218 research outputs found

    Human pharmacogenomic variation of antihypertensive drugs: from population genetics to personalized medicine.

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    AIM: To investigate the human pharmacogenetic variation related to antihypertensive drugs, providing a survey of functional interpopulation differences in hypertension pharmacogenes. MATERIALS & METHODS: The study was divided into two stages. In the first stage, we analyzed 1249 variants located in 57 hypertension pharmacogenes. This first-stage analysis confirmed that geographic origin strongly affects hypertension pharmacogenomic variation and that 31 pharmacogenes are geographically differentiated. In the second stage, we focused our attention on the ethnic-differentiated pharmacogenes, investigating 55,521 genetic variants. In silico analyses were performed to predict the effect of genetic variation. RESULTS: Our analyses indicated functional interpopulation differences, suggesting insight into the mechanisms of antihypertensive drug response. Moreover, our data suggested that rare variants mainly determine the functionality of genes related to antihypertensive drugs. CONCLUSION: Our study provided important knowledge about the genetics of the antihypertensive drug response, suggesting that next-generation sequencing technologies may develop reliable pharmacogenetic tests for antihypertensive drugs

    In silico analysis of TTR gene (coding and non-coding regions, and interactive network) and its implications in transthyretin-related amyloidosis.

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    Introduction: Transthyretin (TTR)-related amyloidosis is a life-threatening disease. Currently, several questions about the pathogenic mechanisms of TTR-related amyloidosis remain unanswered. Methods: We have investigated various TTR-related issues using different in silico approaches. Results: Using an amino acid similarity-based analysis, we have indicated the most relevant TTR secondary structures in determining mutation impact. Our amyloidogenic propensity analysis of TTR missense substitutions has highlighted a similar pattern for wild-type and mutated TTR amino b acid sequences. However, some mutations present differences with respect to the general distribution. We have identified non-coding variants in cis-regulatory elements of the TTR gene, and our analysis on V122I-related haplotypes has indicated differences in non-coding regulatory variants, suggesting differences among V122I carriers. The analysis of methylation status indicated CpG sites that may affect TTR expression. Finally, our interactive network analysis revealed functional partners of TTR that may play a modifier role in the pathogenesis of TTR-related amyloidosis. Discussion and conclusion: Our data provided new insights into the pathogenesis of TTR-related amyloidosis that, if they were to be confirmed through experimental investigations, could significantly improve our understanding of the disease

    Haplotype differences for copy number variants in the 22q11.23 region among human populations: a pigmentation-based model for selective pressure.

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    Two gene clusters are tightly linked in a narrow region of chromosome 22q11.23: the macrophage migration inhibitory factor (MIF) gene family and the glutathione S-transferase theta class. Within 120 kb in this region, two 30-kb deletions reach high frequencies in human populations. This gives rise to four haplotypic arrangements, which modulate the number of genes in both families. The variable patterns of linkage disequilibrium (LD) between these copy number variants (CNVs) in diverse human populations remain poorly understood. We analyzed 2469 individuals belonging to 27 human populations with different ethnic origins. Then we correlated the genetic variability of 22q11.23 CNVs with environmental variables. We confirmed an increasing strength of LD from Africa to Asia and to Europe. Further, we highlighted strongly significant correlations between the frequency of one of the haplotypes and pigmentation-related variables: skin color (R2=0.675, P<0.001), distance from the equator (R2=0.454, P<0.001), UVA radiation (R2=0.439, P<0.001), and UVB radiation (R2=0.313, P=0.002). The fact that all MIF-related genes are retained on this haplotype and the evidences gleaned from experimental systems seem to agree with the role of MIF-related genes in melanogenesis. As such, we propose a model that explains the geographic and ethnic distribution of 22q11.23 CNVs among human populations, assuming that MIF-related gene dosage could be associated with adaptation to low UV radiatio

    Decoy peptide targeted to Toll-IL-1R domain inhibits LPS and TLR4-active metabolite morphine-3 glucuronide sensitization of sensory neurons

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    Accumulating evidence indicates that Toll-like receptor (TLR) signaling adapter protein interactions with Toll/Interleukin-1 Receptor (TIR) domains present in sensory neurons may modulate neuropathic pain states. Following ligand interaction with TLRs, TIR serves to both initiate intracellular signaling and facilitate recruitment of signaling adapter proteins to the intracytoplasmic domain. Although TLR TIR is central to a number of TLR signaling cascades, its role in sensory neurons is poorly understood. In this study we investigated the degree to which TLR TIR decoy peptide modified to include a TAT sequence (Trans-Activator of Transcription gene in HIV; TAT-4BB) affected LPS-induced intracellular calcium flux and excitation in sensory neurons, and behavioral changes due to TLR4 active metabolite, morphine-3-glucuronide (M3G) exposure in vivo. TAT-4BB inhibited LPS-induced calcium changes in a majority of sensory neurons and decreased LPS-dependent neuronal excitability in small diameter neurons. Acute systemic administration of the TAT-4BB reversed M3G-induced tactile allodynia in a dose-dependent manner but did not affect motor activity, anxiety or responses to noxious thermal stimulus. These data suggest that targeting TLR TIR domains may provide novel pharmacological targets to reduce or reverse TLR4-dependent pain behavior in the rodent

    A putative causal relationship between genetically determined female body shape and posttraumatic stress disorder

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    Background: The nature and underlying mechanisms of the observed increased vulnerability to posttraumatic stress disorder (PTSD) in women are unclear. Methods: We investigated the genetic overlap of PTSD with anthropometric traits and reproductive behaviors and functions in women. The analysis was conducted using female-specific summary statistics from large genome-wide association studies (GWAS) and a cohort of 3577 European American women (966 PTSD cases and 2611 trauma-exposed controls). We applied a high-resolution polygenic score approach and Mendelian randomization analysis to investigate genetic correlations and causal relationships. Results: We observed an inverse association of PTSD with genetically determined anthropometric traits related to body shape, independent of body mass index (BMI). The top association was related to BMI-adjusted waist circumference (WCadj; R = -0.079, P &lt; 0.001, Q = 0.011). We estimated a relative decrease of 64.6% (95% confidence interval = 27.5-82.7) in the risk of PTSD per 1-SD increase in WCadj. MR-Egger regression intercept analysis showed no evidence of pleiotropic effects in this association (Ppleiotropy = 0.979). We also observed associations of genetically determined WCadj with age at first sexual intercourse and number of sexual partners (P = 0.013 and P &lt; 0.001, respectively). Conclusions: There is a putative causal relationship between genetically determined female body shape and PTSD, which could be mediated by evolutionary mechanisms involved in human sexual behaviors

    Association of OPRM1 Functional Coding Variant With Opioid Use Disorder: A Genome-Wide Association Study.

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    Importance: With the current opioid crisis, it is important to improve understanding of the biological mechanisms of opioid use disorder (OUD). Objectives: To detect genetic risk variants for OUD and determine genetic correlations and causal association with OUD and other traits. Design, Setting, and Participants: A genome-wide association study of electronic health record-defined OUD in the Million Veteran Program sample was conducted, comprising 8529 affected European American individuals and 71 200 opioid-exposed European American controls (defined by electronic health record trajectory analysis) and 4032 affected African American individuals and 26 029 opioid-exposed African American controls. Participants were enrolled from January 10, 2011, to May 21, 2018, with electronic health record data for OUD diagnosis from October 1, 1999, to February 7, 2018. Million Veteran Program results and additional OUD case-control genome-wide association study results from the Yale-Penn and Study of Addiction: Genetics and Environment samples were meta-analyzed (total numbers: European American individuals, 10 544 OUD cases and 72 163 opioid-exposed controls; African American individuals, 5212 cases and 26 876 controls). Data on Yale-Penn participants were collected from February 14, 1999, to April 1, 2017, and data on Study of Addiction: Genetics and Environment participants were collected from 1990 to 2007. The key result was replicated in 2 independent cohorts: proxy-phenotype buprenorphine treatment in the UK Biobank and newly genotyped Yale-Penn participants. Genetic correlations between OUD and other traits were tested, and mendelian randomization analysis was conducted to identify potential causal associations. Main Outcomes and Measures: Main outcomes were International Classification of Diseases, Ninth Revision-diagnosed OUD or International Statistical Classification of Diseases and Related Health Problems, Tenth Revision-diagnosed OUD (Million Veteran Program), and DSM-IV-defined opioid dependence (Yale-Penn and Study of Addiction: Genetics and Environment). Results: A total of 114 759 individuals (101 016 men [88%]; mean [SD] age, 60.1 [12.8] years) were included. In 82 707 European American individuals, a functional coding variant (rs1799971, encoding Asn40Asp) in OPRM1 (μ-opioid receptor gene, the main biological target for opioid drugs; OMIM 600018) reached genome-wide significance (G allele: β = -0.066 [SE = 0.012]; P = 1.51 × 10-8). The finding was replicated in 2 independent samples. Single-nucleotide polymorphism-based heritability of OUD was 11.3% (SE = 1.8%). Opioid use disorder was genetically correlated with 83 traits, including multiple substance use traits, psychiatric illnesses, cognitive performance, and others. Mendelian randomization analysis revealed the following associations with OUD: risk of tobacco smoking, depression, neuroticism, worry neuroticism subcluster, and cognitive performance. No genome-wide significant association was detected for African American individuals or in transpopulation meta-analysis. Conclusions and Relevance: This genome-wide meta-analysis identified a significant association of OUD with an OPRM1 variant, which was replicated in 2 independent samples. Post-genome-wide association study analysis revealed associated pleiotropic characteristics. Recruitment of additional individuals with OUD for future studies-especially those of non-European ancestry-is a crucial next step in identifying additional significant risk loci

    Investigation of convergent and divergent genetic influences underlying schizophrenia and alcohol use disorder

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    Background Alcohol use disorder (AUD) and schizophrenia (SCZ) frequently co-occur, and large-scale genome-wide association studies (GWAS) have identified significant genetic correlations between these disorders. Methods We used the largest published GWAS for AUD (total cases = 77 822) and SCZ (total cases = 46 827) to identify genetic variants that influence both disorders (with either the same or opposite direction of effect) and those that are disorder specific. Results We identified 55 independent genome-wide significant single nucleotide polymorphisms with the same direction of effect on AUD and SCZ, 8 with robust effects in opposite directions, and 98 with disorder-specific effects. We also found evidence for 12 genes whose pleiotropic associations with AUD and SCZ are consistent with mediation via gene expression in the prefrontal cortex. The genetic covariance between AUD and SCZ was concentrated in genomic regions functional in brain tissues (p = 0.001). Conclusions Our findings provide further evidence that SCZ shares meaningful genetic overlap with AUD

    Enhancing discovery of genetic variants for posttraumatic stress disorder through integration of quantitative phenotypes and trauma exposure information

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    Background Posttraumatic stress disorder (PTSD) is heritable and a potential consequence of exposure to traumatic stress. Evidence suggests that a quantitative approach to PTSD phenotype measurement and incorporation of lifetime trauma exposure (LTE) information could enhance the discovery power of PTSD genome-wide association studies (GWASs). Methods A GWAS on PTSD symptoms was performed in 51 cohorts followed by a fixed-effects meta-analysis (N = 182,199 European ancestry participants). A GWAS of LTE burden was performed in the UK Biobank cohort (N = 132,988). Genetic correlations were evaluated with linkage disequilibrium score regression. Multivariate analysis was performed using Multi-Trait Analysis of GWAS. Functional mapping and annotation of leading loci was performed with FUMA. Replication was evaluated using the Million Veteran Program GWAS of PTSD total symptoms. Results GWASs of PTSD symptoms and LTE burden identified 5 and 6 independent genome-wide significant loci, respectively. There was a 72% genetic correlation between PTSD and LTE. PTSD and LTE showed largely similar patterns of genetic correlation with other traits, albeit with some distinctions. Adjusting PTSD for LTE reduced PTSD heritability by 31%. Multivariate analysis of PTSD and LTE increased the effective sample size of the PTSD GWAS by 20% and identified 4 additional loci. Four of these 9 PTSD loci were independently replicated in the Million Veteran Program. Conclusions Through using a quantitative trait measure of PTSD, we identified novel risk loci not previously identified using prior case-control analyses. PTSD and LTE have a high genetic overlap that can be leveraged to increase discovery power through multivariate methods
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