Multi-trait genome-wide association study of opioid addiction: OPRM1 and beyond.

Opioid addiction (OA) is moderately heritable, yet only rs1799971, the A118G variant in OPRM1, has been identified as a genome-wide significant association with OA and independently replicated. We applied genomic structural equation modeling to conduct a GWAS of the new Genetics of Opioid Addiction Consortium (GENOA) data together with published studies (Psychiatric Genomics Consortium, Million Veteran Program, and Partners Health), comprising 23,367 cases and effective sample size of 88,114 individuals of European ancestry. Genetic correlations among the various OA phenotypes were uniformly high (rg > 0.9). We observed the strongest evidence to date for OPRM1: lead SNP rs9478500 (p = 2.56 × 10-9). Gene-based analyses identified novel genome-wide significant associations with PPP6C and FURIN. Variants within these loci appear to be pleiotropic for addiction and related traits.

Retraction Note: 11,670 whole-genome sequences representative of the Han Chinese population from the CONVERGE project.

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

ALDH2*2 and peer drinking in East Asian college students.

BACKGROUND: The ALDH2*2 allele (A-allele) at rs671 is more commonly carried by Asians and is associated with alcohol-related flushing, a strong adverse reaction to alcohol that is protective against drinking. Social factors, such as having friends who binge drink, also contribute to drinking in Asian youth. OBJECTIVES: This study examined the interplay between ALDH2*2, peer drinking, and alcohol consumption in college students. We hypothesized that the relationship between ALDH2*2 and standard grams of ethanol per month would vary based on the level of peer drinking. METHODS: Subjects (N = 318, 63.25% female) were East Asian college students in the United States who reported drinking alcohol. Data were from the freshman year of a university survey that included a saliva DNA sample. ALDH2*2 status was coded ALDH2*2(+) (A/G and A/A genotypes) and ALDH2*2(-) (G/G genotype). Peer drinking was students' perception of how many of their friends "got drunk". RESULTS: Main effects of ALDH2*2(-) and having more friends who got drunk were associated with greater alcohol consumption. The ALDH2*2 × peer drunkenness interaction showed a stronger positive association with alcohol consumption for ALDH2*2(-) versus ALDH2*2(+) at increasing levels of peer drunkenness. Follow-up comparisons within each peer drunkenness level identified significantly higher alcohol consumption for ALDH2*2(-) compared to ALDH2*2(+) at the all friends got drunk level. CONCLUSION: There was evidence of a stronger effect for ALDH2*2(-) compared to ALDH2*2(+) with greater alcohol use when students were more exposed to peer drinking. Findings contribute to a growing literature on the interrelationships between genetic influences and more permissive environments for alcohol consumption.

11,670 whole-genome sequences representative of the Han Chinese population from the CONVERGE project.

The China, Oxford and Virginia Commonwealth University Experimental Research on Genetic Epidemiology (CONVERGE) project on Major Depressive Disorder (MDD) sequenced 11,670 female Han Chinese at low-coverage (1.7X), providing the first large-scale whole genome sequencing resource representative of the largest ethnic group in the world. Samples are collected from 58 hospitals from 23 provinces around China. We are able to call 22 million high quality single nucleotide polymorphisms (SNP) from the nuclear genome, representing the largest SNP call set from an East Asian population to date. We use these variants for imputation of genotypes across all samples, and this has allowed us to perform a successful genome wide association study (GWAS) on MDD. The utility of these data can be extended to studies of genetic ancestry in the Han Chinese and evolutionary genetics when integrated with data from other populations. Molecular phenotypes, such as copy number variations and structural variations can be detected, quantified and analysed in similar ways.

A simple yet accurate correction for winner's curse can predict signals discovered in much larger genome scans.

MOTIVATION: For genetic studies, statistically significant variants explain far less trait variance than 'sub-threshold' association signals. To dimension follow-up studies, researchers need to accurately estimate 'true' effect sizes at each SNP, e.g. the true mean of odds ratios (ORs)/regression coefficients (RRs) or Z-score noncentralities. Naïve estimates of effect sizes incur winner's curse biases, which are reduced only by laborious winner's curse adjustments (WCAs). Given that Z-scores estimates can be theoretically translated on other scales, we propose a simple method to compute WCA for Z-scores, i.e. their true means/noncentralities. RESULTS: WCA of Z-scores shrinks these towards zero while, on P-value scale, multiple testing adjustment (MTA) shrinks P-values toward one, which corresponds to the zero Z-score value. Thus, WCA on Z-scores scale is a proxy for MTA on P-value scale. Therefore, to estimate Z-score noncentralities for all SNPs in genome scans, we propose F: DR I: nverse Q: uantile T: ransformation (FIQT). It (i) performs the simpler MTA of P-values using FDR and (ii) obtains noncentralities by back-transforming MTA P-values on Z-score scale. When compared to competitors, realistic simulations suggest that FIQT is more (i) accurate and (ii) computationally efficient by orders of magnitude. Practical application of FIQT to Psychiatric Genetic Consortium schizophrenia cohort predicts a non-trivial fraction of sub-threshold signals which become significant in much larger supersamples. CONCLUSIONS: FIQT is a simple, yet accurate, WCA method for Z-scores (and ORs/RRs, via simple transformations). AVAILABILITY AND IMPLEMENTATION: A 10 lines R function implementation is available at https://github.com/bacanusa/FIQT CONTACT: sabacanu@vcu.edu SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

A genome-wide significant linkage for severe depression on chromosome 3: the depression network study.

OBJECTIVE: The purpose of this study was to find loci for major depression via linkage analysis of a large sibling pair sample. METHOD: The authors conducted a genome-wide linkage analysis of 839 families consisting of 971 affected sibling pairs with severe recurrent major depression, comprising waves I and II of the Depression Network Study cohort. In addition to examining affected status, linkage analyses in the full data set were performed using diagnoses restricted by impairment severity, and association mapping of hits in a large case-control data set was attempted. RESULTS: The authors identified genome-wide significant linkage to chromosome 3p25-26 when the diagnoses were restricted by severity, which was a maximum LOD score of 4.0 centered at the linkage marker D3S1515. The linkage signal identified was genome-wide significant after correction for the multiple phenotypes tested, although subsequent association mapping of the region in a genome-wide association study of a U.K. depression sample did not provide significant results. CONCLUSIONS: The authors report a genome-wide significant locus for depression that implicates genes that are highly plausible for involvement in the etiology of recurrent depression. Despite the fact that association mapping in the region was negative, the linkage finding was replicated by another group who found genome-wide-significant linkage for depression in the same region. This suggests that 3p25-26 is a new locus for severe recurrent depression. This represents the first report of a genome-wide significant locus for depression that also has an independent genome-wide significant replication.

High-resolution mass spectrometry proteomics for the identification of candidate plasma protein biomarkers for chronic obstructive pulmonary disease.

Although cigarette smoking is recognized as the most important cause of chronic obstructive pulmonary disease (COPD), the pathophysiological mechanisms underlying the lung function decline are not well understood. Using off-line strong cation exchange fractionation with RP-LC-ESI-MS/MS and robust database searching, 1758 tryptic peptides were identified in plasma samples from cigarette smokers. Using two statistical approaches, 30 peptides were identified to be associated with the annualized rate of lung function decline over 5 years among smokers with COPD characterized as having rapid (n = 18) or slow (n = 18) decline and 18 smokers without COPD. The identified peptides belong to proteins that are involved in the complement or coagulation systems or have antiprotease or metabolic functions. This research demonstrates the utility of proteomic profiling to improve the understanding of molecular mechanisms involved in cigarette smoking-related COPD by identifying plasma proteins that correlate with decline in lung function.

(1)H nuclear magnetic resonance metabolomics analysis identifies novel urinary biomarkers for lung function.

Chronic obstructive pulmonary disease (COPD), characterized by chronic airflow limitation, is a serious public health concern. In this study, we used proton nuclear magnetic resonance ((1)H NMR) spectroscopy to identify and quantify metabolites associated with lung function in COPD. Plasma and urine were collected from 197 adults with COPD and from 195 without COPD. Samples were assayed using a 600 MHz NMR spectrometer, and the resulting spectra were analyzed against quantitative spirometric measures of lung function. After correcting for false discoveries and adjusting for covariates (sex, age, smoking) several spectral regions in urine were found to be significantly associated with baseline lung function. These regions correspond to the metabolites trigonelline, hippurate and formate. Concentrations of each metabolite, standardized to urinary creatinine, were associated with baseline lung function (minimum p-value = 0.0002 for trigonelline). No significant associations were found with plasma metabolites. Urinary hippurate and formate are often related to gut microflora. This could suggest that the microbiome varies between individuals with different lung function. Alternatively, the associated metabolites may reflect lifestyle differences affecting overall health. Our results will require replication and validation, but demonstrate the utility of NMR metabolomics as a screening tool for identifying novel biomarkers of pulmonary outcomes.

In silico whole genome association scan for murine prepulse inhibition.

BACKGROUND: The complex trait of prepulse inhibition (PPI) is a sensory gating measure related to schizophrenia and can be measured in mice. Large-scale public repositories of inbred mouse strain genotypes and phenotypes such as PPI can be used to detect Quantitative Trait Loci (QTLs) in silico. However, the method has been criticized for issues including insufficient number of strains, not controlling for false discoveries, the complex haplotype structure of inbred mice, and failing to account for genotypic and phenotypic subgroups. METHODOLOGY/PRINCIPAL FINDINGS: We have implemented a method that addresses these issues by incorporating phylogenetic analyses, multilevel regression with mixed effects, and false discovery rate (FDR) control. A genome-wide scan for PPI was conducted using over 17,000 single nucleotide polymorphisms (SNPs) in 37 strains phenotyped. Eighty-nine SNPs were significant at a false discovery rate (FDR) of 5%. After accounting for long-range linkage disequilibrium, we found 3 independent QTLs located on murine chromosomes 1 and 13. One of the PPI positives corresponds to a region of human chromosome 6p which includes DTNBP1, a gene implicated in schizophrenia. Another region includes the gene Tsn which alters PPI when knocked out. These genes also appear to have correlated expression with PPI. CONCLUSIONS/SIGNIFICANCE: These results support the usefulness of using an improved in silico mapping method to identify QTLs for complex traits such as PPI which can be then be used for to help identify loci influencing schizophrenia in humans.

Model-based gene selection shows engrailed 1 is associated with antipsychotic response.

OBJECTIVES: Schizophrenia is an highly heritable complex disorder with a significant impact on public health. A variety of antipsychotics are available for treatment of the disorder and individual response to treatment is variable. To date, only a limited number of potential candidate genes have been examined for genetic association with treatment response. As there is lack of understanding of disease etiology and variation in treatment response, a large number of additional genes are potential targets for investigation. A variety of strategies for selecting candidate genes for further investigation are available and in most cases information used is weighed and ranked intuitively by the investigator. We sought to find genes that may influence treatment response in a less biased manner, after integrating heterogeneous data sources related to schizophrenia. METHODS: A method to select liability and treatment response candidate genes for schizophrenia using multiple data sets was constructed. The method successfully selected DTNBP1, a strong candidate gene for schizophrenia. We then evaluated novel genes picked by the method. Thirty-six single nucleotide polymorphisms in two genes engrailed 1 (EN1) and secretin receptor (SCTR) were genotyped in the Clinical Antipsychotic Trials of Intervention Effectiveness study sample. Outcomes analyzed were the Positive and Negative Syndrome Scale and six different neurocognitive measures. RESULTS: Several of the seven single nucleotide polymorphisms genotyped in the EN1 gene were associated with schizophrenia symptoms (smallest P value=0.0061) and the effects of antipsychotics on symptoms (smallest P value=2.4x10). The estimated probabilities of being a false discovery were 0.14 for symptoms and 0.0012 for drug response. CONCLUSION: These findings show that EN1 may influence individual variation in response to antipsychotics. In addition, model-based data integration of schizophrenia-related data seems to improve the prior probability of selecting genes that have an effect on antipsychotics response.

Identification of susceptibility loci for alcohol-related traits in the Irish Affected Sib Pair Study of Alcohol Dependence.

BACKGROUND: Alcoholism is a phenotypically and probably genetically heterogeneous condition. Thus, one strategy for finding genes influencing liability to alcoholism is to study the components of alcoholism, which may be more directly related to the underlying pathophysiology than is clinical diagnosis. The goal of this study was to identify genomic regions containing susceptibility loci for alcohol-related traits. METHODS: A 4-cM dense whole-genome linkage study was conducted in the Irish Affected Sib Pair Study of Alcohol Dependence. Probands, affected siblings, and parents were evaluated by structured interview. Variance component linkage analysis was applied to data from 485 families for 5 measures: initial sensitivity and tolerance (based on scales from the self-report of the effects of ethanol; maximum drinks within 24 hours, an empirically derived factor score based on withdrawal symptoms, and age at onset of alcohol dependence. RESULTS: Evidence for linkage (p<0.005) was found on 9 chromosomes. For age at onset, 2 regions were found on chromosome 9 (highest Lod=2.3, p=0.0005). For initial level of response to alcohol, suggestive regions were on chromosomes 1 and 11 (highest Lod=2.9, p=0.0001 on chromosome 11), while those for tolerance signals were on chromosomes 1, 6, and 22. Maximum drinking was associated with regions on chromosomes 12 and 18. For withdrawal symptoms, the highest peak was on chromosome 2 (Lod=2.2, p=0.0007). CONCLUSIONS: Using quantitative measures of components of alcohol dependence, we identified several regions of the genome that may contain susceptibility loci for specific alcohol-related traits and merit additional study.