Human mutations in high-confidence Tourette disorder genes affect sensorimotor behavior, reward learning, and striatal dopamine in mice.

Tourette disorder (TD) is poorly understood, despite affecting 1/160 children. A lack of animal models possessing construct, face, and predictive validity hinders progress in the field. We used CRISPR/Cas9 genome editing to generate mice with mutations orthologous to human de novo variants in two high-confidence Tourette genes, CELSR3 and WWC1. Mice with human mutations in Celsr3 and Wwc1 exhibit cognitive and/or sensorimotor behavioral phenotypes consistent with TD. Sensorimotor gating deficits, as measured by acoustic prepulse inhibition, occur in both male and female Celsr3 TD models. Wwc1 mice show reduced prepulse inhibition only in females. Repetitive motor behaviors, common to Celsr3 mice and more pronounced in females, include vertical rearing and grooming. Sensorimotor gating deficits and rearing are attenuated by aripiprazole, a partial agonist at dopamine type II receptors. Unsupervised machine learning reveals numerous changes to spontaneous motor behavior and less predictable patterns of movement. Continuous fixed-ratio reinforcement shows that Celsr3 TD mice have enhanced motor responding and reward learning. Electrically evoked striatal dopamine release, tested in one model, is greater. Brain development is otherwise grossly normal without signs of striatal interneuron loss. Altogether, mice expressing human mutations in high-confidence TD genes exhibit face and predictive validity. Reduced prepulse inhibition and repetitive motor behaviors are core behavioral phenotypes and are responsive to aripiprazole. Enhanced reward learning and motor responding occur alongside greater evoked dopamine release. Phenotypes can also vary by sex and show stronger affection in females, an unexpected finding considering males are more frequently affected in TD.

LD block disorder-specific pleiotropic roles of novel CRHR1 in type 2 diabetes and depression disorder comorbidity.

Major depressive disorder (MDD) and type 2 diabetes (T2D) are complex disorders whose comorbidity can be due to hypercortisolism and may be explained by dysfunction of the corticotropin-releasing hormone receptor 1 (CRHR1) and cortisol feedback within the hypothalamic-pituitary-adrenal axis (HPA axis). To investigate the role of the CRHR1 gene in familial T2D, MDD, and MDD-T2D comorbidity, we tested 152 CRHR1 single-nucleotide-polymorphisms (SNPs), via 2-point parametric linkage and linkage disequilibrium (LD; i.e., association) analyses using 4 models, in 212 peninsular families with T2D and MDD. We detected linkage/LD/association to/with MDD and T2D with 122 (116 novel) SNPs. MDD and T2D had 4 and 3 disorder-specific novel risk LD blocks, respectively, whose risk variants reciprocally confirm one another. Comorbidity was conferred by 3 novel independent SNPs. In silico analyses reported novel functional changes, including the binding site of glucocorticoid receptor-alpha [GR-α] on CRHR1 for transcription regulation. This is the first report of CRHR1 pleiotropic linkage/LD/association with peninsular familial MDD and T2D. CRHR1 contribution to MDD is stronger than to T2D and may antecede T2D onset. Our findings suggest a new molecular-based clinical entity of MDD-T2D and should be replicated in other ethnic groups.

Comorbidity of Novel CRHR2 Gene Variants in Type 2 Diabetes and Depression.

The corticotropin-releasing hormone receptor 2 (CRHR2) gene encodes CRHR2, contributing to the hypothalamic-pituitary-adrenal stress response and to hyperglycemia and insulin resistance. CRHR2-/- mice are hypersensitive to stress, and the CRHR2 locus has been linked to type 2 diabetes and depression. While CRHR2 variants confer risk for mood disorders, MDD, and type 2 diabetes, they have not been investigated in familial T2D and MDD. In 212 Italian families with type 2 diabetes and depression, we tested 17 CRHR2 single nucleotide polymorphisms (SNPs), using two-point parametric-linkage and linkage-disequilibrium (i.e., association) analysis (models: dominant-complete-penetrance-D1, dominant-incomplete-penetrance-D2, recessive-complete-penetrance-R1, recessive-incomplete-penetrance-R2). We detected novel linkage/linkage-disequilibrium/association to/with depression (3 SNPs/D1, 2 SNPs/D2, 3 SNPs/R1, 3 SNPs/R2) and type 2 diabetes (3 SNPs/D1, 2 SNPs/D2, 2 SNPs/R1, 1 SNP/R2). All detected risk variants are novel. Two depression-risk variants within one linkage-disequilibrium block replicate each other. Two independent novel SNPs were comorbid while the most significant conferred either depression- or type 2 diabetes-risk. Although the families were primarily ascertained for type 2 diabetes, depression-risk variants showed higher significance than type 2 diabetes-risk variants, implying CRHR2 has a stronger role in depression-risk than type 2 diabetes-risk. In silico analysis predicted variants' dysfunction. CRHR2 is for the first time linked to/in linkage-disequilibrium/association with depression-type 2 diabetes comorbidity and may underlie the shared genetic pathogenesis via pleiotropy.

Investigation of previously implicated genetic variants in chronic tic disorders: a transmission disequilibrium test approach.

Genetic studies in Tourette syndrome (TS) are characterized by scattered and poorly replicated findings. We aimed to replicate findings from candidate gene and genome-wide association studies (GWAS). Our cohort included 465 probands with chronic tic disorder (93% TS) and both parents from 412 families (some probands were siblings). We assessed 75 single nucleotide polymorphisms (SNPs) in 465 parent-child trios; 117 additional SNPs in 211 trios; and 4 additional SNPs in 254 trios. We performed SNP and gene-based transmission disequilibrium tests and compared nominally significant SNP results with those from a large independent case-control cohort. After quality control 71 SNPs were available in 371 trios; 112 SNPs in 179 trios; and 3 SNPs in 192 trios. 17 were candidate SNPs implicated in TS and 2 were implicated in obsessive-compulsive disorder (OCD) or autism spectrum disorder (ASD); 142 were tagging SNPs from eight monoamine neurotransmitter-related genes (including dopamine and serotonin); 10 were top SNPs from TS GWAS; and 13 top SNPs from attention-deficit/hyperactivity disorder, OCD, or ASD GWAS. None of the SNPs or genes reached significance after adjustment for multiple testing. We observed nominal significance for the candidate SNPs rs3744161 (TBCD) and rs4565946 (TPH2) and for five tagging SNPs; none of these showed significance in the independent cohort. Also, SLC1A1 in our gene-based analysis and two TS GWAS SNPs showed nominal significance, rs11603305 (intergenic) and rs621942 (PICALM). We found no convincing support for previously implicated genetic polymorphisms. Targeted re-sequencing should fully appreciate the relevance of candidate genes.

An Analytic Solution to the Computation of Power and Sample Size for Genetic Association Studies under a Pleiotropic Mode of Inheritance.

Our motivation here is to calculate the power of 3 statistical tests used when there are genetic traits that operate under a pleiotropic mode of inheritance and when qualitative phenotypes are defined by use of thresholds for the multiple quantitative phenotypes. Specifically, we formulate a multivariate function that provides the probability that an individual has a vector of specific quantitative trait values conditional on having a risk locus genotype, and we apply thresholds to define qualitative phenotypes (affected, unaffected) and compute penetrances and conditional genotype frequencies based on the multivariate function. We extend the analytic power and minimum-sample-size-necessary (MSSN) formulas for 2 categorical data-based tests (genotype, linear trend test [LTT]) of genetic association to the pleiotropic model. We further compare the MSSN of the genotype test and the LTT with that of a multivariate ANOVA (Pillai). We approximate the MSSN for statistics by linear models using a factorial design and ANOVA. With ANOVA decomposition, we determine which factors most significantly change the power/MSSN for all statistics. Finally, we determine which test statistics have the smallest MSSN. In this work, MSSN calculations are for 2 traits (bivariate distributions) only (for illustrative purposes). We note that the calculations may be extended to address any number of traits. Our key findings are that the genotype test usually has lower MSSN requirements than the LTT. More inclusive thresholds (top/bottom 25% vs. top/bottom 10%) have higher sample size requirements. The Pillai test has a much larger MSSN than both the genotype test and the LTT, as a result of sample selection. With these formulas, researchers can specify how many subjects they must collect to localize genes for pleiotropic phenotypes.

Expression and characterization of three Aurora kinase C splice variants found in human oocytes.

Chromosome segregation is an extensively choreographed process yet errors still occur frequently in female meiosis, leading to implantation failure, miscarriage or offspring with developmental disorders. Aurora kinase C (AURKC) is a component of the chromosome passenger complex and is highly expressed in gametes. Studies in mouse oocytes indicate that AURKC is required to regulate chromosome segregation during meiosis I; however, little is known about the functional significance of AURKC in human oocytes. Three splice variants of AURKC exist in testis tissue. To determine which splice variants human oocytes express, we performed quantitative real-time PCR using single oocytes and found expression of all three variants. To evaluate the functional differences between the variants, we created green fluorescent protein-tagged constructs of each variant to express in oocytes from Aurkc(-/-) mice. By quantifying metaphase chromosome alignment, cell cycle progression, phosphorylation of INCENP and microtubule attachments to kinetochores, we found that AURKC_v1 was the most capable of the variants at supporting metaphase I chromosome segregation. AURKC_v3 localized to chromosomes properly and supported cell cycle progression to metaphase II, but its inability to correct erroneous microtubule attachments to kinetochores meant that chromosome segregation was not as accurate compared with the other two variants. Finally, when we expressed the three variants simultaneously, error correction was more robust than when they were expressed on their own. Therefore, oocytes express three variants of AURKC that are not functionally equivalent in supporting meiosis, but fully complement meiosis when expressed simultaneously.

A meta-analysis identifies adolescent idiopathic scoliosis association with LBX1 locus in multiple ethnic groups.

BACKGROUND: Adolescent idiopathic scoliosis (AIS) is a common rotational deformity of the spine that presents in children worldwide, yet its etiology is poorly understood. Recent genome-wide association studies (GWAS) have identified a few candidate risk loci. One locus near the chromosome 10q24.31 LBX1 gene (OMIM #604255) was originally identified by a GWAS of Japanese subjects and replicated in additional Asian populations. To extend this result, and to create larger AIS cohorts for the purpose of large-scale meta-analyses in multiple ethnicities, we formed a collaborative group called the International Consortium for Scoliosis Genetics (ICSG). METHODS: Here, we report the first ICSG study, a meta-analysis of the LBX1 locus in six Asian and three non-Asian cohorts. RESULTS: We find significant evidence for association of this locus with AIS susceptibility in all nine cohorts. Results for seven cohorts containing both genders yielded P=1.22×10-43 for rs11190870, and P=2.94×10-48 for females in all nine cohorts. Comparing the regional haplotype structures for three populations, we refined the boundaries of association to a ∼25 kb block encompassing the LBX1 gene. The LBX1 protein, a homeobox transcription factor that is orthologous to the Drosophila ladybird late gene, is involved in proper migration of muscle precursor cells, specification of cardiac neural crest cells, and neuronal determination in developing neural tubes. CONCLUSIONS: Our results firmly establish the LBX1 region as the first major susceptibility locus for AIS in Asian and non-Hispanic white groups, and provide a platform for larger studies in additional ancestral groups.

A novel method for analyzing genetic association with longitudinal phenotypes.

Knowledge of genes influencing longitudinal patterns may offer information about predicting disease progression. We developed a systematic procedure for testing association between SNP genotypes and longitudinal phenotypes. We evaluated false positive rates and statistical power to localize genes for disease progression. We used genome-wide SNP data from the Framingham Heart Study. With longitudinal data from two real studies unrelated to Framingham, we estimated three trajectory curves from each study. We performed simulations by randomly selecting 500 individuals. In each simulation replicate, we assigned each individual to one of the three trajectory groups based on the underlying hypothesis (null or alternative), and generated corresponding longitudinal data. Individual Bayesian posterior probabilities (BPPs) for belonging to a specific trajectory curve were estimated. These BPPs were treated as a quantitative trait and tested (using the Wald test) for genome-wide association. Empirical false positive rates and power were calculated. Our method maintained the expected false positive rate for all simulation models. Also, our method achieved high empirical power for most simulations. Our work presents a method for disease progression gene mapping. This method is potentially clinically significant as it may allow doctors to predict disease progression based on genotype and determine treatment accordingly.

Genome-wide association studies of adolescent idiopathic scoliosis suggest candidate susceptibility genes.

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.

A keratin 15 containing stem cell population from the hair follicle contributes to squamous papilloma development in the mouse.

The multistage model of nonmelanoma skin carcinogenesis has contributed significantly to our understanding of epithelial cancer in general. We used the Krt1-15CrePR1;R26R transgenic mouse to determine the contribution of keratin 15+ cells from the hair follicle to skin tumor development by following the labeled progeny of the keratin 15 expressing cells into papillomas. We present three novel observations. First, we found that keratin 15 expressing cells contribute to most of the papillomas by 20 weeks of promotion. Second, in contrast to the transient behavior of labeled keratin 15-derived progeny in skin wound healing, keratin 15 progeny persist in papillomas, and some malignancies for many months following transient induction of the reporter gene. Third, papillomas have surprising heterogeneity not only in their cellular composition, but also in their expression of the codon 61 signature Ha-ras mutation with approximately 30% of keratin 15-derived regions expressing the mutation. Together, these results demonstrate that keratin 15 expressing cells of the hair follicle contribute to cutaneous papillomas with long term persistence and a subset of which express the Ha-ras signature mutation characteristic of initiated cells.

Single-variant and multi-variant trend tests for genetic association with next-generation sequencing that are robust to sequencing error.

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 those 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.

A putative RUNX1 binding site variant between SLC9A3R1 and NAT9 is associated with susceptibility to psoriasis.

Psoriasis (OMIM 177900) is a chronic inflammatory skin disorder of unknown pathogenesis affecting approximately 2% of the Western population. It occurs more frequently in individuals with human immunodeficiency virus, and 20-30% of individuals with psoriasis have psoriatic arthritis. Psoriasis is associated with HLA class I alleles, and previous linkage analysis by our group identified a second psoriasis locus at 17q24-q25 (PSORS2; ref. 7). Linkage to this locus was confirmed with independent family sets. Additional loci have also been proposed to be associated with psoriasis. Here we describe two peaks of strong association with psoriasis on chromosome 17q25 separated by 6 Mb. Associated single-nucleotide polymorphisms (SNPs) in the proximal peak lie in or near SLC9A3R1 (also called EBP50 and NHERF1) and NAT9, a new member of the N-acetyltransferase family. SLC9A3R1 is a PDZ domain-containing phosphoprotein that associates with members of the ezrin-radixin-moesin family and is implicated in diverse aspects of epithelial membrane biology and immune synapse formation in T cells. The distal peak of association is in RAPTOR (p150 target of rapamycin (TOR)-scaffold protein containing WD-repeats). Expression of SLC9A3R1 is highest in the uppermost stratum Malpighi of psoriatic and normal skin and in inactive versus active T cells. A disease-associated SNP lying between SLC9A3R1 and NAT9 leads to loss of RUNX1 binding. This is the second example of loss of a RUNX1 binding site associated with susceptibility to an autoimmune disease. It also suggests defective regulation of SLC9A3R1 or NAT9 by RUNX1 as a susceptibility factor for psoriasis.

Design, analysis, and interpretation of treatment response heterogeneity in personalized nutrition and obesity treatment research.

It is increasingly assumed that there is no one-size-fits-all approach to dietary recommendations for the management and treatment of chronic diseases such as obesity. This phenomenon that not all individuals respond uniformly to a given treatment has become an area of research interest given the rise of personalized and precision medicine. To conduct, interpret, and disseminate this research rigorously and with scientific accuracy, however, requires an understanding of treatment response heterogeneity. Here, we define treatment response heterogeneity as it relates to clinical trials, provide statistical guidance for measuring treatment response heterogeneity, and highlight study designs that can quantify treatment response heterogeneity in nutrition and obesity research. Our goal is to educate nutrition and obesity researchers in how to correctly identify and consider treatment response heterogeneity when analyzing data and interpreting results, leading to rigorous and accurate advancements in the field of personalized medicine.

Human mutations in high-confidence Tourette disorder genes affect sensorimotor behavior, reward learning, and striatal dopamine in mice.

Tourette disorder (TD) is poorly understood, despite affecting 1/160 children. A lack of animal models possessing construct, face, and predictive validity hinders progress in the field. We used CRISPR/Cas9 genome editing to generate mice with mutations orthologous to human de novo variants in two high-confidence Tourette genes, CELSR3 and WWC1 . Mice with human mutations in Celsr3 and Wwc1 exhibit cognitive and/or sensorimotor behavioral phenotypes consistent with TD. Sensorimotor gating deficits, as measured by acoustic prepulse inhibition, occur in both male and female Celsr3 TD models. Wwc1 mice show reduced prepulse inhibition only in females. Repetitive motor behaviors, common to Celsr3 mice and more pronounced in females, include vertical rearing and grooming. Sensorimotor gating deficits and rearing are attenuated by aripiprazole, a partial agonist at dopamine type II receptors. Unsupervised machine learning reveals numerous changes to spontaneous motor behavior and less predictable patterns of movement. Continuous fixed-ratio reinforcement shows Celsr3 TD mice have enhanced motor responding and reward learning. Electrically evoked striatal dopamine release, tested in one model, is greater. Brain development is otherwise grossly normal without signs of striatal interneuron loss. Altogether, mice expressing human mutations in high-confidence TD genes exhibit face and predictive validity. Reduced prepulse inhibition and repetitive motor behaviors are core behavioral phenotypes and are responsive to aripiprazole. Enhanced reward learning and motor responding occurs alongside greater evoked dopamine release. Phenotypes can also vary by sex and show stronger affection in females, an unexpected finding considering males are more frequently affected in TD. Significance Statement: We generated mouse models that express mutations in high-confidence genes linked to Tourette disorder (TD). These models show sensorimotor and cognitive behavioral phenotypes resembling TD-like behaviors. Sensorimotor gating deficits and repetitive motor behaviors are attenuated by drugs that act on dopamine. Reward learning and striatal dopamine is enhanced. Brain development is grossly normal, including cortical layering and patterning of major axon tracts. Further, no signs of striatal interneuron loss are detected. Interestingly, behavioral phenotypes in affected females can be more pronounced than in males, despite male sex bias in the diagnosis of TD. These novel mouse models with construct, face, and predictive validity provide a new resource to study neural substrates that cause tics and related behavioral phenotypes in TD.

TDT-HET: a new transmission disequilibrium test that incorporates locus heterogeneity into the analysis of family-based association data.

BACKGROUND: 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. RESULTS: 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. CONCLUSIONS: 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.

IL-18R1 and IL-18RAP SNPs may be associated with bronchopulmonary dysplasia in African-American infants.

INTRODUCTION: 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. RESULTS: Genotype analysis revealed, after multiple comparisons correction, two significant single-nucleotide polymorphism (SNPs), rs3771150 (IL-18RAP) and rs3771171 (IL-18R1), in African Americans (AAs) with BPD (vs. AAs without BPD; q < 0.05). No associations with Caucasian (CA) BPD, AA or CA respiratory distress syndrome (RDS), or prematurity in either AAs or CAs were identified with these SNPs. Respective frequencies were 0.098 and 0.093 in infants 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 8.31 × 10(-7) for rs3771150 and 6.33 × 10(-6) for rs3771171. DISCUSSION: We conclude that 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. METHODS: We conducted a case-control 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 a need for oxygen at 28 days.

A new expectation-maximization statistical test for case-control association studies considering rare variants obtained by high-throughput sequencing.

Genome-wide association studies (GWAS) have been successful in identifying common genetic variation reproducibly associated with disease. However, most associated variants confer very small risk and after meta-analysis of large cohorts a large fraction of expected heritability still remains unexplained. A possible explanation is that rare variants currently undetected by GWAS with SNP arrays could contribute a large fraction of risk when present in cases. This concept has spurred great interest in exploring the role of rare variants in disease. As the cost of sequencing continue to plummet, it is becoming feasible to directly sequence case-control samples for testing disease association including rare variants. We have developed a test statistic that allows for association testing among cases and controls using data directly from sequencing reads. In addition, our method allows for random errors in reads. We determine the probability of a true genotype call based on the observed base pair reads using the expectation-maximization algorithm. We apply the SumStat procedure to obtain a single statistic for a group of multiple rare variant loci. We document the validity of our method through simulations. Our results suggest that our statistic maintains the correct type I error rate, even in the presence of differential misclassification for sequence reads, and that it has good power under a number of scenarios. Finally, our SumStat results show power at least as good as the maximum single locus results.

A cost-effective statistical method to correct for differential genotype misclassification when performing case-control genetic association.

BACKGROUND/AIMS: There is a growing interest regarding the effect of differential misclassification on power and type I error rate in genome-wide association studies. We present an extension of a previously published test statistic: the likelihood ratio test allowing for errors (LRTAE). This test uses double-sample information on a subset of individuals to increase power for genetic association in the presence of nondifferential misclassification. METHODS: We extend the original LRTAE by allowing for differential genotype misclassification between case and control populations. We label this new statistic as LRT(D)A(M)E . We test the performance of this statistic with data simulated under differential misclassification specifications and two different types of genetic models: null and power. For simulations using the null model, we specify that there is no difference between case and control genotype frequencies before the introduction of errors. For simulations under power, we consider three modes of inheritance: dominant, multiplicative, and recessive. RESULTS: We show that the LRT(D)A(M)E , with p values computed using permutation, maintains a correct type I error rate under the null model after the introduction of differential genotyping errors. Also, we find that as little as 10 to 15% of double-sampled genotype data is needed to achieve this effect. Aside from a few situations (particularly recessive mode of inheritance simulations) the LRT(D)A(M)E version that calculates p values through permutation requires 15 to 20% double sampling to maintain an 80% power for a 0.05 significance level and approximately 20% double sampling for a 0.01 significance level.

Increase of rejection rate in case-control studies with the differential genotyping error rates.

Genotyping error adversely affects the statistical power of case-control association studies and introduces bias in the estimated parameters when the same error mechanism and probabilities apply to both affected and unaffected individuals; that is, when there is non-differential genotype misclassification. Simulation studies have shown that differential genotype misclassification leads to a rejection rate that is higher than the nominal significance level (type I error rate) for some tests of association. This study extends previous work by examining this issue analytically using the non-centrality parameter of the asymptotic distribution of the chi-squared test and linear trend test (LTT) when there is no difference between case and control genotype frequencies, but there is differential misclassification with SNP data. The parameters examined are the minor allele frequency (MAF) and sample size. When MAF is less than 0.2, differential genotyping errors lead to a rejection rate much larger than the nominal significance level. As the MAF decreases to zero, the increase in the rejection rate becomes larger. The errors that most increase the rejection rate are differential recording of the more common homozygote as the other homozygote and differential recording of the more common homozygote as the heterozygote. The rejection rate increases as the sample size increases for fixed differential genotyping error rates and nominal significance level for each test.

Transmission disequilibrium test power and sample size in the presence of locus heterogeneity.

Locus heterogeneity is one of the most important issues in gene mapping and can cause significant reductions in statistical power for gene mapping, yet no research to date has provided power and sample size calculations for family-based association methods in the presence of locus heterogeneity. The purpose of this research is three-fold: (i) to provide an analytic solution to the incorporation of locus heterogeneity into power and sample size calculations for the TDT statistic; (ii) to verify our analytic solution with simulations; and (iii) to study how different factors affect sample size requirement for the TDT in the presence of locus heterogeneity. The detection of association in the presence of locus heterogeneity requires a greater sample size than in its absence. This increase is independent of the prevalence of the disease. In addition, as the proportion of families unlinked to the disease locus increases, the sample size necessary to maintain constant power increases. Finally, as the effect size of the disease locus increases, the sample size necessary to detect association decreases in the presence of locus heterogeneity. We provide freely available software that can perform these calculations.