Michael C. Wu

Rare-variant association testing for sequencing data with the sequence kernel association test.

Sequencing studies are increasingly being conducted to identify rare variants associated with complex traits. The limited power of classical single-marker association analysis for rare variants poses a central challenge in such studies. We propose the sequence kernel association test (SKAT), a supervised, flexible, computationally efficient regression method to test for association between genetic variants (common and rare) in a region and a continuous or dichotomous trait while easily adjusting for covariates. As a score-based variance-component test, SKAT can quickly calculate p values analytically by fitting the null model containing only the covariates, and so can easily be applied to genome-wide data. Using SKAT to analyze a genome-wide sequencing study of 1000 individuals, by segmenting the whole genome into 30 kb regions, requires only 7 hr on a laptop. Through analysis of simulated data across a wide range of practical scenarios and triglyceride data from the Dallas Heart Study, we show that SKAT can substantially outperform several alternative rare-variant association tests. We also provide analytic power and sample-size calculations to help design candidate-gene, whole-exome, and whole-genome sequence association studies.

LKB1 modulates lung cancer differentiation and metastasis.

Germline mutation in serine/threonine kinase 11 (STK11, also called LKB1) results in Peutz–Jeghers syndrome, characterized by intestinal hamartomas and increased incidence of epithelial cancers. Although uncommon in most sporadic cancers, inactivating somatic mutations of LKB1 have been reported in primary human lung adenocarcinomas and derivative cell lines. Here we used a somatically activatable mutant Kras-driven model of mouse lung cancer to compare the role of Lkb1 to other tumour suppressors in lung cancer. Although Kras mutation cooperated with loss of p53 or Ink4a/Arf (also known as Cdkn2a) in this system, the strongest cooperation was seen with homozygous inactivation of Lkb1. Lkb1-deficient tumours demonstrated shorter latency, an expanded histological spectrum (adeno-, squamous and large-cell carcinoma) and more frequent metastasis compared to tumours lacking p53 or Ink4a/Arf. Pulmonary tumorigenesis was also accelerated by hemizygous inactivation of Lkb1. Consistent with these findings, inactivation of LKB1 was found in 34% and 19% of 144 analysed human lung adenocarcinomas and squamous cell carcinomas, respectively. Expression profiling in human lung cancer cell lines and mouse lung tumours identified a variety of metastasis-promoting genes, such as NEDD9, VEGFC and CD24, as targets of LKB1 repression in lung cancer. These studies establish LKB1 as a critical barrier to pulmonary tumorigenesis, controlling initiation, differentiation and metastasis.

450K epigenome-wide scan identifies differential DNA methylation in newborns related to maternal smoking during pregnancy.

Background: Epigenetic modifications, such as DNA methylation, due to in utero exposures may play a critical role in early programming for childhood and adult illness. Maternal smoking is a major risk factor for multiple adverse health outcomes in children, but the underlying mechanisms are unclear. Objective: We investigated epigenome-wide methylation in cord blood of newborns in relation to maternal smoking during pregnancy. Methods: We examined maternal plasma cotinine (an objective biomarker of smoking) measured during pregnancy in relation to DNA methylation at 473,844 CpG sites (CpGs) in 1,062 newborn cord blood samples from the Norwegian Mother and Child Cohort Study (MoBa) using the Infinium HumanMethylation450 BeadChip (450K). Results: We found differential DNA methylation at epigenome-wide statistical significance (p-value < 1.06 × 10–7) for 26 CpGs mapped to 10 genes. We replicated findings for CpGs in AHRR, CYP1A1, and GFI1 at strict Bonferroni-corrected statistical significance in a U.S. birth cohort. AHRR and CYP1A1 play a key role in the aryl hydrocarbon receptor signaling pathway, which mediates the detoxification of the components of tobacco smoke. GFI1 is involved in diverse developmental processes but has not previously been implicated in responses to tobacco smoke. Conclusions: We identified a set of genes with methylation changes present at birth in children whose mothers smoked during pregnancy. This is the first study of differential methylation across the genome in relation to maternal smoking during pregnancy using the 450K platform. Our findings implicate epigenetic mechanisms in the pathogenesis of the adverse health outcomes associated with this important in utero exposure.

Powerful SNP-Set Analysis for Case-Control Genome-wide Association Studies

GWAS have emerged as popular tools for identifying genetic variants that are associated with disease risk. Standard analysis of a case-control GWAS involves assessing the association between each individual genotyped SNP and disease risk. However, this approach suffers from limited reproducibility and difficulties in detecting multi-SNP and epistatic effects. As an alternative analytical strategy, we propose grouping SNPs together into SNP sets on the basis of proximity to genomic features such as genes or haplotype blocks, then testing the joint effect of each SNP set. Testing of each SNP set proceeds via the logistic kernel-machine-based test, which is based on a statistical framework that allows for flexible modeling of epistatic and nonlinear SNP effects. This flexibility and the ability to naturally adjust for covariate effects are important features of our test that make it appealing in comparison to individual SNP tests and existing multimarker tests. Using simulated data based on the International HapMap Project, we show that SNP-set testing can have improved power over standard individual-SNP analysis under a wide range of settings. In particular, we find that our approach has higher power than individual-SNP analysis when the median correlation between the disease-susceptibility variant and the genotyped SNPs is moderate to high. When the correlation is low, both individual-SNP analysis and the SNP-set analysis tend to have low power. We apply SNP-set analysis to analyze the Cancer Genetic Markers of Susceptibility (CGEMS) breast cancer GWAS discovery-phase data.

Optimal tests for rare variant effects in sequencing association studies

With development of massively parallel sequencing technologies, there is a substantial need for developing powerful rare variant association tests. Common approaches include burden and non-burden tests. Burden tests assume all rare variants in the target region have effects on the phenotype in the same direction and of similar magnitude. The recently proposed sequence kernel association test (SKAT) (Wu, M. C., and others, 2011. Rare-variant association testing for sequencing data with the SKAT. The American Journal of Human Genetics 89, 82-93], an extension of the C-alpha test (Neale, B. M., and others, 2011. Testing for an unusual distribution of rare variants. PLoS Genetics 7, 161-165], provides a robust test that is particularly powerful in the presence of protective and deleterious variants and null variants, but is less powerful than burden tests when a large number of variants in a region are causal and in the same direction. As the underlying biological mechanisms are unknown in practice and vary from one gene to another across the genome, it is of substantial practical interest to develop a test that is optimal for both scenarios. In this paper, we propose a class of tests that include burden tests and SKAT as special cases, and derive an optimal test within this class that maximizes power. We show that this optimal test outperforms burden tests and SKAT in a wide range of scenarios. The results are illustrated using simulation studies and triglyceride data from the Dallas Heart Study. In addition, we have derived sample size/power calculation formula for SKAT with a new family of kernels to facilitate designing new sequence association studies.

Genome-Wide Analysis of Survival in Early-Stage Non–Small-Cell Lung Cancer

PURPOSE Lung cancer, of which 85% is non-small-cell (NSCLC), is the leading cause of cancer-related death in the United States. We used genome-wide analysis of tumor tissue to investigate whether single nucleotide polymorphisms (SNPs) in tumors are prognostic factors in early-stage NSCLC. PATIENTS AND METHODS One hundred early-stage NSCLC patients from Massachusetts General Hospital (MGH) were used as a discovery set and 89 NSCLC patients collected by the National Institute of Occupational Health, Norway, were used as a validation set. DNA was extracted from flash-frozen lung tissue with at least 70% tumor cellularity. Genome-wide genotyping was done using the high-density SNP chip. Copy numbers were inferred using median smoothing after intensity normalization. Cox models were used to screen and validate significant SNPs associated with the overall survival. RESULTS Copy number gains in chromosomes 3q, 5p, and 8q were observed in both MGH and Norwegian cohorts. The top 50 SNPs associated with overall survival in the MGH cohort (P < or = 2.5 x 10(-4)) were selected and examined using the Norwegian cohort. Five of the top 50 SNPs were validated in the Norwegian cohort with false discovery rate lower than 0.05 (P < .016) and all five were located in known genes: STK39, PCDH7, A2BP1, and EYA2. The numbers of risk alleles of the five SNPs showed a cumulative effect on overall survival (P(trend) = 3.80 x 10(-12) and 2.48 x 10(-7) for MGH and Norwegian cohorts, respectively). CONCLUSION Five SNPs were identified that may be prognostic of overall survival in early-stage NSCLC.

Maternal plasma folate impacts differential DNA methylation in an epigenome-wide meta-analysis of newborns

Folate is vital for fetal development. Periconceptional folic acid supplementation and food fortification are recommended to prevent neural tube defects. Mechanisms whereby periconceptional folate influences normal development and disease are poorly understood: epigenetics may be involved. We examine the association between maternal plasma folate during pregnancy and epigenome-wide DNA methylation using Illuminas HumanMethyl450 Beadchip in 1,988 newborns from two European cohorts. Here we report the combined covariate-adjusted results using meta-analysis and employ pathway and gene expression analyses. Four-hundred forty-three CpGs (320 genes) are significantly associated with maternal plasma folate levels during pregnancy (false discovery rate 5%); 48 are significant after Bonferroni correction. Most genes are not known for folate biology, including APC2, GRM8, SLC16A12, OPCML, PRPH, LHX1, KLK4 and PRSS21. Some relate to birth defects other than neural tube defects, neurological functions or varied aspects of embryonic development. These findings may inform how maternal folate impacts the developing epigenome and health outcomes in offspring.

Sparse linear discriminant analysis for simultaneous testing for the significance of a gene set/pathway and gene selection

MOTIVATION Pathway and gene set-based approaches for the analysis of gene expression profiling experiments have become increasingly popular for addressing problems associated with individual gene analysis. Since most genes are not differently expressed, existing gene set tests, which consider all the genes within a gene set, are subject to considerable noise and power loss, a concern exacerbated in studies in which the degree of differential expression is moderate for truly differentially expressed genes. For a significantly differentially expressed pathway, it is also of substantial interest to select important genes that drive the differential expression of the pathway. METHODS We develop a unified framework to jointly test the significance of a pathway and to select a subset of genes that drive the significant pathway effect. To achieve dimension reduction and gene selection, we decompose each gene pathway into a single score by using a regularized form of linear discriminant analysis, called sparse linear discriminant analysis (sLDA). Testing for the significance of the pathway effect proceeds via permutation of the sLDA score. The sLDA-based test is compared with competing approaches with simulations and two applications: a study on the effect of metal fume exposure on immune response and a study of gene expression profiles among Type II Diabetes patients. RESULTS Our results show that sLDA-based testing provides a powerful approach to test for the significance of a differentially expressed pathway and gene selection. AVAILABILITY An implementation of the proposed sLDA-based pathway test in the R statistical computing environment is available at http://www.hsph.harvard.edu/~mwu/software/. SUPPLEMENTARY INFORMATION Supplementary data are available at Bioinformatics online.

Cadmium exposure and the epigenome: Exposure-associated patterns of DNA methylation in leukocytes from mother-baby pairs

Cadmium (Cd) is prevalent in the environment yet understudied as a developmental toxicant. Cd partially crosses the placental barrier from mother to fetus and is linked to detrimental effects in newborns. Here we examine the relationship between levels of Cd during pregnancy and 5-methylcytosine (5mC) levels in leukocyte DNA collected from 17 mother-newborn pairs. The methylation of cytosines is an epigenetic mechanism known to impact transcriptional signaling and influence health endpoints. A methylated cytosine-guanine (CpG) island recovery assay was used to assess over 4.6 million sites spanning 16,421 CpG islands. Exposure to Cd was classified for each mother-newborn pair according to maternal blood levels and compared with levels of cotinine. Subsets of genes were identified that showed altered DNA methylation levels in their promoter regions in fetal DNA associated with levels of Cd (n = 61), cotinine (n = 366), or both (n = 30). Likewise, in maternal DNA, differentially methylated genes were identified that were associated with Cd (n = 92) or cotinine (n = 134) levels. While the gene sets were largely distinct between maternal and fetal DNA, functional similarities at the biological pathway level were identified including an enrichment of genes that encode for proteins that control transcriptional regulation and apoptosis. Furthermore, conserved DNA motifs with sequence similarity to specific transcription factor binding sites were identified within the CpG islands of the gene sets. This study provides evidence for distinct patterns of DNA methylation or “footprints” in fetal and maternal DNA associated with exposure to Cd.

Maternal smoking and DNA methylation in newborns: In utero effect or epigenetic inheritance?

Background: Maternal smoking in pregnancy is associated with adverse health outcomes in children, including cancers; underlying mechanisms may include epigenetic modifications. Using Illuminas 450K array, we previously identified differential DNA methylation related to maternal smoking during pregnancy at 26 CpG sites (CpGs) in 10 genes in newborn cord bloods from the Norwegian Mother and Child Cohort Study (MoBa). Whether these methylation signals in newborns reflect in utero exposure only or possibly epigenetic inheritance of smoking-related modifications is unclear. Methods: We therefore evaluated the impact of the timing of mothers smoking (before or during pregnancy using cotinine measured at 18 weeks gestation), the fathers smoking before conception, and the grandmothers smoking during her pregnancy with the mother on methylation at these 26 CpGs in 1,042 MoBa newborns. We used robust linear regression, adjusting for covariates, applying Bonferroni correction. Results: The strongest and only statistically significant associations were observed for sustained smoking by the mother during pregnancy through at least gestational week 18 (P < 1.6 × 10−5 for all 26 CpGs). We observed no statistically significant differential methylation due to smoking by the mother before pregnancy or that ceased by week 18, fathers smoking before conception, or grandmothers smoking while pregnant with the mother. Conclusions: Differential methylation at these CpGs in newborns seems to reflect sustained in utero exposure rather than epigenetic inheritance. Impact: Smoking cessation in early pregnancy may negate effects on methylation. Analyses of maternal smoking during pregnancy and offspring health outcomes, including cancer, limited to ever smoking might miss true associations. Cancer Epidemiol Biomarkers Prev; 23(6); 1007–17. ©2014 AACR.