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Acamprosate is an anti-craving drug used for the pharmacotherapy of alcohol use disorder (AUD). However, only some patients achieve optimal therapeutic outcomes. This study was designed to explore differences in metabolomic profiles between patients who maintained sobriety and those who relapsed, to determine whether those differences provide insight into variation in acamprosate treatment response phenotypes.We previously conducted an acamprosate trial involving 442 AUD patients, and 267 of these subjects presented themselves for a 3-month follow-up. The primary outcome was abstinence. Clinical information, genomic data and metabolomics data were collected. Baseline plasma samples were assayed using targeted metabolomics.Baseline plasma arginine, threonine, α-aminoadipic acid and ethanolamine concentrations were associated with acamprosate treatment outcomes and baseline craving intensity, a measure that has been associated with acamprosate treatment response. We next applied a pharmacometabolomics-informed genome-wide association study (GWAS) strategy to identify genetic variants that might contribute to variations in plasma metabolomic profiles that were associated with craving and/or acamprosate treatment outcome. Gene expression data for induced pluripotent stem cell-derived forebrain astrocytes showed that a series of genes identified during the metabolomics-informed GWAS were ethanol responsive. Furthermore, a large number of those genes could be regulated by acamprosate. Finally, we identified a series of single nucleotide polymorphisms that were associated with acamprosate treatment outcomes.These results serve as an important step towards advancing our understanding of disease pathophysiology and drug action responsible for variation in acamprosate response and alcohol craving in AUD patients.

Interest in analyzing X chromosome single nucleotide polymorphisms (SNPs) is growing and several approaches have been proposed. Prior studies have compared power of different approaches, but bias and interpretation of coefficients have received less attention. We performed simulations to demonstrate the impact of X chromosome model assumptions on effect estimates. We investigated the coefficient biases of SNP and sex effects with commonly used models for X chromosome SNPs, including models with and without assumptions of X chromosome inactivation (XCI), and with and without SNP–sex interaction terms. Sex and SNP coefficient biases were observed when assumptions made about XCI and sex differences in SNP effect in the analysis model were inconsistent with the data‐generating model. However, including a SNP–sex interaction term often eliminated these biases. To illustrate these findings, estimates under different genetic model assumptions are compared and interpreted in a real data example. Models to analyze X chromosome SNPs make assumptions beyond those made in autosomal variant analysis. Assumptions made about X chromosome SNP effects should be stated clearly when reporting and interpreting X chromosome associations. Fitting models with SNP × Sex interaction terms can avoid reliance on assumptions, eliminating coefficient bias even in the absence of sex differences in SNP effect.

AIMS Long-term lithium therapy (LTLT) has been associated with kidney insufficiency in bipolar disorder (BD). We aimed to investigate the risk factors of chronic kidney disease (CKD) development and progression among BD patients receiving LTLT. METHODS We included adult patients with BD on LTLT (≥1 year) who were enrolled in the Mayo Clinic Bipolar Biobank, Rochester, Minnesota. We reviewed electronic medical records to extract information related to lithium therapy and kidney-related data to assess changes in the estimated glomerular filtration rate (eGFR). CKD severity was assessed based on eGFR. RESULTS Among 154 patients who received LTLT, 41 patients (27%) developed CKD, of whom 20 (49%) patients continued lithium (continuers) and 19 (46%) discontinued it (discontinuers). The median time to stage 3 CKD development was 21.7 years from the start of Li treatment. Type-2 diabetes mellitus and benzodiazepine use were independent predictors for CKD development in the survival analysis, after controlling for age. The subsequent CKD progression rate did not differ between continuers and discontinuers (mean GFR 48.6 vs. 44.1, p = 0.13) at the end of follow-up duration (mean duration: 3.5 ± 4.4 years for continuers and 4.9 ± 5.3 years for discontinuers). CONCLUSION CKD was observed in one fourth of patients with BD receiving LTLT. There was no significant difference in the progression of CKD among Li continuers versus discontinuers, at the mean follow-up duration of 4.2 years, after the CKD diagnosis. Progression of CKD could be influenced by existing comorbidities and may not necessarily be due to lithium alone.

We previously reported that testis-specific Y-encoded-like protein (TSPYLs) are transcription regulators for CYP3A4, CYP2C9, and CYP2C19. Here, we observed dual roles for TSPYLs in mediating serotonin transport and the metabolism of selective serotonin reuptake inhibitors (SSRIs) in patients with major depressive disorder (MDD). The widely prescribed SSRIs, citalopram, and escitalopram are metabolized mainly by CYP2C19. The TSPYL1 rs3828743 single nucleotide polymorphism (SNP), which decreases its suppression of CYP2C19 expression, was associated with rapid escitalopram metabolism and worse treatment response in the Mayo PGRN-AMPS clinical trial. We also found that TSPYLs can regulate expression of the serotonin transporter protein, SLC6A4, and, in turn, serotonin transport into cells. The SNPs in tight linkage disequilibrium with the TSPYL1 rs10223646 SNP were significantly correlated with baseline severity of depression in patients with MDD in the Sequenced Treatment Alternatives to Relieve Depression and International SSRI Pharmacogenomics Consortium clinical trials. Our findings suggest that genetic variation in TSPYL genes may be novel indicators for baseline severity of depression and SSRI poor response.

We set out to determine whether machine learning–based algorithms that included functionally validated pharmacogenomic biomarkers joined with clinical measures could predict selective serotonin reuptake inhibitor (SSRI) remission/response in patients with major depressive disorder (MDD). We studied 1,030 white outpatients with MDD treated with citalopram/escitalopram in the Mayo Clinic Pharmacogenomics Research Network Antidepressant Medication Pharmacogenomic Study (PGRN‐AMPS; n = 398), Sequenced Treatment Alternatives to Relieve Depression (STAR*D; n = 467), and International SSRI Pharmacogenomics Consortium (ISPC; n = 165) trials. A genomewide association study for PGRN‐AMPS plasma metabolites associated with SSRI response (serotonin) and baseline MDD severity (kynurenine) identified single nucleotide polymorphisms (SNPs) in DEFB1,ERICH3,AHR, and TSPAN5 that we tested as predictors. Supervised machine‐learning methods trained using SNPs and total baseline depression scores predicted remission and response at 8 weeks with area under the receiver operating curve (AUC) > 0.7 (P 69% (P ≤ 0.07) in STAR*D and ISPC. These results demonstrate that machine learning can achieve accurate and, importantly, replicable prediction of SSRI therapy response using total baseline depression severity combined with pharmacogenomic biomarkers.

Author(s): Boeve, Bradley F; Boxer, Adam L; Rosen, Howard J; Forsberg, Leah K; Heuer, Hilary W; Brushaber, Danielle; Appleby, Brian; Biernacka, Joanna M; Bordelon, Yvette M; Botha, Hugo; Brannelly, Patrick; Dickerson, Brad C; Dickson, Dennis W; Kimiko, Domoto‐Reilly; Faber, Kelley; Fagan, Anne; Fields, Julie A; Fishman, Ann; Foroud, Tatiana M; Galasko, Doug R; Gavrilova, Ralitza H; Gendron, Tania F; Geschwind, Daniel H; Ghoshal, Nupur; Goldman, Jill; Graff‐Radford, Jonathan; Graff‐Radford, Neill R; Grant, Ian; Grossman, Murray; Hsiung, Ging‐Yuek Robin; Huang, Eric J; Huey, Edward; Irwin, David J; Jones, David T; Kantarci, Kejal; Karydas, Anna M; Kaufer, Daniel; Knopman, David S; Kramer, Joel H; Kremers, Walter K; Kornak, John; Kukull, Walter A; Lagone, Emma; Leger, Gabriel C; Litvan, Irene; Ljubenkov, Peter A; Lucente, Diane E; Mackenzie, Ian R; Manoochehri, Masood; Masdeu, Joseph C; McGinnis, Scott; Mendez, Mario F; Miller, Bruce L; Miyagawa, Toji; Nelson, Kevin M; Onyike, Chiadi U; Pantelyat, Alex; Pascual, Belen; Pearlman, Rodney; Petrucelli, Leonard; Rademakers, Rosa; Ramos, Eliana Marisa; Rankin, Katherine; Rascovsky, Katya; Rexach, Jessica E; Ritter, Aaron; Roberson, Erik D; Rojas, Julio C; Sabbagh, Marwan N; Salmon, David P; Savica, Rodolfo; Seeley, William W; Staffaroni, Adam M; Syrjanen, Jeremy; Tartaglia, Carmela; Tatton, Nadine; Taylor, Joanne; Toga, Arthur W; Weintraub, Sandra; Wheaton, Diana; Wong, Bonnie; Wszolek, Zbigniew

OBJECTIVES: Bipolar disorder (BD) with early disease onset is associated with an unfavorable clinical outcome and constitutes a clinically and biologically homogenous subgroup within the heterogeneous BD spectrum. Previous studies have found an accumulation of early age at onset (AAO) in BD families and have therefore hypothesized that there is a larger genetic contribution to the early-onset cases than to late onset BD. To investigate the genetic background of this subphenotype, we evaluated whether an increased polygenic burden of BD- and schizophrenia (SCZ)-associated risk variants is associated with an earlier AAO in BD patients. METHODS: A total of 1995 BD type 1 patients from the Consortium of Lithium Genetics (ConLiGen), PsyCourse and Bonn-Mannheim samples were genotyped and their BD and SCZ polygenic risk scores (PRSs) were calculated using the summary statistics of the Psychiatric Genomics Consortium as a training data set. AAO was either separated into onset groups of clinical interest (childhood and adolescence [≤18 years] vs adulthood [>18 years]) or considered as a continuous measure. The associations between BD- and SCZ-PRSs and AAO were evaluated with regression models. RESULTS: BD- and SCZ-PRSs were not significantly associated with age at disease onset. Results remained the same when analyses were stratified by site of recruitment. CONCLUSIONS: The current study is the largest conducted so far to investigate the association between the cumulative BD and SCZ polygenic risk and AAO in BD patients. The reported negative results suggest that such a polygenic influence, if there is any, is not large, and highlight the importance of conducting further, larger scale studies to obtain more information on the genetic architecture of this clinically relevant phenotype. peerReviewed

Objective The study aimed to define thresholds of clinically significant change in 17-item Hamilton Depression Rating Scale (HDRS-17) scores using the Clinical Global Impression-Improvement (CGI-I) Scale as a gold standard. Methods We conducted a secondary analysis of individual patient data from the Pharmacogenomic Research Network Antidepressant Medication Pharmacogenomic Study, an 8-week, single-arm clinical trial of citalopram or escitalopram treatment of adults with major depression. We used equipercentile linking to identify levels of absolute and percent change in HDRS-17 scores that equated with scores on the CGI-I at 4 and 8 weeks. Additional analyses equated changes in the HDRS-7 and Bech-6 scale scores with CGI-I scores. Results A CGI-I score of 2 (much improved) corresponded to an absolute decrease (improvement) in HDRS-17 total score of 11 points and a percent decrease of 50–57%, from baseline values. Similar results were observed for percent change in HDRS-7 and Bech-6 scores. Larger absolute (but not percent) decreases in HDRS-17 scores equated with CGI-I scores of 2 in persons with higher baseline depression severity. Conclusions Our results support the consensus definition of response based on HDRS-17 scores (>50% decrease from baseline). A similar definition of response may apply to the HDRS-7 and Bech-6. Copyright © 2016 John Wiley & Sons, Ltd.

Machine learning methods, including Random Forests (RF), are increasingly used for genetic data analysis. However, the standard RF algorithm does not correctly model the effects of X chromosome single nucleotide polymorphisms (SNPs), leading to biased estimates of variable importance. We propose extensions of RF to correctly model X SNPs, including a stratified approach and an approach based on the process of X chromosome inactivation. We applied the new and standard RF approaches to case-control alcohol dependence data from the Study of Addiction: Genes and Environment (SAGE), and compared the performance of the alternative approaches via a simulation study. Standard RF applied to a case-control study of alcohol dependence yielded inflated variable importance estimates for X SNPs, even when sex was included as a variable, but the results of the new RF methods were consistent with univariate regression-based approaches that correctly model X chromosome data. Simulations showed that the new RF methods eliminate the bias in standard RF variable importance for X SNPs when sex is associated with the trait, and are able to detect causal autosomal and X SNPs. Even in the absence of sex effects, the new extensions perform similarly to standard RF. Thus, we provide a powerful multimarker approach for genetic analysis that accommodates X chromosome data in an unbiased way. This method is implemented in the freely available R package "snpRF" (http://www.cran.r-project.org/web/packages/snpRF/).

Objectives To examine the independent effects of sex on the risk of rapid cycling and other indicators of adverse illness course in patients with bipolar I disorder (BP-I) or bipolar II disorder (BP-II). Methods We analyzed data from the first 1,225 patients enrolled in the Mayo Clinic Individualized Medicine Biobank for Bipolar Disorder. Demographic and clinical variables were ascertained using standardized questionnaires; height and weight were assessed to determine body mass index (BMI). Rates of rapid cycling, cycle acceleration, and increased severity of mood episodes over time were compared between women and men overall and within subgroups defined by bipolar disorder subtype (BP-I or BP-II). Multiple logistic regression analysis was used to assess the independent effect of sex on the risk of these indicators of adverse illness course. Results Women had significantly higher rates of rapid cycling than men. Overall rates of rapid cycling were higher in patients with BP-II than BP-I; and sex differences in the rate of rapid cycling were more pronounced in patients with BP-II than BP-I, although the power to detect statistically significant differences was reduced due to the lower sample size of subjects with BP-II. Female sex was a significant predictor of rapid cycling, cycle acceleration, and increased severity of mood episodes over time after adjusting for age, bipolar disorder subtype, BMI, having any comorbid psychiatric disorder, and current antidepressant use. Conclusions Female sex was associated with significantly higher risk of rapid cycling, cycle acceleration, and increased severity of mood episodes over time in a sample of 1,225 patients with bipolar disorders.

BACKGROUND: Sleep disturbances are extremely common in alcohol recovery. Systematic research into the relationship between alcohol relapse and sleep disturbances using validated scales and accounting for potential confounders is lacking. METHODS: Patients admitted to a 1-month residential addiction treatment program were administered the Pittsburg Sleep Quality Index (PSQI) at admission/discharge. In addition, the Alcohol Use Disorders Identification Test (AUDIT), Patient Health Questionnaire-9 (PHQ-9), and Pennsylvania Alcohol Craving Scale (PACS) were administered. Patients were contacted every 3 months over 1 year following discharge. Associations of clinical factors with time until relapse were examined using univariate Cox proportional hazard models. RESULTS: One-hundred and nineteen patients with alcohol use disorders met inclusion criteria (mean age 50.6 ± 13.2 years, 57% male), relapse data were available for 81 patients. Eighty percent of subjects had other psychiatric diagnoses, 66.3% had sleep disturbances at the time of admission, and 57.1% were using hypnotics; 49.1% of patients had sleep disturbances at discharge. Sleep disturbances at admission and discharge were not associated with alcohol relapse at 12 months (OR = 1.00, 95%CI = 0.89-1.13; p = 0.95 and OR = 0.97, 95%CI = 0.86-1.09; p = 0.61). The PSQI sub-scale scores were also not associated with relapse at 12 months. The use of alcohol to help fall asleep (OR = 3.26, 95% CI = 1.33-7.95; p = 0.008), hypnotic use at admission(OR = 4.03, 95%CI = 1.63-9.97; p = 0.002) and age (OR = 1.03, 95%CI = 1.00-1.06; p = 0.035) were associated with relapse over 12 months. CONCLUSION: In patients completing a residential treatment program, sleep disturbances as measured by the PSQI were not associated with alcohol relapse at 12 months. Alcohol use as a hypnotic and hypnotic use at admission were associated with subsequent relapse. Language: en

Objectives: To determine whether alpha-synuclein dinucleotide repeat (REP1) genotypes are associated with survival in Parkinson's disease (PD). Methods: Investigators from the Genetic Epidemiology of Parkinson's Disease Consortium provided REP1 genotypes and baseline and follow-up clinical data for cases. The primary outcome was time to death. Cox proportional hazards regression models were used to assess the association of REP1 genotypes with survival. Results: Twenty-one sites contributed data for 6,154 cases. There was no significant association between alpha-synuclein REP1 genotypes and survival in PD. However, there was a significant association between REP1 genotypes and age at onset of PD (hazard ratio: 1.06; 95% confidence interval: 1.01-1.10; P value = 0.01). Conclusions: In our large consortium study, alpha-synuclein REP1 genotypes were not associated with survival in PD. Further studies of alpha-synuclein's role in disease progression and long-term outcomes are needed. (C) 2014 International Parkinson and Movement Disorder Society

Identifying genetic variants associated with complex disease in high-dimensional data is a challenging problem, and complicated etiologies such as gene-gene interactions are often ignored in analyses. The data-mining method Random Forests (RF) can handle high-dimensions; however, in high-dimensional data, RF is not an effective filter for identifying risk factors associated with the disease trait via complex genetic models such as gene-gene interactions without strong marginal components. Here we propose an extension called Weighted Random Forests (wRF), which incorporates tree-level weights to emphasize more accurate trees in prediction and calculation of variable importance. We demonstrate through simulation and application to data from a genetic study of addiction that wRF can outperform RF in high-dimensional data, although the improvements are modest and limited to situations with effect sizes that are larger than what is realistic in genetics of complex disease. Thus, the current implementation of wRF is unlikely to improve detection of relevant predictors in high-dimensional genetic data, but may be applicable in other situations where larger effect sizes are anticipated.

Background and Objectives The aim of this study was to investigate potential gender differences in situations associated with heavy alcohol drinking. Methods Data from 395 alcohol dependent patients participating in the Mayo Clinic Intensive Addiction Program were evaluated. Each participant completed the inventory of drug taking situations (IDTS), Penn alcohol craving scale (PACS), patient health questionnaire (PHQ-9), and/or Beck depression inventory (BDI). Gender differences in IDTS scores representing three domains (negative, positive, and temptation) of situations associated with heavy alcohol use were examined. Results Women with alcohol dependence report a higher frequency of heavy drinking in unpleasant emotional (IDTS negative scores mean ± SD women vs. men: 52.3 ± 22.1 vs. 43.8 ± 21.8; p = .0006), and as a result of temptation (IDTS temptation scores mean ± SD women vs. men: 40.4 ± 23.0 vs. 35.3 ± 20.8; p = .035). Upon admission, women also scored significantly higher on depressive symptoms as measured by the BDI (23.4 ± 11.4 vs. 18.2 ± 9.8, p

Background and Objectives: Alcoholism treatment interventions, both psychosocial and pharmacologic, aim to reduce cravings to drink. Yet, the role of craving in treatment outcomes remains unclear. This study evaluated craving intensity measured with the Penn Alcohol Craving Scale (PACS) at admission and discharge from residential treatment as a predictive factor of relapse after treatment. Methods: The study cohort included 314 alcohol-dependent subjects. Associations between relapse after discharge, PACS score, and clinical variables were investigated using time-to-event analyses. The primary analysis, based on the intent-to-treat principle, presumed relapse in those declining follow-up or not responding to contact attempts. Secondary analysis utilized data from 226 subjects successfully contacted after discharge with a median follow-up time of 365 days. Results: The intent-to-treat analysis demonstrated that relapse was associated with higher level of craving at admission (p= .002) and discharge (p < .001). The analysis of data from patients successfully contacted after discharge led to similar results. A multivariable analysis indicated that relapse rates increased as PACS scores increased, and a higher discharge PACS score was significantly associated with relapse (p= .006) even after adjusting for covariates. Conclusions and Scientific Significance: This study demonstrates that higher PACS scores at the time of admission and discharge are associated with relapse following residential addiction treatment. These data support the role of craving in relapse and the utility of craving measurement as a clinical guide in assessing relapse risk. (Am J Addict 2012;21:S20–S26)

To further explore reports of association of alcohol dependence and response to acamprosate treatment with the GATA4 rs13273672 single nucleotide polymorphism (SNP), we genotyped this and 10 other GATA4 SNPs in 816 alcohol-dependent cases and 1248 controls. We tested for association of alcohol dependence with the 11 SNPs individually and performed a global test for association using a principle components analysis. Our analyses demonstrate significant association between GATA4 and alcohol dependence at the gene level (P = 0.009) but no association with rs13273672. Further studies are needed to identify potential causal GATA4 variation(s) and the functional mechanism(s) contributing to this association.

Trazodone is one of the most commonly prescribed hypnotic medications in patients with sleep disturbances in alcohol recovery. A recent study concluded that treating insomnia with trazodone in patients with alcohol dependence might impede improvements in alcohol consumption and lead to increased drinking when trazodone is stopped. We set out to investigate the relationship between trazodone use during alcoholism treatment and relapse rates in patients who were discharged from a residential alcohol treatment program. We retrospectively reviewed records of patients with a diagnosis of alcohol dependence in a residential addiction treatment center from 2005 to 2008 and analyzed the association of trazodone use at discharge and alcohol relapse at 6 months. We also assessed the association between trazodone use and relapse at 6 months adjusting for sex, drug dependence, nonsubstance use Axis I psychiatric diagnoses, patient self-report of difficulties with sleep, and anti-dipsotropic medication use at discharge and evaluated pair-wise interactions of trazodone use with the adjustment variables. Of 283 patients eligible for inclusion, 85 (30%) were taking trazodone at discharge. Older age, self-reported sleep problems, and having a nonsubstance use Axis I psychiatric diagnosis were associated with trazodone use. After discharge, 170 (60%) subjects responded to follow-up efforts. Neither intent to treat nor responder only analysis revealed any association between trazodone use and relapse. Our retrospective study of a complex patient population discharged from a residential treatment setting did not find an association between trazodone use at discharge and relapse rates at 6 months.

Model studies in mice indicate that the severity of alcohol withdrawal is associated with polymorphic variation and expression of the MPDZ gene. Current knowledge about variation in the human MPDZ gene is limited; however, our data indicate its potential association with alcohol dependence. The multi-PDZ protein is an important part of the N-methyl-D-aspartate (NMDA)-dependent α-amino-3-hydroxy-5-methyl-4-isoxazole propionic acid (AMPA) receptor trafficking cascade that controls glutamate-related excitatory neurotransmission. To investigate association of variation in the NMDA-dependent AMPA trafficking cascade with alcohol dependence, we performed a gene-set (pathway) analysis using single nucleotide polymorphism (SNP) data from the Study of Addiction: Genetic and Environment. Rather than testing for association with each SNP individually, which typically has low power to detect small effects of multiple SNPs, gene-set analysis applies a single statistical test to evaluate whether variation in a set of genes is associated with the phenotype of interest. Gene-set analysis of 988 SNPs in 13 genes in the pathway demonstrated a significant association with alcohol dependence, with P < 0.01 for the global effect of variation in this pathway. The statistically significant association of alcohol dependence with genetic variation in the NMDA-dependent AMPA receptor trafficking cascade indicates a need for further investigation of the role of this pathway in alcohol dependence.

Incidence rates of Parkinson's disease are higher in men than in women at all ages, and these differences may be a result of the neuroprotective effects of estrogen on the nigrostriatal pathway. We investigated the association of common variants in 4 estrogen-related genes with Parkinson's disease. Tagging single-nucleotide polymorphisms in the CYP19A1, ESR1, ESR2, and PRDM2 genes were selected from the International Haplotype Map and genotyped in 1103 Parkinson's disease cases from the upper Midwest of the United States and in 1103 individually matched controls (654 unaffected siblings, and 449 unrelated controls from the same region). Of 137 informative single-nucleotide polymorphisms, 2 PRDM2 single-nucleotide polymorphisms were significantly associated with an increased risk of Parkinson's disease at the Bonferroni-corrected significance level of 0.0004 (rs2744690: OR, 1.54; SE(logOR), .109; 99.96% CI, 1.05-2.26; uncorrected P = .0001; rs2744687: OR, 1.53; SE(logOR), .113; 99.96% CI, 1.03-2.29, uncorrected P = .0002); the association was significant in the women-only stratum but not in the men-only stratum. An additional 6 single-nucleotide polymorphisms in PRDM2, 2 in ESR1, 1 in ESR2, and 1 in CYP19A1 had significant P values in the overall sample before Bonferroni correction. None of the single-nucleotide polymorphisms were significantly associated with age at onset of Parkinson's disease after Bonferroni correction. Our results confirm the association of PRDM2 variants with Parkinson's disease susceptibility, especially in women.

Despite the high prevalence rate of comorbid alcohol dependence and bipolar disorder, little is known about how many bipolar patients are actively engaged in addiction treatment or the alcohol consumption characteristics of this group. This retrospective study reviewed the medical records from patients with alcohol dependence admitted to residential treatment at our institution (n = 588). The analyses focused on alcoholism severity measures and discharge clinical diagnoses. Patients with alcoholism + bipolar disorder compromised only 5% of the total study group. The number of drinking years was lower for patients with alcoholism + bipolar disorder (23.1 ± 17.7) than for those with alcoholism + depression (26.8 ± 13.9) or alcoholism alone (28.1 ± 13.2). A trend of higher mean lifetime maximum daily drinks was observed for patients with alcoholism + bipolar disorder; this was because of the significantly higher maximum drinks for women with bipolar disorder (21.0 ± 11.5) than for women in other diagnostic groups. Despite high rates of comorbidity in community-based studies, this retrospective study suggests that patients with bipolar disorder are not highly represented in residential alcoholism addiction treatment. Future studies are encouraged to better understand utilization rates of addiction treatment among patients with bipolar disorder and to identify clinical correlates that predispose bipolar women to high-dose drinking.

The influence of genetic variations in SLC6A4 (serotonin transporter gene) on citalopram treatment of depression using the Sequenced Treatment to Relieve Depression (STAR*D) sample was assessed. Of primary interest were three previously studied polymorphisms: 1) the VNTR variation of the second intron, 2) the indel promoter polymorphism (5HTTLPR or SERT), and 3) a single nucleotide polymorphism (SNP) rs25531. Additionally, SLC6A4 was resequenced to identify new SNPs for exploratory analyses. DNA from 1914 subjects in the STAR*D study were genotyped for the intron 2 VNTR region, the indel promoter polymorphism, and rs25531. Associations of these variants with remission of depressive symptoms were evaluated following citalopram treatment. In white non-Hispanic subjects, variations in the intron 2 VNTR (point-wise P = 0.041) and the indel promoter polymorphism (point-wise P = 0.039) were associated with remission following treatment with citalopram. The haplotype composed of the three candidate loci was also associated with remission, with a global p-value of 0.040 and a maximum statistic simulation p-value of 0.0031 for the S-a-12 haplotype, under a dominant model. One SNP identified through re-sequencing the SLC6A4 gene, Intron7-83-TC, showed point-wise evidence of association, which did not remain significant after correction for the number of SNPs evaluated in this exploratory analysis. No associations between these SLC6A4 variations and remission were found in the white Hispanic or black subjects. These findings suggest that multiple variations in the SLC6A4 gene are associated with remission in white non-Hispanic depressed adults treated with citalopram. The mechanism of action of these variants remains to be determined.

Recently, genome-wide association studies have substantially expanded our knowledge about genetic variants that influence the susceptibility to complex diseases. Although standard statistical tests for each single-nucleotide polymorphism (SNP) separately are able to capture main genetic effects, different approaches are necessary to identify SNPs that influence disease risk jointly or in complex interactions. Experimental and simulated genome-wide SNP data provided by the Genetic Analysis Workshop 16 afforded an opportunity to analyze the applicability and benefit of several machine learning methods. Penalized regression, ensemble methods, and network analyses resulted in several new findings while known and simulated genetic risk variants were also identified. In conclusion, machine learning approaches are promising complements to standard single-and multi-SNP analysis methods for understanding the overall genetic architecture of complex human diseases. However, because they are not optimized for genome-wide SNP data, improved implementations and new variable selection procedures are required.

In a small chromosomal region, a number of polymorphisms may be both linked to and associated with a disease. Distinguishing the potential causal sites from those indirectly associated due to linkage disequilibrium (LD) with a causal site is an important problem. This problem may be approached by determining which of the associations can explain the observed linkage signal. Recently, several methods have been proposed to aid in the identification of disease associated polymorphisms that may explain an observed linkage signal, using genotype data from affected sib pairs (ASPs) [Li et al. [2005] Am. J. Hum. Genet. 76:934–949; Sun et al. [2002] Am. J. Hum. Genet. 70:399–411]. These methods can be used to test the null hypothesis that a candidate single nucleotide polymorphism (SNP) is the sole causal variant in the region, or is in complete LD with the sole causal variant in the region. We extend variations of these methods to test for complete LD between a disease locus and haplotypes composed of two or more tightly linked candidate SNPs. We study properties of the proposed methods by simulation and apply them to type 1 diabetes data for ASPs and their parents at candidate SNP and microsatellite marker loci in the Insulin (INS) gene region. Genet. Epidemiol. 31:2727–740, 2007. © 2007 Wiley-Liss, Inc.

This study examines the clinical correlates of alcohol craving in men and women self-referred for addiction treatment. Admission clinical data from patients participating in the Mayo Clinic 1-month Intensive Addictions Program were evaluated. Women had higher BDI and PACS scores compared with men in both the entire cohort and Dual Diagnoses group. Alcohol-dependent females had the most marked correlation between BDI and PACS (rho= .78). Further prospective study is encouraged to evaluate whether depressive symptoms and concomitant alcohol cravings in women are a marker for relief cravings and, as such, a target symptom for treatment intervention.