Michael P. Epstein

Association of FKBP5 Polymorphisms and Childhood Abuse With Risk of Posttraumatic Stress Disorder Symptoms in Adults

CONTEXT In addition to trauma exposure, other factors contribute to risk for development of posttraumatic stress disorder (PTSD) in adulthood. Both genetic and environmental factors are contributory, with child abuse providing significant risk liability. OBJECTIVE To increase understanding of genetic and environmental risk factors as well as their interaction in the development of PTSD by gene x environment interactions of child abuse, level of non-child abuse trauma exposure, and genetic polymorphisms at the stress-related gene FKBP5. DESIGN, SETTING, AND PARTICIPANTS A cross-sectional study examining genetic and psychological risk factors in 900 nonpsychiatric clinic patients (762 included for all genotype studies) with significant levels of childhood abuse as well as non-child abuse trauma using a verbally presented survey combined with single-nucleotide polymorphism (SNP) genotyping. Participants were primarily urban, low-income, black (>95%) men and women seeking care in the general medical care and obstetrics-gynecology clinics of an urban public hospital in Atlanta, Georgia, between 2005 and 2007. MAIN OUTCOME MEASURES Severity of adult PTSD symptomatology, measured with the modified PTSD Symptom Scale, non-child abuse (primarily adult) trauma exposure and child abuse measured using the traumatic events inventory and 8 SNPs spanning the FKBP5 locus. RESULTS Level of child abuse and non-child abuse trauma each separately predicted level of adult PTSD symptomatology (mean [SD], PTSD Symptom Scale for no child abuse, 8.03 [10.48] vs > or =2 types of abuse, 20.93 [14.32]; and for no non-child abuse trauma, 3.58 [6.27] vs > or =4 types, 16.74 [12.90]; P < .001). Although FKBP5 SNPs did not directly predict PTSD symptom outcome or interact with level of non-child abuse trauma to predict PTSD symptom severity, 4 SNPs in the FKBP5 locus significantly interacted (rs9296158, rs3800373, rs1360780, and rs9470080; minimum P = .0004) with the severity of child abuse to predict level of adult PTSD symptoms after correcting for multiple testing. This gene x environment interaction remained significant when controlling for depression severity scores, age, sex, levels of non-child abuse trauma exposure, and genetic ancestry. This genetic interaction was also paralleled by FKBP5 genotype-dependent and PTSD-dependent effects on glucocorticoid receptor sensitivity, measured by the dexamethasone suppression test. CONCLUSIONS Four SNPs of the FKBP5 gene interacted with severity of child abuse as a predictor of adult PTSD symptoms. There were no main effects of the SNPs on PTSD symptoms and no significant genetic interactions with level of non-child abuse trauma as predictor of adult PTSD symptoms, suggesting a potential gene-childhood environment interaction for adult PTSD.

De novo mutations in epileptic encephalopathies

Epileptic encephalopathies are a devastating group of severe childhood epilepsy disorders for which the cause is often unknown. Here we report a screen for de novo mutations in patients with two classical epileptic encephalopathies: infantile spasms (n = 149) and Lennox–Gastaut syndrome (n = 115). We sequenced the exomes of 264 probands, and their parents, and confirmed 329 de novo mutations. A likelihood analysis showed a significant excess of de novo mutations in the ∼4,000 genes that are the most intolerant to functional genetic variation in the human population (P = 2.9 × 10−3). Among these are GABRB3, with de novo mutations in four patients, and ALG13, with the same de novo mutation in two patients; both genes show clear statistical evidence of association with epileptic encephalopathy. Given the relevant site-specific mutation rates, the probabilities of these outcomes occurring by chance are P = 4.1 × 10−10 and P = 7.8 × 10−12, respectively. Other genes with de novo mutations in this cohort include CACNA1A, CHD2, FLNA, GABRA1, GRIN1, GRIN2B, HNRNPU, IQSEC2, MTOR and NEDD4L. Finally, we show that the de novo mutations observed are enriched in specific gene sets including genes regulated by the fragile X protein (P < 10−8), as has been reported previously for autism spectrum disorders.

Influence of child abuse on adult depression: Moderation by the corticotropin-releasing hormone receptor gene

CONTEXT Genetic inheritance and developmental life stress both contribute to major depressive disorder in adults. Child abuse and trauma alter the endogenous stress response, principally corticotropin-releasing hormone and its downstream effectors, suggesting that a gene x environment interaction at this locus may be important in depression. OBJECTIVE To examine whether the effects of child abuse on adult depressive symptoms are moderated by genetic polymorphisms within the corticotropin-releasing hormone type 1 receptor (CRHR1) gene. DESIGN Association study examining gene x environment interactions between genetic polymorphisms at the CRHR1 locus and measures of child abuse on adult depressive symptoms. SETTING General medical clinics of a large, public, urban hospital and Emory University, Atlanta, Georgia. PARTICIPANTS The primary participant population was 97.4% African American, of low socioeconomic status, and with high rates of lifetime trauma (n = 422). A supportive independent sample (n = 199) was distinct both ethnically (87.7% Caucasian) and socioeconomically (less impoverished). MAIN OUTCOME MEASURES Beck Depression Inventory scores and history of major depressive disorder by the Structured Clinical Interview for DSM-IV Axis I Disorders. RESULTS Fifteen single-nucleotide polymorphisms spanning 57 kilobases of the CRHR1 gene were examined. We found significant gene x environment interactions with multiple individual single-nucleotide polymorphisms (eg, rs110402, P = .008) as well as with a common haplotype spanning intron 1 (P < .001). Specific CRHR1 polymorphisms appeared to moderate the effect of child abuse on the risk for adult depressive symptoms. These protective effects were supported with similar findings in a second independent sample (n = 199). CONCLUSIONS These data support the corticotropin-releasing hormone hypothesis of depression and suggest that a gene x environment interaction is important for the expression of depressive symptoms in adults with CRHR1 risk or protective alleles who have a history of child abuse.

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.

Inference on Haplotype Effects in Case-Control Studies Using Unphased Genotype Data

A variety of statistical methods exist for detecting haplotype-disease association through use of genetic data from a case-control study. Since such data often consist of unphased genotypes (resulting in haplotype ambiguity), such statistical methods typically apply the expectation-maximization (EM) algorithm for inference. However, the majority of these methods fail to perform inference on the effect of particular haplotypes or haplotype features on disease risk. Since such inference is valuable, we develop a retrospective likelihood for estimating and testing the effects of specific features of single-nucleotide polymorphism (SNP)-based haplotypes on disease risk using unphased genotype data from a case-control study. Our proposed method has a flexible structure that allows, among other choices, modeling of multiplicative, dominant, and recessive effects of specific haplotype features on disease risk. In addition, our method relaxes the requirement of Hardy-Weinberg equilibrium of haplotype frequencies in case subjects, which is typically required of EM-based haplotype methods. Also, our method easily accommodates missing SNP information. Finally, our method allows for asymptotic, permutation-based, or bootstrap inference. We apply our method to case-control SNP genotype data from the Finland-United States Investigation of Non-Insulin-Dependent Diabetes Mellitus (FUSION) Genetics study and identify two haplotypes that appear to be significantly associated with type 2 diabetes. Using the FUSION data, we assess the accuracy of asymptotic P values by comparing them with P values obtained from a permutation procedure. We also assess the accuracy of asymptotic confidence intervals for relative-risk parameters for haplotype effects, by a simulation study based on the FUSION data.

Fragile X mental retardation protein deficiency leads to excessive mGluR5-dependent internalization of AMPA receptors.

Fragile X syndrome (FXS), a common inherited form of mental retardation, is caused by the functional absence of the fragile X mental retardation protein (FMRP), an RNA-binding protein that regulates the translation of specific mRNAs at synapses. Altered synaptic plasticity has been described in a mouse FXS model. However, the mechanism by which the loss of FMRP alters synaptic function, and subsequently causes the mental impairment, is unknown. Here, in cultured hippocampal neurons, we used siRNAs against Fmr1 to demonstrate that a reduction of FMRP in dendrites leads to an increase in internalization of the α-amino-3-hydroxy-5-methyl-4-isoxazole propionic acid receptor (AMPAR) subunit, GluR1, in dendrites. This abnormal AMPAR trafficking was caused by spontaneous action potential-driven network activity without synaptic stimulation by an exogenous agonist and was rescued by 2-methyl-6-phenylethynyl-pyridine (MPEP), an mGluR5-specific inverse agonist. Because AMPAR internalization depends on local protein synthesis after mGluR5 stimulation, FMRP, a negative regulator of translation, may be viewed as a counterbalancing signal, wherein the absence of FMRP leads to an apparent excess of mGluR5 signaling in dendrites. Because AMPAR trafficking is a driving process for synaptic plasticity underlying learning and memory, our data suggest that hypersensitive AMPAR internalization in response to excess mGluR signaling may represent a principal cellular defect in FXS, which may be corrected by using mGluR antagonists.

A Powerful and Flexible Multilocus Association Test for Quantitative Traits

Association mapping of complex traits typically employs tagSNP genotype data to identify a trait locus within a region of interest. However, considerable debate exists regarding the most powerful strategy for utilizing such tagSNP data for inference. A popular approach tests each tagSNP within the region individually, but such tests could lose power as a result of incomplete linkage disequilibrium between the genotyped tagSNP and the trait locus. Alternatively, one can jointly test all tagSNPs simultaneously within the region (by using genotypes or haplotypes), but such multivariate tests have large degrees of freedom that can also compromise power. Here, we consider a semiparametric model for quantitative-trait mapping that uses genetic information from multiple tagSNPs simultaneously in analysis but produces a test statistic with reduced degrees of freedom compared to existing multivariate approaches. We fit this model by using a dimension-reducing technique called least-squares kernel machines, which we show is identical to analysis using a specific linear mixed model (which we can fit by using standard software packages like SAS and R). Using simulated SNP data based on real data from the International HapMap Project, we demonstrate that our approach often has superior performance for association mapping of quantitative traits compared to the popular approach of single-tagSNP testing. Our approach is also flexible, because it allows easy modeling of covariates and, if interest exists, high-dimensional interactions among tagSNPs and environmental predictors.

Mutations in TCF8 Cause Posterior Polymorphous Corneal Dystrophy and Ectopic Expression of COL4A3 by Corneal Endothelial Cells

Posterior polymorphous corneal dystrophy (PPCD, also known as PPMD) is a rare disease involving metaplasia and overgrowth of corneal endothelial cells. In patients with PPCD, these cells manifest in an epithelial morphology and gene expression pattern, produce an aberrant basement membrane, and, sometimes, spread over the iris and nearby structures in a way that increases the risk for glaucoma. We previously mapped PPCD to a region (PPCD3) on chromosome 10 containing the gene that encodes the two-handed zinc-finger homeodomain transcription factor TCF8. Here, we report a heterozygous frameshift mutation in TCF8 that segregates with PPCD in the family used to map PPCD3 and four different heterozygous nonsense and frameshift mutations in TCF8 in four other PPCD probands. Family reports of inguinal hernia, hydrocele, and possible bone anomalies in affected individuals suggest that individuals with TCF8 mutations should be examined for nonocular anomalies. We detect transcripts of all three identified PPCD genes (VSX1, COL8A2, and TCF8) in the cornea. We show presence of a complex (core plus secondary) binding site for TCF8 in the promoter of Alport syndrome gene COL4A3, which encodes collagen type IV alpha 3, and we present immunohistochemical evidence of ectopic expression of COL4A3 in corneal endothelium of the proband of the original PPCD3 family. Identification of TCF8 as the PPCD3 gene provides a valuable tool for the study of critical gene regulation events in PPCD pathology and suggests a possible role for TCF8 mutations in altered structure and function of cells lining body cavities other than the anterior chamber of the eye. Thus, this study has identified TCF8 as the gene responsible for approximately half of the cases of PPCD, has implicated TCF8 mutations in developmental abnormalities outside the eye, and has presented the TCF8 regulatory target, COL4A3, as a key, shared molecular component of two different diseases, PPCD and Alport syndrome.

A Simple and Improved Correction for Population Stratification in Case-Control Studies

Population stratification remains an important issue in case-control studies of disease-marker association, even within populations considered to be genetically homogeneous. Campbell et al. (Nature Genetics 2005;37:868-872) illustrated this by showing that stratification induced a spurious association between the lactase gene (LCT) and tall/short status in a European American sample. Furthermore, existing approaches for controlling stratification by use of substructure-informative loci (e.g., genomic control, structured association, and principal components) could not resolve this confounding. To address this problem, we propose a simple two-step procedure. In the first step, we model the odds of disease, given data on substructure-informative loci (excluding the test locus). For each participant, we use this model to calculate a stratification score, which is that participants estimated odds of disease calculated using his or her substructure-informative-loci data in the disease-odds model. In the second step, we assign subjects to strata defined by stratification score and then test for association between the disease and the test locus within these strata. The resulting association test is valid even in the presence of population stratification. Our approach is computationally simple and less model dependent than are existing approaches for controlling stratification. To illustrate these properties, we apply our approach to the data from Campbell et al. and find no association between the LCT locus and tall/short status. Using simulated data, we show that our approach yields a more appropriate correction for stratification than does principal components or genomic control.

Heterozygous mutations of the voltage-gated sodium channel SCN8A are associated with spike-wave discharges and absence epilepsy in mice

In a chemical mutagenesis screen, we identified the novel Scn8a8J allele of the gene encoding the neuronal voltage-gated sodium channel Nav1.6. The missense mutation V929F in this allele alters an evolutionarily conserved residue in the pore loop of domain 2 of Nav1.6. Electroencephalography (EEG) revealed well-defined spike-wave discharges (SWD), the hallmark of absence epilepsy, in Scn8a8J heterozygotes and in heterozygotes for two classical Scn8a alleles, Scn8amed (null) and Scn8amed-jo (missense). Mouse strain background had a significant effect on SWD, with mutants on the C3HeB/FeJ strain showing a higher incidence than on C57BL/6J. The abnormal EEG patterns in heterozygous mutant mice and the influence of genetic background on SWD make SCN8A an attractive candidate gene for common human absence epilepsy, a genetically complex disorder.