with RA-ILD onset earlier in the RA disease course and older age of RA onset. These findings suggest that the MUC5B promoter variant may impact RA-ILD risk early in the RA disease course, particularly in patients with older-onset RA.
Collapse
Affiliation(s)
- Gregory McDermott
- Division of Rheumatology, Inflammation, and Immunity, Brigham and Women's Hospital.,Department of Medicine, Harvard Medical School
| | - Ritu Gill
- Department of Medicine, Harvard Medical School.,Department of Radiology, Beth Israel Deaconess Medical Center
| | - Staci Gagne
- Department of Medicine, Harvard Medical School.,Department of Radiology, Brigham and Women's Hospital, Boston, MA
| | - Suzanne Byrne
- Department of Medicine, Harvard Medical School.,Department of Radiology, Brigham and Women's Hospital, Boston, MA
| | - Weixing Huang
- Division of Rheumatology, Inflammation, and Immunity, Brigham and Women's Hospital
| | - Jing Cui
- Division of Rheumatology, Inflammation, and Immunity, Brigham and Women's Hospital.,Department of Medicine, Harvard Medical School
| | - Lauren Prisco
- Division of Rheumatology, Inflammation, and Immunity, Brigham and Women's Hospital
| | | | - Lily Martin
- Division of Rheumatology, Inflammation, and Immunity, Brigham and Women's Hospital
| | | | - Matthew Moll
- Department of Medicine, Harvard Medical School.,Division of Pulmonary and Critical Care Medicine.,Channing Division of Network Medicine, Brigham and Women's Hospital, Boston, MA, USA
| | - Michael H Cho
- Department of Medicine, Harvard Medical School.,Division of Pulmonary and Critical Care Medicine.,Channing Division of Network Medicine, Brigham and Women's Hospital, Boston, MA, USA
| | - Nancy Shadick
- Division of Rheumatology, Inflammation, and Immunity, Brigham and Women's Hospital.,Department of Medicine, Harvard Medical School
| | - Paul F Dellaripa
- Division of Rheumatology, Inflammation, and Immunity, Brigham and Women's Hospital.,Department of Medicine, Harvard Medical School
| | - Tracy Doyle
- Department of Medicine, Harvard Medical School.,Division of Pulmonary and Critical Care Medicine
| | - Jeffrey A Sparks
- Division of Rheumatology, Inflammation, and Immunity, Brigham and Women's Hospital.,Department of Medicine, Harvard Medical School
| |
Collapse
|
31
|
Verma A, Minnier J, Wan ES, Huffman JE, Gao L, Joseph J, Ho YL, Wu WC, Cho K, Gorman BR, Rajeevan N, Pyarajan S, Garcon H, Meigs JB, Sun YV, Reaven PD, McGeary JE, Suzuki A, Gelernter J, Lynch JA, Petersen JM, Zekavat SM, Natarajan P, Dalal S, Jhala DN, Arjomandi M, Gatsby E, Lynch KE, Bonomo RA, Freiberg M, Pathak GA, Zhou JJ, Donskey CJ, Madduri RK, Wells QS, Huang RDL, Polimanti R, Chang KM, Liao KP, Tsao PS, Wilson PWF, Hung AM, O’Donnell CJ, Gaziano JM, Hauger RL, Iyengar SK, Luoh SW. A MUC5B Gene Polymorphism, rs35705950-T, Confers Protective Effects Against COVID-19 Hospitalization but Not Severe Disease or Mortality. Am J Respir Crit Care Med 2022; 206:1220-1229. [PMID: 35771531 PMCID: PMC9746845 DOI: 10.1164/rccm.202109-2166oc] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/03/2023] Open
Abstract
Rationale: A common MUC5B gene polymorphism, rs35705950-T, is associated with idiopathic pulmonary fibrosis (IPF), but its role in severe acute respiratory syndrome coronavirus 2 infection and disease severity is unclear. Objectives: To assess whether rs35705950-T confers differential risk for clinical outcomes associated with coronavirus disease (COVID-19) infection among participants in the Million Veteran Program (MVP). Methods: The MUC5B rs35705950-T allele was directly genotyped among MVP participants; clinical events and comorbidities were extracted from the electronic health records. Associations between the incidence or severity of COVID-19 and rs35705950-T were analyzed within each ancestry group in the MVP followed by transancestry meta-analysis. Replication and joint meta-analysis were conducted using summary statistics from the COVID-19 Host Genetics Initiative (HGI). Sensitivity analyses with adjustment for additional covariates (body mass index, Charlson comorbidity index, smoking, asbestosis, rheumatoid arthritis with interstitial lung disease, and IPF) and associations with post-COVID-19 pneumonia were performed in MVP subjects. Measurements and Main Results: The rs35705950-T allele was associated with fewer COVID-19 hospitalizations in transancestry meta-analyses within the MVP (Ncases = 4,325; Ncontrols = 507,640; OR = 0.89 [0.82-0.97]; P = 6.86 × 10-3) and joint meta-analyses with the HGI (Ncases = 13,320; Ncontrols = 1,508,841; OR, 0.90 [0.86-0.95]; P = 8.99 × 10-5). The rs35705950-T allele was not associated with reduced COVID-19 positivity in transancestry meta-analysis within the MVP (Ncases = 19,168/Ncontrols = 492,854; OR, 0.98 [0.95-1.01]; P = 0.06) but was nominally significant (P < 0.05) in the joint meta-analysis with the HGI (Ncases = 44,820; Ncontrols = 1,775,827; OR, 0.97 [0.95-1.00]; P = 0.03). Associations were not observed with severe outcomes or mortality. Among individuals of European ancestry in the MVP, rs35705950-T was associated with fewer post-COVID-19 pneumonia events (OR, 0.82 [0.72-0.93]; P = 0.001). Conclusions: The MUC5B variant rs35705950-T may confer protection in COVID-19 hospitalizations.
Collapse
Affiliation(s)
- Anurag Verma
- Corporal Michael J. Crescenz VA Medical Center, Philadelphia, Pennsylvania;,Department of Medicine, Perelman School of Medicine, and
| | - Jessica Minnier
- OHSU-PSU School of Public Health and,Knight Cancer Institute, Oregon Health & Science University, Portland, Oregon;,VA Portland Health Care System, Portland, Oregon
| | - Emily S. Wan
- Department of Medicine, Pulmonary, Critical Care, Sleep, and Allergy Section,,Channing Division of Network Medicine and
| | | | - Lina Gao
- Knight Cancer Institute, Oregon Health & Science University, Portland, Oregon;,VA Portland Health Care System, Portland, Oregon
| | - Jacob Joseph
- Department of Medicine,,Medicine, Cardiovascular, Brigham & Women’s Hospital, Boston, Massachusetts
| | | | - Wen-Chih Wu
- Department of Medicine, Cardiology, Providence VA Healthcare System, Providence, Rhode Island;,Alpert Medical School & School of Public Health, Brown University, Providence, Rhode Island
| | - Kelly Cho
- MAVERIC,,Medicine, Aging, Brigham & Women’s Hospital and
| | | | - Nallakkandi Rajeevan
- Yale Center for Medical Informatics,,Clinical Epidemiology Research Center (CERC)
| | - Saiju Pyarajan
- MAVERIC,,Department of Medicine, Harvard Medical School, Boston, Massachusetts
| | | | | | - Yan V. Sun
- Epidemiology, School of Public Health and,Atlanta VA Healthcare System, Decatur, Georgia
| | - Peter D. Reaven
- Department of Medicine, Phoenix VA Healthcare System, Phoenix, Arizona;,College of Medicine, University of Arizona, Phoenix, Arizona
| | - John E. McGeary
- Department of Psychiatry and Human Behavior, Providence VA Medical Center, Providence, Rhode Island;,Department of Psychiatry and Human Behavior, Brown University Medical School, Providence, Rhode Island
| | - Ayako Suzuki
- Department of Medicine, Gastroenterology, Durham VA Medical Center, Durham, North Carolina;,Department of Medicine, Gastroenterology, Duke University, Durham, North Carolina
| | - Joel Gelernter
- Division of Human Genetics, Department of Psychiatry, and,VA Connecticut Healthcare System, West Haven, Connecticut
| | - Julie A. Lynch
- VA Informatics & Computing Infrastructure (VINCI), VA Salt Lake City Healthcare System, Salt Lake City, Utah;,Department of Medicine and
| | - Jeffrey M. Petersen
- Corporal Michael J. Crescenz VA Medical Center, Philadelphia, Pennsylvania;,Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania
| | - Seyedeh Maryam Zekavat
- Computational Biology & Bioinformatics, Yale University School of Medicine, New Haven, Connecticut;,Program in Medical and Population Genetics, Cardiovascular Disease Initiative, Broad Institute of Harvard and MIT, Cambridge, Massachusetts
| | - Pradeep Natarajan
- Department of Medicine, Harvard Medical School, Boston, Massachusetts;,Cardiovascular Research Center, Massachusetts General Hospital, Boston, Massachusetts;,Program in Medical and Population Genetics, Cardiovascular Disease Initiative, Broad Institute of Harvard and MIT, Cambridge, Massachusetts
| | - Sharvari Dalal
- Corporal Michael J. Crescenz VA Medical Center, Philadelphia, Pennsylvania;,Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania
| | - Darshana N. Jhala
- Corporal Michael J. Crescenz VA Medical Center, Philadelphia, Pennsylvania;,Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania
| | - Mehrdad Arjomandi
- Medicine, Pulmonary and Critical Care, San Francisco VA Healthcare System, University of California, San Francisco, San Francisco, California
| | - Elise Gatsby
- VA Informatics & Computing Infrastructure (VINCI), VA Salt Lake City Healthcare System, Salt Lake City, Utah
| | - Kristine E. Lynch
- VA Informatics & Computing Infrastructure (VINCI), VA Salt Lake City Healthcare System, Salt Lake City, Utah;,Internal Medicine, Epidemiology, University of Utah School of Medicine, Salt Lake City, Utah
| | | | | | - Gita A. Pathak
- Division of Human Genetics, Department of Psychiatry, and,VA Connecticut Healthcare System, West Haven, Connecticut
| | - Jin J. Zhou
- Department of Medicine, University of California, Los Angeles, Los Angeles, California;,Epidemiology and Biostatistics, University of Arizona, Tucson, Arizona
| | | | - Ravi K. Madduri
- Data Science and Learning, Argonne National Laboratory, Lemont, Illinois
| | - Quinn S. Wells
- Department of Medicine,,Department of Biomedical Informatics, and,Department of Pharmacology, Vanderbilt University Medical Center, Nashville, Tennessee
| | | | - Renato Polimanti
- Division of Human Genetics, Department of Psychiatry, and,VA Connecticut Healthcare System, West Haven, Connecticut
| | - Kyong-Mi Chang
- Corporal Michael J. Crescenz VA Medical Center, Philadelphia, Pennsylvania
| | | | - Philip S. Tsao
- Precision Medicine, VA Palo Alto Health Care System, Palo Alto, California
| | - Peter W. F. Wilson
- Emory University, Atlanta, Georgia;,Atlanta VA Healthcare System, Decatur, Georgia
| | - Adriana M. Hung
- Department of Veteran’s Affairs, Tennessee Valley Healthcare System, Vanderbilt University Medical Center, Division of Nephrology & Hypertension, Nashville, Tennessee
| | | | | | - Richard L. Hauger
- Center of Excellence for Stress & Mental Health, VA San Diego Healthcare System, San Diego, California; and,Center for Behavioral Genetics of Aging, University of California, San Diego, La Jolla, California
| | - Sudha K. Iyengar
- Department of Population and Quantitative Health Sciences, Case Western Reserve University, Cleveland, Ohio;,Louis Stokes Cleveland VA Medical Center, Cleveland, Ohio
| | - Shiuh-Wen Luoh
- Knight Cancer Institute, Oregon Health & Science University, Portland, Oregon;,VA Portland Health Care System, Portland, Oregon
| | | |
Collapse
|
32
|
Mishra A, Malik R, Hachiya T, Jürgenson T, Namba S, Posner DC, Kamanu FK, Koido M, Le Grand Q, Shi M, He Y, Georgakis MK, Caro I, Krebs K, Liaw YC, Vaura FC, Lin K, Winsvold BS, Srinivasasainagendra V, Parodi L, Bae HJ, Chauhan G, Chong MR, Tomppo L, Akinyemi R, Roshchupkin GV, Habib N, Jee YH, Thomassen JQ, Abedi V, Cárcel-Márquez J, Nygaard M, Leonard HL, Yang C, Yonova-Doing E, Knol MJ, Lewis AJ, Judy RL, Ago T, Amouyel P, Armstrong ND, Bakker MK, Bartz TM, Bennett DA, Bis JC, Bordes C, Børte S, Cain A, Ridker PM, Cho K, Chen Z, Cruchaga C, Cole JW, de Jager PL, de Cid R, Endres M, Ferreira LE, Geerlings MI, Gasca NC, Gudnason V, Hata J, He J, Heath AK, Ho YL, Havulinna AS, Hopewell JC, Hyacinth HI, Inouye M, Jacob MA, Jeon CE, Jern C, Kamouchi M, Keene KL, Kitazono T, Kittner SJ, Konuma T, Kumar A, Lacaze P, Launer LJ, Lee KJ, Lepik K, Li J, Li L, Manichaikul A, Markus HS, Marston NA, Meitinger T, Mitchell BD, Montellano FA, Morisaki T, Mosley TH, Nalls MA, Nordestgaard BG, O'Donnell MJ, Okada Y, Onland-Moret NC, Ovbiagele B, Peters A, Psaty BM, Rich SS, Rosand J, Sabatine MS, Sacco RL, Saleheen D, Sandset EC, Salomaa V, Sargurupremraj M, Sasaki M, Satizabal CL, Schmidt CO, Shimizu A, Smith NL, Sloane KL, Sutoh Y, Sun YV, Tanno K, Tiedt S, Tatlisumak T, Torres-Aguila NP, Tiwari HK, Trégouët DA, Trompet S, Tuladhar AM, Tybjærg-Hansen A, van Vugt M, Vibo R, Verma SS, Wiggins KL, Wennberg P, Woo D, Wilson PWF, Xu H, Yang Q, Yoon K, Millwood IY, Gieger C, Ninomiya T, Grabe HJ, Jukema JW, Rissanen IL, Strbian D, Kim YJ, Chen PH, Mayerhofer E, Howson JMM, Irvin MR, Adams H, Wassertheil-Smoller S, Christensen K, Ikram MA, Rundek T, Worrall BB, Lathrop GM, Riaz M, Simonsick EM, Kõrv J, França PHC, Zand R, Prasad K, Frikke-Schmidt R, de Leeuw FE, Liman T, Haeusler KG, Ruigrok YM, Heuschmann PU, Longstreth WT, Jung KJ, Bastarache L, Paré G, Damrauer SM, Chasman DI, Rotter JI, Anderson CD, Zwart JA, Niiranen TJ, Fornage M, Liaw YP, Seshadri S, Fernández-Cadenas I, Walters RG, Ruff CT, Owolabi MO, Huffman JE, Milani L, Kamatani Y, Dichgans M, Debette S. Stroke genetics informs drug discovery and risk prediction across ancestries. Nature 2022; 611:115-123. [PMID: 36180795 PMCID: PMC9524349 DOI: 10.1038/s41586-022-05165-3] [Citation(s) in RCA: 173] [Impact Index Per Article: 86.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/15/2021] [Accepted: 07/29/2022] [Indexed: 01/29/2023]
Abstract
Previous genome-wide association studies (GWASs) of stroke - the second leading cause of death worldwide - were conducted predominantly in populations of European ancestry1,2. Here, in cross-ancestry GWAS meta-analyses of 110,182 patients who have had a stroke (five ancestries, 33% non-European) and 1,503,898 control individuals, we identify association signals for stroke and its subtypes at 89 (61 new) independent loci: 60 in primary inverse-variance-weighted analyses and 29 in secondary meta-regression and multitrait analyses. On the basis of internal cross-ancestry validation and an independent follow-up in 89,084 additional cases of stroke (30% non-European) and 1,013,843 control individuals, 87% of the primary stroke risk loci and 60% of the secondary stroke risk loci were replicated (P < 0.05). Effect sizes were highly correlated across ancestries. Cross-ancestry fine-mapping, in silico mutagenesis analysis3, and transcriptome-wide and proteome-wide association analyses revealed putative causal genes (such as SH3PXD2A and FURIN) and variants (such as at GRK5 and NOS3). Using a three-pronged approach4, we provide genetic evidence for putative drug effects, highlighting F11, KLKB1, PROC, GP1BA, LAMC2 and VCAM1 as possible targets, with drugs already under investigation for stroke for F11 and PROC. A polygenic score integrating cross-ancestry and ancestry-specific stroke GWASs with vascular-risk factor GWASs (integrative polygenic scores) strongly predicted ischaemic stroke in populations of European, East Asian and African ancestry5. Stroke genetic risk scores were predictive of ischaemic stroke independent of clinical risk factors in 52,600 clinical-trial participants with cardiometabolic disease. Our results provide insights to inform biology, reveal potential drug targets and derive genetic risk prediction tools across ancestries.
Collapse
Affiliation(s)
- Aniket Mishra
- Bordeaux Population Health Research Center, University of Bordeaux, Inserm, UMR 1219, Bordeaux, France
| | - Rainer Malik
- Institute for Stroke and Dementia Research (ISD), University Hospital, LMU Munich, Munich, Germany
| | - Tsuyoshi Hachiya
- Iwate Tohoku Medical Megabank Organization, Iwate Medical University, Iwate, Japan
| | - Tuuli Jürgenson
- Estonian Genome Centre, Institute of Genomics, University of Tartu, Tartu, Estonia
- Institute of Mathematics and Statistics, University of Tartu, Tartu, Estonia
| | - Shinichi Namba
- Department of Statistical Genetics, Osaka University Graduate School of Medicine, Suita, Japan
| | - Daniel C Posner
- Massachusetts Veterans Epidemiology Research and Information Center (MAVERIC), VA Boston Healthcare System, Boston, MA, USA
| | - Frederick K Kamanu
- TIMI Study Group, Boston, MA, USA
- Division of Cardiovascular Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Masaru Koido
- Division of Molecular Pathology, Institute of Medical Sciences, The University of Tokyo, Tokyo, Japan
- Laboratory of Complex Trait Genomics, Graduate School of Frontier Sciences, The University of Tokyo, Tokyo, Japan
| | - Quentin Le Grand
- Bordeaux Population Health Research Center, University of Bordeaux, Inserm, UMR 1219, Bordeaux, France
| | - Mingyang Shi
- Laboratory of Complex Trait Genomics, Graduate School of Frontier Sciences, The University of Tokyo, Tokyo, Japan
| | - Yunye He
- Laboratory of Complex Trait Genomics, Graduate School of Frontier Sciences, The University of Tokyo, Tokyo, Japan
| | - Marios K Georgakis
- Institute for Stroke and Dementia Research (ISD), University Hospital, LMU Munich, Munich, Germany
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA
- Program in Medical and Population Genetics, Broad Institute of Harvard and the Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Ilana Caro
- Bordeaux Population Health Research Center, University of Bordeaux, Inserm, UMR 1219, Bordeaux, France
| | - Kristi Krebs
- Estonian Genome Centre, Institute of Genomics, University of Tartu, Tartu, Estonia
| | - Yi-Ching Liaw
- Laboratory of Clinical Genome Sequencing, Department of Computational Biology and Medical Sciences, Graduate School of Frontier Sciences, The University of Tokyo, Tokyo, Japan
- Department of Public Health and Institute of Public Health, Chung Shan Medical University, Taichung, Taiwan
| | - Felix C Vaura
- Department of Internal Medicine, University of Turku, Turku, Finland
- Department of Public Health and Welfare, Finnish Institute for Health and Welfare, Turku, Finland
| | - Kuang Lin
- Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - Bendik Slagsvold Winsvold
- Department of Research and Innovation, Division of Clinical Neuroscience, Oslo University Hospital, Oslo, Norway
- K. G. Jebsen Center for Genetic Epidemiology, Department of Public Health and Nursing, Faculty of Medicine and Health Sciences, Norwegian University of Science and Technology (NTNU), Trondheim, Norway
- Department of Neurology, Oslo University Hospital, Oslo, Norway
| | - Vinodh Srinivasasainagendra
- Department of Biostatistics, School of Public Health, University of Alabama at Birmingham, Birmingham, AL, USA
| | - Livia Parodi
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA
- Program in Medical and Population Genetics, Broad Institute of Harvard and the Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Hee-Joon Bae
- Department of Neurology and Cerebrovascular Disease Center, Seoul National University Bundang Hospital, Seoul National University College of Medicine, Seongnam, Republic of Korea
| | | | - Michael R Chong
- Thrombosis and Atherosclerosis Research Institute, David Braley Cardiac, Vascular and Stroke Research Institute, Hamilton, Ontario, Canada
- Department of Pathology and Molecular Medicine, Michael G. DeGroote School of Medicine, McMaster University, Hamilton, Ontario, Canada
| | - Liisa Tomppo
- Department of Neurology, Helsinki University Hospital and University of Helsinki, Helsinki, Finland
| | - Rufus Akinyemi
- Center for Genomic and Precision Medicine, College of Medicine, University of Ibadan, Ibadan, Nigeria
- Neuroscience and Ageing Research Unit Institute for Advanced Medical Research and Training, College of Medicine, University of Ibadan, Ibadan, Nigeria
| | - Gennady V Roshchupkin
- Department of Epidemiology, Erasmus MC University Medical Center Rotterdam, Rotterdam, The Netherlands
- Department of Radiology and Nuclear Medicine, Erasmus MC University Medical Center Rotterdam, Rotterdam, The Netherlands
| | - Naomi Habib
- The Edmond and Lily Safra Center for Brain Sciences, The Hebrew University of Jerusalem, Jerusalem, Israel
| | - Yon Ho Jee
- Department of Epidemiology, Harvard T. H. Chan School of Public Health, Boston, MA, USA
| | - Jesper Qvist Thomassen
- Department of Clinical Biochemistry, Copenhagen University Hospital-Rigshospitalet, Copenhagen, Denmark
| | - Vida Abedi
- Department of Molecular and Functional Genomics, Weis Center for Research, Geisinger Health System, Danville, VA, USA
- Department of Public Health Sciences, College of Medicine, The Pennsylvania State University, State College, PA, USA
| | - Jara Cárcel-Márquez
- Stroke Pharmacogenomics and Genetics Laboratory, Biomedical Research Institute Sant Pau (IIB Sant Pau), Barcelona, Spain
- Departament de Medicina, Universitat Autònoma de Barcelona, Barcelona, Spain
| | - Marianne Nygaard
- The Danish Twin Registry, Department of Public Health, University of Southern Denmark, Odense, Denmark
- Department of Clinical Genetics, Odense University Hospital, Odense, Denmark
| | - Hampton L Leonard
- Center for Alzheimer's and Related Dementias, National Institutes of Health, Bethesda, MD, USA
- Laboratory of Neurogenetics, National Institute on Aging, National Institutes of Health, Bethesda, MD, USA
- Data Tecnica International, Glen Echo, MD, USA
| | - Chaojie Yang
- Center for Public Health Genomics, University of Virginia, Charlottesville, VA, USA
- Department of Biochemistry and Molecular Genetics, University of Virginia, Charlottesville, VA, USA
| | - Ekaterina Yonova-Doing
- British Heart Foundation Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
- Department of Genetics, Novo Nordisk Research Centre Oxford, Oxford, UK
| | - Maria J Knol
- Department of Epidemiology, Erasmus MC University Medical Center Rotterdam, Rotterdam, The Netherlands
| | - Adam J Lewis
- Department of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Renae L Judy
- Department of Surgery, University of Pennsylvania, Philadelphia, PA, USA
| | - Tetsuro Ago
- Department of Medicine and Clinical Science, Graduate School of Medical Sciences, Kyushu University, Fukuoka, Japan
| | - Philippe Amouyel
- University of Lille, INSERM U1167, RID-AGE, LabEx DISTALZ, Risk Factors and Molecular Determinants of Aging-Related Diseases, Lille, France
- CHU Lille, Public Health Department, Lille, France
- Institut Pasteur de Lille, Lille, France
| | - Nicole D Armstrong
- Department of Epidemiology, University of Alabama at Birmingham, Birmingham, AL, USA
| | - Mark K Bakker
- UMC Utrecht Brain Center, Department of Neurology and Neurosurgery, University Medical Center Utrecht, University Utrecht, Utrecht, The Netherlands
| | - Traci M Bartz
- Cardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle, WA, USA
- Department of Biostatistics, University of Washington, Seattle, WA, USA
| | - David A Bennett
- Rush Alzheimer's Disease Center, Rush University Medical Center, Chicago, IL, USA
| | - Joshua C Bis
- Cardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle, WA, USA
| | - Constance Bordes
- Bordeaux Population Health Research Center, University of Bordeaux, Inserm, UMR 1219, Bordeaux, France
| | - Sigrid Børte
- K. G. Jebsen Center for Genetic Epidemiology, Department of Public Health and Nursing, Faculty of Medicine and Health Sciences, Norwegian University of Science and Technology (NTNU), Trondheim, Norway
- Institute of Clinical Medicine, Faculty of Medicine, University of Oslo, Oslo, Norway
- Research and Communication Unit for Musculoskeletal Health (FORMI), Department of Research and Innovation, Division of Clinical Neuroscience, Oslo University Hospital, Oslo, Norway
| | - Anael Cain
- The Edmond and Lily Safra Center for Brain Sciences, The Hebrew University of Jerusalem, Jerusalem, Israel
| | - Paul M Ridker
- Division of Preventive Medicine, Brigham and Women's Hospital, Boston, MA, USA
- Harvard Medical School, Boston, MA, USA
| | - Kelly Cho
- Massachusetts Veterans Epidemiology Research and Information Center (MAVERIC), VA Boston Healthcare System, Boston, MA, USA
| | - Zhengming Chen
- Nuffield Department of Population Health, University of Oxford, Oxford, UK
- MRC Population Health Research Unit, University of Oxford, Oxford, UK
| | - Carlos Cruchaga
- Department of Psychiatry, Washington University School of Medicine, Saint Louis, MO, USA
- NeuroGenomics and Informatics Center, Washington University School of Medicine, Saint Louis, MO, USA
| | - John W Cole
- VA Maryland Health Care System, Baltimore, MD, USA
- Department of Neurology, University of Maryland School of Medicine, Baltimore, MD, USA
| | - Phil L de Jager
- Program in Medical and Population Genetics, Broad Institute of Harvard and the Massachusetts Institute of Technology, Cambridge, MA, USA
- Center for Translational and Computational Neuroimmunology, Department of Neurology, Columbia University Medical Center, New York, NY, USA
| | - Rafael de Cid
- GenomesForLife-GCAT Lab Group, Germans Trias i Pujol Research Institute (IGTP), Badalona, Spain
| | - Matthias Endres
- Klinik und Hochschulambulanz für Neurologie, Charité-Universitätsmedizin Berlin, Berlin, Germany
- Center for Stroke Research Berlin, Berlin, Germany
- German Center for Neurodegenerative Diseases (DZNE), partner site Berlin, Berlin, Germany
- German Centre for Cardiovascular Research (DZHK), partner site Berlin, Berlin, Germany
| | - Leslie E Ferreira
- Post-Graduation Program on Health and Environment, Department of Medicine and Joinville Stroke Biobank, University of the Region of Joinville, Santa Catarina, Brazil
| | - Mirjam I Geerlings
- Department of Epidemiology, Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht University, Utrecht, The Netherlands
| | - Natalie C Gasca
- Department of Biostatistics, University of Washington, Seattle, WA, USA
| | - Vilmundur Gudnason
- Icelandic Heart Association, Kopavogur, Iceland
- Faculty of Medicine, University of Iceland, Reykjavik, Iceland
| | - Jun Hata
- Department of Epidemiology and Public Health, Graduate School of Medical Sciences, Kyushu University, Fukuoka, Japan
| | - Jing He
- Department of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Alicia K Heath
- Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, UK
| | - Yuk-Lam Ho
- Massachusetts Veterans Epidemiology Research and Information Center (MAVERIC), VA Boston Healthcare System, Boston, MA, USA
| | - Aki S Havulinna
- Department of Public Health and Welfare, Finnish Institute for Health and Welfare, Helsinki, Finland
- Institute for Molecular Medicine Finland, FIMM-HiLIFE, Helsinki, Finland
| | - Jemma C Hopewell
- Clinical Trial Service and Epidemiological Studies Unit (CTSU), Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - Hyacinth I Hyacinth
- Department of Neurology and Rehabilitation Medicine, University of Cincinnati College of Medicine, Cincinnati, OH, USA
| | - Michael Inouye
- British Heart Foundation Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
- Cambridge Baker Systems Genomics Initiative, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
- Cambridge Baker Systems Genomics Initiative, Baker Heart and Diabetes Institute, Melbourne, Victoria, Australia
- Health Data Research UK Cambridge, Wellcome Genome Campus and University of Cambridge, Cambridge, UK
- British Heart Foundation Centre of Research Excellence, University of Cambridge, Cambridge, UK
| | - Mina A Jacob
- Department of Neurology, Donders Center for Medical Neuroscience, Radboud University Medical Center, Nijmegen, The Netherlands
| | - Christina E Jeon
- Los Angeles County Department of Public Health, Los Angeles, CA, USA
| | - Christina Jern
- Institute of Biomedicine, Department of Laboratory Medicine, the Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden
- Department of Clinical Genetics and Genomics, Sahlgrenska University Hospital, Gothenburg, Sweden
| | - Masahiro Kamouchi
- Department of Health Care Administration and Management, Graduate School of Medical Sciences, Kyushu University, Fukuoka, Japan
| | - Keith L Keene
- Department of Biology, Brody School of Medicine Center for Health Disparities, East Carolina University, Greenville, NC, USA
| | - Takanari Kitazono
- Department of Medicine and Clinical Science, Graduate School of Medical Sciences, Kyushu University, Fukuoka, Japan
| | - Steven J Kittner
- Department of Neurology, University of Maryland School of Medicine, Baltimore, MD, USA
- Department of Neurology and Geriatric Research and Education Clinical Center, VA Maryland Health Care System, Baltimore, MD, USA
| | - Takahiro Konuma
- Department of Statistical Genetics, Osaka University Graduate School of Medicine, Suita, Japan
| | - Amit Kumar
- Rajendra Institute of Medical Sciences, Ranchi, India
| | - Paul Lacaze
- Department of Epidemiology and Preventive Medicine, School of Public Health and Preventive Medicine, Monash University, Melbourne, Victoria, Australia
| | - Lenore J Launer
- Intramural Research Program, National Institute on Aging, NIH, Baltimore, MD, USA
| | - Keon-Joo Lee
- Department of Neurology, Korea University Guro Hospital, Seoul, Republic of Korea
| | - Kaido Lepik
- Estonian Genome Centre, Institute of Genomics, University of Tartu, Tartu, Estonia
- Department of Computational Biology, University of Lausanne, Lausanne, Switzerland
- Swiss Institute of Bioinformatics, Lausanne, Switzerland
- University Center for Primary Care and Public Health, Lausanne, Switzerland
| | - Jiang Li
- Department of Molecular and Functional Genomics, Weis Center for Research, Geisinger Health System, Danville, VA, USA
| | - Liming Li
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University Health Science Center, Beijing, China
| | - Ani Manichaikul
- Center for Public Health Genomics, University of Virginia, Charlottesville, VA, USA
| | - Hugh S Markus
- Stroke Research Group, Department of Clinical Neurosciences, University of Cambridge, Cambridge, UK
| | - Nicholas A Marston
- TIMI Study Group, Boston, MA, USA
- Division of Cardiovascular Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Thomas Meitinger
- Institute of Human Genetics, Technical University of Munich, Munich, Germany
- Institute of Human Genetics, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
| | - Braxton D Mitchell
- Department of Medicine, University of Maryland School of Medicine, Baltimore, MD, USA
- Geriatrics Research and Education Clinical Center, Baltimore Veterans Administration Medical Center, Baltimore, MD, USA
| | - Felipe A Montellano
- Institute of Clinical Epidemiology and Biometry, University of Würzburg, Würzburg, Germany
- Department of Neurology, University Hospital Würzburg, Würzburg, Germany
| | - Takayuki Morisaki
- Division of Molecular Pathology, Institute of Medical Sciences, The University of Tokyo, Tokyo, Japan
| | - Thomas H Mosley
- The MIND Center, University of Mississippi Medical Center, Jackson, MS, USA
| | - Mike A Nalls
- Center for Alzheimer's and Related Dementias, National Institutes of Health, Bethesda, MD, USA
- Laboratory of Neurogenetics, National Institute on Aging, National Institutes of Health, Bethesda, MD, USA
- Data Tecnica International, Glen Echo, MD, USA
| | - Børge G Nordestgaard
- Department of Clinical Biochemistry, Copenhagen University Hospital-Herlev and Gentofte, Copenhagen, Denmark
- Department of Clinical Medicine, University of Copenhagen, Copenhagen, Denmark
| | - Martin J O'Donnell
- College of Medicine Nursing and Health Science, NUI Galway, Galway, Ireland
| | - Yukinori Okada
- Department of Statistical Genetics, Osaka University Graduate School of Medicine, Suita, Japan
- Department of Genome Informatics, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan
- Laboratory for Systems Genetics, RIKEN Center for Integrative Medical Sciences, Yokohama, Japan
- Laboratory of Statistical Immunology, Immunology Frontier Research Center (WPI-IFReC), Osaka University, Suita, Japan
- Integrated Frontier Research for Medical Science Division, Institute for Open and Transdisciplinary Research Initiatives, Osaka University, Suita, Japan
- Center for Infectious Disease Education and Research (CiDER), Osaka University, Suita, Japan
| | - N Charlotte Onland-Moret
- Department of Epidemiology, Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht University, Utrecht, The Netherlands
| | - Bruce Ovbiagele
- Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, CA, USA
| | - Annette Peters
- Institute of Epidemiology, Helmholtz Zentrum München,, German Research Center for Environmental Health, Neuherberg, Germany
- Institute for Medical Information Processing, Biometry and Epidemiology, Ludwig Maximilian University Munich, Munich, Germany
- German Centre for Cardiovascular Research (DZHK), partner site Munich, Munich, Germany
| | - Bruce M Psaty
- Cardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle, WA, USA
- Department of Epidemiology, University of Washington, Seattle, WA, USA
- Department of Health Systems and Population Health, University of Washington, Seattle, WA, USA
| | - Stephen S Rich
- Center for Public Health Genomics, University of Virginia, Charlottesville, VA, USA
| | - Jonathan Rosand
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA
- Program in Medical and Population Genetics, Broad Institute of Harvard and the Massachusetts Institute of Technology, Cambridge, MA, USA
- McCance Center for Brain Health, Massachusetts General Hospital, Boston, MA, USA
| | - Marc S Sabatine
- TIMI Study Group, Boston, MA, USA
- Division of Cardiovascular Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Ralph L Sacco
- Department of Neurology, University of Miami Miller School of Medicine, Miami, FL, USA
- Evelyn F. McKnight Brain Institute, Gainesville, FL, USA
| | - Danish Saleheen
- Division of Cardiology, Department of Medicine, Columbia University, New York, NY, USA
| | - Else Charlotte Sandset
- Stroke Unit, Department of Neurology, Oslo University Hospital, Oslo, Norway
- Research and Development, The Norwegian Air Ambulance Foundation, Oslo, Norway
| | - Veikko Salomaa
- Department of Public Health and Welfare, Finnish Institute for Health and Welfare, Helsinki, Finland
| | - Muralidharan Sargurupremraj
- Glenn Biggs Institute for Alzheimer's and Neurodegenerative Diseases, University of Texas Health Sciences Center, San Antonio, TX, USA
| | - Makoto Sasaki
- Iwate Tohoku Medical Megabank Organization, Iwate Medical University, Iwate, Japan
| | - Claudia L Satizabal
- Glenn Biggs Institute for Alzheimer's and Neurodegenerative Diseases, University of Texas Health Sciences Center, San Antonio, TX, USA
- Framingham Heart Study, Framingham, MA, USA
| | - Carsten O Schmidt
- University Medicine Greifswald, Institute for Community Medicine, SHIP/KEF, Greifswald, Germany
| | - Atsushi Shimizu
- Iwate Tohoku Medical Megabank Organization, Iwate Medical University, Iwate, Japan
| | - Nicholas L Smith
- Department of Epidemiology, University of Washington, Seattle, WA, USA
- Kaiser Permanente Washington Health Research Institute, Kaiser Permanente Washington, Seattle, WA, USA
- Department of Veterans Affairs Office of Research and Development, Seattle Epidemiologic Research and Information Center, Seattle, WA, USA
| | - Kelly L Sloane
- Department of Neurology, University of Pennsylvania, Philadelphia, PA, USA
| | - Yoichi Sutoh
- Iwate Tohoku Medical Megabank Organization, Iwate Medical University, Iwate, Japan
| | - Yan V Sun
- Atlanta VA Health Care System, Decatur, GA, USA
- Department of Epidemiology, Emory University Rollins School of Public Health, Atlanta, GA, USA
| | - Kozo Tanno
- Iwate Tohoku Medical Megabank Organization, Iwate Medical University, Iwate, Japan
| | - Steffen Tiedt
- Institute for Stroke and Dementia Research (ISD), University Hospital, LMU Munich, Munich, Germany
| | - Turgut Tatlisumak
- Department of Clinical Neuroscience, Institute of Neuroscience and Physiology, Sahlgrenska Unviersity Hospital, Gothenburg, Sweden
| | - Nuria P Torres-Aguila
- Stroke Pharmacogenomics and Genetics Laboratory, Biomedical Research Institute Sant Pau (IIB Sant Pau), Barcelona, Spain
| | - Hemant K Tiwari
- Department of Biostatistics, School of Public Health, University of Alabama at Birmingham, Birmingham, AL, USA
| | - David-Alexandre Trégouët
- Bordeaux Population Health Research Center, University of Bordeaux, Inserm, UMR 1219, Bordeaux, France
| | - Stella Trompet
- Department of Internal Medicine, Section of Gerontology and Geriatrics, Leiden University Medical Center, Leiden, The Netherlands
- Department of Cardiology, Leiden University Medical Center, Leiden, The Netherlands
| | - Anil Man Tuladhar
- Department of Neurology, Donders Center for Medical Neuroscience, Radboud University Medical Center, Nijmegen, The Netherlands
| | - Anne Tybjærg-Hansen
- Department of Clinical Biochemistry, Copenhagen University Hospital-Rigshospitalet, Copenhagen, Denmark
- Department of Clinical Medicine, University of Copenhagen, Copenhagen, Denmark
| | - Marion van Vugt
- Division Heart & Lungs, Department of Cardiology, University Medical Center Utrecht, Utrecht University, Utrecht, The Netherlands
| | - Riina Vibo
- Department of Neurology and Neurosurgery, University of Tartu, Tartu, Estonia
| | - Shefali S Verma
- Department of Pathology and Laboratory Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Kerri L Wiggins
- Cardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle, WA, USA
| | - Patrik Wennberg
- Department of Public Health and Clinical Medicine, Umeå University, Umeå, Sweden
| | - Daniel Woo
- Department of Neurology and Rehabilitation Medicine, University of Cincinnati College of Medicine, Cincinnati, OH, USA
| | - Peter W F Wilson
- Atlanta VA Health Care System, Decatur, GA, USA
- Department of Medicine, Division of Cardiovascular Disease, Emory University School of Medicine, Atlanta, GA, USA
| | - Huichun Xu
- Department of Medicine, University of Maryland School of Medicine, Baltimore, MD, USA
| | - Qiong Yang
- Framingham Heart Study, Framingham, MA, USA
- Department of Biostatistics, Boston University School of Public Health, Boston, MA, USA
| | - Kyungheon Yoon
- Division of Genome Science, Department of Precision Medicine, National Institute of Health, Cheongju, Republic of Korea
| | - Iona Y Millwood
- Nuffield Department of Population Health, University of Oxford, Oxford, UK
- MRC Population Health Research Unit, University of Oxford, Oxford, UK
| | - Christian Gieger
- Research Unit Molecular Epidemiology, Institute of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
| | - Toshiharu Ninomiya
- Department of Epidemiology and Public Health, Graduate School of Medical Sciences, Kyushu University, Fukuoka, Japan
| | - Hans J Grabe
- Department of Psychiatry and Psychotherapy, University Medicine Greifswald, Greifswald, Germany
- German Center for Neurodegenerative Diseases (DZNE), site Rostock/Greifswald, Rostock, Germany
| | - J Wouter Jukema
- Department of Cardiology, Leiden University Medical Center, Leiden, The Netherlands
- Netherlands Heart Institute, Utrecht, The Netherlands
- Einthoven Laboratory for Experimental Vascular Medicine, LUMC, Leiden, The Netherlands
| | - Ina L Rissanen
- Department of Epidemiology, Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht University, Utrecht, The Netherlands
| | - Daniel Strbian
- Department of Neurology, Helsinki University Hospital and University of Helsinki, Helsinki, Finland
| | - Young Jin Kim
- Division of Genome Science, Department of Precision Medicine, National Institute of Health, Cheongju, Republic of Korea
| | - Pei-Hsin Chen
- Department of Public Health and Institute of Public Health, Chung Shan Medical University, Taichung, Taiwan
| | - Ernst Mayerhofer
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA
- Program in Medical and Population Genetics, Broad Institute of Harvard and the Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Joanna M M Howson
- British Heart Foundation Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
- Department of Genetics, Novo Nordisk Research Centre Oxford, Oxford, UK
| | - Marguerite R Irvin
- Department of Epidemiology, University of Alabama at Birmingham, Birmingham, AL, USA
| | - Hieab Adams
- Department of Clinical Genetics, Department of Radiology and Nuclear Medicine, Erasmus MC, Rotterdam, The Netherlands
- Latin American Brain Health (BrainLat), Universidad Adolfo Ibáñez, Santiago, Chile
| | - Sylvia Wassertheil-Smoller
- Department of Epidemiology and Population Health, Albert Einstein College of Medicine, New York, NY, USA
| | - Kaare Christensen
- The Danish Twin Registry, Department of Public Health, University of Southern Denmark, Odense, Denmark
- Department of Clinical Genetics, Odense University Hospital, Odense, Denmark
- Department of Clinical Biochemistry and Pharmacology, Odense University Hospital, Odense, Denmark
| | - Mohammad A Ikram
- Department of Epidemiology, Erasmus MC University Medical Center Rotterdam, Rotterdam, The Netherlands
| | - Tatjana Rundek
- Department of Neurology, University of Miami Miller School of Medicine, Miami, FL, USA
- Evelyn F. McKnight Brain Institute, Gainesville, FL, USA
| | - Bradford B Worrall
- Department of Neurology, University of Virginia, Charlottesville, VA, USA
- Department of Public Health Science, University of Virginia, Charlottesville, VA, USA
| | | | - Moeen Riaz
- Department of Epidemiology and Preventive Medicine, School of Public Health and Preventive Medicine, Monash University, Melbourne, Victoria, Australia
| | - Eleanor M Simonsick
- Longitudinal Studies Section, Translational Gerontology Branch, National Institute on Aging, Baltimore, MD, USA
| | - Janika Kõrv
- Department of Neurology and Neurosurgery, University of Tartu, Tartu, Estonia
| | - Paulo H C França
- Post-Graduation Program on Health and Environment, Department of Medicine and Joinville Stroke Biobank, University of the Region of Joinville, Santa Catarina, Brazil
| | - Ramin Zand
- Geisinger Neuroscience Institute, Geisinger Health System, Danville, PA, USA
- Department of Neurology, College of Medicine, The Pennsylvania State University, State College, PA, USA
| | | | - Ruth Frikke-Schmidt
- Department of Clinical Biochemistry, Copenhagen University Hospital-Rigshospitalet, Copenhagen, Denmark
- Department of Clinical Medicine, University of Copenhagen, Copenhagen, Denmark
| | - Frank-Erik de Leeuw
- Department of Neurology, Donders Center for Medical Neuroscience, Radboud University Medical Center, Nijmegen, The Netherlands
| | - Thomas Liman
- Center for Stroke Research Berlin, Berlin, Germany
- Department of Epidemiology, Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht University, Utrecht, The Netherlands
- Klinik für Neurologie, Carl von Ossietzky University of Oldenburg, Oldenburg, Germany
| | | | - Ynte M Ruigrok
- UMC Utrecht Brain Center, Department of Neurology and Neurosurgery, University Medical Center Utrecht, University Utrecht, Utrecht, The Netherlands
| | - Peter Ulrich Heuschmann
- Institute of Clinical Epidemiology and Biometry, University of Würzburg, Würzburg, Germany
- Comprehensive Heart Failure Center, University Hospital Würzburg, Würzburg, Germany
- Clinical Trial Center, University Hospital Würzburg, Würzburg, Germany
| | - W T Longstreth
- Department of Epidemiology, University of Washington, Seattle, WA, USA
- Department of Neurology, University of Washington, Seattle, WA, USA
| | - Keum Ji Jung
- Nuffield Department of Population Health, University of Oxford, Oxford, UK
- Institute for Health Promotion, Graduate School of Public Health, Yonsei University, Seoul, Republic of Korea
| | - Lisa Bastarache
- Department of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Guillaume Paré
- Thrombosis and Atherosclerosis Research Institute, David Braley Cardiac, Vascular and Stroke Research Institute, Hamilton, Ontario, Canada
- Department of Pathology and Molecular Medicine, Michael G. DeGroote School of Medicine, McMaster University, Hamilton, Ontario, Canada
- Department of Health Research Methods, Evidence and Impact, McMaster University, Hamilton, Ontario, Canada
- Population Health Research Institute, David Braley Cardiac, Vascular and Stroke Research Institute, Hamilton, Ontario, Canada
| | - Scott M Damrauer
- Department of Surgery and Department of Genetics, University of Pennsylvania, Philadelphia, PA, USA
- Corporal Michael Crescenz VA Medical Center, Philadelphia, PA, USA
| | - Daniel I Chasman
- Division of Preventive Medicine, Brigham and Women's Hospital, Boston, MA, USA
- Harvard Medical School, Boston, MA, USA
| | - Jerome I Rotter
- The Institute for Translational Genomics and Population Sciences, Department of Pediatrics, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance, CA, USA
| | - Christopher D Anderson
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA
- Program in Medical and Population Genetics, Broad Institute of Harvard and the Massachusetts Institute of Technology, Cambridge, MA, USA
- McCance Center for Brain Health, Massachusetts General Hospital, Boston, MA, USA
- Department of Neurology, Brigham and Women's Hospital, Boston, MA, USA
| | - John-Anker Zwart
- Department of Research and Innovation, Division of Clinical Neuroscience, Oslo University Hospital, Oslo, Norway
- K. G. Jebsen Center for Genetic Epidemiology, Department of Public Health and Nursing, Faculty of Medicine and Health Sciences, Norwegian University of Science and Technology (NTNU), Trondheim, Norway
- Institute of Clinical Medicine, Faculty of Medicine, University of Oslo, Oslo, Norway
| | - Teemu J Niiranen
- Department of Internal Medicine, University of Turku, Turku, Finland
- Department of Public Health and Welfare, Finnish Institute for Health and Welfare, Turku, Finland
- Division of Medicine, Turku University Hospital, Turku, Finland
| | - Myriam Fornage
- Brown Foundation Institute of Molecular Medicine, McGovern Medical School, University of Texas Health Science Center at Houston, Houston, TX, USA
- Human Genetics Center, School of Public Health, University of Texas Health Science Center at Houston, Houston, TX, USA
| | - Yung-Po Liaw
- Department of Public Health and Institute of Public Health, Chung Shan Medical University, Taichung, Taiwan
- Department of Medical Imaging, Chung Shan Medical University Hospital, Taichung, Taiwan
| | - Sudha Seshadri
- Glenn Biggs Institute for Alzheimer's and Neurodegenerative Diseases, University of Texas Health Sciences Center, San Antonio, TX, USA
- Framingham Heart Study, Framingham, MA, USA
- Department of Neurology, Boston University School of Medicine, Boston, MA, USA
| | - Israel Fernández-Cadenas
- Stroke Pharmacogenomics and Genetics Laboratory, Biomedical Research Institute Sant Pau (IIB Sant Pau), Barcelona, Spain
| | - Robin G Walters
- Nuffield Department of Population Health, University of Oxford, Oxford, UK
- MRC Population Health Research Unit, University of Oxford, Oxford, UK
| | - Christian T Ruff
- TIMI Study Group, Boston, MA, USA
- Division of Cardiovascular Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Mayowa O Owolabi
- Center for Genomic and Precision Medicine, College of Medicine, University of Ibadan, Ibadan, Nigeria
- Department of Medicine, University of Ibadan, Ibadan, Nigeria
| | - Jennifer E Huffman
- Massachusetts Veterans Epidemiology Research and Information Center (MAVERIC), VA Boston Healthcare System, Boston, MA, USA
| | - Lili Milani
- Estonian Genome Centre, Institute of Genomics, University of Tartu, Tartu, Estonia
| | - Yoichiro Kamatani
- Laboratory of Complex Trait Genomics, Graduate School of Frontier Sciences, The University of Tokyo, Tokyo, Japan
| | - Martin Dichgans
- Institute for Stroke and Dementia Research (ISD), University Hospital, LMU Munich, Munich, Germany.
- Munich Cluster for Systems Neurology, Munich, Germany.
- German Center for Neurodegenerative Diseases (DZNE), Munich, Germany.
| | - Stephanie Debette
- Bordeaux Population Health Research Center, University of Bordeaux, Inserm, UMR 1219, Bordeaux, France.
- Department of Neurology, Institute for Neurodegenerative Diseases, CHU de Bordeaux, Bordeaux, France.
| |
Collapse
|
33
|
Partanen JJ, Häppölä P, Zhou W, Lehisto AA, Ainola M, Sutinen E, Allen RJ, Stockwell AD, Leavy OC, Oldham JM, Guillen-Guio B, Cox NJ, Hirbo JB, Schwartz DA, Fingerlin TE, Flores C, Noth I, Yaspan BL, Jenkins RG, Wain LV, Ripatti S, Pirinen M, Laitinen T, Kaarteenaho R, Myllärniemi M, Daly MJ, Koskela JT. Leveraging global multi-ancestry meta-analysis in the study of idiopathic pulmonary fibrosis genetics. CELL GENOMICS 2022; 2:100181. [PMID: 36777997 PMCID: PMC9903787 DOI: 10.1016/j.xgen.2022.100181] [Citation(s) in RCA: 21] [Impact Index Per Article: 10.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/25/2022] [Revised: 05/24/2022] [Accepted: 09/07/2022] [Indexed: 04/12/2023]
Abstract
The research of rare and devastating orphan diseases, such as idiopathic pulmonary fibrosis (IPF) has been limited by the rarity of the disease itself. The prognosis is poor-the prevalence of IPF is only approximately four times the incidence, limiting the recruitment of patients to trials and studies of the underlying biology. Global biobanking efforts can dramatically alter the future of IPF research. We describe a large-scale meta-analysis of IPF, with 8,492 patients and 1,355,819 population controls from 13 biobanks around the globe. Finally, we combine this meta-analysis with the largest available meta-analysis of IPF, reaching 11,160 patients and 1,364,410 population controls. We identify seven novel genome-wide significant loci, only one of which would have been identified if the analysis had been limited to European ancestry individuals. We observe notable pleiotropy across IPF susceptibility and severe COVID-19 infection and note an unexplained sex-heterogeneity effect at the strongest IPF locus MUC5B.
Collapse
Affiliation(s)
- Juulia J. Partanen
- Institute for Molecular Medicine, Finland (FIMM), HiLIFE, University of Helsinki, Helsinki, Finland
| | - Paavo Häppölä
- Institute for Molecular Medicine, Finland (FIMM), HiLIFE, University of Helsinki, Helsinki, Finland
| | - Wei Zhou
- Analytic and Translational Genetics Unit, Department of Medicine, Massachusetts General Hospital, Boston, MA, USA
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Arto A. Lehisto
- Institute for Molecular Medicine, Finland (FIMM), HiLIFE, University of Helsinki, Helsinki, Finland
| | - Mari Ainola
- Individualized Drug Therapy Research Program, Faculty of Medicine, University of Helsinki, Helsinki, Finland
- Department of Pulmonary Medicine, Heart and Lung Center, Helsinki University Hospital, Helsinki, Finland
| | - Eva Sutinen
- Individualized Drug Therapy Research Program, Faculty of Medicine, University of Helsinki, Helsinki, Finland
- Department of Pulmonary Medicine, Heart and Lung Center, Helsinki University Hospital, Helsinki, Finland
| | - Richard J. Allen
- Department of Health Sciences, University of Leicester, Leicester, UK
| | | | - Olivia C. Leavy
- Department of Health Sciences, University of Leicester, Leicester, UK
| | - Justin M. Oldham
- Division of Pulmonary, Critical Care and Sleep Medicine, Department of Internal Medicine, University of California, Davis, Sacramento, CA, USA
| | | | - Nancy J. Cox
- Department of Medicine, Division of Genetic Medicine, Vanderbilt University Medical Center, Nashville, TN, USA
- Vanderbilt Genetic Institute, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Jibril B. Hirbo
- Department of Medicine, Division of Genetic Medicine, Vanderbilt University Medical Center, Nashville, TN, USA
- Vanderbilt Genetic Institute, Vanderbilt University Medical Center, Nashville, TN, USA
| | | | - Tasha E. Fingerlin
- Center for Genes, Environment and Health, National Jewish Health, Denver, CO, USA
| | - Carlos Flores
- Research Unit, Hospital Universitario Ntra. Sra. de Candelaria, Santa Cruz de Tenerife, Spain
- CIBER de Enfermedades Respiratorias, Instituto de Salud Carlos III, Madrid, Spain
- Genomics Division, Instituto Tecnológico y de Energías Renovables (ITER), Santa Cruz de Tenerife, Spain
- Faculty of Health Sciences, University of Fernando Pessoa Canarias, Las Palmas de Gran Canaria, Spain
| | - Imre Noth
- Division of Pulmonary and Critical Care Medicine, Department of Medicine, University of Virginia, Charlottesville, VA, USA
| | | | - R. Gisli Jenkins
- National Heart and Lung Institute, Imperial College London, London, UK
- Royal Brompton and Harefield Hospitals, Guy's and St Thomas' NHS Foundation Trust, London, UK
| | - Louise V. Wain
- Department of Health Sciences, University of Leicester, Leicester, UK
- National Institute for Health Research, Leicester Respiratory Biomedical Research Centre, Glenfield Hospital, Leicester, UK
| | - Samuli Ripatti
- Institute for Molecular Medicine, Finland (FIMM), HiLIFE, University of Helsinki, Helsinki, Finland
- Faculty of Medicine, University of Helsinki, Helsinki, Finland
| | - Matti Pirinen
- Institute for Molecular Medicine, Finland (FIMM), HiLIFE, University of Helsinki, Helsinki, Finland
- Department of Public Health, University of Helsinki, Helsinki, Finland
- Department of Mathematics and Statistics, University of Helsinki, Helsinki, Finland
| | - International IPF Genetics Consortium
- Institute for Molecular Medicine, Finland (FIMM), HiLIFE, University of Helsinki, Helsinki, Finland
- Analytic and Translational Genetics Unit, Department of Medicine, Massachusetts General Hospital, Boston, MA, USA
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Individualized Drug Therapy Research Program, Faculty of Medicine, University of Helsinki, Helsinki, Finland
- Department of Pulmonary Medicine, Heart and Lung Center, Helsinki University Hospital, Helsinki, Finland
- Department of Health Sciences, University of Leicester, Leicester, UK
- Human Genetics, Genentech, South San Francisco, CA, USA
- Division of Pulmonary, Critical Care and Sleep Medicine, Department of Internal Medicine, University of California, Davis, Sacramento, CA, USA
- Department of Medicine, Division of Genetic Medicine, Vanderbilt University Medical Center, Nashville, TN, USA
- Vanderbilt Genetic Institute, Vanderbilt University Medical Center, Nashville, TN, USA
- Department of Medicine, University of Colorado, Aurora, CO, USA
- Center for Genes, Environment and Health, National Jewish Health, Denver, CO, USA
- Research Unit, Hospital Universitario Ntra. Sra. de Candelaria, Santa Cruz de Tenerife, Spain
- CIBER de Enfermedades Respiratorias, Instituto de Salud Carlos III, Madrid, Spain
- Genomics Division, Instituto Tecnológico y de Energías Renovables (ITER), Santa Cruz de Tenerife, Spain
- Faculty of Health Sciences, University of Fernando Pessoa Canarias, Las Palmas de Gran Canaria, Spain
- Division of Pulmonary and Critical Care Medicine, Department of Medicine, University of Virginia, Charlottesville, VA, USA
- National Heart and Lung Institute, Imperial College London, London, UK
- Royal Brompton and Harefield Hospitals, Guy's and St Thomas' NHS Foundation Trust, London, UK
- National Institute for Health Research, Leicester Respiratory Biomedical Research Centre, Glenfield Hospital, Leicester, UK
- Faculty of Medicine, University of Helsinki, Helsinki, Finland
- Department of Public Health, University of Helsinki, Helsinki, Finland
- Department of Mathematics and Statistics, University of Helsinki, Helsinki, Finland
- Administration Center, Tampere University Hospital and University of Tampere, Tampere, Finland
- Research Unit of Internal Medicine, University of Oulu, Oulu, Finland
- Medical Research Center Oulu, Oulu University Hospital, Oulu, Finland
| | - Global Biobank Meta-Analysis Initiative (GBMI)
- Institute for Molecular Medicine, Finland (FIMM), HiLIFE, University of Helsinki, Helsinki, Finland
- Analytic and Translational Genetics Unit, Department of Medicine, Massachusetts General Hospital, Boston, MA, USA
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Individualized Drug Therapy Research Program, Faculty of Medicine, University of Helsinki, Helsinki, Finland
- Department of Pulmonary Medicine, Heart and Lung Center, Helsinki University Hospital, Helsinki, Finland
- Department of Health Sciences, University of Leicester, Leicester, UK
- Human Genetics, Genentech, South San Francisco, CA, USA
- Division of Pulmonary, Critical Care and Sleep Medicine, Department of Internal Medicine, University of California, Davis, Sacramento, CA, USA
- Department of Medicine, Division of Genetic Medicine, Vanderbilt University Medical Center, Nashville, TN, USA
- Vanderbilt Genetic Institute, Vanderbilt University Medical Center, Nashville, TN, USA
- Department of Medicine, University of Colorado, Aurora, CO, USA
- Center for Genes, Environment and Health, National Jewish Health, Denver, CO, USA
- Research Unit, Hospital Universitario Ntra. Sra. de Candelaria, Santa Cruz de Tenerife, Spain
- CIBER de Enfermedades Respiratorias, Instituto de Salud Carlos III, Madrid, Spain
- Genomics Division, Instituto Tecnológico y de Energías Renovables (ITER), Santa Cruz de Tenerife, Spain
- Faculty of Health Sciences, University of Fernando Pessoa Canarias, Las Palmas de Gran Canaria, Spain
- Division of Pulmonary and Critical Care Medicine, Department of Medicine, University of Virginia, Charlottesville, VA, USA
- National Heart and Lung Institute, Imperial College London, London, UK
- Royal Brompton and Harefield Hospitals, Guy's and St Thomas' NHS Foundation Trust, London, UK
- National Institute for Health Research, Leicester Respiratory Biomedical Research Centre, Glenfield Hospital, Leicester, UK
- Faculty of Medicine, University of Helsinki, Helsinki, Finland
- Department of Public Health, University of Helsinki, Helsinki, Finland
- Department of Mathematics and Statistics, University of Helsinki, Helsinki, Finland
- Administration Center, Tampere University Hospital and University of Tampere, Tampere, Finland
- Research Unit of Internal Medicine, University of Oulu, Oulu, Finland
- Medical Research Center Oulu, Oulu University Hospital, Oulu, Finland
| | - Tarja Laitinen
- Administration Center, Tampere University Hospital and University of Tampere, Tampere, Finland
| | - Riitta Kaarteenaho
- Research Unit of Internal Medicine, University of Oulu, Oulu, Finland
- Medical Research Center Oulu, Oulu University Hospital, Oulu, Finland
| | - Marjukka Myllärniemi
- Individualized Drug Therapy Research Program, Faculty of Medicine, University of Helsinki, Helsinki, Finland
- Department of Pulmonary Medicine, Heart and Lung Center, Helsinki University Hospital, Helsinki, Finland
| | - Mark J. Daly
- Institute for Molecular Medicine, Finland (FIMM), HiLIFE, University of Helsinki, Helsinki, Finland
- Analytic and Translational Genetics Unit, Department of Medicine, Massachusetts General Hospital, Boston, MA, USA
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Jukka T. Koskela
- Institute for Molecular Medicine, Finland (FIMM), HiLIFE, University of Helsinki, Helsinki, Finland
| |
Collapse
|
34
|
Hartley AE, Power GM, Sanderson E, Smith GD. A Guide for Understanding and Designing Mendelian Randomization Studies in the Musculoskeletal Field. JBMR Plus 2022; 6:e10675. [PMID: 36248277 PMCID: PMC9549705 DOI: 10.1002/jbm4.10675] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/20/2022] [Accepted: 08/08/2022] [Indexed: 11/10/2022] Open
Abstract
Mendelian randomization (MR) is an increasingly popular component of an epidemiologist's toolkit, used to provide evidence of a causal effect of one trait (an exposure, eg, body mass index [BMI]) on an outcome trait or disease (eg, osteoarthritis). Identifying these effects is important for understanding disease etiology and potentially identifying targets for therapeutic intervention. MR uses genetic variants as instrumental variables for the exposure, which should not be influenced by the outcome or confounding variables, overcoming key limitations of traditional epidemiological analyses. For MR to generate a valid estimate of effect, key assumptions must be met. In recent years, there has been a rapid rise in MR methods that aim to test, or are robust to violations of, these assumptions. In this review, we provide an overview of MR for a non-expert audience, including an explanation of these key assumptions and how they are often tested, to aid a better reading and understanding of the MR literature. We highlight some of these new methods and how they can be useful for specific methodological challenges in the musculoskeletal field, including for conditions or traits that share underlying biological pathways, such as bone and joint disease. © 2022 The Authors. JBMR Plus published by Wiley Periodicals LLC on behalf of American Society for Bone and Mineral Research.
Collapse
Affiliation(s)
- April E Hartley
- MRC‐Integrative Epidemiology UnitPopulation Health Sciences, Bristol Medical SchoolBristolUK
| | - Grace M Power
- MRC‐Integrative Epidemiology UnitPopulation Health Sciences, Bristol Medical SchoolBristolUK
| | - Eleanor Sanderson
- MRC‐Integrative Epidemiology UnitPopulation Health Sciences, Bristol Medical SchoolBristolUK
| | - George Davey Smith
- MRC‐Integrative Epidemiology UnitPopulation Health Sciences, Bristol Medical SchoolBristolUK
| |
Collapse
|
35
|
Seviiri M, Scolyer RA, Bishop DT, Newton-Bishop JA, Iles MM, Lo SN, Stretch JR, Saw RPM, Nieweg OE, Shannon KF, Spillane AJ, Gordon SD, Olsen CM, Whiteman DC, Landi MT, Thompson JF, Long GV, MacGregor S, Law MH. Higher polygenic risk for melanoma is associated with improved survival in a high ultraviolet radiation setting. J Transl Med 2022; 20:403. [PMID: 36064556 PMCID: PMC9446843 DOI: 10.1186/s12967-022-03613-2] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/01/2022] [Accepted: 08/24/2022] [Indexed: 12/03/2022] Open
Abstract
BACKGROUND The role of germline genetic factors in determining survival from cutaneous melanoma (CM) is not well understood. OBJECTIVE To perform a genome-wide association study (GWAS) meta-analysis of melanoma-specific survival (MSS), and test whether a CM-susceptibility polygenic risk score (PRS) is associated with MSS. METHODS We conducted two Cox proportional-hazard GWAS of MSS using data from the Melanoma Institute Australia, a high ultraviolet (UV) radiation setting (MIA; 5,762 patients with melanoma; 800 melanoma deaths) and UK Biobank (UKB: 5,220 patients with melanoma; 241 melanoma deaths), and combined them in a fixed-effects meta-analysis. Significant (P < 5 × 10-8) results were investigated in the Leeds Melanoma Cohort (LMC; 1,947 patients with melanoma; 370 melanoma deaths). We also developed a CM-susceptibility PRS using a large independent GWAS meta-analysis (23,913 cases, 342,870 controls). The PRS was tested for an association with MSS in the MIA and UKB cohorts. RESULTS Two loci were significantly associated with MSS in the meta-analysis of MIA and UKB with lead SNPs rs41309643 (G allele frequency 1.6%, HR = 2.09, 95%CI = 1.61-2.71, P = 2.08 × 10-8) on chromosome 1, and rs75682113 (C allele frequency 1.8%, HR = 2.38, 95%CI = 1.77-3.21, P = 1.07 × 10-8) on chromosome 7. While neither SNP replicated in the LMC, rs75682113 was significantly associated in the combined discovery and replication sets. After adjusting for age at diagnosis, sex and the first ten principal components, a one standard deviation increase in the CM-susceptibility PRS was associated with improved MSS in the discovery meta-analysis (HR = 0.88, 95% CI = 0.83-0.94, P = 6.93 × 10-5; I2 = 88%). However, this was only driven by the high UV setting cohort (MIA HR = 0.84, 95% CI = 0.78-0.90). CONCLUSION We found two loci potentially associated with MSS. Increased genetic susceptibility to develop CM is associated with improved MSS in a high UV setting.
Collapse
Affiliation(s)
- Mathias Seviiri
- Statistical Genetics Lab, QIMR Berghofer Medical Research Institute, 300 Herston Road, Herston, QLD 4006 Australia
- School of Biomedical Sciences, Faculty of Health, Queensland University of Technology, Brisbane, QLD Australia
- Center for Genomics and Personalised Health, Queensland University of Technology, Brisbane, QLD Australia
| | - Richard A. Scolyer
- Melanoma Institute Australia, The University of Sydney, Sydney, NSW Australia
- Faculty of Medicine and Health, The University of Sydney, Sydney, NSW Australia
- Department of Tissue Oncology and Diagnostic Pathology, Royal Prince Alfred Hospital, Sydney, NSW Australia
- NSW Health Pathology, Sydney, NSW Australia
| | - D. Timothy Bishop
- Division of Haematology and Immunology, Leeds Institute of Medical Research at St James’, University of Leeds, Leeds, UK
| | - Julia A. Newton-Bishop
- Division of Haematology and Immunology, Leeds Institute of Medical Research at St James’, University of Leeds, Leeds, UK
| | - Mark M. Iles
- St James’s Institute of Medical Research, University of Leeds, Leeds, UK
- Leeds Institute of Data Analytics, University of Leeds, Leeds, UK
| | - Serigne N. Lo
- Melanoma Institute Australia, The University of Sydney, Sydney, NSW Australia
- Faculty of Medicine and Health, The University of Sydney, Sydney, NSW Australia
| | - Johnathan R. Stretch
- Melanoma Institute Australia, The University of Sydney, Sydney, NSW Australia
- Faculty of Medicine and Health, The University of Sydney, Sydney, NSW Australia
- Department of Melanoma and Surgical Oncology, Royal Prince Alfred Hospital, Camperdown, NSW Australia
| | - Robyn P. M. Saw
- Melanoma Institute Australia, The University of Sydney, Sydney, NSW Australia
- Faculty of Medicine and Health, The University of Sydney, Sydney, NSW Australia
- Department of Melanoma and Surgical Oncology, Royal Prince Alfred Hospital, Camperdown, NSW Australia
| | - Omgo E. Nieweg
- Melanoma Institute Australia, The University of Sydney, Sydney, NSW Australia
- Faculty of Medicine and Health, The University of Sydney, Sydney, NSW Australia
- Department of Melanoma and Surgical Oncology, Royal Prince Alfred Hospital, Camperdown, NSW Australia
| | - Kerwin F. Shannon
- Melanoma Institute Australia, The University of Sydney, Sydney, NSW Australia
- Department of Melanoma and Surgical Oncology, Royal Prince Alfred Hospital, Camperdown, NSW Australia
- Sydney Head & Neck Cancer Institute, Chris O’Brien Lifehouse Cancer Center, Sydney, NSW Australia
| | - Andrew J. Spillane
- Melanoma Institute Australia, The University of Sydney, Sydney, NSW Australia
- Faculty of Medicine and Health, The University of Sydney, Sydney, NSW Australia
- Department of Breast and Melanoma Surgery, Royal North Shore Hospital, Sydney, NSW Australia
| | - Scott D. Gordon
- Genetic Epidemiology Lab, QIMR Berghofer Medical Research Institute, Brisbane, QLD Australia
| | - Catherine M. Olsen
- Cancer Control Group, QIMR Berghofer Medical Research Institute, Brisbane, QLD Australia
- Faculty of Medicine, University of Queensland, Brisbane, QLD Australia
| | - David C. Whiteman
- Cancer Control Group, QIMR Berghofer Medical Research Institute, Brisbane, QLD Australia
| | - Maria Teresa Landi
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, MD USA
| | - John F. Thompson
- Melanoma Institute Australia, The University of Sydney, Sydney, NSW Australia
- Faculty of Medicine and Health, The University of Sydney, Sydney, NSW Australia
- Department of Melanoma and Surgical Oncology, Royal Prince Alfred Hospital, Camperdown, NSW Australia
| | - Georgina V. Long
- Melanoma Institute Australia, The University of Sydney, Sydney, NSW Australia
- Faculty of Medicine and Health, The University of Sydney, Sydney, NSW Australia
- Department of Medical Oncology, Mater Hospital, North Sydney, NSW Australia
- Department of Medical Oncology, Royal North Shore Hospital, St Leonards, NSW Australia
| | - Stuart MacGregor
- Statistical Genetics Lab, QIMR Berghofer Medical Research Institute, 300 Herston Road, Herston, QLD 4006 Australia
- School of Biomedical Sciences, Faculty of Health, Queensland University of Technology, Brisbane, QLD Australia
| | - Matthew H. Law
- Statistical Genetics Lab, QIMR Berghofer Medical Research Institute, 300 Herston Road, Herston, QLD 4006 Australia
- School of Biomedical Sciences, Faculty of Health, Queensland University of Technology, Brisbane, QLD Australia
| |
Collapse
|
36
|
Towards Treatable Traits for Pulmonary Fibrosis. J Pers Med 2022; 12:jpm12081275. [PMID: 36013224 PMCID: PMC9410230 DOI: 10.3390/jpm12081275] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/15/2022] [Revised: 07/24/2022] [Accepted: 07/29/2022] [Indexed: 11/17/2022] Open
Abstract
Interstitial lung diseases (ILD) are a heterogeneous group of disorders, of which many have the potential to lead to progressive pulmonary fibrosis. A distinction is usually made between primarily inflammatory ILD and primarily fibrotic ILD. As recent studies show that anti-fibrotic drugs can be beneficial in patients with primarily inflammatory ILD that is characterized by progressive pulmonary fibrosis, treatment decisions have become more complicated. In this perspective, we propose that the ‘treatable trait’ concept, which is based on the recognition of relevant exposures, various treatable phenotypes (disease manifestations) or endotypes (shared molecular mechanisms) within a group of diseases, can be applied to progressive pulmonary fibrosis. These targets for medical intervention can be identified through validated biomarkers and are not necessarily related to specific diagnostic labels. Proposed treatable traits are: cigarette smoking, occupational, allergen or drug exposures, excessive (profibrotic) auto- or alloimmunity, progressive pulmonary fibrosis, pulmonary hypertension, obstructive sleep apnea, tuberculosis, exercise intolerance, exertional hypoxia, and anxiety and depression. There are also several potential traits that have not been associated with relevant outcomes or for which no effective treatment is available at present: air pollution, mechanical stress, viral infections, bacterial burden in the lungs, surfactant-related pulmonary fibrosis, telomere-related pulmonary fibrosis, the rs35705950 MUC5B promoter polymorphism, acute exacerbations, gastro-esophageal reflux, dyspnea, and nocturnal hypoxia. The ‘treatable traits’ concept can be applied in new clinical trials for patients with progressive pulmonary fibrosis and could be used for developing new treatment strategies.
Collapse
|
37
|
Yang Q, Sanderson E, Tilling K, Borges MC, Lawlor DA. Exploring and mitigating potential bias when genetic instrumental variables are associated with multiple non-exposure traits in Mendelian randomization. Eur J Epidemiol 2022; 37:683-700. [PMID: 35622304 PMCID: PMC9329407 DOI: 10.1007/s10654-022-00874-5] [Citation(s) in RCA: 22] [Impact Index Per Article: 11.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/06/2020] [Accepted: 04/18/2022] [Indexed: 12/19/2022]
Abstract
With the increasing size and number of genome-wide association studies, individual single nucleotide polymorphisms are increasingly found to associate with multiple traits. Many different mechanisms could result in proposed genetic IVs for an exposure of interest being associated with multiple non-exposure traits, some of which could bias MR results. We describe and illustrate, through causal diagrams, a range of scenarios that could result in proposed IVs being related to non-exposure traits in MR studies. These associations could occur due to five scenarios: (i) confounding, (ii) vertical pleiotropy, (iii) horizontal pleiotropy, (iv) reverse causation and (v) selection bias. For each of these scenarios we outline steps that could be taken to explore the underlying mechanism and mitigate any resulting bias in the MR estimation. We recommend MR studies explore possible IV-non-exposure associations across a wider range of traits than is usually the case. We highlight the pros and cons of relying on sensitivity analyses without considering particular pleiotropic paths versus systematically exploring and controlling for potential pleiotropic or other biasing paths via known traits. We apply our recommendations to an illustrative example of the effect of maternal insomnia on offspring birthweight in UK Biobank.
Collapse
Affiliation(s)
- Qian Yang
- MRC Integrative Epidemiology Unit at the University of Bristol, Bristol, UK.
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK.
| | - Eleanor Sanderson
- MRC Integrative Epidemiology Unit at the University of Bristol, Bristol, UK
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
| | - Kate Tilling
- MRC Integrative Epidemiology Unit at the University of Bristol, Bristol, UK
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
- National Institute for Health Research Bristol Biomedical Centre, University Hospitals Bristol NHS Foundation Trust and University of Bristol, Bristol, UK
| | - Maria Carolina Borges
- MRC Integrative Epidemiology Unit at the University of Bristol, Bristol, UK
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
| | - Deborah A Lawlor
- MRC Integrative Epidemiology Unit at the University of Bristol, Bristol, UK
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
- National Institute for Health Research Bristol Biomedical Centre, University Hospitals Bristol NHS Foundation Trust and University of Bristol, Bristol, UK
| |
Collapse
|
38
|
Liu GY, Budinger GRS, Dematte JE. Advances in the management of idiopathic pulmonary fibrosis and progressive pulmonary fibrosis. BMJ 2022; 377:e066354. [PMID: 36946547 DOI: 10.1136/bmj-2021-066354] [Citation(s) in RCA: 24] [Impact Index Per Article: 12.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/03/2022]
Abstract
Similarly to idiopathic pulmonary fibrosis (IPF), other interstitial lung diseases can develop progressive pulmonary fibrosis (PPF) characterized by declining lung function, a poor response to immunomodulatory therapies, and early mortality. The pathophysiology of disordered lung repair involves common downstream pathways that lead to pulmonary fibrosis in both IPF and PPF. The antifibrotic drugs, such as nintedanib, are indicated for the treatment of IPF and PPF, and new therapies are being evaluated in clinical trials. Clinical, radiographic, and molecular biomarkers are needed to identify patients with PPF and subgroups of patients likely to respond to specific therapies. This article reviews the evidence supporting the use of specific therapies in patients with IPF and PPF, discusses agents being considered in clinical trials, and considers potential biomarkers based on disease pathogenesis that might be used to provide a personalized approach to care.
Collapse
Affiliation(s)
- Gabrielle Y Liu
- Division of Pulmonary and Critical Care Medicine, Department of Medicine, Northwestern University, Chicago, IL, USA
| | - G R Scott Budinger
- Division of Pulmonary and Critical Care Medicine, Department of Medicine, Northwestern University, Chicago, IL, USA
| | - Jane E Dematte
- Division of Pulmonary and Critical Care Medicine, Department of Medicine, Northwestern University, Chicago, IL, USA
| |
Collapse
|
39
|
Lee H, Han B. A theory-based practical solution to correct for sex-differential participation bias. Genome Biol 2022; 23:138. [PMID: 35761388 PMCID: PMC9238114 DOI: 10.1186/s13059-022-02703-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/22/2021] [Accepted: 06/13/2022] [Indexed: 11/24/2022] Open
Abstract
Most genomic cohorts are retrospective where the exposures and outcomes are predetermined prior to sample collection. Therefore, a spurious association between an exposure and an outcome can arise if both variables affect study participation. Such concerns were raised in previous studies questioning the representativeness of the UK Biobank. Recently, a genome-wide association study (GWAS) on biological sex found many autosomal hits and non-negligible autosomal heritability which the authors attribute to selection bias. In this study, we propose a simple and a practical method that can overcome sex-driven selection bias based on theoretical analysis and simulations.
Collapse
Affiliation(s)
- Hanbin Lee
- Department of Medicine, Seoul National University College of Medicine, 103 Daehak-ro, Jongno-gu, Seoul, 03080, Republic of Korea.
| | - Buhm Han
- Department of Medicine, Seoul National University College of Medicine, 103 Daehak-ro, Jongno-gu, Seoul, 03080, Republic of Korea. .,Department of Biomedical Sciences, BK21 Plus Biomedical Science Project, Seoul National University College of Medicine, 103 Daehak-ro, Jongno-gu, Seoul, 03080, Republic of Korea. .,Interdisciplinary Program in Bioengineering, Seoul National University, Seoul, 08826, Republic of Korea.
| |
Collapse
|
40
|
Cai S, Hartley A, Mahmoud O, Tilling K, Dudbridge F. Adjusting for collider bias in genetic association studies using instrumental variable methods. Genet Epidemiol 2022; 46:303-316. [PMID: 35583096 PMCID: PMC9544531 DOI: 10.1002/gepi.22455] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/01/2022] [Revised: 04/12/2022] [Accepted: 04/20/2022] [Indexed: 11/16/2022]
Abstract
Genome‐wide association studies have provided many genetic markers that can be used as instrumental variables to adjust for confounding in epidemiological studies. Recently, the principle has been applied to other forms of bias in observational studies, especially collider bias that arises when conditioning or stratifying on a variable that is associated with the outcome of interest. An important case is in studies of disease progression and survival. Here, we clarify the links between the genetic instrumental variable methods proposed for this problem and the established methods of Mendelian randomisation developed to account for confounding. We highlight the critical importance of weak instrument bias in this context and describe a corrected weighted least‐squares procedure as a simple approach to reduce this bias. We illustrate the range of available methods on two data examples. The first, waist–hip ratio adjusted for body‐mass index, entails statistical adjustment for a quantitative trait. The second, smoking cessation, is a stratified analysis conditional on having initiated smoking. In both cases, we find little effect of collider bias on the primary association results, but this may propagate into more substantial effects on further analyses such as polygenic risk scoring and Mendelian randomisation.
Collapse
Affiliation(s)
- Siyang Cai
- Department of Health Sciences, University of Leicester, Leicester, UK
| | - April Hartley
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol, UK
| | - Osama Mahmoud
- Department of Mathematical Sciences, University of Essex, Colchester, UK
| | - Kate Tilling
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol, UK.,Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
| | - Frank Dudbridge
- Department of Health Sciences, University of Leicester, Leicester, UK
| |
Collapse
|
41
|
Hamilton FW, Somers J, Mitchell RE, Ghazal P, Timpson NJ. HMOX1 genetic polymorphisms and outcomes in infectious disease: A systematic review. PLoS One 2022; 17:e0267399. [PMID: 35551540 PMCID: PMC9098073 DOI: 10.1371/journal.pone.0267399] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/24/2021] [Accepted: 04/07/2022] [Indexed: 11/18/2022] Open
Abstract
INTRODUCTION Heme-oxygenase 1 (HMOX1) is a critical stress response gene that catalyzes the multistep oxidation of heme. A GT(n) repeat of variable length in the promoter in has been associated with a wide range of human diseases, including infections. This paper aims to summarise and systematically review associations between the length of the HMOX1 GT(n) promoter and infectious disease in humans. METHODS A search using relevant terms was performed in PubMED and EMBASE through to 15/01/21 identifying all research that studied an association between the HMOX1 GT(n) repeat polymorphism and the incidence and/or outcome of any human infectious disease. Citations were screened for additional studies. Potential studies were screened for inclusion by two authors. Data was extracted on allele frequency, genotype, strength of association, mechanism of genotyping, and potential biases. A narrative review was performed across each type of infection. RESULTS 1,533 studies were identified in the search, and one via citation screening. Sixteen studies were ultimately included, seven in malaria, three in HIV, three in sepsis, and one each in pneumonia, hepatitis C, and acute respiratory distress syndrome (ARDS). Sample sizes for nearly all studies were small (biggest study, n = 1,646). Allelic definition was different across all included studies. All studies were at some risk of bias. In malaria, three studies suggested that longer alleles were associated with reduced risk of severe malaria, particularly malaria-induced renal dysfunction, with four studies identifying a null association. In sepsis, two studies suggested an association with longer alleles and better outcomes. CONCLUSIONS Despite the importance of HMOX1 in survival from infection, and the association between repeat length and gene expression, the clinical data supporting an association between repeat length and incidence and/or outcome of infection remain inconclusive.
Collapse
Affiliation(s)
- Fergus W. Hamilton
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol, United Kingdom
- Infection Sciences, North Bristol NHS Trust, Bristol, United Kingdom
| | - Julia Somers
- Knight Cancer Research Building, Oregon Health and Sciences University, Portland, Oregon, United States of America
| | - Ruth E. Mitchell
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol, United Kingdom
| | - Peter Ghazal
- System Immunity Research Institute, Division of Infection and Immunity, Cardiff University, Cardiff, United Kingdom
| | - Nicholas J. Timpson
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol, United Kingdom
| |
Collapse
|
42
|
Zhou A, Selvanayagam JB, Hyppönen E. Non-linear Mendelian randomization analyses support a role for vitamin D deficiency in cardiovascular disease risk. Eur Heart J 2022; 43:1731-1739. [PMID: 34891159 DOI: 10.1093/eurheartj/ehab809] [Citation(s) in RCA: 104] [Impact Index Per Article: 52.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/17/2021] [Revised: 09/28/2021] [Accepted: 11/12/2021] [Indexed: 11/14/2022] Open
Abstract
AIMS Low vitamin D status is associated with a higher risk for cardiovascular diseases (CVDs). Although most existing linear Mendelian randomization (MR) studies reported a null effect of vitamin D on CVD risk, a non-linear effect cannot be excluded. Our aim was to apply the non-linear MR design to investigate the association of serum 25-hydroxyvitamin D [25(OH)D] concentration with CVD risk. METHODS AND RESULTS The non-linear MR analysis was conducted in the UK Biobank with 44 519 CVD cases and 251 269 controls. Blood pressure (BP) and cardiac-imaging-derived phenotypes were included as secondary outcomes. Serum 25(OH)D concentration was instrumented using 35 confirmed genome-wide significant variants.We also estimated the potential reduction in CVD incidence attributable to correction of low vitamin D status. There was a L-shaped association between genetically predicted serum 25(OH)D and CVD risk (Pnon-linear = 0.007), where CVD risk initially decreased steeply with increasing concentrations and levelled off at around 50 nmol/L. A similar association was seen for systolic (Pnon-linear = 0.03) and diastolic (Pnon-linear = 0.07) BP. No evidence of association was seen for cardiac-imaging phenotypes (P = 0.05 for all). Correction of serum 25(OH)D level below 50 nmol/L was predicted to result in a 4.4% reduction in CVD incidence (95% confidence interval: 1.8- 7.3%). CONCLUSION Vitamin D deficiency can increase the risk of CVD. Burden of CVD could be reduced by population-wide correction of low vitamin D status.
Collapse
Affiliation(s)
- Ang Zhou
- Australian Center for Precision Health, University of South Australia Cancer Research Institute, GPO Box 2471, Adelaide, SA 5001, Australia
- South Australian Health and Medical Research Institute, North Terrace, Adelaide, SA 5000, Australia
| | - Joseph B Selvanayagam
- South Australian Health and Medical Research Institute, North Terrace, Adelaide, SA 5000, Australia
- Department of Cardiovascular Medicine, Flinders Medical Centre, Bedford Park, Adelaide, SA 5042, Australia
| | - Elina Hyppönen
- Australian Center for Precision Health, University of South Australia Cancer Research Institute, GPO Box 2471, Adelaide, SA 5001, Australia
- South Australian Health and Medical Research Institute, North Terrace, Adelaide, SA 5000, Australia
- Population, Policy and Practice, UCL Great Ormond Street Institute of Child Health, 30 Guilford Street, London, UK
| |
Collapse
|
43
|
Dhooria S, Bal A, Sehgal IS, Prasad KT, Kashyap D, Sharma R, Muthu V, Agarwal R, Aggarwal AN. MUC5B Promoter Polymorphism and Survival in Indian Patients With Idiopathic Pulmonary Fibrosis. Chest 2022; 162:824-827. [DOI: 10.1016/j.chest.2022.04.001] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/08/2022] [Revised: 03/26/2022] [Accepted: 04/03/2022] [Indexed: 10/18/2022] Open
|
44
|
Verstockt B, Parkes M, Lee JC. How Do We Predict a Patient's Disease Course and Whether They Will Respond to Specific Treatments? Gastroenterology 2022; 162:1383-1395. [PMID: 34995535 DOI: 10.1053/j.gastro.2021.12.245] [Citation(s) in RCA: 28] [Impact Index Per Article: 14.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/01/2021] [Revised: 12/09/2021] [Accepted: 12/09/2021] [Indexed: 02/07/2023]
Abstract
Gastroenterologists will be all too familiar with the difficult decisions that managing inflammatory bowel disease often presents. How aggressively should I treat this patient? Do I expect them to have a mild or aggressive form of disease? Do they need a biologic? If so, which one? And when should I start it? The reality is that the answers that would be right for one patient might be disastrous for another. The growing therapeutic armamentarium will only make these decisions more difficult, and yet, we have seen how other specialties have begun to use the molecular heterogeneity in their diseases to provide some answers. Here, we review the progress that has been made in predicting the future for any given patient with inflammatory bowel disease-whether that is the course of disease that they will experience or whether or not they will respond to, or indeed tolerate, a particular therapy.
Collapse
Affiliation(s)
- Bram Verstockt
- Department of Gastroenterology and Hepatology, University Hospitals Leuven, Katholieke Universiteit Leuven, Leuven, Belgium; Department of Chronic Diseases and Metabolism, Translational Research Center for Gastrointestinal Disorders-Inflammatory Bowel Disease (TARGID-IBD), Katholieke Universiteit Leuven, Leuven, Belgium
| | - Miles Parkes
- Department of Medicine, University of Cambridge School of Clinical Medicine, Cambridge Biomedical Campus, Cambridge, United Kingdom
| | - James C Lee
- Genetic Mechanisms of Disease Laboratory, Francis Crick Institute, London, United Kingdom; Institute for Liver & Digestive Health, Royal Free London Hospital, University College London, London, United Kingdom.
| |
Collapse
|
45
|
Mahmoud O, Dudbridge F, Davey Smith G, Munafo M, Tilling K. A robust method for collider bias correction in conditional genome-wide association studies. Nat Commun 2022; 13:619. [PMID: 35110547 PMCID: PMC8810923 DOI: 10.1038/s41467-022-28119-9] [Citation(s) in RCA: 22] [Impact Index Per Article: 11.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/05/2020] [Accepted: 01/04/2022] [Indexed: 11/26/2022] Open
Abstract
Estimated genetic associations with prognosis, or conditional on a phenotype (e.g. disease incidence), may be affected by collider bias, whereby conditioning on the phenotype induces associations between causes of the phenotype and prognosis. We propose a method, 'Slope-Hunter', that uses model-based clustering to identify and utilise the class of variants only affecting the phenotype to estimate the adjustment factor, assuming this class explains more variation in the phenotype than any other variant classes. Simulation studies show that our approach eliminates the bias and outperforms alternatives even in the presence of genetic correlation. In a study of fasting blood insulin levels (FI) conditional on body mass index, we eliminate paradoxical associations of the underweight loci: COBLLI; PPARG with increased FI, and reveal an association for the locus rs1421085 (FTO). In an analysis of a case-only study for breast cancer mortality, a single region remains associated with more pronounced results.
Collapse
Affiliation(s)
- Osama Mahmoud
- Department of Mathematical Sciences, University of Essex, Colchester, UK.
- Department of Applied Statistics, Helwan University, Helwan, Egypt.
| | - Frank Dudbridge
- Department of Health Sciences, University of Leicester, Leicester, UK
| | - George Davey Smith
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol, UK
- Department of Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
| | - Marcus Munafo
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol, UK
- School of Psychological Science, University of Bristol, Bristol, UK
| | - Kate Tilling
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol, UK
- Department of Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
| |
Collapse
|
46
|
Untangling 11p15.5 for Chronic Hypersensitivity Pneumonitis. Chest 2022; 161:307-308. [DOI: 10.1016/j.chest.2021.08.055] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/17/2021] [Accepted: 08/17/2021] [Indexed: 11/18/2022] Open
|
47
|
Chong MR, Narula S, Morton R, Judge C, Akhabir L, Cawte N, Pathan N, Lali R, Mohammadi-Shemirani P, Shoamanesh A, O'Donnell M, Yusuf S, Langhorne P, Paré G. Mitochondrial DNA Copy Number as a Marker and Mediator of Stroke Prognosis: Observational and Mendelian Randomization Analyses. Neurology 2022; 98:e470-e482. [PMID: 34880091 PMCID: PMC8826461 DOI: 10.1212/wnl.0000000000013165] [Citation(s) in RCA: 11] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/08/2021] [Accepted: 11/24/2021] [Indexed: 02/03/2023] Open
Abstract
BACKGROUND AND OBJECTIVES Low buffy coat mitochondrial DNA copy number (mtDNA-CN) is associated with incident risk of stroke and poststroke mortality; however, its prognostic utility has not been extensively explored. Our goal was to investigate whether low buffy coat mtDNA-CN is a marker and causal determinant of poststroke outcomes using epidemiologic and genetic studies. METHODS First, we performed association testing between baseline buffy coat mtDNA-CN measurements and 1-month poststroke outcomes in 3,498 cases of acute, first stroke from 25 countries from the international, multicenter case-control study Importance of Conventional and Emerging Risk Factors of Stroke in Different Regions and Ethnic Groups of the World (INTERSTROKE). Then, we performed 2-sample mendelian randomization analyses to evaluate potential causative effects of low mtDNA-CN on 3-month modified Rankin Scale (mRS) score. Genetic variants associated with mtDNA-CN levels were derived from the UK Biobank study (N = 383,476), and corresponding effects on 3-month mRS score were ascertained from the Genetics of Ischemic Stroke Functional Outcome (GISCOME; N = 6,021) study. RESULTS A 1-SD lower mtDNA-CN at baseline was associated with stroke severity (baseline mRS score: odds ratio [OR] 1.27, 95% confidence interval [CI] 1.19-1.36; p = 4.7 × 10-12). Independently of baseline stroke severity, lower mtDNA-CN was associated with increased odds of greater 1-month disability (ordinal mRS score: OR 1.16, 95% CI 1.08-1.24; p = 4.4 × 10-5), poor functional outcome status (mRS score 3-6 vs 0-2: OR 1.21, 95% CI 1.08-1.34; p = 6.9 × 10-4), and mortality (OR 1.35, 95% CI 1.14-1.59; p = 3.9 × 10-4). Subgroup analyses demonstrated consistent effects across stroke type, sex, age, country income level, and education level. In addition, mtDNA-CN significantly improved reclassification of poor functional outcome status (net reclassification index [NRI] score 0.16, 95% CI 0.08-0.23; p = 3.6 × 10-5) and mortality (NRI score 0.31, 95% CI 0.19-0.43; p = 1.7 × 10-7) beyond known prognosticators. With the use of independent datasets, mendelian randomization revealed that a 1-SD decrease in genetically determined mtDNA-CN was associated with increased odds of greater 3-month disability quantified by ordinal mRS score (OR 2.35, 95% CI 1.13-4.90; p = 0.02) and poor functional outcome status (OR 2.68, 95% CI 1.05-6.86; p = 0.04). DISCUSSION Buffy coat mtDNA-CN is a novel and robust marker of poststroke prognosis that may also be a causal determinant of poststroke outcomes. CLASSIFICATION OF EVIDENCE This study provides Class II evidence that low buffy coat mtDNA-CN (>1 SD) was associated with worse baseline severity and 1-month outcomes in patients with ischemic or hemorrhagic stroke.
Collapse
Affiliation(s)
- Michael Robert Chong
- From the Population Health Research Institute (M.R.C., S.N., R.M., C.J., L.A., N.C., N.P., R.L., P.M.-S., A.S., M.O., S.Y., G.P.), David Braley Cardiac, Vascular and Stroke Research Institute, Hamilton Health Sciences; Thrombosis and Atherosclerosis Research Institute (M.R.C., S.N., R.M., C.J., L.A., N.C., N.P., R.L., P.M.-S., S.Y., G.P.); Department of Biochemistry and Biomedical Sciences (M.R.C., G.P.), Departments of Pathology and Molecular Medicine (M.R.C., R.M., P.M.-S., G.P.) and Medicine (L.A., A.S., S.Y., G.P.), Michael G. DeGroote School of Medicine, and Department of Health Research Methods, Evidence, and Impact (S.N., R.L., S.Y., G.P.), McMaster University, Hamilton, Ontario, Canada; National University of Ireland Galway (C.J., M.O.); and Institute of Cardiovascular and Medical Sciences (P.L.), University of Glasgow, UK
| | - Sukrit Narula
- From the Population Health Research Institute (M.R.C., S.N., R.M., C.J., L.A., N.C., N.P., R.L., P.M.-S., A.S., M.O., S.Y., G.P.), David Braley Cardiac, Vascular and Stroke Research Institute, Hamilton Health Sciences; Thrombosis and Atherosclerosis Research Institute (M.R.C., S.N., R.M., C.J., L.A., N.C., N.P., R.L., P.M.-S., S.Y., G.P.); Department of Biochemistry and Biomedical Sciences (M.R.C., G.P.), Departments of Pathology and Molecular Medicine (M.R.C., R.M., P.M.-S., G.P.) and Medicine (L.A., A.S., S.Y., G.P.), Michael G. DeGroote School of Medicine, and Department of Health Research Methods, Evidence, and Impact (S.N., R.L., S.Y., G.P.), McMaster University, Hamilton, Ontario, Canada; National University of Ireland Galway (C.J., M.O.); and Institute of Cardiovascular and Medical Sciences (P.L.), University of Glasgow, UK
| | - Robert Morton
- From the Population Health Research Institute (M.R.C., S.N., R.M., C.J., L.A., N.C., N.P., R.L., P.M.-S., A.S., M.O., S.Y., G.P.), David Braley Cardiac, Vascular and Stroke Research Institute, Hamilton Health Sciences; Thrombosis and Atherosclerosis Research Institute (M.R.C., S.N., R.M., C.J., L.A., N.C., N.P., R.L., P.M.-S., S.Y., G.P.); Department of Biochemistry and Biomedical Sciences (M.R.C., G.P.), Departments of Pathology and Molecular Medicine (M.R.C., R.M., P.M.-S., G.P.) and Medicine (L.A., A.S., S.Y., G.P.), Michael G. DeGroote School of Medicine, and Department of Health Research Methods, Evidence, and Impact (S.N., R.L., S.Y., G.P.), McMaster University, Hamilton, Ontario, Canada; National University of Ireland Galway (C.J., M.O.); and Institute of Cardiovascular and Medical Sciences (P.L.), University of Glasgow, UK
| | - Conor Judge
- From the Population Health Research Institute (M.R.C., S.N., R.M., C.J., L.A., N.C., N.P., R.L., P.M.-S., A.S., M.O., S.Y., G.P.), David Braley Cardiac, Vascular and Stroke Research Institute, Hamilton Health Sciences; Thrombosis and Atherosclerosis Research Institute (M.R.C., S.N., R.M., C.J., L.A., N.C., N.P., R.L., P.M.-S., S.Y., G.P.); Department of Biochemistry and Biomedical Sciences (M.R.C., G.P.), Departments of Pathology and Molecular Medicine (M.R.C., R.M., P.M.-S., G.P.) and Medicine (L.A., A.S., S.Y., G.P.), Michael G. DeGroote School of Medicine, and Department of Health Research Methods, Evidence, and Impact (S.N., R.L., S.Y., G.P.), McMaster University, Hamilton, Ontario, Canada; National University of Ireland Galway (C.J., M.O.); and Institute of Cardiovascular and Medical Sciences (P.L.), University of Glasgow, UK
| | - Loubna Akhabir
- From the Population Health Research Institute (M.R.C., S.N., R.M., C.J., L.A., N.C., N.P., R.L., P.M.-S., A.S., M.O., S.Y., G.P.), David Braley Cardiac, Vascular and Stroke Research Institute, Hamilton Health Sciences; Thrombosis and Atherosclerosis Research Institute (M.R.C., S.N., R.M., C.J., L.A., N.C., N.P., R.L., P.M.-S., S.Y., G.P.); Department of Biochemistry and Biomedical Sciences (M.R.C., G.P.), Departments of Pathology and Molecular Medicine (M.R.C., R.M., P.M.-S., G.P.) and Medicine (L.A., A.S., S.Y., G.P.), Michael G. DeGroote School of Medicine, and Department of Health Research Methods, Evidence, and Impact (S.N., R.L., S.Y., G.P.), McMaster University, Hamilton, Ontario, Canada; National University of Ireland Galway (C.J., M.O.); and Institute of Cardiovascular and Medical Sciences (P.L.), University of Glasgow, UK
| | - Nathan Cawte
- From the Population Health Research Institute (M.R.C., S.N., R.M., C.J., L.A., N.C., N.P., R.L., P.M.-S., A.S., M.O., S.Y., G.P.), David Braley Cardiac, Vascular and Stroke Research Institute, Hamilton Health Sciences; Thrombosis and Atherosclerosis Research Institute (M.R.C., S.N., R.M., C.J., L.A., N.C., N.P., R.L., P.M.-S., S.Y., G.P.); Department of Biochemistry and Biomedical Sciences (M.R.C., G.P.), Departments of Pathology and Molecular Medicine (M.R.C., R.M., P.M.-S., G.P.) and Medicine (L.A., A.S., S.Y., G.P.), Michael G. DeGroote School of Medicine, and Department of Health Research Methods, Evidence, and Impact (S.N., R.L., S.Y., G.P.), McMaster University, Hamilton, Ontario, Canada; National University of Ireland Galway (C.J., M.O.); and Institute of Cardiovascular and Medical Sciences (P.L.), University of Glasgow, UK
| | - Nazia Pathan
- From the Population Health Research Institute (M.R.C., S.N., R.M., C.J., L.A., N.C., N.P., R.L., P.M.-S., A.S., M.O., S.Y., G.P.), David Braley Cardiac, Vascular and Stroke Research Institute, Hamilton Health Sciences; Thrombosis and Atherosclerosis Research Institute (M.R.C., S.N., R.M., C.J., L.A., N.C., N.P., R.L., P.M.-S., S.Y., G.P.); Department of Biochemistry and Biomedical Sciences (M.R.C., G.P.), Departments of Pathology and Molecular Medicine (M.R.C., R.M., P.M.-S., G.P.) and Medicine (L.A., A.S., S.Y., G.P.), Michael G. DeGroote School of Medicine, and Department of Health Research Methods, Evidence, and Impact (S.N., R.L., S.Y., G.P.), McMaster University, Hamilton, Ontario, Canada; National University of Ireland Galway (C.J., M.O.); and Institute of Cardiovascular and Medical Sciences (P.L.), University of Glasgow, UK
| | - Ricky Lali
- From the Population Health Research Institute (M.R.C., S.N., R.M., C.J., L.A., N.C., N.P., R.L., P.M.-S., A.S., M.O., S.Y., G.P.), David Braley Cardiac, Vascular and Stroke Research Institute, Hamilton Health Sciences; Thrombosis and Atherosclerosis Research Institute (M.R.C., S.N., R.M., C.J., L.A., N.C., N.P., R.L., P.M.-S., S.Y., G.P.); Department of Biochemistry and Biomedical Sciences (M.R.C., G.P.), Departments of Pathology and Molecular Medicine (M.R.C., R.M., P.M.-S., G.P.) and Medicine (L.A., A.S., S.Y., G.P.), Michael G. DeGroote School of Medicine, and Department of Health Research Methods, Evidence, and Impact (S.N., R.L., S.Y., G.P.), McMaster University, Hamilton, Ontario, Canada; National University of Ireland Galway (C.J., M.O.); and Institute of Cardiovascular and Medical Sciences (P.L.), University of Glasgow, UK
| | - Pedrum Mohammadi-Shemirani
- From the Population Health Research Institute (M.R.C., S.N., R.M., C.J., L.A., N.C., N.P., R.L., P.M.-S., A.S., M.O., S.Y., G.P.), David Braley Cardiac, Vascular and Stroke Research Institute, Hamilton Health Sciences; Thrombosis and Atherosclerosis Research Institute (M.R.C., S.N., R.M., C.J., L.A., N.C., N.P., R.L., P.M.-S., S.Y., G.P.); Department of Biochemistry and Biomedical Sciences (M.R.C., G.P.), Departments of Pathology and Molecular Medicine (M.R.C., R.M., P.M.-S., G.P.) and Medicine (L.A., A.S., S.Y., G.P.), Michael G. DeGroote School of Medicine, and Department of Health Research Methods, Evidence, and Impact (S.N., R.L., S.Y., G.P.), McMaster University, Hamilton, Ontario, Canada; National University of Ireland Galway (C.J., M.O.); and Institute of Cardiovascular and Medical Sciences (P.L.), University of Glasgow, UK
| | - Ashkan Shoamanesh
- From the Population Health Research Institute (M.R.C., S.N., R.M., C.J., L.A., N.C., N.P., R.L., P.M.-S., A.S., M.O., S.Y., G.P.), David Braley Cardiac, Vascular and Stroke Research Institute, Hamilton Health Sciences; Thrombosis and Atherosclerosis Research Institute (M.R.C., S.N., R.M., C.J., L.A., N.C., N.P., R.L., P.M.-S., S.Y., G.P.); Department of Biochemistry and Biomedical Sciences (M.R.C., G.P.), Departments of Pathology and Molecular Medicine (M.R.C., R.M., P.M.-S., G.P.) and Medicine (L.A., A.S., S.Y., G.P.), Michael G. DeGroote School of Medicine, and Department of Health Research Methods, Evidence, and Impact (S.N., R.L., S.Y., G.P.), McMaster University, Hamilton, Ontario, Canada; National University of Ireland Galway (C.J., M.O.); and Institute of Cardiovascular and Medical Sciences (P.L.), University of Glasgow, UK
| | - Martin O'Donnell
- From the Population Health Research Institute (M.R.C., S.N., R.M., C.J., L.A., N.C., N.P., R.L., P.M.-S., A.S., M.O., S.Y., G.P.), David Braley Cardiac, Vascular and Stroke Research Institute, Hamilton Health Sciences; Thrombosis and Atherosclerosis Research Institute (M.R.C., S.N., R.M., C.J., L.A., N.C., N.P., R.L., P.M.-S., S.Y., G.P.); Department of Biochemistry and Biomedical Sciences (M.R.C., G.P.), Departments of Pathology and Molecular Medicine (M.R.C., R.M., P.M.-S., G.P.) and Medicine (L.A., A.S., S.Y., G.P.), Michael G. DeGroote School of Medicine, and Department of Health Research Methods, Evidence, and Impact (S.N., R.L., S.Y., G.P.), McMaster University, Hamilton, Ontario, Canada; National University of Ireland Galway (C.J., M.O.); and Institute of Cardiovascular and Medical Sciences (P.L.), University of Glasgow, UK
| | - Salim Yusuf
- From the Population Health Research Institute (M.R.C., S.N., R.M., C.J., L.A., N.C., N.P., R.L., P.M.-S., A.S., M.O., S.Y., G.P.), David Braley Cardiac, Vascular and Stroke Research Institute, Hamilton Health Sciences; Thrombosis and Atherosclerosis Research Institute (M.R.C., S.N., R.M., C.J., L.A., N.C., N.P., R.L., P.M.-S., S.Y., G.P.); Department of Biochemistry and Biomedical Sciences (M.R.C., G.P.), Departments of Pathology and Molecular Medicine (M.R.C., R.M., P.M.-S., G.P.) and Medicine (L.A., A.S., S.Y., G.P.), Michael G. DeGroote School of Medicine, and Department of Health Research Methods, Evidence, and Impact (S.N., R.L., S.Y., G.P.), McMaster University, Hamilton, Ontario, Canada; National University of Ireland Galway (C.J., M.O.); and Institute of Cardiovascular and Medical Sciences (P.L.), University of Glasgow, UK
| | - Peter Langhorne
- From the Population Health Research Institute (M.R.C., S.N., R.M., C.J., L.A., N.C., N.P., R.L., P.M.-S., A.S., M.O., S.Y., G.P.), David Braley Cardiac, Vascular and Stroke Research Institute, Hamilton Health Sciences; Thrombosis and Atherosclerosis Research Institute (M.R.C., S.N., R.M., C.J., L.A., N.C., N.P., R.L., P.M.-S., S.Y., G.P.); Department of Biochemistry and Biomedical Sciences (M.R.C., G.P.), Departments of Pathology and Molecular Medicine (M.R.C., R.M., P.M.-S., G.P.) and Medicine (L.A., A.S., S.Y., G.P.), Michael G. DeGroote School of Medicine, and Department of Health Research Methods, Evidence, and Impact (S.N., R.L., S.Y., G.P.), McMaster University, Hamilton, Ontario, Canada; National University of Ireland Galway (C.J., M.O.); and Institute of Cardiovascular and Medical Sciences (P.L.), University of Glasgow, UK
| | - Guillaume Paré
- From the Population Health Research Institute (M.R.C., S.N., R.M., C.J., L.A., N.C., N.P., R.L., P.M.-S., A.S., M.O., S.Y., G.P.), David Braley Cardiac, Vascular and Stroke Research Institute, Hamilton Health Sciences; Thrombosis and Atherosclerosis Research Institute (M.R.C., S.N., R.M., C.J., L.A., N.C., N.P., R.L., P.M.-S., S.Y., G.P.); Department of Biochemistry and Biomedical Sciences (M.R.C., G.P.), Departments of Pathology and Molecular Medicine (M.R.C., R.M., P.M.-S., G.P.) and Medicine (L.A., A.S., S.Y., G.P.), Michael G. DeGroote School of Medicine, and Department of Health Research Methods, Evidence, and Impact (S.N., R.L., S.Y., G.P.), McMaster University, Hamilton, Ontario, Canada; National University of Ireland Galway (C.J., M.O.); and Institute of Cardiovascular and Medical Sciences (P.L.), University of Glasgow, UK.
| |
Collapse
|
48
|
Abstract
Mendelian randomization (MR) is a method of studying the causal effects of modifiable exposures (i.e., potential risk factors) on health, social, and economic outcomes using genetic variants associated with the specific exposures of interest. MR provides a more robust understanding of the influence of these exposures on outcomes because germline genetic variants are randomly inherited from parents to offspring and, as a result, should not be related to potential confounding factors that influence exposure-outcome associations. The genetic variant can therefore be used as a tool to link the proposed risk factor and outcome, and to estimate this effect with less confounding and bias than conventional epidemiological approaches. We describe the scope of MR, highlighting the range of applications being made possible as genetic data sets and resources become larger and more freely available. We outline the MR approach in detail, covering concepts, assumptions, and estimation methods. We cover some common misconceptions, provide strategies for overcoming violation of assumptions, and discuss future prospects for extending the clinical applicability, methodological innovations, robustness, and generalizability of MR findings.
Collapse
Affiliation(s)
- Rebecca C Richmond
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol BS8 2BN, United Kingdom
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol BS8 2BN, United Kingdom
| | - George Davey Smith
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol BS8 2BN, United Kingdom
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol BS8 2BN, United Kingdom
- NIHR Bristol Biomedical Research Centre, University Hospitals Bristol NHS Foundation Trust and University of Bristol, Bristol BS1 3NU, United Kingdom
| |
Collapse
|
49
|
Wootton RE, Jones HJ, Sallis HM. Mendelian randomisation for psychiatry: how does it work, and what can it tell us? Mol Psychiatry 2022; 27:53-57. [PMID: 34088980 PMCID: PMC8960388 DOI: 10.1038/s41380-021-01173-3] [Citation(s) in RCA: 17] [Impact Index Per Article: 8.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/06/2021] [Revised: 05/05/2021] [Accepted: 05/12/2021] [Indexed: 11/09/2022]
Abstract
The successful prevention of mental illness relies upon the identification of causal, modifiable risk factors. However, observational evidence exploring such risk factors often produces contradictory results and randomised control trials are often expensive, time-consuming or unethical to conduct. Mendelian randomisation (MR) is a complementary approach that uses naturally occurring genetic variation to identify possible causal effects between a risk factor and an outcome in a time-efficient and low-cost manner. MR utilises genetic variants as instrumental variables for the risk factor of interest. MR studies are becoming more frequent in the field of psychiatry, warranting a reflection upon both the possibilities and the pitfalls. In this Perspective, we consider several limitations of the MR method that are of particular relevance to psychiatry. We also present new MR methods that have exciting applications to questions of mental illness. While we believe that MR can make an important contribution to the field of psychiatry, we also wish to emphasise the importance of clear causal questions, thorough sensitivity analyses, and triangulation with other forms of evidence.
Collapse
Affiliation(s)
- Robyn E Wootton
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol, UK.
- Department of Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK.
- Nic Waals Institute, Lovisenberg Diaconal Hospital, Oslo, Norway.
| | - Hannah J Jones
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol, UK
- Department of Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
- National Institute for Health Research Bristol Biomedical Research Centre, University Hospitals Bristol NHS Foundation Trust, University of Bristol, Bristol, UK
- Centre for Academic Mental Health, Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
| | - Hannah M Sallis
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol, UK
- Department of Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
- Centre for Academic Mental Health, Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
- School of Psychological Science, University of Bristol, Bristol, UK
| |
Collapse
|
50
|
Wang C, Cardenas A, Hutchinson JN, Just A, Heiss J, Hou L, Zheng Y, Coull BA, Kosheleva A, Koutrakis P, Baccarelli AA, Schwartz JD. Short- and intermediate-term exposure to ambient fine particulate elements and leukocyte epigenome-wide DNA methylation in older men: the Normative Aging Study. ENVIRONMENT INTERNATIONAL 2022; 158:106955. [PMID: 34717175 PMCID: PMC8710082 DOI: 10.1016/j.envint.2021.106955] [Citation(s) in RCA: 11] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/18/2021] [Revised: 10/18/2021] [Accepted: 10/22/2021] [Indexed: 05/08/2023]
Abstract
BACKGROUND Several epigenome-wide association studies (EWAS) of ambient particulate matter with aerodynamic diameter ≤ 2.5 µm (PM2.5) have been reported. However, EWAS of PM2.5 elements (PEs), reflecting different emission sources, are very limited. OBJECTIVES We performed EWAS of short- and intermediate-term exposure to PM2.5 and 13 PEs. We hypothesized that significant changes in DNAm may vary by PM2.5 mass and its elements. METHODS We repeatedly collected blood samples in the Normative Aging Study and measured leukocyte DNA methylation (DNAm) with the Illumina HumanMethylation450K BeadChip. We collected daily PM2.5 and 13 PEs at a fixed central site. To estimate the associations between each PE and DNAm at individual cytosine-phosphate-guanine (CpG) sites, we incorporated a distributed-lag (0-27 d) term in the setting of median regression with subject-specific intercept and examined cumulative lag associations. We also accounted for selection bias due to loss to follow-up and mortality prior to enrollment. Significantly differentially methylated probes (DMPs) were identified using Bonferroni correction for multiple testing. We further conducted regional and pathway analyses to identify significantly differentially methylated regions (DMRs) and pathways. RESULTS We included 695 men with 1,266 visits between 1999 and 2013. The subjects had a mean age of 75 years. The significant DMPs, DMRs, and pathways varied by to PM2.5 total mass and PEs. For example, PM2.5 total mass was associated with 2,717 DMPs and 10,470 DMRs whereas Pb was associated with 3,173 DMPs and 637 DMRs. The identified pathways by PM2.5 mass were mostly involved in mood disorders, neuroplasticity, immunity, and inflammation, whereas the pathways associated with motor vehicles (BC, Cu, Pb, and Zn) were related with cardiovascular disease and cancer (e.g., "PPARs signaling"). CONCLUSIONS PM2.5 and PE were associated with methylation changes at multiple probes and along multiple pathways, in ways that varied by particle components.
Collapse
Affiliation(s)
- Cuicui Wang
- Department of Environmental Health, Harvard T.H. Chan School of Public Health, Boston, MA 02115, USA.
| | - Andres Cardenas
- Division of Environmental Health Sciences, School of Public Health and Center for Computational Biology, University of California, Berkeley, Berkeley, CA 94720, USA
| | - John N Hutchinson
- Department of Biostatistics, Harvard T. H. Chan School of Public Health, Boston, MA 02115, USA
| | - Allan Just
- Department of Environmental Medicine and Public Health, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Jonathan Heiss
- Department of Environmental Medicine and Public Health, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Lifang Hou
- Department of Preventive Medicine, Feinberg School of Medicine, Northwestern University, Chicago, IL 60611, USA
| | - Yinan Zheng
- Department of Preventive Medicine, Feinberg School of Medicine, Northwestern University, Chicago, IL 60611, USA
| | - Brent A Coull
- Department of Biostatistics, Harvard T. H. Chan School of Public Health, Boston, MA 02115, USA
| | - Anna Kosheleva
- Department of Environmental Health, Harvard T.H. Chan School of Public Health, Boston, MA 02115, USA
| | - Petros Koutrakis
- Department of Environmental Health, Harvard T.H. Chan School of Public Health, Boston, MA 02115, USA
| | - Andrea A Baccarelli
- Department of Environmental Health Sciences, Columbia Mailman School of Public Health, New York, NY 10032, USA
| | - Joel D Schwartz
- Department of Environmental Health, Harvard T.H. Chan School of Public Health, Boston, MA 02115, USA; Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA 02115, USA
| |
Collapse
|