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Lithium (Li) is one of the most effective drugs for treating bipolar disorder (BD), however, there is presently no way to predict response to guide treatment. The aim of this study is to identify functional genes and pathways that distinguish BD Li responders (LR) from BD Li non-responders (NR). An initial Pharmacogenomics of Bipolar Disorder study (PGBD) GWAS of lithium response did not provide any significant results. As a result, we then employed network-based integrative analysis of transcriptomic and genomic data. In transcriptomic study of iPSC-derived neurons, 41 significantly differentially expressed (DE) genes were identified in LR vs NR regardless of lithium exposure. In the PGBD, post-GWAS gene prioritization using the GWA-boosting (GWAB) approach identified 1119 candidate genes. Following DE-derived network propagation, there was a highly significant overlap of genes between the top 500- and top 2000-proximal gene networks and the GWAB gene list (Phypergeometric = 1.28E-09 and 4.10E-18, respectively). Functional enrichment analyses of the top 500 proximal network genes identified focal adhesion and the extracellular matrix (ECM) as the most significant functions. Our findings suggest that the difference between LR and NR was a much greater effect than that of lithium. The direct impact of dysregulation of focal adhesion on axon guidance and neuronal circuits could underpin mechanisms of response to lithium, as well as underlying BD. It also highlights the power of integrative multi-omics analysis of transcriptomic and genomic profiling to gain molecular insights into lithium response in BD.

BackgroundBiological aging estimators derived from DNA methylation data are heritable and correlate with morbidity and mortality. Consequently, identification of genetic and environmental contributors to the variation in these measures in populations has become a major goal in the field.ResultsLeveraging DNA methylation and SNP data from more than 40,000 individuals, we identify 137 genome-wide significant loci, of which 113 are novel, from genome-wide association study (GWAS) meta-analyses of four epigenetic clocks and epigenetic surrogate markers for granulocyte proportions and plasminogen activator inhibitor 1 levels, respectively. We find evidence for shared genetic loci associated with the Horvath clock and expression of transcripts encoding genes linked to lipid metabolism and immune function. Notably, these loci are independent of those reported to regulate DNA methylation levels at constituent clock CpGs. A polygenic score for GrimAge acceleration showed strong associations with adiposity-related traits, educational attainment, parental longevity, and C-reactive protein levels.ConclusionThis study illuminates the genetic architecture underlying epigenetic aging and its shared genetic contributions with lifestyle factors and longevity.

Lithium remains the gold standard for the treatment of bipolar disorder (BD); however, its use has declined over the years mainly due to the side effects and the subjective experience of cognitive numbness reported by patients. In the present study, we aim to methodically test the effects of lithium on neurocognitive functioning in the largest single cohort (n = 262) of BD patients reported to date by harnessing the power of a multi-site, ongoing clinical trial of lithium monotherapy. At the cross-sectional level, multivariate analysis of covariance (MANCOVA) was conducted to examine potential group differences across neurocognitive tests [California Verbal Learning Test (CVLT trials 1-5,CVLT delayed recall), Wechsler Digit Symbol, Trail-making Test parts A and B (TMT-A; TMT-B), and a global cognition index]. At the longitudinal level, on a subset of patients (n = 88) who achieved mood stabilization with lithium monotherapy, we explored the effect of lithium treatment across time on neurocognitive functioning. There were no differences at baseline between BD patients that were taking lithium compared with those that were not. At follow-up a significant neurocognitive improvement in the global cognitive index score [F = 31.69; p

Key Points: Question: Are the genetic liabilities of psychiatric disorders, substance use behaviors, or their comorbidity associated with reduced longevity? Findings: In this cohort study, multivariable mendelian randomization (MR) found that the genetic liability for smoking had a deleterious association with longevity, while corresponding genetic liabilities for major psychiatric disorders had no independent associations when accounting for comorbid substance use in cohorts of European ancestry. Transcriptomic imputation identified 249 smoking-associated genes, including several with associations between smoking and aging, and cis-instrument MR prioritized brain proteins to inform therapeutic development for smoking cessation. Meaning: The findings in this genetics-based study suggest that reduced healthy aging associated with major psychiatric disorders may be primarily driven by the negative impact of smoking; novel transcriptomic and proteomic targets might offer opportunities for therapeutic drug development for smoking cessation. This cohort study assesses associations between psychiatric disorders, substance use behaviors, and longevity. Importance: Observational studies suggest that major psychiatric disorders and substance use behaviors reduce longevity, making it difficult to disentangle their relationships with aging-related outcomes. Objective: To evaluate the associations between the genetic liabilities for major psychiatric disorders, substance use behaviors (smoking and alcohol consumption), and longevity. Design, Settings, and Participants: This 2-sample mendelian randomization (MR) study assessed associations between psychiatric disorders, substance use behaviors, and longevity using single-variable and multivariable models. Multiomics analyses were performed elucidating transcriptomic underpinnings of the MR associations and identifying potential proteomic therapeutic targets. This study sourced summary-level genome-wide association study (GWAS) data, gene expression, and proteomic data from cohorts of European ancestry. Analyses were performed from May 2022 to November 2023. Exposures: Genetic susceptibility for major depression (n = 500 199), bipolar disorder (n = 413 466), schizophrenia (n = 127 906), problematic alcohol use (n = 435 563), weekly alcohol consumption (n = 666 978), and lifetime smoking index (n = 462 690). Main Outcomes and Measures: The main outcome encompassed aspects of health span, lifespan, and exceptional longevity. Additional outcomes were epigenetic age acceleration (EAA) clocks. Results: Findings from multivariable MR models simultaneously assessing psychiatric disorders and substance use behaviorsm suggest a negative association between smoking and longevity in cohorts of European ancestry (n = 709 709; 431 503 [60.8%] female; β, −0.33; 95% CI, −0.38 to −0.28; P = 4.59 × 10−34) and with increased EAA (n = 34 449; 18 017 [52.3%] female; eg, PhenoAge: β, 1.76; 95% CI, 0.72 to 2.79; P = 8.83 × 10−4). Transcriptomic imputation and colocalization identified 249 genes associated with smoking, including 36 novel genes not captured by the original smoking GWAS. Enriched pathways included chromatin remodeling and telomere assembly and maintenance. The transcriptome-wide signature of smoking was inversely associated with longevity, and estimates of individual smoking-associated genes, eg, XRCC3 and PRMT6, aligned with the smoking-longevity MR analyses, suggesting underlying transcriptomic mediators. Cis-instrument MR prioritized brain proteins associated with smoking behavior, including LY6H (β, 0.02; 95% CI, 0.01 to 0.03; P = 2.37 × 10−6) and RIT2 (β, 0.02; 95% CI, 0.01 to 0.03; P = 1.05 × 10−5), which had favorable adverse-effect profiles across 367 traits evaluated in phenome-wide MR. Conclusions: The findings suggest that the genetic liability of smoking, but not of psychiatric disorders, is associated with longevity. Transcriptomic associations offer insights into smoking-related pathways, and identified proteomic targets may inform therapeutic development for smoking cessation strategies. [ABSTRACT FROM AUTHOR]

Alcohol dependence (ALC) is a chronic, relapsing disorder that increases the burden of chronic disease and significantly contributes to numerous premature deaths each year. Previous research suggests that chronic, heavy alcohol consumption is associated with differential DNA methylation patterns. In addition, DNA methylation levels at certain CpG sites have been correlated with age. We used an epigenetic clock to investigate the potential role of excessive alcohol consumption in epigenetic aging. We explored this question in five independent cohorts, including DNA methylation data derived from datasets from blood (n = 129, n = 329), liver (n = 92, n = 49), and postmortem prefrontal cortex (n = 46). One blood dataset and one liver tissue dataset of individuals with ALC exhibited positive age acceleration (p

Dopamine transporters (DAT) are implicated in the pathogenesis and treatment of attention-deficit hyperactivity disorder (ADHD) and are upregulated by chronic treatment with methylphenidate, commonly prescribed for ADHD. Methylation of the DAT1 gene in brain and blood has been associated with DAT expression in rodents' brains. Here we tested the association between methylation of the DAT1 promoter derived from blood and DAT availability in the striatum of unmedicated ADHD adult participants and in that of healthy age-matched controls (HC) using Positron Emission Tomography (PET) and [11 C]cocaine. Results showed no between-group differences in DAT1 promoter methylation or striatal DAT availability. However, the degree of methylation in the promoter region of DAT1 correlated negatively with DAT availability in caudate in ADHD participants only. DAT availability in VS correlated with inattention scores in ADHD participants. We verified in a postmortem cohort with ADHD diagnosis and without, that DAT1 promoter methylation in peripheral blood correlated positively with DAT1 promoter methylation extracted from substantia nigra (SN) in both groups. In the cohort without ADHD diagnosis, DAT1 gene expression in SN further correlated positively with DAT protein expression in caudate; however, the sample size of the cohort with ADHD was insufficient to investigate DAT1 and DAT expression levels. Overall, these findings suggest that peripheral DAT1 promoter methylation may be predictive of striatal DAT availability in adults with ADHD. Due to the small sample size, more work is needed to validate whether DAT1 methylation in blood predicts DAT1 methylation in SN in ADHD and controls.

Background: Alcohol use disorder (AUD) is associated with increased mortality and morbidity risk. A reason for this could be accelerated biological aging, which is strongly influenced by disease processes such as inflammation. As recent studies of AUD show changes in DNA methylation and gene expression in neuroinflammation‐related pathways in the brain, biological aging represents a potentially important construct for understanding the adverse effects of substance use disorders. Epigenetic clocks have shown accelerated aging in blood samples from individuals with AUD. However, no systematic evaluation of biological age measures in AUD across different tissues and brain regions has been undertaken. Methods: As markers of biological aging (BioAge markers), we assessed Levine's and Horvath's epigenetic clocks, DNA methylation telomere length (DNAmTL), telomere length (TL), and mitochondrial DNA copy number (mtDNAcn) in postmortem brain samples from Brodmann Area 9 (BA9), caudate nucleus, and ventral striatum (N = 63–94), and in whole blood samples (N = 179) of individuals with and without AUD. To evaluate the association between AUD status and BioAge markers, we performed linear regression analyses while adjusting for covariates. Results: The majority of BioAge markers were significantly associated with chronological age in all samples. Levine's epigenetic clock and DNAmTL were indicative of accelerated biological aging in AUD in BA9 and whole blood samples, while Horvath's showed the opposite effect in BA9. No significant association of AUD with TL and mtDNAcn was detected. Measured TL and DNAmTL showed only small correlations in blood and none in brain. Conclusions: The present study is the first to simultaneously investigate epigenetic clocks, telomere length, and mtDNAcn in postmortem brain and whole blood samples in individuals with AUD. We found evidence for accelerated biological aging in AUD in blood and brain, as measured by Levine's epigenetic clock, and DNAmTL. Additional studies of different tissues from the same individuals are needed to draw valid conclusions about the congruence of biological aging in blood and brain. [ABSTRACT FROM AUTHOR]

Background Alcohol consumption and smoking, 2 major risk factors for cardiovascular disease (CVD), often occur together. The objective of this study is to use a wide range of CVD risk factors and outcomes to evaluate potential total and direct causal roles of alcohol and tobacco use on CVD risk factors and events. Methods and findings Using large publicly available genome-wide association studies (GWASs) (results from more than 1.2 million combined study participants) of predominantly European ancestry, we conducted 2-sample single-variable Mendelian randomization (SVMR) and multivariable Mendelian randomization (MVMR) to simultaneously assess the independent impact of alcohol consumption and smoking on a wide range of CVD risk factors and outcomes. Multiple sensitivity analyses, including complementary Mendelian randomization (MR) methods, and secondary alcohol consumption and smoking datasets were used. SVMR showed genetic predisposition for alcohol consumption to be associated with CVD risk factors, including high-density lipoprotein cholesterol (HDL-C) (beta 0.40, 95% confidence interval (CI), 0.04-0.47, P value = 1.72 x 10.sup.-28 ), triglycerides (TRG) (beta -0.23, 95% CI, -0.30, -0.15, P value = 4.69 x 10.sup.-10 ), automated systolic blood pressure (BP) measurement (beta 0.11, 95% CI, 0.03-0.18, P value = 4.72 x 10.sup.-3 ), and automated diastolic BP measurement (beta 0.09, 95% CI, 0.03-0.16, P value = 5.24 x 10.sup.-3). Conversely, genetically predicted smoking was associated with increased TRG (beta 0.097, 95% CI, 0.014-0.027, P value = 6.59 x 10.sup.-12). Alcohol consumption was also associated with increased myocardial infarction (MI) and coronary heart disease (CHD) risks (MI odds ratio (OR) = 1.24, 95% CI, 1.03-1.50, P value = 0.02; CHD OR = 1.21, 95% CI, 1.01-1.45, P value = 0.04); however, its impact was attenuated in MVMR adjusting for smoking. Conversely, alcohol maintained an association with coronary atherosclerosis (OR 1.02, 95% CI, 1.01-1.03, P value = 5.56 x 10.sup.-4). In comparison, after adjusting for alcohol consumption, smoking retained its association with several CVD outcomes including MI (OR = 1.84, 95% CI, 1.43, 2.37, P value = 2.0 x 10.sup.-6 ), CHD (OR = 1.64, 95% CI, 1.28-2.09, P value = 8.07 x 10.sup.-5 ), heart failure (HF) (OR = 1.61, 95% CI, 1.32-1.95, P value = 1.9 x 10.sup.-6 ), and large artery atherosclerosis (OR = 2.4, 95% CI, 1.41-4.07, P value = 0.003). Notably, using the FinnGen cohort data, we were able to replicate the association between smoking and several CVD outcomes including MI (OR = 1.77, 95% CI, 1.10-2.84, P value = 0.02), HF (OR = 1.67, 95% CI, 1.14-2.46, P value = 0.008), and peripheral artery disease (PAD) (OR = 2.35, 95% CI, 1.38-4.01, P value = 0.002). The main limitations of this study include possible bias from unmeasured confounders, inability of summary-level MR to investigate a potentially nonlinear relationship between alcohol consumption and CVD risk, and the generalizability of the UK Biobank (UKB) to other populations. Conclusions Evaluating the widest range of CVD risk factors and outcomes of any alcohol consumption or smoking MR study to date, we failed to find a cardioprotective impact of genetically predicted alcohol consumption on CVD outcomes. However, alcohol was associated with and increased HDL-C, decreased TRG, and increased BP, which may indicate pathways through impact CVD risk, warranting further study. We found smoking to be a risk factor for many CVDs even after adjusting for alcohol. While future studies incorporating alcohol consumption patterns are necessary, our data suggest causal inference between alcohol, smoking, and CVD risk, further supporting that lifestyle modifications might be able to reduce overall CVD risk., Author(s): Daniel B. Rosoff 1, George Davey Smith 2, Nehal Mehta 3, Toni-Kim Clarke 4, Falk W. Lohoff 1,* Introduction Cardiovascular disease (CVD) is a leading cause of mortality and [...]