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.

Alzheimer’s disease (AD) is a multifactorial neurological condition associated with genetic profiles that are still not completely understood. We performed a family-based low-density genome-wide association analysis of age at onset (AAO) in AD (244 patients and their relatives) using Illumina 6 K single-nucleotide polymorphisms (SNPs) panel and the FBAT-logrank statistic. We observed 10 SNPs associated with AAO in AD with p < 2 × 10−3. The most significant hit within a known gene, the neuronal protein astrotactin 2 (ASTN2), was SNP rs1334071 (p = 8.74 × 10−4). ASTN2 has been implicated in several neuropsychiatric disorders, including cognitive disorders, autism and schizophrenia. We then conducted a replication study focusing on ASTN2 gene in a Canadian sample of 791 AD patients and 782 controls using the logrank test. Five ASTN2 SNPs (highest association is rs16933774 with p = 0.0053) showed associations with AAO in this Canadian sample (p < 0.05). Furthermore, Kaplan–Meier survival analysis of SNP rs16933774 showed that the AAO of AD in individuals heterozygous for AG genotype of rs16933774 (median of AAO = 68.5 years) was approximately 4.5 years earlier than those individuals having the AA genotype (median of AAO = 73 years). In conclusion, a significant association of ASTN2 genetic variants with AAO of AD in two independent samples demonstrates a role for ASTN2 in the pathogenesis of AD. Future functional studies of this gene may help to characterize the genetic architecture of the AAO of AD. Genetic factors in AAO may be a critical factor for early AD intervention and prevention efforts.

Several genome-wide association (GWA) studies of alcohol dependence (AD) and alcohol-related phenotypes have been conducted; however, little is known about genetic variants influencing alcohol withdrawal symptoms (AWS). We conducted the first GWA study of AWS using 461 cases of AD with AWS and 408 controls in Caucasian population in the Collaborative Study on the Genetics of Alcoholism (COGA) sample. Logistic regression analysis of AWS as a binary trait, adjusted for age and sex, was performed using PLINK. We identified 51 SNPs associated with AWS with p<10 -4. The first best signal was rs770182 (p = 3.65 × 10 -6) at 5q21 near EFNA5 gene which was replicated in the Australian twin-family study of 273 families (p = 0.0172). Furthermore, three SNPs (rs10975990, rs10758821 and rs1407862) within KDM4C gene at 9p24.1 showed p<10 -4 (p = 7.15 × 10 -6, 2.79 × 10 -5 and 4.93 × 10 -5, respectively) in the COGA sample while one SNP rs12001158 within KDM4C with p = 1.97 × 10 -4 in the COGA sample was replicated in the family sample (p = 0.01). Haplotype analysis further supported the associations of single-marker analyses of KDM4C in the COGA sample. Moreover, two SNPs (rs2046593 and rs10497668) near FSIP2 at 2q32.1 with moderate associations with AWS in the COGA sample (p = 2.66 × 10 -4 and 9.48 × 10 -5, respectively) were replicated in the family sample (p = 0.0013 and 0.0162, respectively). In addition, several SNPs in GABRA1, GABRG1, and GABRG3 were associated with AWS (p<10 -2) in the COGA sample. In conclusion, we identified several loci associated with AWS. These findings offer the potential for new insights into the pathogenesis of AD and AWS.

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.

Background: Major depressive disorder (MDD) is a universally prevalent, genetic, and environment dependent mental condition that disables people of every culture, race, gender, and age. While the gender differences for MDD have been widely reported in literature, few genome-wide analyses of gender differences have been reported to date. Methods: We conducted a genome-wide association analysis of gender differences for MDD using the Netherlands NESDA and NTR population-based samples (1726 cases and 1630 controls). PLINK software was used to analyze the genome-wide association data of Perlegen 600 K SNP Chips. Results: We identified 40 male-specific and 56 female-specific MDD associated SNPs with P-values less than 10- 4. The best male-specific SNP was rs9352774 (P = 2.26 × 10- 6) within LGSN gene while the best female-specific SNP was rs2715148 (P = 5.64 × 10- 7) within PCLO gene. We also found 38 SNPs showing gene × gender interactions in influencing MDD (P < 10- 4). The best SNP was rs12692709 (P = 5.75 × 10- 6) near FIGN gene at 2q24.3 while the next best SNP was rs11039588 (P = 1.16 × 10- 5) within OR4B1 gene. Limitations: The findings from this study need be replicated in other populations. Conclusions: These results provide genetic basis for gender differences in MDD and will serve as a resource for replication in other populations to elucidate the potential role of these genetic variants in MDD.

Family, twin, and adoption studies have indicated that human intelligence quotient (IQ) has significant genetic components. We performed a low-density genome-wide association analysis with a family-based association test to identify genetic variants influencing IQ, as measured by Wechsler Adult Intelligence Scale full-score IQ (FSIQ). We examined 11,120 single-nucleotide polymorphisms (SNPs) from the Affymetrix GeneChips 10K mapping array genotyped in 292 nuclear families from Genetic Analysis Workshop 14, a subset from the Collaborative Study on the Genetics of Alcoholism (COGA). A replication analysis was performed using part of International Multi-Center ADHD Genetics Project (IMAGE) dataset. Twenty-two SNPs were identified as having suggestive associations with IQ (p<10-3) in the COGA sample and eleven of the SNPs were located within known genes. In particular, NTM at 11q25 (rs411280, p=0.000764) and NR3C2 at 4q31.1 (rs3846329, p=0.000675) were two novel genes which have not been associated with IQ in other studies. It has been reported that NTM might play a role in late-onset Alzheimer disease while NR3C2 may be associated with cognitive function and major depression. The associations of these two genes were well-replicated by single-marker and haplotype analyses in the IMAGE sample. In conclusion, our findings provide evidence that chromosome regions of 11q25 and 4q31.1 contain genes affecting IQ. This study will serve as a resource for replication in other populations.

We performed a genome-wide association analysis to identify genetic variants influencing age at onset (AAO) and examine gene×gender interactions for AAO in schizophrenia (SCZ) using a European-American sample (1,162 cases). Linear regression model in PLINK was used to test for associations with AAO while the GxE option was chosen to test for the influence of gene×gender interactions. The most significant association with AAO was observed with SNP rs7819815 (P=3.10×10-7) at 8q24.22. The next best signal was at 4q25 in COL25A1 gene (rs17039583, P=4.30×10-6) and the third region was at 4p16.1 (rs17407555, P=4.56×10-6, near RAF1P1, and rs4697924, P=1.23×10-5 within WDR1 gene). Conditional analysis on chromosome 4 indicated that 4p16.1 and 4q25 loci were independent. Furthermore, 2 SNPs (rs16834822 and rs16834824) at 1q43 in RYR2 showed strong associations in the female sample (P=2.10×10-6 and 2.33×10-6, respectively) and strong gene×gender interactions in influencing AAO (P=9.23×10-7 and 1.15×10-6, respectively) while the second best region showing gene×gender interaction was at 7q22.3 (rs179863, P=2.33×10-6). Using an independent sample of 1,068 cases, we could not replicate the associations for above top SNPs; however, we found nominal significance associations for their flanking SNPs (P<0.05). These findings provide evidence of several genetic variants influencing AAO of SCZ.

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.