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Genetic liability to substance use disorders can be parsed into loci that confer general or substance-specific addiction risk. We report a multivariate genome-wide association meta-analysis that disaggregates general and substance-specific loci for published summary statistics of problematic alcohol use, problematic tobacco use, cannabis use disorder, and opioid use disorder in a sample of individuals of European descent and African descent. Nineteen independent SNPs were genome-wide significant ( < 5e-8) for the general addiction risk factor ( ), which showed high polygenicity. Across ancestries, was significant (among other genes), suggesting dopamine regulation as a cross-substance vulnerability. An polygenic risk score was associated with substance use disorders, psychopathologies, somatic conditions, and environments associated with the onset of addictions. Substance-specific loci (9 for alcohol, 32 for tobacco, 5 for cannabis, 1 for opioids) included metabolic and receptor genes. These findings provide insight into genetic risk loci for substance use disorders that could be leveraged as treatment targets.

Background Genomes of men and women differ in only a limited number of genes located on the sex chromosomes, whereas the transcriptome is far more sex-specific. Identification of sex-biased gene expression will contribute to understanding the molecular basis of sex-differences in complex traits and common diseases. Results Sex differences in the human peripheral blood transcriptome were characterized using microarrays in 5,241 subjects, accounting for menopause status and hormonal contraceptive use. Sex-specific expression was observed for 582 autosomal genes, of which 57.7% was upregulated in women (female-biased genes). Female-biased genes were enriched for several immune system GO categories, genes linked to rheumatoid arthritis (16%) and genes regulated by estrogen (18%). Male-biased genes were enriched for genes linked to renal cancer (9%). Sex-differences in gene expression were smaller in postmenopausal women, larger in women using hormonal contraceptives and not caused by sex-specific eQTLs, confirming the role of estrogen in regulating sex-biased genes. Conclusions This study indicates that sex-bias in gene expression is extensive and may underlie sex-differences in the prevalence of common diseases.

The clinical diagnosis of patients with multisystem involvement including a pronounced neurologic damage is challenging. High-throughput sequencing methods remains crucial to provide an accurate diagnosis. In this study, we reported a Tunisian patient manifesting hypotonia and global developmental delay with visual and skin abnormalities. Exome sequencing was conducted followed by segregation analysis and, subsequently additional investigations. In silico analysis of non-synonymous variants (nsSNPs) described in COG5 in conserved positions was made. Results revealed a homozygous missense variant c.298 C > T (p.Leu100Phe) in the COG5 inherited from both parents. This variant altered both protein solubility and stability, in addition to a putative disruption of the COG5-COG7 interaction. This disruption has been confirmed using patient-derived cells in vitro in a COG5 co-immuno-precipitation, where interaction with binding partner COG7 was abrogated. Hence, we established the COG5-CDG diagnosis. Clinically, the patient shared common features with the already described cases with the report of the ichtyosis as a new manifestation. Conversely, the CADD scoring revealed 19 putatively pathogenic nsSNPs (Minor Allele Frequency MAF < 0.001, CADD > 30), 11 of which had a significant impact on the solubility and/or stability of COG5. These properties seem to be disrupted by six of the seven missense COG5-CDG variants. In conclusion, our study expands the genetic and phenotypic spectrum of COG5-CDG disease and highlight the utility of the next generation sequencing as a powerful tool in accurate diagnosis. Our results shed light on a likely molecular mechanism underlying the pathogenic effect of missense COG5 variants, which is the alteration of COG5 stability and solubility.

Background: Wide application of genome sequencing technologies has highlighted extensive genetic diversity in Acute Myeloid Leukemia (AML), yet the specific roles of individual genes remain unclear. This systematic review and meta-analysis aims to provide robust evidence for the prognostic impact of somatic gene mutations in de novo AML patients, while also exploring the prevalence of these mutations. Methods: Eligible studies were identified from PubMed and Scopus, with a focus on those reporting the prognostic influence of somatic gene mutations on overall survival (OS) or relapse-free survival (RFS) when compared to wild-type carriers. We calculated the pooled prevalence with 95% confidence intervals to assess the frequency of these mutations, and the pooled Hazard Ratio (HR) to compare OS and RFS associated with specific gene mutations. Results: We evaluated 53 somatic gene mutations using 80 studies, involving 20,048 de novo AML patients. The analysis revealed that the most prevalent affected genes were NPM1 (27%), DNMT3A (26%), and FLT3-ITD (24%). Mutations in CSF3R, TET2, and TP53 were significantly associated with poorer OS or RFS (p < 0.05). Sensitivity analysis confirmed that ASXL1, DNMT3A, and RUNX1 mutations were consistently linked to inferior OS or RFS. In contrast, CEBPAdm mutations were associated with favorable OS [HR = 0.39 (0.30–0.50)] and RFS [HR = 0.44 (0.37–0.54)]. Subgroup analysis showed that FLT3-ITD mutations were consistently associated with worse OS or RFS across all subgroups, though no significant subgroup differences were noted. No significant impact on OS or RFS was observed for mutations in GATA2, FLT3-TKD, KRAS, NRAS, IDH1, and IDH2. Conclusions: These findings provide critical insights into AML prognosis, aiding clinical decision-making and improving risk stratification strategies.

Pharmacogenetic (PGx)‐informed medication prescription is a cutting‐edge genomic application in contemporary medicine, offering the potential to overcome the conventional “trial‐and‐error” approach in drug prescription. The ability to use an individual's genetic profile to predict drug responses allows for personalized drug and dosage selection, thereby enhancing the safety and efficacy of treatments. However, despite significant scientific and clinical advancements in PGx, its integration into routine healthcare practices remains limited. To address this gap, the Qatar Genome Program (QGP) has embarked on an ambitious initiative known as QPGx‐CARES (Qatar Pharmacogenetics Clinical Applications and Research Enhancement Strategies), which aims to set a roadmap for optimizing PGx research and clinical implementation on a national scale. The goal of QPGx‐CARES initiative is to integrate PGx testing into clinical settings with the aim of improving patient health outcomes. In 2022, QGP initiated several implementation projects in various clinical settings. These projects aimed to evaluate the clinical utility of PGx testing, gather valuable insights into the effective dissemination of PGx data to healthcare professionals and patients, and identify the gaps and the challenges for wider adoption. QPGx‐CARES strategy aimed to integrate evidence‐based PGx findings into clinical practice, focusing on implementing PGx testing for cardiovascular medications, supported by robust scientific evidence. The current initiative sets a precedent for the nationwide implementation of precision medicine across diverse clinical domains.

MHC class I polypeptide-related chain A (MICA) molecule is induced in response to viral infection and various types of stress. We recently reported that a single nucleotide polymorphism (SNP) rs2596542 located in the MICA promoter region was significantly associated with the risk for hepatitis C virus (HCV)-induced hepatocellular carcinoma (HCC) and also with serum levels of soluble MICA (sMICA). In this study, we focused on the possible involvement of MICA in liver carcinogenesis related to hepatitis B virus (HBV) infection and examined correlation between the MICA polymorphism and the serum sMICA levels in HBV-induced HCC patients. The genetic association analysis revealed a nominal association with an SNP rs2596542; a G allele was considered to increase the risk of HBV-induced HCC (P = 0.029 with odds ratio of 1.19). We also found a significant elevation of sMICA in HBV-induced HCC cases. Moreover, a G allele of SNP rs2596542 was significantly associated with increased sMICA levels (P = 0.009). Interestingly, HCC patients with the high serum level of sMICA (>5 pg/ml) exhibited poorer prognosis than those with the low serum level of sMICA (≤5 pg/ml) (P = 0.008). Thus, our results highlight the importance of MICA genetic variations and the significance of sMICA as a predictive biomarker for HBV-induced HCC.

The tendency to conceive spontaneous dizygotic (DZ) twins is a complex trait with important contributions from both environmental factors and genetic disposition. In earlier work, we identified the first two genes as maternal susceptibility loci for DZ twinning. The aim of this study was to identify genetic variants influencing multiple births and to genetically correlate the findings across a broad range of traits. We performed a genome-wide association study (GWAS) in 8962 participants with Caucasian ancestry from UK Biobank who reported being part of a multiple birth, and 409,591 singleton controls. We replicated the association between FSHB, SMAD3 and twinning in the gene-based (but not SNP-based) test, which had been established in previous genome-wide association analyses in mothers with dizygotic twin offspring. Additionally, we report a novel genetic variant associated with multiple birth, rs428022 at 15q23 (p = 2.84 × 10−8) close to two genes: PIAS1 and SKOR1. Finally, we identified meaningful genetic correlations between being part of a multiple birth and other phenotypes (anthropometric traits, health-related traits, and fertility-related measures). The outcomes of this study provide important new insights into the genetic aetiology of multiple births and fertility, and open up novel directions for fertility and reproduction research.

Background Genetic factors have a substantial role in determining development of rheumatoid arthritis (RA), and are likely to account for 50–60% of disease susceptibility. Genome-wide association studies have identified non-human leucocyte antigen RA susceptibility loci which associate with RA with low-to-moderate risk. Objectives To investigate recently identified RA susceptibility markers using cohorts from six European countries, and perform a meta-analysis including previously published results. Methods 3311 DNA samples were collected from patients from six countries (UK, Germany, France, Greece, Sweden and Denmark). Genotype data or DNA samples for 3709 controls were collected from four countries (not Sweden or Denmark). Eighteen single nucleotide polymorphisms (SNPs) were genotyped using Sequenom MassArray technology. Samples with a >95% success rate and only those SNPs with a genotype success rate of >95% were included in the analysis. Scandinavian patient data were pooled and previously published Swedish control data were accessed as a comparison group. Meta-analysis was used to combine results from this study with all previously published data. Results After quality control, 3209 patients and 3692 controls were included in the study. Eight markers (ie, rs1160542 (AFF3), rs1678542 (KIF5A), rs2476601 (PTPN22), rs3087243 (CTLA4), rs4810485 (CD40), rs5029937 (6q23), rs10760130 (TRAF1/C5) and rs7574865 (STAT4)) were significantly associated with RA by meta-analysis. All 18 markers were associated with RA when previously published studies were incorporated in the analysis. Data from this study increased the significance for association with RA and nine markers. Conclusions In a large European RA cohort further evidence for the association of 18 markers with RA development has been obtained.

The non-synonymous SNP rs2228145 in the IL6R gene on chromosome 1q21.3 is associated with a wide range of common diseases, including asthma, rheumatoid arthritis, type 1 diabetes and coronary heart disease. We examined the contribution of this functional IL6R gene polymorphism rs2228145 versus other genome-wide SNPs to the variance of sIL-6R levels in blood plasma in a large population-based sample (N ~5,000), and conducted an expression QTL analysis to identify SNPs associated with IL6R gene expression. Based on data from 2,360 twin families, the broad heritability of sIL-6R was estimated at 72 and 51 % of the total variance was explained by the functional SNP rs2228145. Converging findings from GWAS, linkage, and GCTA analyses indicate that additional variance of sIL-6R levels can be explained by other variants in the IL6R region, including variants at the 3′-end of IL6R tagged by rs60760897 that are associated with IL6R RNA expression.