HLA-DRA gene polymorphisms might play an important role in alcohol dependence (AD). We examined genetic associations of 29 single-nucleotide polymorphisms (SNPs) within the HLA-DRA gene with AD using two Caucasian samples - the Collaborative Study on the Genetics of Alcoholism (COGA) sample (660 AD cases and 400 controls) and the Study of Addiction: Genetics and Environment (SAGE) sample (623 cases and 1,016 controls). Logistic regression analysis using PLINK showed that 16 SNPs were associated with AD in the COGA sample and 13 SNPs were associated with AD in the SAGE sample (p < 0.05). The best novel signal was SNP rs2239803 associated with AD in both samples (p = 0.000817 for the COGA sample and p = 0.0026 for the SAGE sample, respectively) while one flanking SNP rs4935356 also showed strong association in both samples (p = 0.00219 and 0.0026 for the COGA and SAGE samples, respectively). Furthermore, these two SNPs revealed stronger associations in meta-analysis of these two samples (p = 8.97 × 10-6 and 2.02 × 10-5 for rs2239803 and rs4935356, respectively). In addition, the G-A haplotype from these two SNPs revealed a significant association with AD in both the COGA and SAGE samples (p = 0.0007 and 0.0019, respectively). These findings highlight the novel associations with HLA-DRA that may play an important role in the etiology of AD.

Maximum number of drinks (MaxDrinks) defined as "Maximum number of alcoholic drinks consumed in a 24-h period" is an intermediate phenotype that is closely related to alcohol dependence (AD). Family, twin and adoption studies have shown that the heritability of MaxDrinks is approximately 0.5. We conducted the first genome-wide association (GWA) study and meta-analysis of MaxDrinks as a continuous phenotype. 1059 individuals were from the Collaborative Study on the Genetics of Alcoholism (COGA) sample and 1628 individuals were from the Study of Addiction - Genetics and Environment (SAGE) sample. Family sample with 3137 individuals was from the Australian twin-family study of alcohol use disorder (OZALC). Two population-based Caucasian samples (COGA and SAGE) with 1 million single-nucleotide polymorphisms (SNPs) were used for gene discovery and one family-based Caucasian sample was used for replication. Through meta-analysis we identified 162 SNPs associated with MaxDirnks (p<10-4). The most significant association with MaxDrinks was observed with SNP rs11128951 (p=4.27×10-8) near SGOL1 gene at 3p24.3. Furthermore, several SNPs (rs17144687 near DTWD2, rs12108602 near NDST4, and rs2128158 in KCNB2) showed significant associations with MaxDrinks (p<5×10-7) in the meta-analysis. Especially, 8 SNPs in DDC gene showed significant associations with MaxDrinks (p<5×10-7) in the SAGE sample. Several flanking SNPs in above genes/regions were confirmed in the OZALC family sample. In conclusions, we identified several genes/regions associated with MaxDrinks. These findings can improve the understanding about the pathogenesis of alcohol consumption phenotypes and alcohol-related disorders.

Objective: To quantitatively characterize change in health-related quality of life (HRQoL) in the context of behavioral (n = 16), surgical (n = 5), and pharmacological (n = 1) interventions for pediatric overweight and obesity. A secondary goal was to examine the relationship between change in HRQoL and change in body mass index (ΔBMI) by treatment type. The amount of weight loss necessary to observe a minimally clinically important difference (MCID) in HRQoL was determined. Method: Data were gathered from studies reporting on weight change and ΔHRQoL over the course of obesity interventions (N = 22) in youths (N = 1,332) with average ages between 7.4 and 16.5 years (M = 12.2). An overall effect size was calculated for ΔHRQoL. Moderation analyses were conducted using analysis of variance and weighted regression. MCID analyses were conducted by converting HRQoL data to standard error of measurement units. Results: The overall effect size for ΔHRQoL in the context of pediatric obesity interventions was medium (g = 0.51). A significant linear relationship was detected between ΔBMI and ΔHRQoL (R2 = 0.87). This relationship was moderated by treatment type, with medical (i.e., surgical) interventions demonstrating a stronger relationship. Results indicated that it takes a change of 0.998 BMI units to detect true change in HRQoL. Conclusion: This study provides the first known quantitative examination of changes in HRQoL associated with weight loss in pediatric interventions. Medical interventions appear to offer a more substantial increase in HRQoL per unit of BMI change. These results offer a concrete weight loss goal for noticing positive effects in daily life activities.

Alcohol addiction may increase the risk of obesity due to shared genetic components. The Copine V (CPNE5) gene is involved in Ca2+ binding and may play an important role in the development of the central nervous system. This study tested the genetic associations of 77 single-nucleotide polymorphisms (SNPs) within the CPNE5 gene with alcohol dependence (AD) and obesity using a Caucasian sample - The Study of Addiction - Genetics and Environment (SAGE) sample (1066 AD cases and 1278 non-AD controls, 422 obese cases and 1395 non-obese controls). The Marshfield sample (1442 obese cases and 2122 non-obese controls) was used for replication of obesity. Multiple logistic regression analysis was performed using the PLINK software. In the SAGE sample, we identified 10 SNPs associated with AD and 17 SNPs associated with obesity (p < 0.05). Interestingly, 6 SNPs (rs9986517, rs9470387, rs3213534, rs10456444, rs3752482, and rs9470386) were associated with both AD (OR = 0.77, 0.77, 0.83, 0.84, 0.79 and 1.14, respectively; p = 9.72 × 10-5, 1.1 × 10-4, 4.09 × 10-3, 5.26 × 10-3, 1.59 × 10-2, and 3.81 × 10-2, respectively) and obesity (OR = 0.77, 0.77, 0.78, 0.77, 0.68 and 1.18, respectively; p = 2.74 × 10-3, 2.69 × 10-3, 2.45 × 10-3, 1.01 × 10-3, 5.18 × 10-3 and 3.85 × 10-2, respectively). In the Marshfield sample, rs3752480 was associated with obesity (p = 0.0379). In addition, four SNPs (rs9986517, rs10456444, rs7763347 and rs4714010) showed associations with obesity in the meta-analysis using both samples (p = 0.00493, 0.0274, 0.00346, and 0.0141, respectively). These findings provide the first evidence of common genetic variants in the CPNE5 gene influencing both the AD and obesity; and will serve as a resource for replication in other populations.

The DPYSL2 gene at 8p22-p21 is expressed widely in neuronal tissues and has been implicated in multiple psychiatric disorders such as Alzheimer's disease and schizophrenia. We therefore hypothesized that DPYSL2 gene polymorphisms may play a role in alcohol dependence (AD). We investigated the genetic associations of 57 single-nucleotide polymorphisms (SNPs) within the DPYSL2 gene with AD using two Caucasian samples - the Collaborative Study on the Genetics of Alcoholism (COGA) sample (660 AD cases and 400 controls), and the Study of Addiction: Genetics and Environment (SAGE) sample (623 cases and 1,016 controls). The SNP rs11995227 was most significantly associated with AD (p = 0.000122) in the COGA sample while one flanking SNP rs7832576 revealed the second most significant association with AD (p = 0.00163) in the COGA sample and association with AD (p = 0.0195) in the SAGE sample. Meta-analysis of two samples showed both rs119952227 and rs7832576 were associated with AD (p = 0.000363 and 0.000184, respectively). Furthermore, the C-A haplotype from rs11995227 and rs7832576 revealed significant association with AD (p = 0.0000899) in the COGA sample while the T-G haplotype revealed association with AD both in the COGA and SAGE samples (p = 0.00098 and 0.021, respectively). These findings suggest that genetic variants in DPYSL2 may play a role in susceptibility to AD.

Twin and family studies have shown that there is substantial evidence for a genetic component in the vulnerability to nicotine dependence (ND). The purpose of this study was to perform a meta-analysis on two genome-wide association (GWA) data involving 1079 cases of ND and 1341 controls in Caucasian populations. Through meta-analysis we identified 50 SNPs associated with ND with p<10-4. The best associated SNP rs7163369 (p=3.27×10-6) was located at 15q26 within SLCO3A1 gene while the second best SNP was rs9308631 (p=9.06×10-6) at 2q12.1 near ANAPC1. The third interesting locus rs688011 (p=1.08×10-5) was at 11q23.2 intergenic between NCAM1 and TCC12. Through meta-analysis, we found two additional ND associated genes ZCCHC14 (the top SNP was rs13334632, p=1.28×10-5) and KANK1 (the top SNP was rs13286166, p=1.49×10-5). The first top SNP rs7163369 within SLCO3A1 in the meta-analysis was replicated in the Australian twin-family study of 778 families (p=6.11×10-5) while SNP rs9653414 within ANAPC1 (p=4.61×10-5) in the meta-analysis was replicated in the family sample (p=9.31×10-4). Furthermore, rs2241617 in ZCCHC14 and rs4742225 in KANK1 showed strong associations with ND (p=1.06×10-7 and 4.81×10-7, respectively) in the replication sample. In addition, several SNPs of these loci (ANAPC1, KANK1, NACM1, TCC12, SLCO3A1 and ZCCHC14) were associated with alcohol dependence. In conclusion, we identified several loci associated with ND through meta-analysis of two GWA studies. These findings offer the potential for new insights into the pathogenesis of ND.

Formal thought disorder (FTD), or disorganized speech, is one of the central signs of schizophrenia; however, little is known about the etiology of FTD. To identify new genetic loci associated with FTD, we conducted the first genome-wide association meta-analysis of two datasets of 835 cases of FTD and 2,694 controls with 729,454 single-nucleotide polymorphisms (SNPs). Logistic regression analysis of FTD as a binary trait, adjusted for age and sex, was performed using PLINK. For meta-analysis of two datasets, the fixed-effect model in PLINK was applied. Through meta-analysis we identified 61 SNPs associated with FTD with p < 10-4. The most significant association with FTD was observed with rs1783925 (p = 4.4 × 10-7) within PKNOX2 gene at 11q24.2 while the second interesting locus was rs2277644 (p = 1.18 × 10-5) within MYH13 at 17p13. Haplotype analyses of PKNOX2 and MYH13 loci further supported the associations with FTD. The third locus was PHF2 at 9q22.31 (the top SNP was rs12238738 with p = 2.08 × 10-5) while the fourth locus was GPC6 at 13q32 (the top SNP was rs17196161 with p = 3.12 × 10-5). In conclusion, we identified four new loci (PKNOX2, MYH13, PHF2, and GPC6) associated with FTD. These findings offer the potential for new insights into the pathogenesis of FTD and schizophrenia.

Family, twin and adoption studies have clearly demonstrated that genetic factors are important in modulating the vulnerability to alcohol dependence. Several genome-wide association (GWA) studies of alcohol dependence have been conducted; however, few loci have been replicated. A meta-analysis was performed on two GWA studies of 1283 cases of alcohol dependence and 1416 controls in Caucasian populations. Through meta-analysis we identified 131 SNPs associated with alcohol dependence with p<10-4. The best novel signal was rs6701037 (p=1.86 × 10-7) at 1q24-q25 within KIAA0040 gene while the second best novel hit was rs1869324 (p=4.71 × 10-7) at 2q22.1 within THSD7B. The third novel locus was NRD1 at 1p32.2 (the top SNP was rs2842576 with p=7.90 × 10-6). We confirmed the association of PKNOX2 at 11q24.4 with alcohol dependence. The top hit of PKNOX2 (rs750338 with p=1.47 × 10-6) in the meta-analysis was replicated with the Australian Twin-Family Study of 778 families (p=1.39 × 10-2) Furthermore, several flanking SNPs of the top hits in the meta-analysis demonstrated borderline associations with alcohol dependence in the family sample (top SNPs were rs2269655, rs856613, and rs10496768 with p=4.58 × 10-3, 2.1 × 10-4, and 2.86 × 10-3 for KIAA0040, NRD1 and THSD7B, respectively). In addition, ALK, CASC4, and SEMA5A were strongly associated with alcohol dependence (p<2 × 10-5) in the meta-analysis. In conclusion, we identified three new loci (KIAA0040, THSD7B and NRD1) and confirmed the previous association of PKNOX2 with alcohol dependence. These findings offer the potential for new insights into the pathogenesis of alcohol dependence.

Schizophrenia and bipolar disorder both have strong inherited components. Recent studies have indicated that schizophrenia and bipolar disorder may share more than half of their genetic determinants. In this study, we performed a meta-analysis (combined analysis) for genome-wide association data of the Affymetrix Genome-Wide Human SNP array 6.0 to detect genetic variants influencing both schizophrenia and bipolar disorder using European-American samples (653 bipolar cases and 1034 controls, 1172 schizophrenia cases and 1379 controls). The best associated SNP rs11789399 was located at 9q33.1 (p=2.38×10-6, 5.74×10-4, and 5.56×10-9, for schizophrenia, bipolar disorder and meta-analysis of schizophrenia and bipolar disorder, respectively), where one flanking gene, ASTN2 (220kb away) has been associated with attention deficit/hyperactivity disorder and schizophrenia. The next best SNP was rs12201676 located at 6q15 (p=2.67×10-4, 2.12×10-5, 3.88×10-8 for schizophrenia, bipolar disorder and meta-analysis, respectively), near two flanking genes, GABRR1 and GABRR2 (15 and 17kb away, respectively). The third interesting SNP rs802568 was at 7q35 within CNTNAP2 (p=8.92×10-4, 1.38×10-5, and 1.62×10-7 for schizophrenia, bipolar disorder and meta-analysis, respectively). Through meta-analysis, we found two additional associated genes NALCN (the top SNP is rs2044117, p=4.57×10-7) and NAP5 (the top SNP is rs10496702, p=7.15×10-7). Haplotype analyses of above five loci further supported the associations with schizophrenia and bipolar disorder. These results provide evidence of common genetic variants influencing schizophrenia and bipolar disorder. These findings will serve as a resource for replication in other populations to elucidate the potential role of these genetic variants in schizophrenia and bipolar disorder.

The Substance Abuse Subtle Screening Inventory (SASSI) is a 10 scale indirect screening instrument used to detect substance use disorders. The current meta-analytic study described reliability reporting practices across 48 studies involving the SASSI. Reliability generalization methods were then employed to evaluate typical score reliability for the screening measure. Results showed approximately 73 of studies did not report reliability estimates. Analysis of data from the remaining studies revealed adequate reliability for the total scale (α .87) and face valid scales (FVA α .88 and FVOD α .92), but substantially lower reliability estimates for the indirect scales (range of α .23.65). The study's findings underscore the need for improved reliability reporting for the SASSI and suggest cautious use of the measure, especially its indirect scales, as an indicator of problematic substance use/abuse in clinical settings.