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1.  Mapping genes with longitudinal phenotypes via Bayesian posterior probabilities 
BMC Proceedings  2014;8(Suppl 1):S81.
Most association studies focus on disease risk, with less attention paid to disease progression or severity. These phenotypes require longitudinal data. This paper presents a new method for analyzing longitudinal data to map genes in both population-based and family-based studies. Using simulated systolic blood pressure measurements obtained from Genetic Analysis Workshop 18, we cluster the phenotype data into trajectory subgroups. We then use the Bayesian posterior probability of being in the high subgroup as a quantitative trait in an association analysis with genotype data. This method maintains high power (>80%) in locating genes known to affect the simulated phenotype for most specified significance levels (α). We believe that this method can be useful to aid in the discovery of genes that affect severity or progression of disease.
PMCID: PMC4143622  PMID: 25519410
2.  Single variant and multi-variant trend tests for genetic association with next generation sequencing that are robust to sequencing error 
Human heredity  2013;74(0):10.1159/000346824.
As with any new technology, next generation sequencing (NGS) has potential advantages and potential challenges. One advantage is the identification of multiple causal variants for disease that might otherwise be missed by SNP-chip technology. One potential challenge is misclassification error (as with any emerging technology) and the issue of power loss due to multiple testing.
Here, we develop an extension of the linear trend test for association that incorporates differential misclassification error and may be applied to any number of SNPs. We call the statistic the linear trend test allowing for error, applied to NGS, or LTTae,NGS. This statistic allows for differential misclassification.
The observed data are phenotypes for unrelated cases and controls, coverage, and the number of putative causal variants for every individual at all SNPs. We simulate data considering multiple factors (disease mode of inheritance, genotype relative risk, causal variant frequency, sequence error rate in cases, sequence error rate in controls, number of loci, and others) and evaluate type I error rate and power for each vector of factor settings. We compare our results with two recently published NGS statistics. Also, we create a fictitious disease model, based on downloaded 1000 Genomes data for 5 SNPs and 388 individuals, and apply our statistic to that data.
We find that the LTTae,NGS maintains the correct type I error rate in all simulations (differential and non-differential error), while the other statistics show large inflation in type I error for lower coverage. Power for all three methods is approximately the same for all three statistics in the presence of non-differential error.
Application of our statistic to the 1000 Genomes data suggests that, for the data downloaded, there is a 1.5% sequence misclassification rate over all SNPs.
Finally, application of the multi-variant form of LTTae,NGS shows high power for a number of simulation settings, although it can have lower power than the corresponding single variant simulation results, most probably due to our specification of multi-variant SNP correlation values.
In conclusion, our LTTae,NGS addresses two key challenges with NGS disease studies; first, it allows for differential misclassification when computing the statistic; and second, it addresses the multiple-testing issue in that there is a multi-variant form of the statistic that has only one degree of freedom, and provides a single p-value, no matter how many loci.
PMCID: PMC3863939  PMID: 23594495
next gen; rare variant; trend test; genetic association; GWAS; allele; locus
3.  Evidence for association of two variants of the nociceptin/orphanin FQ receptor gene OPRL1 with vulnerability to develop opiate addiction in Caucasians 
Psychiatric genetics  2010;20(2):10.1097/YPG.0b013e32833511f6.
The OPRL1 gene encodes the nociceptin/orphanin FQ receptor (NOP-R), which plays a role in regulating tolerance and behavioral responses to morphine. However, there is limited information on whether variants of OPRL1 are associated with vulnerability to develop opiate addiction. In this study, we examined five variants of OPRL1 and their role in determining vulnerability to develop opiate addiction.
We recruited 447 subjects: 271 former severe heroin addicts and 176 healthy controls. Using a 5′-fluorogenic exonuclease assay (TaqMan®), we genotyped subjects at five variants in OPRL1. It was then determined whether there was a significant association of allele, genotype, or haplotype frequency with vulnerability to develop opiate addiction.
When the cohort was stratified by ethnicity, we found that, in Caucasians but not in African Americans or Hispanics, the allele frequency of rs6090041 and rs6090043 were significantly associated point-wise with opiate addiction (P = 0.03 and 0.04, respectively). Of the haplotypes formed by these two variants, one haplotype was found to be associated with protection from developing opiate addiction in both African Americans (point-wise P = 0.04) and Caucasians (point-wise P = 0.04), and another haplotype with vulnerability to develop opiate addiction in Caucasians only (P = 0.020).
This study provides evidence for an association of two variants of the OPRL1 gene, rs6090041 and rs6090043, with vulnerability to develop opiate addiction, suggesting a role for NOP-R in the development of opiate addiction.
PMCID: PMC3832186  PMID: 20032820
OPRL1; ORL1; nociceptin/orphanin FQ receptor; polymorphism; variant; opiate addiction; heroin
4.  IL-18R1 and IL-18RAP SNPs may associate with Bronchopulmonary Dysplasia in African American infants 
Pediatric research  2012;71(1):107-114.
The genetic contribution to the development of bronchopulmonary dysplasia (BPD) in prematurely born infants is substantial, but information related to the specific genes involved is lacking. We conducted a case-control single nucleotide polymorphism (SNP) association study of candidate genes (n=601) or 6,324 SNPs in 1,091 prematurely born infants with gestational age <35 weeks, with or without neonatal lung disease including BPD. BPD was defined as need for oxygen at 28 days. Genotype analysis revealed, after multiple comparisons correction, two significant SNPs, rs3771150 (IL-18RAP) and rs3771171 (IL-18R1), in African Americans (AA) with BPD (vs. AA without BPD; q<0.05). No associations with Caucasian (CA) BPD, AA or CA RDS, or prematurity in either AA or CA, were identified with these SNPs. Respective frequencies were 0.098 and 0.093 without BPD and 0.38 for each SNP in infants with BPD. In the replication set (82 cases; 102 controls), the p-values were 0.012 for rs3771150 and 0.07 for rs3771171. Combining p-values using Fisher's method, overall p-values were 8.31E-07 for rs3771150, and 6.33E-06 for rs3771171. We conclude, IL-18RAP and IL-18R1 SNPs identify AA infants at risk for BPD. These genes may contribute to AA BPD pathogenesis via inflammatory-mediated processes and require further study.
PMCID: PMC3610412  PMID: 22289858
5.  Genome-wide association studies of adolescent idiopathic scoliosis suggest candidate susceptibility genes 
Human Molecular Genetics  2011;20(7):1456-1466.
Adolescent idiopathic scoliosis (AIS) is an unexplained and common spinal deformity seen in otherwise healthy children. Its pathophysiology is poorly understood despite intensive investigation. Although genetic underpinnings are clear, replicated susceptibility loci that could provide insight into etiology have not been forthcoming. To address these issues, we performed genome-wide association studies (GWAS) of ∼327 000 single nucleotide polymorphisms (SNPs) in 419 AIS families. We found strongest evidence of association with chromosome 3p26.3 SNPs in the proximity of the CHL1 gene (P < 8 × 10−8 for rs1400180). We genotyped additional chromosome 3p26.3 SNPs and tested replication in two follow-up case–control cohorts, obtaining strongest results when all three cohorts were combined (rs10510181 odds ratio = 1.49, 95% confidence interval = 1.29–1.73, P = 2.58 × 10−8), but these were not confirmed in a separate GWAS. CHL1 is of interest, as it encodes an axon guidance protein related to Robo3. Mutations in the Robo3 protein cause horizontal gaze palsy with progressive scoliosis (HGPPS), a rare disease marked by severe scoliosis. Other top associations in our GWAS were with SNPs in the DSCAM gene encoding an axon guidance protein in the same structural class with Chl1 and Robo3. We additionally found AIS associations with loci in CNTNAP2, supporting a previous study linking this gene with AIS. Cntnap2 is also of functional interest, as it interacts directly with L1 and Robo class proteins and participates in axon pathfinding. Our results suggest the relevance of axon guidance pathways in AIS susceptibility, although these findings require further study, particularly given the apparent genetic heterogeneity in this disease.
PMCID: PMC3049353  PMID: 21216876
6.  TDT-HET: A new transmission disequilibrium test that incorporates locus heterogeneity into the analysis of family-based association data 
BMC Bioinformatics  2012;13:13.
Locus heterogeneity is one of the most documented phenomena in genetics. To date, relatively little work had been done on the development of methods to address locus heterogeneity in genetic association analysis. Motivated by Zhou and Pan's work, we present a mixture model of linked and unlinked trios and develop a statistical method to estimate the probability that a heterozygous parent transmits the disease allele at a di-allelic locus, and the probability that any trio is in the linked group. The purpose here is the development of a test that extends the classic transmission disequilibrium test (TDT) to one that accounts for locus heterogeneity.
Our simulations suggest that, for sufficiently large sample size (1000 trios) our method has good power to detect association even the proportion of unlinked trios is high (75%). While the median difference (TDT-HET empirical power - TDT empirical power) is approximately 0 for all MOI, there are parameter settings for which the power difference can be substantial. Our multi-locus simulations suggest that our method has good power to detect association as long as the markers are reasonably well-correlated and the genotype relative risk are larger. Results of both single-locus and multi-locus simulations suggest our method maintains the correct type I error rate.
Finally, the TDT-HET statistic shows highly significant p-values for most of the idiopathic scoliosis candidate loci, and for some loci, the estimated proportion of unlinked trios approaches or exceeds 50%, suggesting the presence of locus heterogeneity.
We have developed an extension of the TDT statistic (TDT-HET) that allows for locus heterogeneity among coded trios. Benefits of our method include: estimates of parameters in the presence of heterogeneity, and reasonable power even when the proportion of linked trios is small. Also, we have extended multi-locus methods to TDT-HET and have demonstrated that the empirical power may be high to detect linkage. Last, given that we obtain PPBs, we conjecture that the TDT-HET may be a useful method for correctly identifying linked trios. We anticipate that researchers will find this property increasingly useful as they apply next-generation sequencing data in family based studies.
PMCID: PMC3292499  PMID: 22264315
7.  Heroin addiction in African Americans: a hypothesis-driven association study 
Genes, brain, and behavior  2009;8(5):531-540.
Heroin addiction is a chronic complex disease with a substantial genetic contribution. This study was designed to identify gene variants associated with heroin addiction in African Americans. The emphasis was on genes involved in reward modulation, behavioral control, cognitive function, signal transduction, and stress response. We have performed a case-control association analysis by screening with 1350 variants of 130 genes. The sample consisted of 202 former severe heroin addicts in methadone treatment and 167 healthy controls with no history of drug abuse. Single-SNP, haplotype and multi-SNP genotype pattern analyses were performed. Seventeen SNPs showed point-wise significant association with heroin addiction (nominal P < 0.01). These SNPs are from genes encoding several receptors: adrenergic (ADRA1A), arginine vasopressin (AVPR1A), cholinergic (CHRM2), dopamine (DRD1), GABA-A (GABRB3), glutamate (GRIN2A), and serotonin (HTR3A), as well as alcohol dehydrogenase (ADH7), glutamic acid decarboxylase (GAD1 and GAD2), the nucleoside transporter (SLC29A1), and diazepam binding inhibitor (DBI). The most significant result of the analyses was obtained for the GRIN2A haplotype G-A-T (rs4587976-rs1071502-rs1366076) with protective effect (P uncorrected = 9.6E-05, P corrected = 0.058). This study corroborates several reported associations with alcohol and drug addiction as well as other related disorders, and extends the list of variants that may affect the development of heroin addiction. Further studies will be necessary to replicate these associations and to elucidate the roles of these variants in drug addiction vulnerability.
PMCID: PMC2716061  PMID: 19500151
association study; heroin addiction; polymorphisms; African Americans; NMDA glutamate receptor
8.  Density-based clustering in haplotype analysis for association mapping 
BMC Proceedings  2007;1(Suppl 1):S27.
Clustering of related haplotypes in haplotype-based association mapping has the potential to improve power by reducing the degrees of freedom without sacrificing important information about the underlying genetic structure. We have modified a generalized linear model approach for association analysis by incorporating a density-based clustering algorithm to reduce the number of coefficients in the model. Using the GAW 15 Problem 3 simulated data, we show that our novel method can substantially enhance power to detect association with the binary rheumatoid arthritis (RA) phenotype at the HLA-DRB1 locus on chromosome 6. In contrast, clustering did not appreciably improve performance at locus D, perhaps a consequence of a rare susceptibility allele and of the overwhelming effect of HLA-DRB1/locus C, 5 cM distal. Optimization of parameters governing the clustering algorithm identified a set of parameters that delivered nearly ideal performance in a variety of situations. The cluster-based score test was valid over a wide range of haplotype diversity, and was robust to severe departures from Hardy-Weinberg equilibrium encountered near HLA-DRB1 in RA case-control samples.
PMCID: PMC2367537  PMID: 18466524

Results 1-8 (8)