Dan L Nicolae

University of Chicago, Chicago, Illinois, United States

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Publications (115)1121.54 Total impact

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    ABSTRACT: Genome-wide association studies (GWAS) have identified thousands of variants robustly associated with complex traits. However, the biological mechanisms underlying these associations are, in general, not well understood. We propose a gene-based association method called PrediXcan that directly tests the molecular mechanisms through which genetic variation affects phenotype. The approach estimates the component of gene expression determined by an individual's genetic profile and correlates 'imputed' gene expression with the phenotype under investigation to identify genes involved in the etiology of the phenotype. Genetically regulated gene expression is estimated using whole-genome tissue-dependent prediction models trained with reference transcriptome data sets. PrediXcan enjoys the benefits of gene-based approaches such as reduced multiple-testing burden and a principled approach to the design of follow-up experiments. Our results demonstrate that PrediXcan can detect known and new genes associated with disease traits and provide insights into the mechanism of these associations.
    Nature Genetics 08/2015; DOI:10.1038/ng.3367 · 29.65 Impact Factor
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    ABSTRACT: Understanding the functional consequences of genetic variation, and how it affects complex human disease and quantitative traits, remains a critical challenge for biomedicine. We present an analysis of RNA sequencing data from 1641 samples across 43 tissues from 175 individuals, generated as part of the pilot phase of the Genotype-Tissue Expression (GTEx) project. We describe the landscape of gene expression across tissues, catalog thousands of tissue-specific and shared regulatory expression quantitative trait loci (eQTL) variants, describe complex network relationships, and identify signals from genome-wide association studies explained by eQTLs. These findings provide a systematic understanding of the cellular and biological consequences of human genetic variation and of the heterogeneity of such effects among a diverse set of human tissues.
    Science 05/2015; 348(6235):648-660. · 31.48 Impact Factor
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    ABSTRACT: Atopic dermatitis (AD) is a heterogeneous chronic inflammatory skin disease. Most AD during infancy resolves during childhood, but moderate-to-severe AD with allergic sensitization is more likely to persist into adulthood and more often occurs with other allergic diseases. We sought to find susceptibility loci by performing the first genome-wide association study (GWAS) of AD in Korean children with recalcitrant AD, which was defined as moderate-to-severe AD with allergic sensitization. Our study included 246 children with recalcitrant AD and 551 adult control subjects with a negative history of both allergic disease and allergic sensitization. DNA from these subjects was genotyped; sets of common single nucleotide polymorphisms (SNPs) were imputed and used in the GWAS after quality control checks. SNPs at a region on 13q21.31 were associated with recalcitrant AD at a genome-wide threshold of significance (P < 2.0 × 10(-8)). These associated SNPs are more than 1 Mb from the closest gene, protocadherin (PCDH)9. SNPs at 4 additional loci had P values of less than 1 × 10(-6), including SNPs at or near the neuroblastoma amplified sequence (NBAS; 2p24.3), thymus-expressed molecule involved in selection (THEMIS; 6q22.33), GATA3 (10p14), and S-phase cyclin A-associated protein in the ER (SCAPER; 15q24.3) genes. Further analysis of total serum IgE levels suggested 13q21.31 might be primarily an IgE locus, and analyses of published data demonstrated that SNPs at the 15q24.3 region are expression quantitative trait loci for 2 nearby genes, ISL2 and proline-serine-threonine phosphatase interacting protein 1 (PSTPIP1), in immune cells. Our GWAS of recalcitrant AD identified new susceptibility regions containing genes involved in epithelial cell function and immune dysregulation, 2 key features of AD, and potentially extend our understanding of their role in pathogenesis. Copyright © 2015 American Academy of Allergy, Asthma & Immunology. Published by Elsevier Inc. All rights reserved.
    The Journal of allergy and clinical immunology 04/2015; DOI:10.1016/j.jaci.2015.03.030 · 11.25 Impact Factor
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    ABSTRACT: Rationale Stress is associated with asthma morbidity in Puerto Ricans (PRs), who have reduced bronchodilator response (BDR). Objectives To examine whether stress and/or a gene regulating anxiety (ADCYAP1R1) is associated with BDR in PR/non-PR children with asthma. Methods Cross-sectional study of stress and BDR (percent change in FEV1 after BD) in 234 PRs ages 9-14 years with asthma. We assessed child stress using the Checklist of Children's Distress Symptoms (CCDS), and maternal stress using the perceived stress scale (PSS). Replication analyses were conducted in two cohorts. Polymorphisms in ADCYAP1R1 were genotyped in our study and six replication studies. Multivariable models of stress and BDR were adjusted for age, sex, income, environmental tobacco smoke and use of inhaled corticosteroids. Measurements and Main Results High child stress was associated with reduced BDR in three cohorts. PR children who were highly stressed (upper quartile, CCDS) and whose mothers had high stress (upper quartile, PSS) had a BDR that was 10.2% (95% CI= 6.1% to 14.2%) lower than children who had neither high stress nor a highly stressed mother. A polymorphism in ADCYAP1R1 (rs34548976) was associated with reduced BDR. This SNP is associated with reduced expression of the gene for the β2-adrenergic receptor (ADRB2) in CD4+ lymphocytes of subjects with asthma, and affects brain connectivity of the amygdala and the insula (a biomarker of anxiety). Conclusions High child stress and an ADCYAP1R1 SNP are associated with reduced BDR in children with asthma. This is likely due to down-regulation of ADRB2 in highly stressed children.
    American Journal of Respiratory and Critical Care Medicine 04/2015; 192(1). DOI:10.1164/rccm.201501-0037OC · 11.99 Impact Factor
  • Matthew Reimherr · Dan Nicolae
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    ABSTRACT: Quantifying heritability is the first step in understanding the contribution of genetic variation to the risk architecture of complex human diseases and traits. Heritability can be estimated for univariate phenotypes from non-family data using linear mixed effects models. There is, however, no fully developed methodology for defining or estimating heritability from longitudinal studies. By examining longitudinal studies, researchers have the opportunity to better understand the genetic influence on the temporal development of diseases, which can be vital for populations with rapidly changing phenotypes such as children or the elderly. To define and estimate heritability for longitudinally measured phenotypes, we present a framework based on functional data analysis, FDA. While our procedures have important genetic consequences, they also represent a substantial development for FDA. In particular, we present a very general methodology for constructing optimal, unbiased estimates of variance components in functional linear models. Such a problem is challenging as likelihoods and densities do not readily generalize to infinite dimensional settings. Our procedure can be viewed as a functional generalization of the minimum norm quadratic unbiased estimation procedure, MINQUE, presented by C. R. Rao, and is equivalent to residual maximum likelihood, REML, in univariate settings. We apply our methodology to the Childhood Asthma Management Program, CAMP, a four year longitudinal study examining the long term effects of daily asthma medications on children.
    Journal of the American Statistical Association 04/2015; DOI:10.1080/01621459.2015.1016224 · 2.11 Impact Factor
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    ABSTRACT: The airway transcriptome includes genes that contribute to the pathophysiologic heterogeneity seen in individuals with asthma. We analyzed sputum gene expression for transcriptomic endotypes of asthma (TEA); gene signatures that discriminate phenotypes of disease. Gene expression in sputum and blood of asthma patients was measured using Affymetrix gene expression microarrays. Unsupervised clustering analysis based on pathways from the Kyoto Encyclopedia of Genes and Genomes was used to identify TEA clusters. Logistic regression analysis of matched blood samples defined an expression profile in the circulation to determine the TEA cluster assignment in a cohort of children with asthma for validation. Three TEA clusters were identified. TEA cluster 1 had the most subjects with a history of intubation (P = 0.05), a lower pre-bronchodilator FEV1 (P = 0.006), a higher bronchodilator response (P = 0.03), and higher exhaled nitric oxide levels (P = 0.04), compared to the other TEA clusters. TEA cluster 2, the smallest cluster had the most subjects that were hospitalized for asthma (P = 0.04). TEA cluster 3, the largest cluster, had normal lung function, low exhaled nitric oxide levels, and lower inhaled steroid requirements. Evaluation of TEA clusters in children confirmed that TEA clusters 1 and 2 are associated with a history of intubation (P = 5.58 x 10-06) and hospitalization (P = 0.01), respectively. There are common patterns of gene expression in the sputum and blood of children and adults that are associated with near fatal, severe and milder asthma.
    American Journal of Respiratory and Critical Care Medicine 03/2015; 191(10). DOI:10.1164/rccm.201408-1440OC · 11.99 Impact Factor
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    ABSTRACT: Founder populations and large pedigrees offer many well-known advantages for genetic mapping studies, including cost-efficient study designs. Here, we describe PRIMAL (PedigRee IMputation ALgorithm), a fast and accurate pedigree-based phasing and imputation algorithm for founder populations. PRIMAL incorporates both existing and original ideas, such as a novel indexing strategy of Identity-By-Descent (IBD) segments based on clique graphs. We were able to impute the genomes of 1,317 South Dakota Hutterites, who had genome-wide genotypes for ~300,000 common single nucleotide variants (SNVs), from 98 whole genome sequences. Using a combination of pedigree-based and LD-based imputation, we were able to assign 87% of genotypes with >99% accuracy over the full range of allele frequencies. Using the IBD cliques we were also able to infer the parental origin of 83% of alleles, and genotypes of deceased recent ancestors for whom no genotype information was available. This imputed data set will enable us to better study the relative contribution of rare and common variants on human phenotypes, as well as parental origin effect of disease risk alleles in >1,000 individuals at minimal cost.
    PLoS Computational Biology 03/2015; 11(3):e1004139. DOI:10.1371/journal.pcbi.1004139 · 4.83 Impact Factor
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    ABSTRACT: Common variants at many loci have been robustly associated with asthma but explain little of the overall genetic risk. Here we investigate the role of rare (<1%) and low-frequency (1-5%) variants using the Illumina HumanExome BeadChip array in 4,794 asthma cases, 4,707 non-asthmatic controls and 590 case-parent trios representing European Americans, African Americans/African Caribbeans and Latinos. Our study reveals one low-frequency missense mutation in the GRASP gene that is associated with asthma in the Latino sample (P=4.31 × 10(-6); OR=1.25; MAF=1.21%) and two genes harbouring functional variants that are associated with asthma in a gene-based analysis: GSDMB at the 17q12-21 asthma locus in the Latino and combined samples (P=7.81 × 10(-8) and 4.09 × 10(-8), respectively) and MTHFR in the African ancestry sample (P=1.72 × 10(-6)). Our results suggest that associations with rare and low-frequency variants are ethnic specific and not likely to explain a significant proportion of the 'missing heritability' of asthma.
    Nature Communications 01/2015; 6. DOI:10.1038/ncomms6965 · 10.74 Impact Factor
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    ABSTRACT: Background IgE is a key mediator of allergic inflammation, and its levels are frequently increased in patients with allergic disorders. Objective We sought to identify genetic variants associated with IgE levels in Latinos. Methods We performed a genome-wide association study and admixture mapping of total IgE levels in 3334 Latinos from the Genes-environments & Admixture in Latino Americans (GALA II) study. Replication was evaluated in 454 Latinos, 1564 European Americans, and 3187 African Americans from independent studies. Results We confirmed associations of 6 genes identified by means of previous genome-wide association studies and identified a novel genome-wide significant association of a polymorphism in the zinc finger protein 365 gene (ZNF365) with total IgE levels (rs200076616, P = 2.3 × 10−8). We next identified 4 admixture mapping peaks (6p21.32-p22.1, 13p22-31, 14q23.2, and 22q13.1) at which local African, European, and/or Native American ancestry was significantly associated with IgE levels. The most significant peak was 6p21.32-p22.1, where Native American ancestry was associated with lower IgE levels (P = 4.95 × 10−8). All but 22q13.1 were replicated in an independent sample of Latinos, and 2 of the peaks were replicated in African Americans (6p21.32-p22.1 and 14q23.2). Fine mapping of 6p21.32-p22.1 identified 6 genome-wide significant single nucleotide polymorphisms in Latinos, 2 of which replicated in European Americans. Another single nucleotide polymorphism was peak-wide significant within 14q23.2 in African Americans (rs1741099, P = 3.7 × 10−6) and replicated in non–African American samples (P = .011). Conclusion We confirmed genetic associations at 6 genes and identified novel associations within ZNF365, HLA-DQA1, and 14q23.2. Our results highlight the importance of studying diverse multiethnic populations to uncover novel loci associated with total IgE levels.
    The Journal of allergy and clinical immunology 12/2014; DOI:10.1016/j.jaci.2014.10.033 · 11.25 Impact Factor
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    ABSTRACT: Allergic rhinitis is a common disease whose genetic basis is incompletely explained. We report an integrated genomic analysis of allergic rhinitis. We performed genome wide association studies (GWAS) of allergic rhinitis in 5633 ethnically diverse North American subjects. Next, we profiled gene expression in disease-relevant tissue (peripheral blood CD4+ lymphocytes) collected from subjects who had been genotyped. We then integrated the GWAS and gene expression data using expression single nucleotide (eSNP), coexpression network, and pathway approaches to identify the biologic relevance of our GWAS. GWAS revealed ethnicity-specific findings, with 4 genome-wide significant loci among Latinos and 1 genome-wide significant locus in the GWAS meta-analysis across ethnic groups. To identify biologic context for these results, we constructed a coexpression network to define modules of genes with similar patterns of CD4+ gene expression (coexpression modules) that could serve as constructs of broader gene expression. 6 of the 22 GWAS loci with P-value ≤ 1x10−6 tagged one particular coexpression module (4.0-fold enrichment, P-value 0.0029), and this module also had the greatest enrichment (3.4-fold enrichment, P-value 2.6 × 10−24) for allergic rhinitis-associated eSNPs (genetic variants associated with both gene expression and allergic rhinitis). The integrated GWAS, coexpression network, and eSNP results therefore supported this coexpression module as an allergic rhinitis module. Pathway analysis revealed that the module was enriched for mitochondrial pathways (8.6-fold enrichment, P-value 4.5 × 10−72). Our results highlight mitochondrial pathways as a target for further investigation of allergic rhinitis mechanism and treatment. Our integrated approach can be applied to provide biologic context for GWAS of other diseases.
    BMC Medical Genomics 08/2014; 7(1):48. DOI:10.1186/1755-8794-7-48 · 3.91 Impact Factor
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    Matthew Reimherr · Xiao-Li Meng · Dan L. Nicolae
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    ABSTRACT: Dramatically expanded routine adoption of the Bayesian approach has substantially increased the need to assess both the confirmatory and contradictory information in our prior distribution with regard to the information provided by our likelihood function. We propose a diagnostic approach that starts with the familiar posterior matching method. For a given likelihood model, we identify the difference in information needed to form two likelihood functions that, when combined respectively with a given prior and a baseline prior, will lead to the same posterior uncertainty. In cases with independent, identically distributed samples, sample size is the natural measure of information, and this difference can be viewed as the prior data size $M(k)$, with regard to a likelihood function based on $k$ observations. When there is no detectable prior-likelihood conflict relative to the baseline, $M(k)$ is roughly constant over $k$, a constant that captures the confirmatory information. Otherwise $M(k)$ tends to decrease with $k$ because the contradictory prior detracts information from the likelihood function. In the case of extreme contradiction, $M(k)/k$ will approach its lower bound $-1$, representing a complete cancelation of prior and likelihood information due to conflict. We also report an intriguing super-informative phenomenon where the prior effectively gains an extra $(1+r)^{-1}$ percent of prior data size relative to its nominal size when the prior mean coincides with the truth, where $r$ is the percentage of the nominal prior data size relative to the total data size underlying the posterior. We demonstrate our method via several examples, including an application exploring the effect of immunoglobulin levels on lupus nephritis. We also provide a theoretical foundation of our method for virtually all likelihood-prior pairs that possess asymptotic conjugacy.
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    Christopher Ryan King · Dan L Nicolae
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    ABSTRACT: The success of genome-wide association studies (GWAS) in uncovering genetic risk factors for complex traits has generated great promise for the complete data generated by sequencing. The bumpy transition from GWAS to whole-exome or whole-genome association studies (WGAS) based on sequencing investigations has highlighted important differences in analysis and interpretation. We show how the loss in power due to the allele frequency spectrum targeted by sequencing is difficult to compensate for with realistic effect sizes and point to study designs that may help. We discuss several issues in interpreting the results, including a special case of the winner's curse. Extrapolation and prediction using rare SNPs is complex, because of the selective ascertainment of SNPs in case-control studies and the low amount of information at each SNP, and naive procedures are biased under the alternative. We also discuss the challenges in tuning gene-based tests and accounting for multiple testing when genes have very different sets of SNPs. The examples we emphasize in this paper highlight the difficult road we must travel for a two-letter switch.
    Genes 06/2014; 5(2):460-476. DOI:10.3390/genes5020460
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    ABSTRACT: Asthma is a complex disease with sex-specific differences in prevalence. Candidate gene studies have suggested that genotype-by-sex interaction effects on asthma risk exist, but this has not yet been explored at a genome-wide level. We aimed to identify sex-specific asthma risk alleles by performing a genome-wide scan for genotype-by-sex interactions in the ethnically diverse participants in the EVE Asthma Genetics Consortium. We performed male- and female-specific genome-wide association studies in 2653 male asthma cases, 2566 female asthma cases and 3830 non-asthma controls from European American, African American, African Caribbean and Latino populations. Association tests were conducted in each study sample, and the results were combined in ancestry-specific and cross-ancestry meta-analyses. Six sex-specific asthma risk loci had P-values < 1 × 10−6, of which two were male specific and four were female specific; all were ancestry specific. The most significant sex-specific association in European Americans was at the interferon regulatory factor 1 (IRF1) locus on 5q31.1. We also identify a Latino female-specific association in RAP1GAP2. Both of these loci included single-nucleotide polymorphisms that are known expression quantitative trait loci and have been associated with asthma in independent studies. The IRF1 locus is a strong candidate region for male-specific asthma susceptibility due to the association and validation we demonstrate here, the known role of IRF1 in asthma-relevant immune pathways and prior reports of sex-specific differences in interferon responses.
    Human Molecular Genetics 05/2014; 23(19). DOI:10.1093/hmg/ddu222 · 6.68 Impact Factor
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    Matthew Reimherr · Dan Nicolae
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    ABSTRACT: We present a new method based on Functional Data Analysis (FDA) for detecting associations between one or more scalar covariates and a longitudinal response, while correcting for other variables. Our methods exploit the temporal structure of longitudinal data in ways that are otherwise difficult with a multivariate approach. Our procedure, from an FDA perspective, is a departure from more established methods in two key aspects. First, the raw longitudinal phenotypes are assembled into functional trajectories prior to analysis. Second, we explore an association test that is not directly based on principal components. We instead focus on quantifying the reduction in $L^2$ variability as a means of detecting associations. Our procedure is motivated by longitudinal genome wide association studies and, in particular, the childhood asthma management program (CAMP) which explores the long term effects of daily asthma treatments. We conduct a simulation study to better understand the advantages (and/or disadvantages) of an FDA approach compared to a traditional multivariate one. We then apply our methodology to data coming from CAMP. We find a potentially new association with a SNP negatively affecting lung function. Furthermore, this SNP seems to have an interaction effect with one of the treatments.
    The Annals of Applied Statistics 04/2014; 8(1). DOI:10.1214/13-AOAS692 · 1.69 Impact Factor
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    ABSTRACT: Loss-of-function mutations protective against human disease provide in vivo validation of therapeutic targets, but none have yet been described for type 2 diabetes (T2D). Through sequencing or genotyping of ~150,000 individuals across 5 ancestry groups, we identified 12 rare protein-truncating variants in SLC30A8, which encodes an islet zinc transporter (ZnT8) and harbors a common variant (p.Trp325Arg) associated with T2D risk and glucose and proinsulin levels. Collectively, carriers of protein-truncating variants had 65% reduced T2D risk (P = 1.7 × 10−6), and non-diabetic Icelandic carriers of a frameshift variant (p.Lys34Serfs*50) demonstrated reduced glucose levels (−0.17 s.d., P = 4.6 × 10−4). The two most common protein-truncating variants (p.Arg138* and p.Lys34Serfs*50) individually associate with T2D protection and encode unstable ZnT8 proteins. Previous functional study of SLC30A8 suggested that reduced zinc transport increases T2D risk, and phenotypic heterogeneity was observed in mouse Slc30a8 knockouts. In contrast, loss-of-function mutations in humans provide strong evidence that SLC30A8 haploinsufficiency protects against T2D, suggesting ZnT8 inhibition as a therapeutic strategy in T2D prevention.
    Nature Genetics 03/2014; · 29.65 Impact Factor
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    ABSTRACT: Early-onset breast cancer (EOBC) causes substantial loss of life and productivity, creating a major burden among women worldwide. We analyzed 1,265,548 Hapmap3 SNPs among a discovery set of 3,523 EOBC incident case and 2,702 population control women aged <=51 years. The SNPs with smallest P-values were examined in a replication set of 3,470 EOBC case and 5,475 control women. We also tested EOBC association with 19,684 genes by annotating each gene with putative functional SNPs, and then combining their P-values to obtain a gene-based P-value. We examined the gene with smallest P-value for replication in 1,145 breast cancer case and 1,142 control women. The combined discovery and replication sets identified 72 new SNPs associated with EOBC (P<4x10-8) located in six genomic regions previously reported to contain SNPs associated largely with later-onset breast cancer (LOBC). SNP rs2229882 and 10 other SNPs on chromosome 5q11.2 remained associated (P<6x10-4) after adjustment for the strongest published SNPs in the region. Thirty-two of the 82 currently known LOBC SNPs were associated with EOBC (P<0.05). Low power is likely responsible for the remaining 50 unassociated known LOBC SNPs. The gene-based analysis identified an association between breast cancer and the phosphofructokinase-muscle (PFKM) gene on chromosome 12q13.11 that met the genomewide gene-based threshold of 2.5x10-In conclusion, EOBC and LOBC appear to have similar genetic etiologies; the 5q11.2 region may contain multiple distinct breast cancer loci; and the PFKM gene region is worthy of further investigation. These findings should enhance our understanding of the etiology of breast cancer.
    Cancer Epidemiology Biomarkers & Prevention 02/2014; 23(4). DOI:10.1158/1055-9965.EPI-13-0340 · 4.32 Impact Factor
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    C Ryan King · Paul J Rathouz · Dan L Nicolae
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    ABSTRACT: Investigators interrogating the genetic basis of complex traits using case-control sequencing studies will want to draw conclusions about collections of variants as well as specific variants. We discuss two easy ways to err on estimates of average effects of SNPs and contrasts between groups of SNPs, such as rare versus common. Both of these errors look like interesting findings, so readers should understand and anticipate them. First, we show that when analyzing only SNPs polymorphic in the sample, on average rare variants increase risk even if they are just as likely to decrease risk. Studies of moderate size are unlikely to observe all the variation in a gene which exists in the source population, and the ascertained SNPs are not representative of the larger set. A rare SNP is more likely to be discovered if it increases risk and is enriched in cases; enrichment of protective alleles among controls is negligible. Common alleles are ascertained regardless of their effect on phenotype, creating a rare variant specific bias. Nuisance parameters change the size of the bias, meaning that studies of the same trait could reach inconsistent conclusions about the impact of rare SNPs. The bias applies more broadly than just rare versus common. Our second note is technical, and reflects well-known results. Ubiquitous methods which directly compare quantities like allele-counts or rare-SNP-burdens to phenotype do not describe the distribution of SNP odds ratios, though it is tempting to interpret them in this way. Our leading example is that the same data can lead to two seemingly different conclusions: 1) possessing more minor alleles is associated with higher risk of disease 2) minor alleles are as likely to decrease risk as increase it. Pure association test calibration is unaffected by either error.

Publication Stats

12k Citations
1,121.54 Total Impact Points

Institutions

  • 1998–2015
    • University of Chicago
      • • Department of Statistics
      • • Department of Medicine
      • • Department of Human Genetics
      Chicago, Illinois, United States
    • Johns Hopkins University
      • Department of Pediatrics
      Baltimore, Maryland, United States
  • 2006–2013
    • University of Illinois at Chicago
      Chicago, Illinois, United States
  • 2012
    • Memorial Sloan-Kettering Cancer Center
      New York, New York, United States
  • 2000
    • The University of Chicago Medical Center
      • Department of Medicine
      Chicago, Illinois, United States
  • 1999
    • deCODE genetics, Inc.
      Reikiavik, Capital Region, Iceland