The Aryl Hydrocarbon Receptor, Epigenetics and the Aging Process.

The aryl hydrocarbon receptor (AhR) is a ligand-dependent transcription factor, classically associated with the regulation of xenobiotic metabolism in response to environmental toxins. In recent years, transgenic rodent models have implicated AhR in aging and longevity. Moreover, several AhR ligands, such as resveratrol and quercetin, are compounds proven to extend the lifespan of model organisms. In this paper, we first review AhR biology with a focus on aging and highlight several AhR ligands with potential anti-aging properties. We outline how AhR-driven expression of xenobiotic metabolism genes into old age may be a key mechanism through which moderate induction of AhR elicits positive benefits on longevity and healthspan. Furthermore, via integration of publicly available datasets, we show that liver-specific AhR target genes are enriched among genes subject to epigenetic aging. Changes to epigenetic states can profoundly affect transcription factor binding and are a hallmark of the aging process. We suggest that the interplay between AhR and epigenetic aging should be the subject of future research and outline several key gaps in the current literature. Finally, we recommend that a broad range of non-toxic AhR ligands should be investigated for their potential to promote healthspan and longevity.

Genome-wide association study of antipsychotic-induced QTc interval prolongation.

QT prolongation is associated with increased risk of cardiac arrhythmias. Identifying the genetic variants that mediate antipsychotic-induced prolongation may help to minimize this risk, which might prevent the removal of efficacious drugs from the market. We performed candidate gene analysis and five drug-specific genome-wide association studies (GWASs) with 492K single-nucleotide polymorphisms to search for genetic variation mediating antipsychotic-induced QT prolongation in 738 schizophrenia patients from the Clinical Antipsychotic Trial of Intervention Effectiveness study. Our candidate gene study suggests the involvement of NOS1AP and NUBPL (P-values=1.45 × 10(-05) and 2.66 × 10(-13), respectively). Furthermore, our top GWAS hit achieving genome-wide significance, defined as a Q-value <0.10 (P-value=1.54 × 10(-7), Q-value=0.07), located in SLC22A23, mediated the effects of quetiapine on prolongation. SLC22A23 belongs to a family of organic ion transporters that shuttle a variety of compounds, including drugs, environmental toxins and endogenous metabolites, across the cell membrane. This gene is expressed in the heart and is integral in mouse heart development. The genes mediating antipsychotic-induced QT prolongation partially overlap with the genes affecting normal QT interval variation. However, some genes may also be unique for drug-induced prolongation. This study demonstrates the potential of GWAS to discover genes and pathways that mediate antipsychotic-induced QT prolongation.

Pharmacogenomic study of side-effects for antidepressant treatment options in STAR*D.

BACKGROUND: Understanding individual differences in susceptibility to antidepressant therapy side-effects is essential to optimize the treatment of depression. METHOD: We performed genome-wide association studies (GWAS) to search for genetic variation affecting the susceptibility to side-effects. The analysis sample consisted of 1439 depression patients, successfully genotyped for 421K single nucleotide polymorphisms (SNPs), from the Sequenced Treatment Alternatives to Relieve Depression (STAR*D) study. Outcomes included four indicators of side-effects: general side-effect burden, sexual side-effects, dizziness and vision/hearing-related side-effects. Our criterion for genome-wide significance was a prespecified threshold ensuring that, on average, only 10% of the significant findings are false discoveries. RESULTS: Thirty-four SNPs satisfied this criterion. The top finding indicated that 10 SNPs in SACM1L mediated the effects of bupropion on sexual side-effects (p = 4.98 × 10(-7), q = 0.023). Suggestive findings were also found for SNPs in MAGI2, DTWD1, WDFY4 and CHL1. CONCLUSIONS: Although our findings require replication and functional validation, this study demonstrates the potential of GWAS to discover genes and pathways that could mediate adverse effects of antidepressant medication.

Genomewide pharmacogenomic study of metabolic side effects to antipsychotic drugs.

Understanding individual differences in the susceptibility to metabolic side effects as a response to antipsychotic therapy is essential to optimize the treatment of schizophrenia. Here, we perform genomewide association studies (GWAS) to search for genetic variation affecting the susceptibility to metabolic side effects. The analysis sample consisted of 738 schizophrenia patients, successfully genotyped for 492K single nucleotide polymorphisms (SNPs), from the genomic subsample of the Clinical Antipsychotic Trial of Intervention Effectiveness study. Outcomes included 12 indicators of metabolic side effects, quantifying antipsychotic-induced change in weight, blood lipids, glucose and hemoglobin A1c, blood pressure and heart rate. Our criterion for genomewide significance was a pre-specified threshold that ensures, on average, only 10% of the significant findings are false discoveries. A total of 21 SNPs satisfied this criterion. The top finding indicated that a SNP in Meis homeobox 2 (MEIS2) mediated the effects of risperidone on hip circumference (q=0.004). The same SNP was also found to mediate risperidone's effect on waist circumference (q=0.055). Genomewide significant finding were also found for SNPs in PRKAR2B, GPR98, FHOD3, RNF144A, ASTN2, SOX5 and ATF7IP2, as well as in several intergenic markers. PRKAR2B and MEIS2 both have previous research indicating metabolic involvement, and PRKAR2B has previously been shown to mediate antipsychotic response. Although our findings require replication and functional validation, this study shows the potential of GWAS to discover genes and pathways that potentially mediate adverse effects of antipsychotic medication.

Genome-wide pharmacogenomic analysis of response to treatment with antipsychotics.

Schizophrenia is an often devastating neuropsychiatric illness. Understanding the genetic variation affecting response to antipsychotics is important to develop novel diagnostic tests to match individual schizophrenia patients to the most effective and safe medication. In this study, we use a genome-wide approach to detect genetic variation underlying individual differences in response to treatment with the antipsychotics olanzapine, quetiapine, risperidone, ziprasidone and perphenazine. Our sample consisted of 738 subjects with DSM-IV schizophrenia who took part in the Clinical Antipsychotic Trials of Intervention Effectiveness. Subjects were genotyped using the Affymetrix 500 K genotyping platform plus a custom 164 K chip to improve genome-wide coverage. Treatment outcome was measured using the Positive and Negative Syndrome Scale. Our criterion for genome-wide significance was a prespecified threshold that ensures that, on an average, only 10% of the significant findings are false discoveries. The top statistical result reached significance at our prespecified threshold and involved a single-nucleotide polymorphism (SNP) in an intergenic region on chromosome 4p15. In addition, SNPs in Ankyrin Repeat and Sterile Alpha Motif Domain-Containing Protein 1B (ANKS1B) and in the Contactin-Associated Protein-Like 5 gene (CNTNAP5), which mediated the effects of olanzapine and risperidone on Negative symptoms, were very close to our threshold for declaring significance. The most significant SNP in CNTNAP5 is nonsynonymous, giving rise to an amino-acid substitution. In addition to highlighting our top results, we provide all P-values for download as a resource for investigators with the requisite samples to carry out replication. This study demonstrates the potential of genome-wide association studies to discover novel genes that mediate the effects of antipsychotics, which could eventually help to tailor drug treatment to schizophrenic patients.

Behavioral metabolomics analysis identifies novel neurochemical signatures in methamphetamine sensitization.

Behavioral sensitization has been widely studied in animal models and is theorized to reflect neural modifications associated with human psychostimulant addiction. While the mesolimbic dopaminergic pathway is known to play a role, the neurochemical mechanisms underlying behavioral sensitization remain incompletely understood. In this study, we conducted the first metabolomics analysis to globally characterize neurochemical differences associated with behavioral sensitization. Methamphetamine (MA)-induced sensitization measures were generated by statistically modeling longitudinal activity data for eight inbred strains of mice. Subsequent to behavioral testing, nontargeted liquid and gas chromatography-mass spectrometry profiling was performed on 48 brain samples, yielding 301 metabolite levels per sample after quality control. Association testing between metabolite levels and three primary dimensions of behavioral sensitization (total distance, stereotypy and margin time) showed four robust, significant associations at a stringent metabolome-wide significance threshold (false discovery rate, FDR <0.05). Results implicated homocarnosine, a dipeptide of GABA and histidine, in total distance sensitization, GABA metabolite 4-guanidinobutanoate and pantothenate in stereotypy sensitization, and myo-inositol in margin time sensitization. Secondary analyses indicated that these associations were independent of concurrent MA levels and, with the exception of the myo-inositol association, suggest a mechanism whereby strain-based genetic variation produces specific baseline neurochemical differences that substantially influence the magnitude of MA-induced sensitization. These findings demonstrate the utility of mouse metabolomics for identifying novel biomarkers, and developing more comprehensive neurochemical models, of psychostimulant sensitization.

Genome-wide pharmacogenomic study of citalopram-induced side effects in STAR*D.

Affecting about 1 in 12 Americans annually, depression is a leading cause of the global disease burden. While a range of effective antidepressants are now available, failure and relapse rates remain substantial, with intolerable side effect burden the most commonly cited reason for discontinuation. Thus, understanding individual differences in susceptibility to antidepressant therapy side effects will be essential to optimize depression treatment. Here we perform genome-wide association studies (GWAS) to identify genetic variation influencing susceptibility to citalopram-induced side effects. The analysis sample consisted of 1762 depression patients, successfully genotyped for 421K single-nucleotide polymorphisms (SNPs), from the Sequenced Treatment Alternatives to Relieve Depression (STAR(*)D) study. Outcomes included five indicators of citalopram side effects: general side effect burden, overall tolerability, sexual side effects, dizziness and vision/hearing side effects. Two SNPs met our genome-wide significance criterion (q<0.1), ensuring that, on average, only 10% of significant findings are false discoveries. In total, 12 additional SNPs demonstrated suggestive associations (q<0.5). The top finding was rs17135437, an intronic SNP within EMID2, mediating the effects of citalopram on vision/hearing side effects (P=3.27 × 10(-8), q=0.026). The second genome-wide significant finding, representing a haplotype spanning ∼30 kb and eight genotyped SNPs in a gene desert on chromosome 13, was associated with general side effect burden (P=3.22 × 10(-7), q=0.096). Suggestive findings were also found for SNPs at LAMA1, AOX2P, EGFLAM, FHIT and RTP2. Although our findings require replication and functional validation, this study demonstrates the potential of GWAS to discover genes and pathways that potentially mediate adverse effects of antidepressant medications.

Catechol-O-methyltransferase and the clinical features of psychosis.

A functional polymorphism (Val-158-Met) at the Catechol-O-methyltransferase (COMT) locus has been identified as a potential etiological factor in schizophrenia. Yet the association has not been convincingly replicated across independent samples. We hypothesized that phenotypic heterogeneity might be diluting the COMT effect. To clarify the putative association, we performed an exploratory analysis to test for association between COMT and five psychosis symptom scales. These were derived through factor analysis of the Operational Criteria Checklist for Psychiatric Illness. Our sample was the Irish Study of High Density Schizophrenia Families, a large collection consisting of 268 multiplex families. This sample has previously shown a small but significant effect of the COMT Val allele in conferring risk for schizophrenia. We tested for preferential transmission of COMT alleles from parent to affected offspring (n = 749) for each of the five factor-derived scales (negative symptoms, delusions, hallucinations, mania, and depression). Significant overtransmission of the Val allele was found for mania (P < 0.05) and depression (P = 0.01) scales. Examination of odds ratios (ORs) revealed a heterogeneous effect of COMT, whereby it had no effect on Negative Symptoms, but largest impact on Depression (OR = 1.4). These results suggest a modest affective vulnerability conferred by this allele in psychosis, but will require replication.