NKAIN1-SERINC2 is a functional, replicable and genome-wide significant risk gene region specific for alcohol dependence in subjects of European descent

NKAIN1, as an oncogene, promotes the proliferation and metastasis of breast cancer, affecting its prognosis

Na, K-ATPase interaction (NKAIN) is a transmembrane protein family, which can interact with Na, K-ATPase β1 subunit. NKAIN1 plays an important role in alcohol-dependent diseases such as endometrial and prostate cancers. However, the relationship between NKAIN1 and human breast cancer has not been studied. Hence, this study aimed to explore the relationship between NKAIN1 expression and breast cancer. Data used in this study were mainly from the Cancer Genome Atlas, including differential expression analysis, Kaplan-Meier survival analysis, receiver operating characteristic curve analysis, multiple Cox regression analysis, co-expression gene analysis, and gene set enrichment analysis. Analyses were performed using reverse transcription-quantitative polymerase chain reaction, western blot analysis, and immunohistochemistry on 46 collected samples. The knockdown or overexpression of NKAIN1 in vitro in MCF-7 and MDA-MB-231 cell lines altered the proliferation and migration abilities of tumor cells. In vivo experiments further confirmed that NKAIN1 knockdown effectively inhibited the proliferation and migration of cancer cells. Therefore, our study identified NKAIN1 as an oncogene that is highly expressed in breast cancer tissues. The findings highlight the potential of NKAIN1 as a molecular biomarker of breast cancer.

Genetic architecture of alcohol consumption identified by a genotype-stratified GWAS and impact on esophageal cancer risk in Japanese people

An East Asian-specific variant on aldehyde dehydrogenase 2 (ALDH2 rs671, G>A) is the major genetic determinant of alcohol consumption. We performed an rs671 genotype-stratified genome-wide association study meta-analysis of alcohol consumption in 175,672 Japanese individuals to explore gene-gene interactions with rs671 behind drinking behavior. The analysis identified three genome-wide significant loci (GCKR, KLB, and ADH1B) in wild-type homozygotes and six (GCKR, ADH1B, ALDH1B1, ALDH1A1, ALDH2, and GOT2) in heterozygotes, with five showing genome-wide significant interaction with rs671. Genetic correlation analyses revealed ancestry-specific genetic architecture in heterozygotes. Of the discovered loci, four (GCKR, ADH1B, ALDH1A1, and ALDH2) were suggested to interact with rs671 in the risk of esophageal cancer, a representative alcohol-related disease. Our results identify the genotype-specific genetic architecture of alcohol consumption and reveal its potential impact on alcohol-related disease risk.

Common and distinguishing genetic factors for substance use behavior and disorder: an integrated analysis of genomic and transcriptomic studies from both human and animal studies

BACKGROUND AND AIMS

Genomic and transcriptomic findings greatly broaden the biological knowledge regarding substance use. However, systematic convergence and comparison evidence of genome-wide findings is lacking for substance use. Here, we combined all the genome-wide findings from both substance use behavior and disorder (SUBD) and identified common and distinguishing genetic factors for different SUBDs.

METHODS

Systemic literature search for genome-wide association (GWAS) and RNA-seq studies of alcohol/nicotine/drug use behavior (partially meets or not reported diagnostic criteria) and alcohol use behavior and disorder (AUBD), nicotine use behavior and disorder (NUBD) and drug use behavior and disorder (DUBD) was performed using PubMed and the GWAS catalog. Drug use was focused upon cannabis, opioid, cocaine and methamphetamine use. GWAS studies required case-control or case/cohort samples. RNA-seq studies were based on brain tissues. The genes which contained significant single nucleotide polymorphism (P ≤ 1 × 10^-6 ) in GWAS and reported as significant in RNA-seq studies were extracted. Pathway enrichment was performed by using Metascape. Gene interaction networks were identified by using the Protein Interaction Network Analysis database.

RESULTS

Total SUBD-related 2910 genes were extracted from 75 GWAS studies (2 773 889 participants) and 17 RNA-seq studies. By overlapping the genes and pathways of AUBD, NUBD and DUBD, four shared genes (CACNB2, GRIN2B, PLXDC2 and PKNOX2), four shared pathways [two Gene Ontology (GO) terms of 'modulation of chemical synaptic transmission', 'regulation of trans-synaptic signaling', two Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways of 'dopaminergic synapse', 'cocaine addiction'] were identified (significantly higher than random, P < 1 × 10^-5 ). The top shared KEGG pathways (Benjamini-Hochberg-corrected P-value < 0.05) in the pairwise comparison of AUBD versus DUBD, NUBD versus DUBD, AUBD versus NUBD were 'Epstein-Barr virus infection', 'protein processing in endoplasmic reticulum' and 'neuroactive ligand-receptor interaction', respectively. We also identified substance-specific genetic factors: i.e. ADH1B and ALDH2 were unique for AUBD, while CHRNA3 and CHRNA4 were unique for NUBD.

CONCLUSIONS

This systematic review identifies the shared and unique genes and pathways for alcohol, nicotine and drug use behaviors and disorders at the genome-wide level and highlights critical biological processes for the common and distinguishing vulnerability of substance use behaviors and disorders.

Effects of stressful life-events on DNA methylation in panic disorder and major depressive disorder

BACKGROUND

Panic disorder (PD) is characterized by recurrent panic attacks and higher affection of women as compared to men. The lifetime prevalence of PD is about 2-3% in the general population leading to tremendous distress and disability. Etiologically, genetic and environmental factors, such as stress, contribute to the onset and relapse of PD. In the present study, we investigated epigenome-wide DNA methylation (DNAm) in respond to a cumulative, stress-weighted life events score (wLE) in patients with PD and its boundary to major depressive disorder (MDD), frequently co-occurring with symptoms of PD.

METHODS

DNAm was assessed by the Illumina HumanMethylation450 BeadChip. In a meta-analytic approach, epigenome-wide DNAm changes in association with wLE were first analyzed in two PD cohorts (with a total sample size of 183 PD patients and 85 healthy controls) and lastly in 102 patients with MDD to identify possible overlapping and opposing effects of wLE on DNAm. Additionally, analysis of differentially methylated regions (DMRs) was conducted to identify regional clusters of association.

RESULTS

Two CpG-sites presented with p-values below 1 × 10^-05 in PD: cg09738429 (p = 6.40 × 10^-06, located in an intergenic shore region in next proximity of PYROXD1) and cg03341655 (p = 8.14 × 10^-06, located in the exonic region of GFOD2). The association of DNAm at cg03341655 and wLE could be replicated in the independent MDD case sample indicating a diagnosis independent effect. Genes mapping to the top hits were significantly upregulated in brain and top hits have been implicated in the metabolic system. Additionally, two significant DMRs were identified for PD only on chromosome 10 and 18, including CpG-sites which have been reported to be associated with anxiety and other psychiatric phenotypes.

CONCLUSION

This first DNAm analysis in PD reveals first evidence of small but significant DNAm changes in PD in association with cumulative stress-weighted life events. Most of the top associated CpG-sites are located in genes implicated in metabolic processes supporting the hypothesis that environmental stress contributes to health damaging changes by affecting a broad spectrum of systems in the body.

SERINC2 increases the risk of bipolar disorder in the Chinese population

BACKGROUND

Although common variants in a large collection of patients are associated with increased risk for bipolar disorder (BD), studies have only been able to predict 25%-45% of risks, suggesting that lots of variants that contribute to the risk for BD haven't been identified. Our study aims to identify novel BD risk genes.

METHODS

We performed whole-exome sequencing of 27 individuals from 6 BD multi-affected Chinese families to identify candidate variants. Targeted sequencing of one of the novel risk genes, SERINC2, in additional sporadic 717 BD patients and 312 healthy controls (HC) validated the association. Magnetic resonance imaging (MRI) were performed to evaluate the effect of the variant to brain structures from 213 subjects (4 BD subjects from a multi-affected family, 130 sporadic BD subjects and 79 HC control).

RESULTS

BD pedigrees had an increased burden of uncommon variants in extracellular matrix (ECM) and calcium ion binding. By large-scale sequencing we identified a novel recessive BD risk gene, SERINC2, which plays a role in synthesis of sphingolipid and phosphatidylserine (PS). MRI image results show the homozygous nonsense variant in SERINC2 affects the volume of white matter in cerebellum.

CONCLUSIONS

Our study identified SERINC2 as a risk gene of BD in the Chinese population.

CNS genomic profiling in the mouse chronic social stress model implicates a novel category of candidate genes integrating affective pathogenesis

Despite high prevalence, medical impact and societal burden, anxiety, depression and other affective disorders remain poorly understood and treated. Clinical complexity and polygenic nature complicate their analyses, often revealing genetic overlap and cross-disorder heritability. However, the interplay or overlaps between disordered phenotypes can also be based on shared molecular pathways and 'crosstalk' mechanisms, which themselves may be genetically determined. We have earlier predicted (Kalueff et al., 2014) a new class of 'interlinking' brain genes that do not affect the disordered phenotypes per se, but can instead specifically determine their interrelatedness. To test this hypothesis experimentally, here we applied a well-established rodent chronic social defeat stress model, known to progress in C57BL/6J mice from the Anxiety-like stage on Day 10 to Depression-like stage on Day 20. The present study analyzed mouse whole-genome expression in the prefrontal cortex and hippocampus during the Day 10, the Transitional (Day 15) and Day 20 stages in this model. Our main question here was whether a putative the Transitional stage (Day 15) would reveal distinct characteristic genomic responses from Days 10 and 20 of the model, thus reflecting unique molecular events underlining the transformation or switch from anxiety to depression pathogenesis. Overall, while in the Day 10 (Anxiety) group both brain regions showed major genomic alterations in various neurotransmitter signaling pathways, the Day 15 (Transitional) group revealed uniquely downregulated astrocyte-related genes, and the Day 20 (Depression) group demonstrated multiple downregulated genes of cell adhesion, inflammation and ion transport pathways. Together, these results reveal a complex temporal dynamics of mouse affective phenotypes as they develop. Our genomic profiling findings provide first experimental support to the idea that novel brain genes (activated here only during the Transitional stage) may uniquely integrate anxiety and depression pathogenesis and, hence, determine the progression from one pathological state to another. This concept can potentially be extended to other brain conditions as well. This preclinical study also further implicates cilial and astrocytal mechanisms in the pathogenesis of affective disorders.

Discovering weaker genetic associations guided by known associations

Background

The current understanding of the genetic basis of complex human diseases is that they are caused and affected by many common and rare genetic variants. A considerable number of the disease-associated variants have been identified by Genome Wide Association Studies, however, they can explain only a small proportion of heritability. One of the possible reasons for the missing heritability is that many undiscovered disease-causing variants are weakly associated with the disease. This can pose serious challenges to many statistical methods, which seems to be only capable of identifying disease-associated variants with relatively stronger coefficients.

Results

In order to help identify weaker variants, we propose a novel statistical method, Constrained Sparse multi-locus Linear Mixed Model (CS-LMM) that aims to uncover genetic variants of weaker associations by incorporating known associations as a prior knowledge in the model. Moreover, CS-LMM accounts for polygenic effects as well as corrects for complex relatednesses. Our simulation experiments show that CS-LMM outperforms other competing existing methods in various settings when the combinations of MAFs and coefficients reflect different scenarios in complex human diseases.

Conclusions

We also apply our method to the GWAS data of alcoholism and Alzheimer’s disease and exploratively discover several SNPs. Many of these discoveries are supported through literature survey. Furthermore, our association results strengthen the belief in genetic links between alcoholism and Alzheimer’s disease.

Genetic determinants of beverage consumption: Implications for nutrition and health

Beverages make important contributions to nutritional intake and their role in health has received much attention. This review focuses on the genetic determinants of common beverage consumption and how research in this field is contributing insight to what and how much we consume and why this genetic knowledge matters from a research and public health perspective. The earliest efforts in gene-beverage behavior mapping involved genetic linkage and candidate gene analysis but these approaches have been largely replaced by genome-wide association studies (GWAS). GWAS have identified biologically plausible loci underlying alcohol and coffee drinking behavior. No GWAS has identified variants specifically associated with consumption of tea, juice, soda, wine, beer, milk or any other common beverage. Thus far, GWAS highlight an important behavior-reward component (as opposed to taste) to beverage consumption which may serve as a potential barrier to dietary interventions. Loci identified have been used in Mendelian randomization and gene×beverage interaction analysis of disease but results have been mixed. This research is necessary as it informs the clinical relevance of SNP-beverage associations and thus genotype-based personalized nutrition, which is gaining interest in the commercial and public health sectors.

Shared additive genetic variation for alcohol dependence among subjects of African and European ancestry

Alcohol dependence (AD) affects individuals from all racial/ethnic groups, and previous research suggests that there is considerable variation in AD risk between and among various ancestrally defined groups in the United States. Although the reasons for these differences are likely due in part to contributions of complex sociocultural factors, limited research has attempted to examine whether similar genetic variation plays a role across ancestral groups. Using a pooled sample of individuals of African and European ancestry (AA/EA) obtained through data shared within the Database for Genotypes and Phenotypes, we estimated the extent to which additive genetic similarity for AD between AA and EAs using common single nucleotide polymorphisms overlapped across the two populations. AD was represented as a factor score by using Diagnostic and Statistical Manual dependence criteria, and genetic data were imputed by using the 1000 Genomes Reference Panel. Analyses revealed a significant single nucleotide polymorphism-based heritability of 17 percent (SE = 5) in EAs and 24 percent (SE = 15) in AAs. Further, a significant genetic correlation of 0.77 (SE = 0.46) suggests that the allelic architecture influencing the AD factor for EAs and AAs is largely similar across the two populations. Analyses indicated that investigating the genetic underpinnings of alcohol dependence in different ethnic groups may serve to highlight core etiological factors common to both groups and unique etiological factors specific to each ethnic group.

Peripheral Acid Sphingomyelinase Activity Is Associated with Biomarkers and Phenotypes of Alcohol Use and Dependence in Patients and Healthy Controls

By catalyzing the hydrolysis of sphingomyelin into ceramide, acid sphingomyelinase (ASM) changes the local composition of the plasma membrane with effects on receptor-mediated signaling. Altered enzyme activities have been noted in common human diseases, including alcohol dependence. However, the underlying mechanisms remain largely unresolved. Blood samples were collected from early-abstinent alcohol-dependent in-patients (n[♂] = 113, n[♀] = 87) and matched healthy controls (n[♂] = 133, n[♀] = 107), and analyzed for routine blood parameters and serum ASM activity. We confirmed increased secretory ASM activities in alcohol-dependent patients compared to healthy control subjects, which decreased slightly during detoxification. ASM activity correlated positively with blood alcohol concentration, withdrawal severity, biomarkers of alcohol dependence (liver enzyme activities of gamma-glutamyl transferase, alanine aminotransferase, aspartate aminotransferase; homocysteine, carbohydrate-deficient transferrin; mean corpuscular volume, and creatine kinase). ASM activity correlated negatively with leukocyte and thrombocyte counts. ASM and gamma-glutamyl transferase were also associated in healthy subjects. Most effects were similar for males and females with different strengths. We describe previously unreported associations between ASM activity and markers of liver damage and myelosuppression. Further research should investigate whether this relationship is causal, or whether these parameters are part of a common pathway in order to gain insights into underlying mechanisms and develop clinical applications.

Human Genetics of Addiction: New Insights and Future Directions

PURPOSE OF REVIEW

With the advent of the genome-wide association study (GWAS), our understanding of the genetics of addiction has made significant strides forward. Here, we summarize genetic loci containing variants identified at genome-wide statistical significance (P < 5 × 10-8) and independently replicated, review evidence of functional or regulatory effects for GWAS-identified variants, and outline multi-omics approaches to enhance discovery and characterize addiction loci.

RECENT FINDINGS

Replicable GWAS findings span 11 genetic loci for smoking, eight loci for alcohol, and two loci for illicit drugs combined and include missense functional variants and noncoding variants with regulatory effects in human brain tissues traditionally viewed as addiction-relevant (e.g., prefrontal cortex [PFC]) and, more recently, tissues often overlooked (e.g., cerebellum). GWAS analyses have discovered several novel, replicable variants contributing to addiction. Using larger sample sizes from harmonized datasets and new approaches to integrate GWAS with multiple 'omics data across human brain tissues holds great promise to significantly advance our understanding of the biology underlying addiction.

Chromosomal microarray analysis in a cohort of underrepresented population identifies SERINC2 as a novel candidate gene for autism spectrum disorder

Chromosomal microarray (CMA) is now recognized as the first-tier genetic test for detection of copy number variations (CNVs) in patients with autism spectrum disorder (ASD). The aims of this study were to identify known and novel ASD associated-CNVs and to evaluate the diagnostic yield of CMA in Thai patients with ASD. The Infinium CytoSNP-850K BeadChip was used to detect CNVs in 114 Thai patients comprised of 68 retrospective ASD patients (group 1) with the use of CMA as a second line test and 46 prospective ASD and developmental delay patients (group 2) with the use of CMA as the first-tier test. We identified 7 (6.1%) pathogenic CNVs and 22 (19.3%) variants of uncertain clinical significance (VOUS). A total of 29 patients with pathogenic CNVs and VOUS were found in 22% (15/68) and 30.4% (14/46) of the patients in groups 1 and 2, respectively. The difference in detected CNV frequencies between the 2 groups was not statistically significant (Chi square = 1.02, df = 1, P = 0.31). In addition, we propose one novel ASD candidate gene, SERINC2, which warrants further investigation. Our findings provide supportive evidence that CMA studies using population-specific reference databases in underrepresented populations are useful for identification of novel candidate genes.

Deep Sequencing of 71 Candidate Genes to Characterize Variation Associated with Alcohol Dependence

BACKGROUND

Previous genomewide association studies (GWASs) have identified a number of putative risk loci for alcohol dependence (AD). However, only a few loci have replicated and these replicated variants only explain a small proportion of AD risk. Using an innovative approach, the goal of this study was to generate hypotheses about potentially causal variants for AD that can be explored further through functional studies.

METHODS

We employed targeted capture of 71 candidate loci and flanking regions followed by next-generation deep sequencing (mean coverage 78X) in 806 European Americans. Regions included in our targeted capture library were genes identified through published GWAS of alcohol, all human alcohol and aldehyde dehydrogenases, reward system genes including dopaminergic and opioid receptors, prioritized candidate genes based on previous associations, and genes involved in the absorption, distribution, metabolism, and excretion of drugs. We performed single-locus tests to determine if any single variant was associated with AD symptom count. Sets of variants that overlapped with biologically meaningful annotations were tested for association in aggregate.

RESULTS

No single, common variant was significantly associated with AD in our study. We did, however, find evidence for association with several variant sets. Two variant sets were significant at the q-value <0.10 level: a genic enhancer for ADHFE1 (p = 1.47 × 10^-5 ; q = 0.019), an alcohol dehydrogenase, and ADORA1 (p = 5.29 × 10^-5 ; q = 0.035), an adenosine receptor that belongs to a G-protein-coupled receptor gene family.

CONCLUSIONS

To our knowledge, this is the first sequencing study of AD to examine variants in entire genes, including flanking and regulatory regions. We found that in addition to protein coding variant sets, regulatory variant sets may play a role in AD. From these findings, we have generated initial functional hypotheses about how these sets may influence AD.

The genetics of alcohol dependence: Twin and SNP-based heritability, and genome-wide association study based on AUDIT scores

Alcohol dependence (AD) is among the most common and costly public health problems contributing to morbidity and mortality throughout the world. In this study, we investigate the genetic basis of AD in a Dutch population using data from the Netherlands Twin Register (NTR) and the Netherlands Study of Depression and Anxiety (NESDA). The presence of AD was ascertained via the Alcohol Use Disorders Identification Test (AUDIT) applying cut-offs with good specificity and sensitivity in identifying those at risk for AD. Twin-based heritability of AD-AUDIT was estimated using structural equation modeling of data in 7,694 MZ and DZ twin pairs. Variance in AD-AUDIT explained by all SNPs was estimated with genome-wide complex trait analysis (GCTA). A genome-wide association study (GWAS) was performed in 7,842 subjects. GWAS SNP effect concordance analysis was performed between our GWAS and a recent AD GWAS using DSM-IV diagnosis. The twin-based heritability of AD-AUDIT was estimated at 60% (55-69%). GCTA showed that common SNPs jointly capture 33% (SE = 0.12, P = 0.002) of this heritability. In the GWAS, the top hits were positioned within four regions (4q31.1, 2p16.1, 6q25.1, 7p14.1) with the strongest association detected for rs55768019 (P = 7.58 × 10(-7) ). This first GWAS of AD using the AUDIT measure found results consistent with previous genetic studies using DSM diagnosis: concordance in heritability estimates and direction of SNPs effect and overlap with top hits from previous GWAS. Thus, the use of appropriate questionnaires may represent cost-effective strategies to phenotype samples in large-scale biobanks or other population-based datasets.

Sex difference of autosomal alleles in populations of European and African descent

In the present study, we aimed to report the individual sex-different genetic markers across autosomes in European- and African-origin populations. A total of 8,400 females and 8,081 males in 19 independent cohorts were genotyped across genomes using Illumina or Affymetrix arrays. The allele frequencies were compared between females and males in 9 non-clean cohorts (with some human disease traits) using genome-wide logistic regression and then the nominally significant associations were replicated across 10 clean cohorts (without disease traits). Meta-analysis was performed to derive the combined p values across all cohorts. We found 13 markers that were genome-wide significant (p≤5×10-8) between females and males in the meta-analysis of all cohorts of European descent, including rs7740449 at SYNE1, rs7531151 at PLD5, rs697455 at PPP1R12B, rs6745746 at LOC100128413, rs17000079 at PARM1, rs11948070 at PDE4D, rs7801825 at INSIG1, rs9551642 at MTUS2, rs2932174 at TPTE2, rs1961597 at SALL3, rs4117529 at METTL4, rs6021473 at SALL4 and rs6092466 at RAE1, and one marker, i.e., rs10145208 at PCNX, that was genome-wide significant in the meta-analysis of all cohorts of African descent. The most robust finding was rs7740449 at SYNE1, next to ESR1. We conclude that there are many sex-different markers on autosomes. These markers may be informative in differentiating females and males.

An Efficient Stepwise Statistical Test to Identify Multiple Linked Human Genetic Variants Associated with Specific Phenotypic Traits

Recent advances in genotyping methodologies have allowed genome-wide association studies (GWAS) to accurately identify genetic variants that associate with common or pathological complex traits. Although most GWAS have focused on associations with single genetic variants, joint identification of multiple genetic variants, and how they interact, is essential for understanding the genetic architecture of complex phenotypic traits. Here, we propose an efficient stepwise method based on the Cochran-Mantel-Haenszel test (for stratified categorical data) to identify causal joint multiple genetic variants in GWAS. This method combines the CMH statistic with a stepwise procedure to detect multiple genetic variants associated with specific categorical traits, using a series of associated I × J contingency tables and a null hypothesis of no phenotype association. Through a new stratification scheme based on the sum of minor allele count criteria, we make the method more feasible for GWAS data having sample sizes of several thousands. We also examine the properties of the proposed stepwise method via simulation studies, and show that the stepwise CMH test performs better than other existing methods (e.g., logistic regression and detection of associations by Markov blanket) for identifying multiple genetic variants. Finally, we apply the proposed approach to two genomic sequencing datasets to detect linked genetic variants associated with bipolar disorder and obesity, respectively.

A New Genomewide Association Meta-Analysis of Alcohol Dependence

BACKGROUND

Conventional meta-analysis based on genetic markers may be less powerful for heterogeneous samples. In this study, we introduced a new meta-analysis for 4 genomewide association studies on alcohol dependence that integrated the information of putative causal variants.

METHODS

A total of 12,481 subjects in 4 independent cohorts were analyzed, including 1 European American cohort (1,409 cases with alcohol dependence and 1,518 controls), 1 European Australian cohort (a total of 6,438 family subjects with 1,645 probands), 1 African American cohort from SAGE + COGA (681 cases and 508 controls), and 1 African American cohort from Yale (1,429 cases and 498 controls). The genomewide association analysis was conducted for each cohort, and then, a new meta-analysis was performed to derive the combined p-values. cis-Acting expression of quantitative locus (cis-eQTL) analysis of each risk variant in human tissues and RNA expression analysis of each risk gene in rat brain served as functional validation.

RESULTS

In meta-analysis of European American and European Australian cohorts, we found 10 top-ranked single nucleotide polymorphisms (SNPs) (p < 10(-6) ) that were associated with alcohol dependence. They included 6 at SERINC2 (3.1 × 10(-8) ≤ p ≤ 9.6 × 10(-8) ), 1 at STK40 (p = 1.3 × 10(-7) ), 2 at KIAA0040 (3.3 × 10(-7) ≤ p ≤ 5.2 × 10(-7) ), and 1 at IPO11 (p = 6.9 × 10(-7) ). In meta-analysis of 2 African American cohorts, we found 2 top-ranked SNPs including 1 at SLC6A11 (p = 2.7 × 10(-7) ) and 1 at CBLN2 (p = 7.4 × 10(-7) ). In meta-analysis of all 4 cohorts, we found 2 top-ranked SNPs in PTP4A1-PHF3 locus (6.0 × 10(-7) ≤ p ≤ 7.2 × 10(-7) ). In an African American cohort only, we found 1 top-ranked SNP at PLD1 (p = 8.3 × 10(-7) ; OR = 1.56). Many risk SNPs had positive cis-eQTL signals, and all these risk genes except KIAA0040 were found to express in both rat and mouse brains.

CONCLUSIONS

We found multiple genes that were significantly or suggestively associated with alcohol dependence. They are among the most appropriate for follow-up as contributors to risk for alcohol dependence.

Genetics of alcohol dependence: a review of clinical studies

BACKGROUND/AIMS

Alcohol dependence is a common severe psychiatric disorder with a multifactorial etiology. Since the completion of the human genome project and with the increased availability of high-throughput genotyping, multiple genetic risk factors for substance-related disorders, including alcohol dependence, have been identified, but not all results could be replicated.

METHODS

We systematically review the clinical literature on genetic risk factors for alcohol dependence and alcohol-related phenotypes, including candidate gene-based studies, linkage studies and genome-wide association studies (GWAS).

RESULTS

Irrespectively of the methodology employed, the most robust findings regarding genetic risk factors for alcohol dependence concern genetic variations that affect alcohol metabolism. GWAS confirm the importance of the alcohol dehydrogenase gene cluster on chromosome 4 in the genetic risk for alcohol dependence with multiple variants that exert a small, but cumulative influence. A single variant with strong influence on individual risk is the aldehyde dehydrogenase 2 ALDHD2*2 variant common in Asian populations. Other robust associations have been found with previously uncharacterized genes like KIAA0040, and such observations can lead to the identification of thus far unknown signaling pathways. Converging evidence also points to a role of glutamatergic, dopaminergic and serotonergic neurotransmitter signaling in the risk for alcohol dependence, but effects are small, and gene-environment interactions further increase the complexity.

CONCLUSION

With few exceptions like ALDH2*2, the contribution of individual genetic variants to the risk for alcohol-related disorders is small. However, the concentration of risk variants within neurotransmitter signaling pathways may help to deepen our understanding of the underlying pathophysiology and thereby contribute to develop novel therapeutic strategies.

Gene-based and pathway-based genome-wide association study of alcohol dependence

BACKGROUND

The organization of risk genes within signaling pathways may provide clues about the converging neurobiological effects of risk genes for alcohol dependence.

AIM

Identify risk genes and risk gene pathways for alcohol dependence.

METHODS

We conducted a pathway-based genome-wide association study (GWAS) of alcohol dependence using a gene-set-rich analytic approach. Approximately one million genetic markers were tested in the discovery sample which included 1409 European-American (EA) alcohol dependent individuals and 1518 EA healthy comparison subjects. An additional 681 African-American (AA) cases and 508 AA healthy subjects served as the replication sample.

RESULTS

We identified several genome-wide replicable risk genes and risk pathways that were significantly associated with alcohol dependence. After applying the Bonferroni correction for multiple testing, the 'cellextracellular matrix interactions' pathway (p<2.0E-4 in EAs) and the PXN gene (which encodes paxillin) (p=3.9E-7 in EAs) within this pathway were the most promising risk factors for alcohol dependence. There were also two nominally replicable pathways enriched in alcohol dependence-related genes in both EAs (0.015≤p≤0.035) and AAs (0.025≤p≤0.050): the 'Na+/Cl- dependent neurotransmitter transporters' pathway and the 'other glycan degradation' pathway.

CONCLUSION

These findings provide new evidence highlighting several genes and biological signaling processes that may be related to the risk for alcohol dependence.

Clinically relevant genetic biomarkers from the brain in alcoholism with representation on high resolution chromosome ideograms

OBJECTIVE

Alcoholism arises from combined effects of multiple biological factors including genetic and non-genetic causes with gene/environmental interaction. Intensive research and advanced genetic technology has generated a long list of genes and biomarkers involved in alcoholism neuropathology. These markers reflect complex overlapping and competing effects of possibly hundreds of genes which impact brain structure, function, biochemical alcohol processing, sensitivity and risk for dependence.

METHOD

We compiled a tabular list of clinically relevant genetic biomarkers for alcoholism targeting expression disturbances in the human brain through an extensive search of keywords related to alcoholism, alcohol abuse, and genetics from peer reviewed medical research articles and related nationally sponsored websites. Gene symbols were then placed on high resolution human chromosome ideograms with gene descriptions in tabular form.

RESULTS

We identified 337 clinically relevant genetic biomarkers and candidate genes for alcoholism and alcohol-responsiveness from human brain research. Genetic biomarkers included neurotransmitter pathways associated with brain reward processes for dopaminergic (e.g., DRD2, MAOA, and COMT), serotoninergic (e.g., HTR3A, HTR1B, HTR3B, and SLC6A4), GABAergic (e.g., GABRA1, GABRA2, and GABRG1), glutaminergic (GAD1, GRIK3, and GRIN2C) and opioid (e.g., OPRM1, OPRD1, and OPRK1) pathways which presumably impact reinforcing properties of alcohol. Gene level disturbances in cellular and molecular networks impacted by alcohol and alcoholism pathology include transketolase (TKT), transferrin (TF), and myelin (e.g., MBP, MOBP, and MOG).

CONCLUSIONS

High resolution chromosome ideograms provide investigators, physicians, geneticists and counselors a convenient visual image of the distribution of alcoholism genetic biomarkers from brain research with alphabetical listing of genes in tabular form allowing comparison between alcoholism-related phenotypes, and clinically-relevant alcoholism gene(s) at the chromosome band level to guide research, diagnosis, and treatment. Chromosome ideograms may facilitate gene-based personalized counseling of alcohol dependent individuals and their families.

XRCC5 as a risk gene for alcohol dependence: evidence from a genome-wide gene-set-based analysis and follow-up studies in Drosophila and humans

Genetic factors have as large role as environmental factors in the etiology of alcohol dependence (AD). Although genome-wide association studies (GWAS) enable systematic searches for loci not hitherto implicated in the etiology of AD, many true findings may be missed owing to correction for multiple testing. The aim of the present study was to circumvent this limitation by searching for biological system-level differences, and then following up these findings in humans and animals. Gene-set-based analysis of GWAS data from 1333 cases and 2168 controls identified 19 significantly associated gene-sets, of which 5 could be replicated in an independent sample. Clustered in these gene-sets were novel and previously identified susceptibility genes. The most frequently present gene, ie in 6 out of 19 gene-sets, was X-ray repair complementing defective repair in Chinese hamster cells 5 (XRCC5). Previous human and animal studies have implicated XRCC5 in alcohol sensitivity. This phenotype is inversely correlated with the development of AD, presumably as more alcohol is required to achieve the desired effects. In the present study, the functional role of XRCC5 in AD was further validated in animals and humans. Drosophila mutants with reduced function of Ku80-the homolog of mammalian XRCC5-due to RNAi silencing showed reduced sensitivity to ethanol. In humans with free access to intravenous ethanol self-administration in the laboratory, the maximum achieved blood alcohol concentration was influenced in an allele-dose-dependent manner by genetic variation in XRCC5. In conclusion, our convergent approach identified new candidates and generated independent evidence for the involvement of XRCC5 in alcohol dependence.

Genome-wide association discoveries of alcohol dependence

OBJECTIVE

To report the genome-wide significant and/or replicable risk variants for alcohol dependence and explore their potential biological functions.

METHODS

We searched in PubMed for all genome-wide association studies (GWASs) of alcohol dependence. The following three types of the results were extracted: genome-wide significant associations in an individual sample, the combined samples, or the meta-analysis (p < 5 × 10(-8) ); top-ranked associations in an individual sample (p < 10(-5) ) that were nominally replicated in other samples (p < .05); and nominally replicable associations across at least three independent GWAS samples (p < .05). These results were meta-analyzed. cis-eQTLs in human, RNA expression in rat and mouse brains and bioinformatics properties of all of these risk variants were analyzed.

RESULTS

The variants located within the alcohol dehydrogenase (ADH) cluster were significantly associated with alcohol dependence at the genome-wide level (p < 5 × 10(-8) ) in at least one sample. Some associations with the ADH cluster were replicable across six independent GWAS samples. The variants located within or near SERINC2, KIAA0040, MREG-PECR or PKNOX2 were significantly associated with alcohol dependence at the genome-wide level (p < 5 × 10(-8) ) in meta-analysis or combined samples, and these associations were replicable across at least one sample. The associations with the variants within NRD1, GPD1L-CMTM8 or MAP3K9-PCNX were suggestive (5 × 10(-8)  < p < 10(-5) ) in some samples, and nominally replicable in other samples. The associations with the variants at HTR7 and OPA3 were nominally replicable across at least three independent GWAS samples (10(-5)  < p < .05). Some risk variants at the ADH cluster, SERINC2, KIAA0040, NRD1, and HTR7 had potential biological functions.

CONCLUSION

The most robust risk locus was the ADH cluster. SERINC2, KIAA0040, NRD1, and HTR7 were also likely to play important roles in alcohol dependence. PKNOX2, MREG, PECR, GPD1L, CMTM8, MAP3K9, PCNX, and OPA3 might play less important roles in risk for alcohol dependence based on the function analysis. This conclusion will significantly contribute to the post-GWAS follow-up studies on alcohol dependence.

Genetics and genomics of alcohol sensitivity

Alcohol abuse and alcoholism incur a heavy socioeconomic cost in many countries. Both genetic and environmental factors contribute to variation in the inebriating effects of alcohol and alcohol addiction among individuals within and across populations. From a genetics perspective, alcohol sensitivity is a quantitative trait determined by the cumulative effects of multiple segregating genes and their interactions with the environment. This review summarizes insights from model organisms as well as human populations that represent our current understanding of the genetic and genomic underpinnings that govern alcohol metabolism and the sedative and addictive effects of alcohol on the nervous system.

Genome-wide association study of alcohol dependence:significant findings in African- and European-Americans including novel risk loci

We report a GWAS of alcohol dependence (AD) in European-American (EA) and African-American (AA) populations, with replication in independent samples of EAs, AAs and Germans. Our sample for discovery and replication was 16 087 subjects, the largest sample for AD GWAS to date. Numerous genome-wide significant (GWS) associations were identified, many novel. Most associations were population specific, but in several cases were GWS in EAs and AAs for different SNPs at the same locus,showing biological convergence across populations. We confirmed well-known risk loci mapped to alcohol-metabolizing enzyme genes, notably ADH1B (EAs: Arg48His, P=1.17 × 10(-31); AAs: Arg369Cys, P=6.33 × 10(-17)) and ADH1C in AAs (Thr151Thr, P=4.94 × 10(-10)), and identified novel risk loci mapping to the ADH gene cluster on chromosome 4 and extending centromerically beyond it to include GWS associations at LOC100507053 in AAs (P=2.63 × 10(-11)), PDLIM5 in EAs (P=2.01 × 10(-8)), and METAP in AAs (P=3.35 × 10(-8)). We also identified a novel GWS association (1.17 × 10(-10)) mapped to chromosome 2 at rs1437396, between MTIF2 and CCDC88A, across all of the EA and AA cohorts, with supportive gene expression evidence, and population-specific GWS for markers on chromosomes 5, 9 and 19. Several of the novel associations implicate direct involvement of, or interaction with, genes previously identified as schizophrenia risk loci. Confirmation of known AD risk loci supports the overall validity of the study; the novel loci are worthy of genetic and biological follow-up. The findings support a convergence of risk genes (but not necessarily risk alleles) between populations, and, to a lesser extent, between psychiatric traits.

Rare SERINC2 variants are specific for alcohol dependence in individuals of European descent

OBJECTIVES

We have previously reported a top-ranked risk gene [i.e., serine incorporator 2 gene (SERINC2)] for alcohol dependence in individuals of European descent by analyzing the common variants in a genome-wide association study. In the present study, we comprehensively examined the rare variants [minor allele frequency (MAF)<0.05] in the NKAIN1-SERINC2 region to confirm our previous finding.

MATERIALS AND METHODS

A discovery sample (1409 European-American patients with alcohol dependence and 1518 European-American controls) and a replication sample (6438 European-Australian family participants with 1645 alcohol-dependent probands) were subjected to an association analysis. A total of 39,903 individuals from 19 other cohorts with 11 different neuropsychiatric and neurological disorders served as contrast groups. The entire NKAIN1-SERINC2 region was imputed in all cohorts using the same reference panels of genotypes that included rare variants from the whole-genome sequencing data. We stringently cleaned the phenotype and genotype data, and obtained a total of about 220 single-nucleotide polymorphisms in individuals of European descent and about 450 single-nucleotide polymorphisms in the individuals of African descent with 0

RESULTS

Using a weighted regression analysis implemented in the program SCORE-Seq, we found a rare variant constellation across the entire NKAIN1-SERINC2 region that was associated with alcohol dependence in European-Americans (Fp: overall, P=1.8×10(-4); VT: overall, P=1.4×10(-4); Collapsing, P=6.5×10(-5)) and European-Australians (Fp: overall, P=0.028; Collapsing, P=0.025), but not in African-Americans, and not associated with any other disorder examined. Association signals in this region came mainly from SERINC2, a gene that codes for an activity-regulated protein expressed in the brain that incorporates serine into lipids. In addition, 26 individual rare variants were nominally associated with alcohol dependence in European-Americans (P<0.05). The associations of five of these rare variants that lay within SERINC2 showed region-wide significance (P<α=0.0006) and 25 associations survived correction for a false discovery rate (q<0.05). The associations of two rare variants at SERINC2 were replicated in European-Australians (P<0.05).

CONCLUSION

We concluded that SERINC2 was a replicable and significant risk gene specific for alcohol dependence in individuals of European descent.

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Key Words

• serinc2
• alcohol dependence
• rare variant constellations
• european descent
• association

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MESH Headings

• Black or African American/genetics
• Alcoholism/complications
• Alcoholism/genetics
• Australia
• Case-Control Studies
• Genetic Association Studies
• Genetic Variation
• Genome-Wide Association Study
• Humans
• Membrane Proteins/genetics
• Mental Disorders/genetics
• Nervous System Diseases/genetics
• Polymorphism, Single Nucleotide
• Regression Analysis
• Risk Factors
• White People/genetics

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Grants

• R01 DA016750 NIDA NIH HHS
• R01NS45012 NINDS NIH HHS
• R01MH62873 NIMH NIH HHS
• R01MH59566 NIMH NIH HHS
• R01 MH059587 NIMH NIH HHS
• R01 MH059586 NIMH NIH HHS
• U01 HG004436 NHGRI NIH HHS
• R01 MH061675 NIMH NIH HHS
• U01HG004446 NHGRI NIH HHS
• U01MH79470 NIMH NIH HHS
• U01HG004438 NHGRI NIH HHS
• R01 MH062873 NIMH NIH HHS
• R01 NS045012 NINDS NIH HHS
• U01MH79469 NIMH NIH HHS
• U01 HG004438 NHGRI NIH HHS
• R01MH59588 NIMH NIH HHS
• U10AA008401 NIAAA NIH HHS
• U01 HG004446 NHGRI NIH HHS
• K01 DA029643 NIDA NIH HHS
• G0601030 Medical Research Council
• R01MH81800 NIMH NIH HHS
• R01MH61675 NIMH NIH HHS
• P50 AA011998 NIAAA NIH HHS
• 075491/Z/04 Wellcome Trust
• R01MH59571 NIMH NIH HHS
• U01 MH046276 NIMH NIH HHS
• R01MH59586 NIMH NIH HHS
• P01 CA089392 NCI NIH HHS
• R21 AA021380 NIAAA NIH HHS
• U01 MH079469 NIMH NIH HHS
• R01MH60870 NIMH NIH HHS
• R01MH059160 NIMH NIH HHS
• R01 MH081803 NIMH NIH HHS
• R01 MH067257 NIMH NIH HHS
• U01HG004422 NHGRI NIH HHS
• P60AA011998 NIAAA NIH HHS
• R01 MH060870 NIMH NIH HHS
• R01DA013423 NIDA NIH HHS
• R01MH081803 NIMH NIH HHS
• R01 MH059571 NIMH NIH HHS
• R01 MH059565 NIMH NIH HHS
• R01MH67257 NIMH NIH HHS
• R01DA016750 NIDA NIH HHS
• U01 HG004422 NHGRI NIH HHS
• R01MH60879 NIMH NIH HHS
• R01 DA013423 NIDA NIH HHS
• R01MH59587 NIMH NIH HHS
• U01 MH079470 NIMH NIH HHS
• U01 MH046289 NIMH NIH HHS
• U01HG004436 NHGRI NIH HHS
• R01 MH059566 NIMH NIH HHS
• R21 AA020319 NIAAA NIH HHS
• Wellcome Trust
• U10 AA008401 NIAAA NIH HHS
• R01AA013320 NIAAA NIH HHS
• R01 MH059588 NIMH NIH HHS
• U01 MH046318 NIMH NIH HHS
• R01MH59565 NIMH NIH HHS
• U01MH46282 NIMH NIH HHS
• M01RR165001 NCRR NIH HHS
• R01 MH060879 NIMH NIH HHS
• R01 AA013320 NIAAA NIH HHS
• R01 AA016015 NIAAA NIH HHS

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Affiliation(s)

Lingjun Zuo Department of Psychiatry, Yale University School of Medicine, New Haven, CT, USA
Ke-Sheng Wang Department of Biostatistics and Epidemiology, College of Public Health, East Tennessee State University, Johnson City, TN, USA
Xiang-Yang Zhang Menninger Department of Psychiatry and Behavioral Sciences, Baylor College of Medicine, Houston, Texas, USA
Chiang-Shan R. Li Department of Psychiatry, Yale University School of Medicine, New Haven, CT, USA
Fengyu Zhang Lieber Institute for Brain Development, Johns Hopkins University Medical Campus, Baltimore, MD, USA
Xiaoping Wang Department of Neurology, First People's Hospital, Shanghai Jiaotong University, Shanghai, China
Wenan Chen Department of Biostatistics, Virginia Commonwealth University, Richmond, VA, USA
Guimin Gao Department of Biostatistics, Virginia Commonwealth University, Richmond, VA, USA
Heping Zhang Department of Biostatistics, Yale University School of Epidemiology and Public Health, New Haven, CT, USA
John H. Krystal Department of Psychiatry, Yale University School of Medicine, New Haven, CT, USA Psychiatry Services, Yale-New Haven Hospital, New Haven, CT VA Alcohol Research Center, VA Connecticut Healthcare System, West Haven, CT
Xingguang Luo Department of Psychiatry, Yale University School of Medicine, New Haven, CT, USA

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