Aberrant transcriptomes and DNA methylomes define pathways that drive pathogenesis and loss of brain laterality/asymmetry in schizophrenia and bipolar disorder.

Although the loss of brain laterality is one of the most consistent modalities in schizophrenia (SCZ) and bipolar disorder (BD), its molecular basis remains elusive. Our limited previous studies indicated that epigenetic modifications are key to the asymmetric transcriptomes of brain hemispheres. We used whole-genome expression microarrays to profile postmortem brain samples from subjects with SCZ, psychotic BD [BD[+]] or non-psychotic BD [BD(-)], or matched controls (10/group) and performed whole-genome DNA methylation (DNAM) profiling of the same samples (3-4/group) to identify pathways associated with SCZ or BD[+] and genes/sites susceptible to epigenetic regulation. qRT-PCR and quantitative DNAM analysis were employed to validate findings in larger sample sets (35/group). Gene Set Enrichment Analysis (GSEA) demonstrated that BMP signaling and astrocyte and cerebral cortex development are significantly (FDR q < 0.25) coordinately upregulated in both SCZ and BD[+], and glutamate signaling and TGFß signaling are significantly coordinately upregulated in SCZ. GSEA also indicated that collagens are downregulated in right versus left brain of controls, but not in SCZ or BD[+] patients. Ingenuity Pathway Analysis predicted that TGFB2 is an upstream regulator of these genes (p = .0012). While lateralized expression of TGFB2 in controls (p = .017) is associated with a corresponding change in DNAM (p ≤ .023), lateralized expression and DNAM of TGFB2 are absent in SCZ or BD. Loss of brain laterality in SCZ and BD corresponds to aberrant epigenetic regulation of TGFB2 and changes in TGFß signaling, indicating potential avenues for disease prevention/treatment.

Atp1a2 and Kcnj9 are candidate genes underlying sensitivity to oxycodone-induced locomotor activation and withdrawal-induced anxiety-like behaviors in C57BL/6 substrains.

Opioid use disorder is heritable, yet its genetic etiology is largely unknown. C57BL/6J and C57BL/6NJ mouse substrains exhibit phenotypic diversity in the context of limited genetic diversity which together can facilitate genetic discovery. Here, we found C57BL/6NJ mice were less sensitive to oxycodone (OXY)-induced locomotor activation versus C57BL/6J mice in a conditioned place preference paradigm. Narrow-sense heritability was estimated at 0.22-0.31, implicating suitability for genetic analysis. Quantitative trait locus (QTL) mapping in an F2 cross identified a chromosome 1 QTL explaining 7-12% of the variance in OXY locomotion and anxiety-like withdrawal in the elevated plus maze. A second QTL for EPM withdrawal behavior on chromosome 5 near Gabra2 (alpha-2 subunit of GABA-A receptor) explained 9% of the variance. To narrow the chromosome 1 locus, we generated recombinant lines spanning 163-181 Mb, captured the QTL for OXY locomotor traits and withdrawal, and fine-mapped a 2.45-Mb region (170.16-172.61 Mb). Transcriptome analysis identified five, localized striatal cis-eQTL transcripts and two were confirmed at the protein level (KCNJ9, ATP1A2). Kcnj9 codes for a potassium channel (GIRK3) that is a major effector of mu opioid receptor signaling. Atp1a2 codes for a subunit of a Na+/K+ ATPase enzyme that regulates neuronal excitability and shows functional adaptations following chronic opioid administration. To summarize, we identified two candidate genes underlying the physiological and behavioral properties of opioids, with direct preclinical relevance to investigators employing these widely used substrains and clinical relevance to human genetic studies of opioid use disorder.

Genome-wide association study of stimulant dependence.

Stimulant dependence is heritable, but specific genetic factors underlying the trait have not been identified. A genome-wide association study for stimulant dependence was performed in a discovery cohort of African- (AA) and European-ancestry (EA) subjects ascertained for genetic studies of alcohol, opioid, and cocaine use disorders. The sample comprised individuals with DSM-IV stimulant dependence (393 EA cases, 5288 EA controls; 155 AA cases, 5603 AA controls). An independent cohort from the family-based Collaborative Study on the Genetics of Alcoholism (532 EA cases, 7635 EA controls; 53 AA cases, AA 3352 controls) was used for replication. One variant in SLC25A16 (rs2394476, p = 3.42 × 10-10, odds ratio [OR] = 3.70) was GWS in AAs. Four other loci showed suggestive evidence, including KCNA4 in AAs (rs11500237, p = 2.99 × 10-7, OR = 2.31) which encodes one of the potassium voltage-gated channel protein that has been linked to several other substance use disorders, and CPVL in the combined population groups (rs1176440, p = 3.05 × 10-7, OR = 1.35), whose expression was previously shown to be upregulated in the prefrontal cortex from users of cocaine, cannabis, and phencyclidine. Analysis of the top GWAS signals revealed a significant enrichment with nicotinic acetylcholine receptor genes (adjusted p = 0.04) and significant pleiotropy between stimulant dependence and alcohol dependence in EAs (padj = 3.6 × 10-3), an anxiety disorder in EAs (padj = 2.1 × 10-4), and ADHD in both AAs (padj = 3.0 × 10-33) and EAs (padj = 6.7 × 10-35). Our results implicate novel genes and pathways as having roles in the etiology of stimulant dependence.

A quantitative trait variant in Gabra2 underlies increased methamphetamine stimulant sensitivity.

Psychostimulant (methamphetamine, cocaine) use disorders have a genetic component that remains mostly unknown. We conducted genome-wide quantitative trait locus (QTL) analysis of methamphetamine stimulant sensitivity. To facilitate gene identification, we employed a Reduced Complexity Cross between closely related C57BL/6 mouse substrains and examined maximum speed and distance traveled over 30 min following methamphetamine (2 mg/kg, i.p.). For maximum methamphetamine-induced speed following the second and third administration, we identified a single genome-wide significant QTL on chromosome 11 that peaked near the Cyfip2 locus (LOD = 3.5, 4.2; peak = 21 cM [36 Mb]). For methamphetamine-induced distance traveled following the first and second administration, we identified a genome-wide significant QTL on chromosome 5 that peaked near a functional intronic indel in Gabra2 coding for the alpha-2 subunit of the GABA-A receptor (LOD = 3.6-5.2; peak = 34-35 cM [66-67 Mb]). Striatal cis-expression QTL mapping corroborated Gabra2 as a functional candidate gene underlying methamphetamine-induced distance traveled. CRISPR/Cas9-mediated correction of the mutant intronic deletion on the C57BL/6J background to the wild-type C57BL/6NJ allele was sufficient to reduce methamphetamine-induced locomotor activity toward the wild-type C57BL/6NJ-like level, thus validating the quantitative trait variant (QTV). These studies show the power and efficiency of Reduced Complexity Crosses in identifying causal variants underlying complex traits. Functionally restoring Gabra2 expression decreased methamphetamine stimulant sensitivity and supports preclinical and human genetic studies implicating the GABA-A receptor in psychostimulant addiction-relevant traits. Importantly, our findings have major implications for studying psychostimulants in the C57BL/6J strain-the gold standard strain in biomedical research.

Identifying factors associated with opioid cessation in a biracial sample using machine learning.

AIM: Racial disparities in opioid use disorder (OUD) management exist, however, and there is limited research on factors that influence opioid cessation in different population groups. METHODS: We employed multiple machine learning prediction algorithms least absolute shrinkage and selection operator, random forest, deep neural network, and support vector machine to assess factors associated with ceasing opioid use in a sample of 1,192 African Americans (AAs) and 2,557 individuals of European ancestry (EAs) who met Diagnostic and Statistical Manual of Mental Disorders, 5th Edition criteria for OUD. Values for nearly 4,000 variables reflecting demographics, alcohol and other drug use, general health, non-drug use behaviors, and diagnoses for other psychiatric disorders, were obtained for each participant from the Semi-Structured Assessment for Drug Dependence and Alcoholism, a detailed semi-structured interview. RESULTS: Support vector machine models performed marginally better on average than other machine learning methods with maximum prediction accuracies of 75.4% in AAs and 79.4% in EAs. Subsequent stepwise regression considered the 83 most highly ranked variables across all methods and models and identified less recent cocaine use (AAs: odds ratio (OR) = 1.82, P = 9.19 × 10-5; EAs: OR = 1.91, P = 3.30 × 10-15), shorter duration of opioid use (AAs: OR = 0.55, P = 5.78 × 10-6; EAs: OR = 0.69, P = 3.01 × 10-7), and older age (AAs: OR = 2.44, P = 1.41 × 10-12; EAs: OR = 2.00, P = 5.74 × 10-9) as the strongest independent predictors of opioid cessation in both AAs and EAs. Attending self-help groups for OUD was also an independent predictor (P < 0.05) in both population groups, while less gambling severity (OR = 0.80, P = 3.32 × 10-2) was specific to AAs and post-traumatic stress disorder recovery (OR = 1.93, P = 7.88 × 10-5), recent antisocial behaviors (OR = 0.64, P = 2.69 × 10-3), and atheism (OR = 1.45, P = 1.34 × 10-2) were specific to EAs. Factors related to drug use comprised about half of the significant independent predictors in both AAs and EAs, with other predictors related to non-drug use behaviors, psychiatric disorders, overall health, and demographics. CONCLUSIONS: These proof-of-concept findings provide avenues for hypothesis-driven analysis, and will lead to further research on strategies to improve OUD management in EAs and AAs.

Genome-Wide Association Study of Opioid Cessation.

The United States is experiencing an epidemic of opioid use disorder (OUD) and overdose-related deaths. However, the genetic basis for the ability to discontinue opioid use has not been investigated. We performed a genome-wide association study (GWAS) of opioid cessation (defined as abstinence from illicit opioids for >1 year or <6 months before the interview date) in 1130 African American (AA) and 2919 European ancestry (EA) participants recruited for genetic studies of substance use disorders and who met lifetime Diagnostic and Statistical Manual of Mental Disorders, 5th Edition (DSM-5) criteria for OUD. Association tests performed separately within each ethnic group were combined by meta-analysis with results obtained from the Comorbidity and Trauma Study. Although there were no genome-wide significant associations, we found suggestive associations with nine independent loci, including three which are biologically relevant: rs4740988 in PTPRD (pAA + EA = 2.24 × 10-6), rs36098404 in MYOM2 (pEA = 2.24 × 10-6), and rs592026 in SNAP25-AS1 (pEA = 6.53 × 10-6). Significant pathways identified in persons of European ancestry (EA) are related to vitamin D metabolism (p = 3.79 × 10-2) and fibroblast growth factor (FGF) signaling (p = 2.39 × 10-2). UK Biobank traits including smoking and drinking cessation and chronic back pain were significantly associated with opioid cessation using GWAS-derived polygenic risk scores. These results provide evidence for genetic influences on opioid cessation, suggest genetic overlap with other relevant traits, and may indicate potential novel therapeutic targets for OUD.

An efficient analytic approach in genome-wide identification of methylation quantitative trait loci response to fenofibrate treatment.

BACKGROUND: The study of DNA methylation quantitative trait loci (meQTLs) helps dissect regulatory mechanisms underlying genetic associations of human diseases. In this study, we conducted the first genome-wide examination of genetic drivers of methylation variation in response to a triglyceride-lowering treatment with fenofibrate (response-meQTL) by using an efficient analytic approach. METHODS: Subjects (n = 429) from the GAW20 real data set with genotype and both pre- (visit 2) and post- (visit 4) fenofibrate treatment methylation measurements were included. Following the quality control steps of removing certain cytosine-phosphate-guanine (CpG) probes, the post-/premethylation changes (post/pre) were log transformed and the association was performed on 208,449 CpG sites. An additive linear mixed-effects model was used to test the association between each CpG probe and single nucleotide polymorphisms (SNPs) around ±1 Mb region, with age, sex, smoke, batch effect, and principal components included as covariates. Bonferroni correction was applied to define the significance threshold (p < 5.6 × 10- 10, given a total of 89,217,303 tests). Finally, we integrated our response-meQTL (re-meQTL) findings with the published genome-wide association study (GWAS) catalog of human diseases/traits. RESULTS: We identified 1087 SNPs as cis re-meQTLs associated with 610 CpG probes/sites located in 351 unique gene loci. Among these 1087 cis re-meQTL SNPs, 229 were unique and 6 were co-localized at 8 unique disease/trait loci reported in the GWAS catalog (enrichment p = 1.51 × 10- 23). Specifically, a lipid SNP, rs10903129, located in intron regions of gene TMEM57, was a re-meQTL (p = 3.12 × 10- 36) associated with the CpG probe cg09222892, which is in the upstream region of the gene RHCE, indicating a new target gene for rs10903129. In addition, we found that SNP rs12710728 has a suggestive association with cg17097782 (p = 1.77 × 10- 4), and that this SNP is in high linkage disequilibrium (LD) (R2 > 0.8) with rs7443270, which was previously reported to be associated with fenofibrate response (p = 5.00 × 10- 6). CONCLUSIONS: By using a novel analytic approach, we efficiently identified thousands of cis re-meQTLs that provide a unique resource for further characterizing functional roles and gene targets of the SNPs that are most responsive to fenofibrate treatment. Our efficient analytic approach can be extended to large response quantitative trait locus studies with large sample sizes and multiple time points data.