Dan L Nicolae

University of Illinois at Chicago, Chicago, Illinois, United States

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Publications (124)1186.27 Total impact

  • Qianying Liu · Lin S Chen · Dan L Nicolae · Brandon L Pierce
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    ABSTRACT: In genome-wide gene-environment interaction (GxE) studies, a common strategy to improve power is to first conduct a filtering test and retain only the SNPs that pass the filtering in the subsequent GxE analyses. Inspired by two-stage tests and gene-based tests in GxE analysis, we consider the general problem of jointly testing a set of parameters when only a few are truly from the alternative hypothesis and when filtering information is available. We propose a unified set-based test that simultaneously considers filtering on individual parameters and testing on the set. We derive the exact distribution and approximate the power function of the proposed unified statistic in simplified settings, and use them to adaptively calculate the optimal filtering threshold for each set. In the context of gene-based GxE analysis, we show that although the empirical power function may be affected by many factors, the optimal filtering threshold corresponding to the peak of the power curve primarily depends on the size of the gene. We further propose a resampling algorithm to calculate P-values for each gene given the estimated optimal filtering threshold. The performance of the method is evaluated in simulation studies and illustrated via a genome-wide gene-gender interaction analysis using pancreatic cancer genome-wide association data.
    No preview · Article · Oct 2015 · Biometrics
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    ABSTRACT: Aging is one of the most important biological processes and is a known risk factor for many age-related diseases in human. Studying age-related transcriptomic changes in tissues across the whole body can provide valuable information for a holistic understanding of this fundamental process. In this work, we catalogue age-related gene expression changes in nine tissues from nearly two hundred individuals collected by the Genotype-Tissue Expression (GTEx) project. In general, we find the aging gene expression signatures are very tissue specific. However, enrichment for some well-known aging components such as mitochondria biology is observed in many tissues. Different levels of cross-tissue synchronization of age-related gene expression changes are observed, and some essential tissues (e.g., heart and lung) show much stronger "co-aging" than other tissues based on a principal component analysis. The aging gene signatures and complex disease genes show a complex overlapping pattern and only in some cases, we see that they are significantly overlapped in the tissues affected by the corresponding diseases. In summary, our analyses provide novel insights to the co-regulation of age-related gene expression in multiple tissues; it also presents a tissue-specific view of the link between aging and age-related diseases.
    Full-text · Article · Oct 2015 · Scientific Reports
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    ABSTRACT: Rationale: Epigenetic changes to airway cells have been proposed as important modulators of the effects of environmental exposures on airway diseases, yet no study to date has shown epigenetic responses to exposures in the airway that correlate with disease state. The Type 2 cytokine interleukin (IL)-13 is a key mediator of allergic airway diseases, such as asthma, and is upregulated in response to many asthma-promoting exposures. Objective: To directly study the epigenetic response of airway epithelial cells (AECs) to IL-13, and test whether IL-13 induced epigenetic changes differ between asthmatic and non-asthmatic individuals. Methods: Genome-wide DNA methylation and gene expression patterns were studied in 58 IL-13 treated and untreated primary AEC cultures and validated in freshly isolated cells from asthmatic and non-asthmatic subjects using the Illumina Human Methylation 450K and HumanHT-12 BeadChips. IL-13 mediated co-methylation modules were identified and correlated with clinical phenotypes using weighted gene co-expression network analysis. Measurements and main results: IL-13 altered global DNA methylation patterns in cultured AECs and were significantly enriched near genes associated with asthma. Importantly, a significant proportion of this IL-13 epigenetic signature was validated in freshly isolated AECs from asthmatic subjects and clustered into two distinct modules with module 1 correlated with asthma severity and lung function and module 2 with eosinophilia. Conclusions: These results suggest that a single exposure of IL-13 may selectively induce long lasting DNA methylation changes in asthmatic airways that alters specific AEC pathways and contribute to asthma phenotypes.
    No preview · Article · Oct 2015 · American Journal of Respiratory and Critical Care Medicine
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    ABSTRACT: Background: Viral respiratory infections can cause acute wheezing illnesses in children and exacerbations of asthma. Objective: We sought to identify variation in genes with known antiviral and pro-inflammatory functions to identify specific associations with more severe viral respiratory illnesses and the risk of virus-induced exacerbations during the peak fall season. Methods: The associations between genetic variation at 326 SNPs in 63 candidate genes and 10 phenotypes related to viral respiratory infection and asthma control were examined in 226 children enrolled in the RhinoGen study. Replication of asthma control phenotypes was performed in 2,128 children in the Copenhagen Prospective Study on Asthma in Childhood (COPSAC). Significant associations in RhinoGen were further validated using virus-induced wheezing illness and asthma phenotypes in an independent sample of 122 children enrolled in the Childhood Origins of Asthma birth cohort study (COAST). Results: A significant excess of P values smaller than 0.05 was observed in the analysis of the 10 RhinoGen phenotypes. Polymorphisms in 12 genes were significantly associated with variation in the four phenotypes showing a significant enrichment of small P values. Six of those genes (STAT4, JAK2, MX1, VDR, DDX58, and EIF2AK2) also showed significant associations with asthma exacerbations in the COPSAC study or with asthma or virus-induced wheezing phenotypes in the COAST study. Conclusions: We identified genetic factors contributing to individual differences in childhood viral respiratory illnesses and virus-induced exacerbations of asthma. Defining mechanisms of these associations may provide insight into the pathogenesis of viral respiratory infections and virus-induced exacerbations of asthma. This article is protected by copyright. All rights reserved.
    Full-text · Article · Sep 2015 · Clinical & Experimental Allergy
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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.
    Full-text · Article · Aug 2015 · Nature Genetics
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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.
    Full-text · Article · May 2015 · Science
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    ABSTRACT: Background: 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. Objective: 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. Methods: 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. Results: 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. Conclusion: 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.
    No preview · Article · Apr 2015 · The Journal of allergy and clinical immunology
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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.
    Full-text · Article · Apr 2015 · American Journal of Respiratory and Critical Care Medicine
  • 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.
    No preview · Article · Apr 2015 · Journal of the American Statistical Association
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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.
    No preview · Article · Mar 2015 · American Journal of Respiratory and Critical Care Medicine
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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.
    Full-text · Article · Mar 2015 · PLoS Computational Biology
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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.
    Full-text · Article · Jan 2015 · Nature Communications
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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.
    Full-text · Article · Dec 2014 · The Journal of allergy and clinical immunology
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    Full-text · Dataset · Aug 2014
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    Full-text · Dataset · Aug 2014
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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.
    Full-text · Article · Aug 2014 · BMC Medical Genomics
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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.
    Full-text · Article · Jun 2014
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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.
    Preview · Article · Jun 2014 · Genes
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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.
    Full-text · Article · May 2014 · Human Molecular Genetics
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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.
    Full-text · Article · Apr 2014 · The Annals of Applied Statistics

Publication Stats

13k Citations
1,186.27 Total Impact Points

Institutions

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