Design and quality control of large-scale two-sample Mendelian randomization studies

Philip C Haycock; Maria Carolina Borges; Kimberley Burrows; Rozenn N Lemaitre; Sean Harrison; Stephen Burgess; Xuling Chang; Jason Westra; Nikhil K Khankari; Kostas K Tsilidis; Tom Gaunt; Gibran Hemani; Jie Zheng; Therese Truong; Tracy A O'Mara; Amanda B Spurdle; Matthew H Law; Susan L Slager; Brenda M Birmann; Fatemeh Saberi Hosnijeh; Daniela Mariosa; Christopher I Amos; Rayjean J Hung; Wei Zheng; Marc J Gunter; George Davey Smith; Caroline Relton; Richard M Martin; Fatty Acids in Cancer Mendelian Randomization Collaboration

doi:10.1093/ije/dyad018

Design and quality control of large-scale two-sample Mendelian randomization studies

Int J Epidemiol. 2023 Apr 12;52(5):1498-1521. doi: 10.1093/ije/dyad018. eCollection 2023 Oct.

Authors

Philip C Haycock^{1

2}, Maria Carolina Borges^{1

2}, Kimberley Burrows^{1

2}, Rozenn N Lemaitre³, Sean Harrison^{1

2}, Stephen Burgess⁴, Xuling Chang^{5

6}, Jason Westra⁷, Nikhil K Khankari⁸, Kostas K Tsilidis^{9

10}, Tom Gaunt^{1

2}, Gibran Hemani^{1

2}, Jie Zheng^{1

2}, Therese Truong¹¹, Tracy A O'Mara^{12

13}, Amanda B Spurdle^{12

13}, Matthew H Law^{14

15}, Susan L Slager¹⁶, Brenda M Birmann¹⁷, Fatemeh Saberi Hosnijeh¹⁸, Daniela Mariosa¹⁹, Christopher I Amos²⁰, Rayjean J Hung²¹, Wei Zheng²², Marc J Gunter²³, George Davey Smith^{1

2}, Caroline Relton^{1

2}, Richard M Martin^{1

2

24}; Fatty Acids in Cancer Mendelian Randomization Collaboration

Affiliations

¹ MRC Integrative Epidemiology Unit (IEU), University of Bristol, Bristol, UK.
² Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK.
³ Department of Medicine, University of Washington, Seattle, WA, USA.
⁴ MRC Biostatistics Unit, University of Cambridge, Cambridge, UK.
⁵ Department of Paediatrics, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore.
⁶ Khoo Teck Puat-National University Children's Medical Institute, National University Health System, Singapore, Singapore.
⁷ Department of Mathematics, Statistics, and Computer Science, Dordt College, Sioux Center, IA, USA.
⁸ Division of Genetic Medicine, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, USA.
⁹ Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, UK.
¹⁰ Department of Hygiene and Epidemiology, University of Ioannina School of Medicine, Ioannina, Greece.
¹¹ Université Paris-Saclay, UVSQ, Inserm, Gustave Roussy, Team "Exposome, Heredity, Cancer and Health", CESP, Villejuif, France.
¹² Genetics and Computational Biology Division, QIMR Berghofer Medical Research Institute, Brisbane, QLD, Australia.
¹³ School of Medicine, Faculty of Health Sciences, University of Queensland, Brisbane, Australia.
¹⁴ Statistical Genetics, QIMR Berghofer Medical Research Institute, Brisbane, QLD, Australia.
¹⁵ School of Biomedical Sciences, Faculty of Health, and Institute of Health and Biomedical Innovation, Queensland University of Technology, Kelvin Grove, QLD, Australia.
¹⁶ Department of Health Sciences Research, Mayo Clinic, Rochester, MN, USA.
¹⁷ Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA.
¹⁸ Institute for Risk Assessment Sciences, Utrecht University, Utrecht, The Netherlands.
¹⁹ Genomic Epidemiology Branch, International Agency for Research on Cancer (IARC), Lyon, France.
²⁰ Dan L Duncan Comprehensive Cancer Center Baylor College of Medicine, Houston, USA.
²¹ Lunenfeld-Tanenbaum Research Institute, Sinai Health and University of Toronto, Toronto, Canada.
²² Division of Epidemiology, Department of Medicine, Vanderbilt Epidemiology Center, Vanderbilt University Medical Center, Nashville, TN, USA.
²³ Section of Nutrition and Metabolism, International Agency for Research on Cancer (IARC), Lyon, France.
²⁴ NIHR Biomedical Research Centre at University Hospitals Bristol and Weston NHS Foundation Trust and the University of Bristol, Bristol, UK.

Abstract

Background: Mendelian randomization (MR) studies are susceptible to metadata errors (e.g. incorrect specification of the effect allele column) and other analytical issues that can introduce substantial bias into analyses. We developed a quality control (QC) pipeline for the Fatty Acids in Cancer Mendelian Randomization Collaboration (FAMRC) that can be used to identify and correct for such errors.

Methods: We collated summary association statistics from fatty acid and cancer genome-wide association studies (GWAS) and subjected the collated data to a comprehensive QC pipeline. We identified metadata errors through comparison of study-specific statistics to external reference data sets (the National Human Genome Research Institute-European Bioinformatics Institute GWAS catalogue and 1000 genome super populations) and other analytical issues through comparison of reported to expected genetic effect sizes. Comparisons were based on three sets of genetic variants: (i) GWAS hits for fatty acids, (ii) GWAS hits for cancer and (iii) a 1000 genomes reference set.

Results: We collated summary data from 6 fatty acid and 54 cancer GWAS. Metadata errors and analytical issues with the potential to introduce substantial bias were identified in seven studies (11.6%). After resolving metadata errors and analytical issues, we created a data set of 219 842 genetic associations with 90 cancer types, generated in analyses of 566 665 cancer cases and 1 622 374 controls.

Conclusions: In this large MR collaboration, 11.6% of included studies were affected by a substantial metadata error or analytical issue. By increasing the integrity of collated summary data prior to their analysis, our protocol can be used to increase the reliability of downstream MR analyses. Our pipeline is available to other researchers via the CheckSumStats package (https://github.com/MRCIEU/CheckSumStats).

Keywords: Mendelian randomization; genome-wide association study; metadata error; summary data.

MeSH terms

Fatty Acids
Genome-Wide Association Study*
Humans
Mendelian Randomization Analysis
Neoplasms* / epidemiology
Neoplasms* / genetics
Quality Control
Reproducibility of Results

Substances

Fatty Acids

Abstract

MeSH terms

Substances

Grants and funding