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Joseph A Boscarino1,2, Porat M Erlich1,3, Stuart N Hoffman4, Xiaopeng Zhang51Center for Health Research, Geisinger Clinic, Danville, PA, 2Department of Psychiatry, 3Department of Medicine, Temple University School of Medicine, Philadelphia, PA, 4Department of Neurology, 5Department of Anesthesiology, Geisinger Clinic, Danville, PA, USAObjective: The study aim was to assess the cumulative burden of polymorphisms located within four genetic loci previously associated with posttraumatic stress disorder (PTSD) among outpatients at risk for PTSD.Methods: Diagnostic interviews were completed and DNA samples collected among 412 pain patients to determine if FKBP5 (rs9470080), COMT (rs4680), CHRNA5 (rs16969968), and CRHR1 (rs110402) single nucleotide polymorphisms were cumulatively associated with increased risk for PTSD.Results: In bivariate analyses, it was found that a count of specific PTSD risk alleles located within FKBP5, COMT, CHRNA5, and CRHR1 genetic loci (allele range = 0–6, mean count = 2.92, standard deviation = 1.36) was associated with lifetime (t [409] = 3.430, P = 0.001) and early onset PTSD (t [409] = 4.239, P = 0.000028). In logistic regression, controlling for demographic factors, personality traits, and trauma exposures, this risk allele count remained associated with both lifetime (odds ratio = 1.49, P = 0.00158) and early onset PTSD (odds ratio = 2.36, P = 0.000093). Interaction effects were also detected, whereby individuals with higher risk allele counts and higher trauma exposures had an increased risk of lifetime PTSD (allele count × high trauma, P = 0.026) and early onset PTSD (allele count × high trauma, P = 0.016) in these logistic regressions. Those with no or few risk alleles appeared resilient to PTSD, regardless of exposure history.Conclusion: A cumulative risk allele count involving four single nucleotide polymorphisms located within the FKBP5, COMT, CHRNA5, and CRHR1 genes are associated with PTSD. Level of trauma exposure interacts with risk allele count, such that PTSD is increased in those with higher risk allele counts and higher trauma exposures. Since the single nucleotide polymorphisms studied encompass stress circuitry and addiction biology, these findings may have implications for neuropsychiatric research and treatment.Keywords: posttraumatic stress disorder, genetic association study, single nucleotide polymorphism, risk alleles, trauma exposure, neuroticism, childhood adversity

Aims Ourstudysoughttoassesstheprevalenceof andriskfactorsforopioiddrugdependenceamongout-patientson long-term opioid therapy in a large health-care system. Methods Using electronic health records, we identified out-patients receiving 4+ physician orders for opioid therapy in the past 12 months for non-cancer pain within a large US health-care system. We completed diagnostic interviews with 705 of these patients to identify opioid use disorders and assess risk factors. Results Preliminary analyses suggested that current opioid dependence might be as high as 26% (95% confidence interval (CI) = 22.0-29.9) among the patients studied. Logistic regressions indicated that current dependence was associated with variables often in the medical record, including age

Previous studies suggested that low total cholesterol was associated with external mortality, including deaths from suicide, homicide, and accidents. However, this reported association was potentially confounded, since cholesterol was also reported to be associated with alcohol abuse, anti-social personality disorder, and other risk factors for external mortality.We examined external-cause mortality among a national sample of 4462 male, US veterans at baseline in 1985. Using Cox regressions to estimate survival time, we assessed the impact of low baseline total cholesterolor =165 mg/dl, age, race, intelligence, BMI, alcohol abuse, anti-social personality disorder, depression, and other factors at follow-up. Study follow-up continued until December 31, 2000. A total of 55 external mortalities occurred during this approximately 16-year period.Multivariate Cox regressions predicting external-cause mortality suggested that three predictor variables were significant: low total cholesterol, morbid depression, and anti-social personality disorder, with hazard ratios (HRs) of 1.97 (p=0.046), 1.76 (p=0.043), and 2.22 (p=0.006), respectively. In addition, a significant interaction was detected for low cholesterol x morbid depression (p0.005), whereby those with both at baseline were approximately 7 times more likely to die from external mortality (HR=6.5, 95% CI=3.07-13.76).Among a national random sample of community-based men, lower baseline cholesterol predicted external mortality and revealed an interaction with morbid depression. Patients presenting with low cholesterol and morbid depression in clinical practice may warrant clinical attention and surveillance.

Magnetic resonance imaging (MRI) traits can serve as more specific measures of degenerative or cerebrovascular brain injury than can be ascertained through personal history, risk factors, clinical signs, or symptoms. They are potentially useful intermediate phenotypes for genetic studies of Alzheimer disease (AD). Recent studies have estimated heritability of white matter hyperintensity (WMH) among cognitively normal family members to be between 0.55 and 0.73. Persons discordant for AD are expected to have substantially different MRI phenotype distributions; our goal was to determine whether MRI traits in siblings discordant for AD are heritable. We measured cerebral atrophy, medial temporal atrophy (MTA), WMH, and a rating of cerebrovascular disease (CVR) via MRI in 815 participants from 424 families of the Multi-Institutional Research in Alzheimer's Genetic Epidemiology Study. Residual heritability after adjustment for covariates ranged from 0.17 (P = 0.009) for MTA to 0.57 (P = 10- 7 ) for CVR. The number of APOE-s4 alleles was significantly associated with WMH (P = 0.01) and CVR (P = 0.005) but not cerebral atrophy (P = 0.25) or MTA (P = 0.83). Heritability remained significant and high after adjusting for APOE genotype, suggesting that a substantial proportion of the additive genetic variation in these MRI traits is explained by other genes. In the Multi-Institutional Research in Alzheimer's Genetic Epidemiology Study of AD-discordant siblings, MRI traits are heritable and are potential endophenotypes for genetic association studies.

Paraoxonase is an arylesterase enzyme that is expressed in the liver and found in the circulation in association with apoA1 and the high-density lipoprotein, and prevents the accumulation of oxidized lipids in low-density lipoproteins in vitro. Common polymorphisms in genes encoding paraoxonase are established risk factors in a variety of vascular disorders including coronary artery disease and carotid artery stenosis, but their association with Alzheimer disease (AD) is controversial. We tested the association of 29 SNPs in PON1, PON2 and PON3 with AD in 730 Caucasian and 467 African American participants of the MIRAGE Study, an ongoing multi-center family-based genetic epidemiology study of AD. Eight SNPs were associated with AD in the African American families (0.0001< or =P< or =0.04) and two SNPs were associated with AD in Caucasian families (0.01< or =P< or =0.04). Of note, the pattern of association for the PON1 promoter SNP -161[C/T] was the same in both ethnic groups (P=0.006). Haplotype analysis using sliding windows revealed 11 contiguous SNP combinations spanning the three PON genes with significant global test scores (0.006< or =P< or =0.04) in the two ethnic groups combined. The most significantly associated haplotype comprised SNPs in the region spanning the -161[C/T] SNP (P=0.00009). Our results demonstrate association between AD and variants in the PON gene cluster in Caucasians and African Americans.

Human chromosome 17q has been implicated to contain a gene that influences hypertension susceptibility. This region contains the WNK4 gene that causes the mendelian disorder pseudohypoaldosteronism type II, characterized by high potassium levels and hypertension. The goal of this study was to identify genetic variants in all exons of WNK4 in hypertensive individuals and to examine the association of these variants with essential hypertension. Single-nucleotide polymorphims (SNPs) were identified by sequencing the entire coding region in 32 whites and 32 African Americans with hypertension. A single SNP in whites and 8 SNPs in African Americans were genotyped in a larger cohort of whites (165 hypertensives; 91 normotensives) and African Americans (120 hypertensives; 98 normotensives). The frequency of the rare allele differed significantly between hypertensive whites (13.0%) and normotensive whites (7.1%, P =0.040) for the single intronic SNP (bp 1 156 666). This difference remained significant after adjusting for body mass index and sex ( P =0.035). Genotypic frequencies differed significantly between hypertensive and normotensive individuals when a dominant model either with ( P =0.027) or without ( P =0.028) covariate adjustment was assumed. The odds ratio for hypertension was 2.28 for AA or AG individuals vs those with the GG genotype (95% confidence interval, 1.09 to 4.75). No significant differences in allelic or genotypic frequencies were observed in African Americans for any SNPs. The finding in whites is consistent with the hypothesis that polymorphisms in WNK4 influence the risk of hypertension. However, because the associated SNP does not appear to be a functional variant and the limitations of case/control association studies, confirmation of these results in additional cohorts is warranted.

Emerging biomarkers for acute myocardial infarction (AMI) may enhance conventional risk-prediction algorithms if they are informative and associated with risk independently of established predictors. In this study, we constructed a cohort for testing emerging biomarkers for AMI in managed-care populations using existing biospecimen repositories linked to electronic health records (EHR).Electronic health record-based biorepositories collected by healthcare systems can be federated to provide large, methodologically sound testing sets for biomarker validation.Subjects ages 40 to 80 years were selected from 2 existing population-based biospecimen repositories. Incident AMI status and covariates were ascertained from the EHR. An ad hoc model for AMI risk was parameterized and validated. Simulation was used to test incremental gains in performance due to the inclusion of biomarkers in this model. Gains in performance were assessed in terms of area under the receiver operating characteristic curve (ROC-AUC) and case reclassification.A total of 18 329 individuals (57% female) contributed 108 400 person-years of EHR follow-up. The crude AMI incidence was 10.8 and 5.0 per 1000 person-years among males and females, respectively. Compared with the model with risk factors alone, inclusion of a simulated biomarker yielded substantial gains in sensitivity without loss of specificity. Furthermore, a net ROC-AUC gain of 13.3% was observed, as well as correct reclassification of 9.8% of incident cases (79 of 806) that were otherwise not considered statin-indicated at baseline under the National Cholesterol Education Program Adult Treatment Panel III criteria.More research is needed to assess incremental contribution of emerging biomarkers for AMI prediction in managed-care populations.

Objective Posttraumatic stress disorder (PTSD) is associated with altered neuropsychological function, possibly including complex visual information processing. Grapheme-color synesthesia refers to the phenomenon that a particular letter or number elicits the visual perception of a specific color. The study objective was to assess if grapheme-color synesthesia was associated with PTSD among US veterans. Method We surveyed 700 veterans who were outpatients in a multihospital system in Pennsylvania. All veterans had served at least one warzone deployment. PTSD and grapheme-color synesthesia were assessed using validated research instruments. Results The mean age of veterans was 59 years, and 96% were men. The prevalence of current PTSD was 7% (95% confidence interval [CI] = 5.1-8.8), and current partial PTSD was 11% (95% CI = 9.3-14.0). The prevalence of current depression was 6% (95% CI = 4.7-8.3). Altogether, 6% (95% CI = 4.8-8.5) of veterans screened positive for grapheme-color synesthesia. Bivariate analyses suggested that grapheme-color synesthesia was associated with current PTSD (odds ratio [OR] = 3.4, p = .004) and current partial PTSD (OR = 2.4, p = .013), but not current depression (OR = 1.1, p = .91). Multivariate logistic regression results, adjusting for age, sex, marital status, level of education, current psychotropic medication use, and concussion history, confirmed these results. Conclusions Grapheme-color synesthesia seems to be associated with PTSD among veterans who had been deployed. This finding may have implications for PTSD diagnostic screening and treatment. Research is recommended to confirm this finding and to determine if synesthesia is a risk indicator for PTSD among nonveterans.

The authors estimated the prevalence of lifetime prescription opioid-use disorder among outpatients on opioid therapy using criteria from both versions 4 and 5 of the Diagnostic and Statistical Manual of Mental Disorders (DSM). Using electronic records from a large health care system, a random sample of outpatients undergoing long-term opioid therapy for non-cancer pain was identified and 705 participants completed diagnostic interviews. The prevalence of lifetime DSM-5 opioid-use disorder among these patients was 34.9% (95% confidence interval [CI] = 30.5?39.5), similar to the prevalence of DSM-4 opioid dependence (35.5%, 95% CI = 31.1?40.2). The Kappa value between DSM-5 and DSM-4 criteria was high (Kappa = 0.873, p < 0.0001). Logistic regressions suggested DSM-5 opioid-use disorder was associated with age younger than 65 (odds ratio [OR] = 2.25, p = 0.009), history of opioid abuse (OR = 4.94, p < 0.001), higher opioid withdrawal symptoms (OR = 3.01, p = 0.008), and history of substance abuse treatment (OR = 1.62, p = 0.015), similar to DSM-4. Based on DSM-5, 21.7% of patients met criteria for moderate and 13.2% for severe opioid-use disorder, respectively. Given the changes proposed, the finding that the prevalence of and risk factors for DSM-5 opioid-use disorders were similar to DSM-4 were unexpected. Further research is advised.

To the Editor: Several genetic components for posttraumatic stress disorder (PTSD) have been identified, including biologic pathways involving the hypothalamic–pituitary–adrenocortical, locus coeruleus/noradrenergic, and the limbic systems (Broekman, et al., 2007; Koenen, 2007; Rauch and Drevets, 2009). In our IRB-approved study, lifetime PTSD was assessed among adult outpatients with chronic, non-malignant pain, a condition commonly associated with PTSD (McFarlane, 2010). We assessed PTSD with an instrument widely used in previous epidemiologic studies (Boscarino et al., 2010). We examined genetic markers using a multivariate design that assessed single nucleotide polymorphisms (SNPs) located within the FK506 binding protein-5 (FKBP5), catechol-O-methyltransferase (COMT), and cholinergic receptor nicotinic alpha3/alpha-5 (CHRNA3/CHRNA5) gene clusters. SNPs were selected using agnostic LD tagging with consideration of prior evidence and functional annotation (Erlich, et al., 2010). The COMT gene is associated with anxiety disorders, psychosis, depression, and other conditions involving catecholamine pathway regulation (Craddock, et al., 2006; Montag et al., 2008). This gene is also associated with PTSD (Kolassa et al., 2010). The FKBP5 gene regulates glucocorticoid receptor sensitivity, is functionally involved in HPA stress axis activity, and is associated with PTSD (Binder, 2009; Gillespie, et al., 2009). The CHRNA3/5 gene cluster, which encodes components of the nicotinic acetylcholine receptor, is associated with nicotine dependence, smoking, and other substance misuse (Erlich, et al., 2010). PTSD is also associated with cigarette smoking and substance use (Boscarino et al., 2006; Fu et al., 2007). Using trained interviewers and following informed consent, we completed diagnostic interviews with 502 subjects and collected DNA to determine if FKBP5, COMT, and CHRNA3/5 SNPs were associated with PTSD (mean age = 55, S.D. = 13.4; PTSD = 15%, 95% CI = 11.7–18.1%). Non-Caucasian patients were excluded from this analysis. Genotyping was performed on an Applied BioSystems 7500 real-time PCR platform, using TaqMan kits. Using multivariate logistic regressions that included demographic (age, gender, income, education, and marital status) and environmental (trauma exposure, childhood adversity, and neuroticism) variables, 3 of 9 SNPs examined were associated with PTSD (p

Our study sought to assess the prevalence of and risk factors for opioid drug dependence among out-patients on long-term opioid therapy in a large health-care system.Using electronic health records, we identified out-patients receiving 4+ physician orders for opioid therapy in the past 12 months for non-cancer pain within a large US health-care system. We completed diagnostic interviews with 705 of these patients to identify opioid use disorders and assess risk factors.Preliminary analyses suggested that current opioid dependence might be as high as 26% [95% confidence interval (CI) = 22.0-29.9] among the patients studied. Logistic regressions indicated that current dependence was associated with variables often in the medical record, including age65 [odds ratio (OR) = 2.33, P = 0.001], opioid abuse history (OR = 3.81, P0.001), high dependence severity (OR = 1.85, P = 0.001), major depression (OR = 1.29, P = 0.022) and psychotropic medication use (OR = 1.73, P = 0.006). Four variables combined (age, depression, psychotropic medications and pain impairment) predicted increased risk for current dependence, compared to those without these factors (OR = 8.01, P0.001). Knowing that the patient also had a history of severe dependence and opioid abuse increased this risk substantially (OR = 56.36, P0.001).Opioid misuse and dependence among prescription opioid patients in the United States may be higher than expected. A small number of factors, many documented in the medical record, predicted opioid dependence among the out-patients studied. These preliminary findings should be useful in future research efforts.

A locus on chromosome 15q25.1 previously implicated in nicotine, alcohol, and cocaine dependence, smoking, and lung cancer encodes subunits of the nicotinic acetylcholine receptor (nAChR) expressed in the mesolimbic system and thought to mediate substance dependence. Opioid dependence severity (ODS), nicotine dependence severity (NDS), smoking status and quantity, and the number of attempts to quit were assessed using questionnaire instruments in 505 subjects who were prescribed opioid medications for chronic pain in outpatient practice sites. Multivariate regression was used to test for genetic association of these phenotypes with 5 SNPs in the nAChR gene cluster on chromosome 15q25.1, adjusting for background variables. A coding variant in CHRNA5 (rs16969968[A]) was significantly associated with 1.4-unit higher ODS (p < 0.00017). A variant in the 3′ untranslated region of CHRNA3 (rs660652[G]) was significantly associated with 1.7-fold higher odds of lifetime smoking (p < 0.0092), 1.1-unit higher NDS (p < 0.0007), 0.7 more pack-years of cigarette smoking (p < 0.0038), and 0.8 more lifetime attempts to quit (p < 0.0084). Our data suggest an association of DNA variants in the nAChR gene cluster on chromosome 15q25.1 with ODS, as well as NDS and related smoking phenotypes. While the association of this locus with NDS and smoking phenotypes is well known, the association with ODS, a dimension of opioid substance dependence, is novel and requires verification in independent studies.

Background: Research on the genetics of opioid addiction among illicit drug users is difficult given challenges to case ascertainment and selection of an appropriate control group. To address this limitation, we tested a model by studying prescription opioid users. Methods: We undertook a case-control, candidate-gene study of opioid-dependent users and nondependent users among Geisinger Clinic outpatients. Electronic health record (EHR) data were reviewed for patients who were prescribed opioids. Patients were selected for a phone interview if they had five or more prescription orders for opioids in the prior 12 months for non-cancer pain. Cases were identified based on the Diagnostic and Statistical Manual of Mental Disorder, Version IV (DSM-IV) criteria for opioid dependence. A modified Composite International Diagnostic Interview (CIDI) was used to obtain data on dependence status and history. Data were also gathered on detailed drug, psychological, and environmental exposures. Altogether, 703 patients completed the CIDI; 512 of these patients (73%) provided DNA for genotyping and completed the NEO Five-factor Personality Inventory. Findings: Altogether 37.4% (95% CI = 33.8–41.1) of patients met DSM-IV criteria for lifetime opioid dependence and 30.7% (95% CI = 27.3–34.3) met criteria for current dependence. Significant predictors of opioid dependence included younger age, unemployment, psychotropic medication use, as well as history of PTSD, anxiety, depression, alcohol abuse, anti-social personality, illicit drug use, trauma exposure, and substance abuse treatment (all P-values < 0.001). Preliminary Genetic analyses suggested that opioid dependence was associated with dopamine receptors D2 and D3 and the COMT genes. Gene by environment (G x E) interactions were also detected related to opioid dependence and exposure to mental trauma. Conclusion: The prevalence of drug dependence is high among pain patients on long-term opioid therapy in the outpatient setting. This disorder is associated with a history of other mental health conditions, employment status, psychotropic medication use, illicit drug use, and exposure to mental trauma. Genetic analyses suggested associations with genes related to neurocognitive processes associated with impulse control and reward regulation. Several G x E interactions were also detected.

Magnetic resonance imaging (MRI) can aid clinical assessment of brain changes potentially correlated with Alzheimer disease (AD). MRI traits may improve our ability to identify genes associated with AD-outcomes. We evaluated semi-quantitative MRI measures as endophenotypes for genetic studies by assessing their association with AD in families from the Multi-Institutional Research in Alzheimer Genetic Epidemiology (MIRAGE) Study.Discordant siblings from multiple ethnicities were ascertained through a single affected proband. Semi-quantitative MRI measures were obtained for each individual. The association between continuous/ordinal MRI traits and AD were analyzed using generalized estimating equations. Medical history and Apolipoprotein E (APOE)epsilon4 status were evaluated as potential confounders.Comparisons of 214 affected and 234 unaffected subjects from 229 sibships revealed that general cerebral atrophy, white matter hyperintensities (WMH), and mediotemporal atrophy differed significantly between groups (each at P.0001) and varied by ethnicity. Age at MRI and duration of AD confounded all associations between AD and MRI traits. Among unaffected sibs, the presence of at least one APOEepsilon4 allele and MRI infarction was associated with more WMH after adjusting for age at MRI.The strong association between MRI traits and AD suggests that MRI traits may be informative endophenotypes for basic and clinical studies of AD. In particular, WMH may be a marker of vascular disease that contributes to AD pathogenesis.

Joseph A Boscarino,1,2 H Lester Kirchner,3,4 Stuart N Hoffman,5 Porat M Erlich1,4 1Center for Health Research, Geisinger Clinic, Danville, 2Department of Psychiatry, Temple University School of Medicine, Philadelphia, 3Division of Medicine, Geisinger Clinic, Danville, 4Department of Medicine, Temple University School of Medicine, Philadelphia, 5Department of Neurology, Geisinger Clinic, Danville, PA, USA Background: We previously developed a post-traumatic stress disorder (PTSD) screening instrument, ie, the New York PTSD Risk Score (NYPRS), that was effective in predicting PTSD. In the present study, we assessed a version of this risk score that also included genetic information. Methods: Utilizing diagnostic testing methods, we hierarchically examined different prediction variables identified in previous NYPRS research, including genetic risk-allele information, to assess lifetime and current PTSD status among a population of trauma-exposed adults. Results: We found that, in predicting lifetime PTSD, the area under the receiver operating characteristic curve (AUC) for the Primary Care PTSD Screen alone was 0.865. When we added psychosocial predictors from the original NYPRS to the model, including depression, sleep disturbance, and a measure of health care access, the AUC increased to 0.902, which was a significant improvement (P = 0.0021). When genetic information was added in the form of a count of PTSD risk alleles located within FKBP, COMT, CHRNA5, and CRHR1 genetic loci (coded 0–6), the AUC increased to 0.920, which was also a significant improvement (P = 0.0178). The results for current PTSD were similar. In the final model for current PTSD with the psychosocial risk factors included, genotype resulted in a prediction weight of 17 for each risk allele present, indicating that a person with six risk alleles or more would receive a PTSD risk score of 17 × 6 = 102, the highest risk score for any of the predictors studied. Conclusion: Genetic information added to the NYPRS helped improve the accuracy of prediction results for a screening instrument that already had high AUC test results. This improvement was achieved by increasing PTSD prediction specificity. Further research validation is advised. Keywords: post-traumatic stress disorder, psychological trauma, diagnostic screening, test development, genotype, single nucleotide polymorphism

Previous studies have shown association of single nucleotide polymorphisms (SNPs) in three contiguous genes (PON1, PON2 and PON3) encoding paraoxonase with risk of Alzheimer disease (AD). We evaluated the association of serum paraoxonase activity measured by phenyl acetate (PA) and thiobutyl butyrolactone (TBBL) with risk of AD and with 26 SNPs spanning the PON gene cluster in 266 AD cases and 306 sibling controls from the MIRAGE Study. The odds of AD (adjusted for age, gender and ethnicity) increased 20% for each standard deviation decrease in PA or TBBL activity. There were association signals with activity in all three genes. Haplotypes including SNPs spanning the PON genes were generally more significant than haplotypes comprising SNPs from one gene. Significant interactions were observed between SNP pairs located across the PON cluster with either serum activity measure as the outcome, and between several PON SNPs and PA activity with AD status as the outcome. Our results suggest that low serum paraoxonase activity is a risk factor for AD. Furthermore, multiple variants in PON influence serum paraoxonase activity and their effects may be synergistic.

Background To find specific genes predisposing to heavy alcohol consumption (self-reported consumption of 24 grams or more of alcohol per day among men and 12 grams or more among women), we studied 330 families collected by the Framingham Heart Study made available to participants in the Genetic Analysis Workshop 13 (GAW13). Results Parametric and nonparametric methods of linkage analysis were used. No significant evidence of linkage was found; however, weak signals were identified in several chromosomal regions, including 1p22, 4q12, 4q25, and 11q24, which are in the vicinity of those reported in other similar studies. Conclusion Our study did not reveal significant evidence of linkage to heavy alcohol use; however, we found weak confirmation of studies carried out in other populations.