Synthetic associations created by rare variants do not explain most GWAS results.
- Authors
- Wray, Naomi R; Purcell, Shaun M; Visscher, Peter M
- Year
- 2011
- Journal
- PLoS biology
- PMID
- 21267061
- DOI
- 10.1371/journal.pbio.1000579
- PMCID
- PMC3022526
LD between causal and genotyped SNPs and synthetic association.SNPs 1β10 are independent SNPs in a short chromosomal region, with population frequencies indicated by the values in the box. Rare mutations tend to be younger than common mutations. A mutation event in the region creates causal variant C1. C1 has a higher probability of arising on the major allele (dark) of any SNP than the minor allele (light). However, in the absence of recombination, the highest associated SNP will be the one where C1 is coupled (see Box 2) with the SNP allele of lowest frequency, SNP 3; recombination between the SNP and the causal variant could break down this synthetic association. An independent mutation event in the region gives rise to a second causal SNP, C2. Again C2 has higher probability of arising on the major allele of each SNP. If C2 had been the only mutation in the region then SNP 10 would be the most highly associated, as the coupled allele has lowest frequency. However, when both events arise in the same region, the associations at SNPs 3 and 10 are partially masked as they carry risk variants on both their alleles. C1 and C2 arise on the same background allele for many SNPs, but SNP 8 has the allele of lowest frequency that harbours both risk alleles. In the absence of recombination, and depending on effect size, the highest association might be with SNP 8, rather than SNPs 3 or 10. Individuals are very unlikely to carry both C1 and C2. As more causal variants arise in the region, the most associated SNP will be the one with a detectable difference in the contribution to risk from the risk alleles harboured on each allele. Other representations of synthetic association could be viewed in parallel with this representation [4],[5],[16].
Frequency distributions of a) the risk allele frequency of the most associated SNPs listed in the GWAS Catalog [1] for the diseases in Table 3.b) MAF of all SNPs simulated under the coalescence model, c) MAF of SNPs used in analyses to be representative of SNPs included in GWAS. dβf) Coupled allele of most associated SNP from simulations of 1, 9, or 36 causal variants in a 100 kb region.
Minimum fold increase in genetic variance at single rare causal locus given the frequency of the risk allele at the genotyped associated locus.The minimum fold increase is calculated as 1/r 2, with r 2 calculated as the maximum r 2 given the frequency of the trait increasing allele at the genotyped SNP and the frequency of the causal allele (see Box 2).
Polygenic analyses following the International Schizophrenia Consortium [12].a) The original results for polygenic score analysis in the ISC, when stratified by quintile of risk-increasing allele frequency (Q1 being the lowest risk-increasing allele frequency, Q5 the most common; the range is between 0.02 and 0.98). b) We repeated these analyses on simulated data, generated under a βrare variant onlyβ model and using the same simulation procedure as Dickson et al., assuming that risk loci harbor 9 causal variants, GRR = 4, MAF 0.005β0.02). The pile-up of signal in the lower quintiles, which is expected under Dickson et al.'s model, is clearly not consistent with the observed ISC results. In the simulations, SNPs are generated through a coalescent process; a subset of SNPs is selected as βgenotypedβ to represent the marker density, frequency distribution and LD profile observed in the original ISC study (which has properties that are typical of most GWAS, including the under-representation of low frequency variants). The y axis is the βlog10P from the logistic regression of case-control status on profile score in an independent βtargetβ case-control sample using a score calculated as the number of alleles identified as associated (with p-value less than a threshold pT) in the discovery case-control sample association analysis, scaled within each figure as so that the maximum value observed for five significance thresholds (pT = 0.1, 0.2, 0.3, 0.4, and 0.5, plotted left to right in each quintile) is scaled to 1 and the minimum is scaled to zero.
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| Inferring causal direction between two traits using R<sup>2</sup> with application to transcriptome-wide association studies. | Liao H et al. | β | 2024 | β |
| Computational Assessment of the Expression-modulating Potential for Non-coding Variants. | Shi FY et al. | β | 2023 | β |
| From Hazard Rate to Age-at-Onset Distribution: Mind the Gap. | Chatterjee N et al. | β | 2023 | β |
| kGWASflow: a modular, flexible, and reproducible Snakemake workflow for k-mers-based GWAS. | Corut AK et al. | β | 2023 | β |
| Refining the genetic risk of breast cancer with rare haplotypes and pattern mining. | Letsou W et al. | β | 2023 | β |
| From pharmacogenetics to pharmaco-omics: Milestones and future directions. | Auwerx C et al. | β | 2022 | β |
| Common genetic variants and modifiable risk factors underpin hypertrophic cardiomyopathy susceptibility and expressivity. | Harper AR et al. | β | 2021 | β |
| Common genetic variants with fetal effects on birth weight are enriched for proximity to genes implicated in rare developmental disorders. | Beaumont RN et al. | β | 2021 | β |
| Genome-wide association study in hexaploid wheat identifies novel genomic regions associated with resistance to root lesion nematode (Pratylenchus thornei). | Kumar D et al. | β | 2021 | β |
| Identification of pleiotropy at the gene level between psychiatric disorders and related traits. | Polushina T et al. | β | 2021 | β |
| Canalization and Robustness in Human Genetics and Disease. | Gibson G et al. | β | 2020 | β |
| Common genetic variants with fetal effects on birth weight are enriched for proximity to genes implicated in rare developmental disorders | Beaumont RN et al. | β | 2020 | β |
| Cumulative Burden of Colorectal Cancer-Associated Genetic Variants Is More Strongly Associated With Early-Onset vs Late-Onset Cancer. | Archambault AN et al. | β | 2020 | β |
| Evolutionary perspectives on polygenic selection, missing heritability, and GWAS. | Uricchio LH | β | 2020 | β |
| Genetics of Circulating Resistin Level, a Biomarker for Cardiovascular Diseases, Is Informed by Mendelian Randomization and the Unique Characteristics of African Genomes. | Meeks KAC et al. | β | 2020 | β |
| Benefits and limitations of genome-wide association studies. | Tam V et al. | β | 2019 | β |
| Relevance of Multi-Omics Studies in Cardiovascular Diseases. | Leon-Mimila P et al. | β | 2019 | β |
| Common Variant Burden Contributes to the Familial Aggregation of Migraine in 1,589 Families. | Gormley P et al. | β | 2018 | β |
| Evolutionary Perspectives on Genetic and Environmental Risk Factors for Psychiatric Disorders. | Keller MC | β | 2018 | β |
| Genetic architecture: the shape of the genetic contribution to human traits and disease. | Timpson NJ et al. | β | 2018 | β |
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| A Model of Compound Heterozygous, Loss-of-Function Alleles Is Broadly Consistent with Observations from Complex-Disease GWAS Datasets. | Sanjak JS et al. | β | 2017 | β |
| CNV-association meta-analysis in 191,161 European adults reveals new loci associated with anthropometric traits. | MacΓ© A et al. | β | 2017 | β |
| Common variants of T-cells contribute differently to phenotypic variation in sarcoidosis. | Rivera NV et al. | β | 2017 | β |
| Heritability Estimation using a Regularized Regression Approach (HERRA): Applicable to continuous, dichotomous or age-at-onset outcome. | Gorfine M et al. | β | 2017 | β |
| Predicting Polygenic Obesity Using Genetic Information. | Loos RJF et al. | β | 2017 | β |
| A meta-analysis of 120 246 individuals identifies 18 new loci for fibrinogen concentration. | de Vries PS et al. | β | 2016 | β |
| Fine-mapping, novel loci identification, and SNP association transferability in a genome-wide association study of QRS duration in African Americans. | Evans DS et al. | β | 2016 | β |
| Functional Impact of An ADHD-Associated DIRAS2 Promoter Polymorphism. | GrΓΌnewald L et al. | β | 2016 | β |
| Genome-wide association mapping revealed a diverse genetic basis of seed dormancy across subpopulations in rice (Oryza sativa L.). | Magwa RA et al. | β | 2016 | β |
| GWASeq: targeted re-sequencing follow up to GWAS. | Salomon MP et al. | β | 2016 | β |
| Haplotype synthesis analysis reveals functional variants underlying known genome-wide associated susceptibility loci. | Lacour A et al. | β | 2016 | β |
| Progress from genome-wide association studies and copy number variant studies in epilepsy. | Leu C et al. | β | 2016 | β |
| Quantitative magnetic resonance imaging traits as endophenotypes for genetic mapping in epilepsy. | Alhusaini S et al. | β | 2016 | β |
| Recent progress in genetics, epigenetics and metagenomics unveils the pathophysiology of human obesity. | Pigeyre M et al. | β | 2016 | β |
| The genetic architecture of type 2 diabetes. | Fuchsberger C et al. | β | 2016 | β |
| Type 2 diabetes: genetic data sharing to advance complex disease research. | Flannick J et al. | β | 2016 | β |
| A reconsideration of the role of self-identified races in epidemiology and biomedical research. | Lorusso L et al. | β | 2015 | β |
| Association analyses identify 38 susceptibility loci for inflammatory bowel disease and highlight shared genetic risk across populations. | Liu JZ et al. | β | 2015 | β |
| Capture Hi-C identifies the chromatin interactome of colorectal cancer risk loci. | JΓ€ger R et al. | β | 2015 | β |
| Contemporary Considerations for Constructing a Genetic Risk Score: An Empirical Approach. | Goldstein BA et al. | β | 2015 | β |
| Dissecting the genetic determinants of hemostasis and thrombosis. | Desch KC | β | 2015 | β |
| Fine mapping in the MHC region accounts for 18% additional genetic risk for celiac disease. | Gutierrez-Achury J et al. | β | 2015 | β |
| Genome Wide Association Analysis Reveals New Production Trait Genes in a Male Duroc Population. | Wang K et al. | β | 2015 | β |
| Heritability in inflammatory bowel disease: from the first twin study to genome-wide association studies. | Gordon H et al. | β | 2015 | β |
| In Silico Post Genome-Wide Association Studies Analysis of C-Reactive Protein Loci Suggests an Important Role for Interferons. | Vaez A et al. | β | 2015 | β |
| The Fourth Law of Behavior Genetics. | Chabris CF et al. | β | 2015 | β |
| The genetics of neuropsychiatric diseases: looking in and beyond the exome. | Heinzen EL et al. | β | 2015 | β |
| The genetics of osteoporosis. | Clark GR et al. | β | 2015 | β |
| The Nature of Genetic Variation for Complex Traits Revealed by GWAS and Regional Heritability Mapping Analyses. | Caballero A et al. | β | 2015 | β |
| A meta-analysis of genome-wide association studies for adiponectin levels in East Asians identifies a novel locus near WDR11-FGFR2. | Wu Y et al. | β | 2014 | β |
| Applying compressed sensing to genome-wide association studies. | Vattikuti S et al. | β | 2014 | β |
| Association mapping in crop plants: opportunities and challenges. | Gupta PK et al. | β | 2014 | β |
| Association of the p53 codon 72 polymorphism with clinicopathological characteristics of colorectal cancer through mRNA analysis. | De Oliveira LP et al. | β | 2014 | β |
| Common variants associated with general and MMR vaccine-related febrile seizures. | Feenstra B et al. | β | 2014 | β |
| Conditions for the validity of SNP-based heritability estimation. | Lee JJ et al. | β | 2014 | β |
| Does genetic heterogeneity account for the divergent risk of type 2 diabetes in South Asian and white European populations? | Sohani ZN et al. | β | 2014 | β |
| Explaining additional genetic variation in complex traits. | Robinson MR et al. | β | 2014 | β |
| Gene-environment dependence creates spurious gene-environment interaction. | Dudbridge F et al. | β | 2014 | β |
| Genome-wide linkage disequilibrium in nine-spined stickleback populations. | Yang J et al. | β | 2014 | β |
| Laying a solid foundation for Manhattan--'setting the functional basis for the post-GWAS era'. | Zhang X et al. | β | 2014 | β |
| Most genetic risk for autism resides with common variation. | Gaugler T et al. | β | 2014 | β |
| Review: The genetics of Alzheimer's disease; putting flesh on the bones. | Medway C et al. | β | 2014 | β |
| Schizophrenia genetics comes of age. | Need AC et al. | β | 2014 | β |
| Shared and independent colorectal cancer risk alleles in TGFΞ²-related genes in African and European Americans. | Kupfer SS et al. | β | 2014 | β |
| The impact of population demography and selection on the genetic architecture of complex traits. | Lohmueller KE | β | 2014 | β |
| Unbiased analysis of potential targets of breast cancer susceptibility loci by Capture Hi-C. | Dryden NH et al. | β | 2014 | β |
| Whole genome prediction of bladder cancer risk with the Bayesian LASSO. | de Maturana EL et al. | β | 2014 | β |
| Behavior genetics: past, present, future. | Jaffee SR et al. | β | 2013 | β |
| Case-control association testing of common variants from sequencing of DNA pools. | McRae AF et al. | β | 2013 | β |
| Child development and molecular genetics: 14 years later. | Plomin R | β | 2013 | β |
| Common biological networks underlie genetic risk for alcoholism in African- and European-American populations. | Kos MZ et al. | β | 2013 | β |
| Genetic risk prediction: individualized variability in susceptibility to toxicants. | Nebert DW et al. | β | 2013 | β |
| Haplotype kernel association test as a powerful method to identify chromosomal regions harboring uncommon causal variants. | Lin WY et al. | β | 2013 | β |
| Have we learnt all we need to know from genetic studies - is genetics over in Alzheimer's disease? | Hampel H et al. | β | 2013 | β |
| High trans-ethnic replicability of GWAS results implies common causal variants. | Marigorta UM et al. | β | 2013 | β |
| Immune-mediated disease genetics: the shared basis of pathogenesis. | Cotsapas C et al. | β | 2013 | β |
| Low-density lipoprotein receptor mutations generate synthetic genome-wide associations. | Oosterveer DM et al. | β | 2013 | β |
| Low frequency variants, collapsed based on biological knowledge, uncover complexity of population stratification in 1000 genomes project data. | Moore CB et al. | β | 2013 | β |
| Properties and modeling of GWAS when complex disease risk is due to non-complementing, deleterious mutations in genes of large effect. | Thornton KR et al. | β | 2013 | β |
| Rare variants in hypermutable genes underlie common morphology and growth traits in wild Saccharomyces paradoxus. | Roop JI et al. | β | 2013 | β |
| Resequencing three candidate genes for major depressive disorder in a Dutch cohort. | Verbeek EC et al. | β | 2013 | β |
| Systems genetics in "-omics" era: current and future development. | Li H | β | 2013 | β |
| The advantages and limitations of trait analysis with GWAS: a review. | Korte A et al. | β | 2013 | β |
| The emerging spectrum of allelic variation in schizophrenia: current evidence and strategies for the identification and functional characterization of common and rare variants. | Mowry BJ et al. | β | 2013 | β |
| The molecular genetic architecture of self-employment. | van der Loos MJ et al. | β | 2013 | β |
| Using extended genealogy to estimate components of heritability for 23 quantitative and dichotomous traits. | Zaitlen N et al. | β | 2013 | β |
| Why it is hard to find genes associated with social science traits: theoretical and empirical considerations. | Chabris CF et al. | β | 2013 | β |
| A novel approach for the simultaneous analysis of common and rare variants in complex traits. | Yuan A et al. | β | 2012 | β |
| Association genetics of the loblolly pine (Pinus taeda, Pinaceae) metabolome. | Eckert AJ et al. | β | 2012 | β |
| Challenges and opportunities in genome-wide environmental interaction (GWEI) studies. | Aschard H et al. | β | 2012 | β |
| Current understanding of human genetics and genetic analysis of psoriasis. | Oka A et al. | β | 2012 | β |
| Estimating causal effects of genetic risk variants for breast cancer using marker data from bilateral and familial cases. | Dudbridge F et al. | β | 2012 | β |
| Estimating the proportion of variation in susceptibility to schizophrenia captured by common SNPs. | Lee SH et al. | β | 2012 | β |
| Evidence-based psychiatric genetics, AKA the false dichotomy between common and rare variant hypotheses. | Visscher PM et al. | β | 2012 | β |
| Evidence for a role of the rare p.A152T variant in MAPT in increasing the risk for FTD-spectrum and Alzheimer's diseases. | Coppola G et al. | β | 2012 | β |
| Five years of GWAS discovery. | Visscher PM et al. | β | 2012 | β |
| Genetic architectures of psychiatric disorders: the emerging picture and its implications. | Sullivan PF et al. | β | 2012 | β |
| Genetic determinants of common obesity and their value in prediction. | Loos RJ | β | 2012 | β |
| Genetic epidemiology with a capital E: where will we be in another 10 years? | Thomas DC | β | 2012 | β |
| Genetics of coronary artery disease: genome-wide association studies and beyond. | Prins BP et al. | β | 2012 | β |
| Genome-wide association study of multiplex schizophrenia pedigrees. | Levinson DF et al. | β | 2012 | β |
| Heritability in the genome-wide association era. | Zaitlen N et al. | β | 2012 | β |
| Human complex trait genetics: lifting the lid of the genomics toolbox - from pathways to prediction. | Rowe SJ et al. | β | 2012 | β |
| Identifying plausible genetic models based on association and linkage results: application to type 2 diabetes. | Guan W et al. | β | 2012 | β |
| Inferring causality and functional significance of human coding DNA variants. | Sunyaev SR | β | 2012 | β |
| Maintenance of genetic variation in human personality: testing evolutionary models by estimating heritability due to common causal variants and investigating the effect of distant inbreeding. | Verweij KJ et al. | β | 2012 | β |
| Modelling the contribution of family history and variation in single nucleotide polymorphisms to risk of schizophrenia: a Danish national birth cohort-based study. | Agerbo E et al. | β | 2012 | β |
| Personalized medicine: hope or hype? | Salari K et al. | β | 2012 | β |
| Predicting signatures of "synthetic associations" and "natural associations" from empirical patterns of human genetic variation. | Chang D et al. | β | 2012 | β |
| PSMC1 Gene in Parkinson's Disease. | GΓ³mez-Garre P et al. | β | 2012 | β |
| Rare and common variants: twenty arguments. | Gibson G | β | 2012 | β |
| Recent genomic advances in schizophrenia. | Doherty JL et al. | β | 2012 | β |
| What is complex about complex disorders? | Mitchell KJ | β | 2012 | β |
| Common disease: are causative alleles common or rare? | Shields R | β | 2011 | β |
| Current status of genome-wide association studies in cancer. | Chung CC et al. | β | 2011 | β |
| Dissecting the genetic architecture of human personality. | MunafΓ² MR et al. | β | 2011 | β |
| Multiple common susceptibility variants near BMP pathway loci GREM1, BMP4, and BMP2 explain part of the missing heritability of colorectal cancer. | Tomlinson IP et al. | β | 2011 | β |
| Pharmacogenomics and epilepsy: the road ahead. | Cavalleri GL et al. | β | 2011 | β |
| Schizophrenia genetics: where next? | Kim Y et al. | β | 2011 | β |