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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.

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]

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]

Alcohol use disorder (AUD) is a major contributor to morbidity and mortality worldwide. Although there is a heritable component, the etiology of AUD is complex and can involve environmental exposures like trauma and can be associated with many different patterns of alcohol consumption. Epigenetic modifications, which can mediate the influence of genetic variants and environmental variables on gene expression, have emerged as an important area of AUD research. Over the past decade, the number of studies investigating AUD and DNA methylation, a form of epigenetic modification, has grown rapidly. Yet we are still far from understanding how DNA methylation contributes to or reflects aspects of AUD. In this paper, we reviewed studies of DNA methylation and AUD and discussed how the field has evolved. We found that global DNA and candidate DNA methylation studies did not produce replicable results. To assess whether findings of epigenome‐wide association studies (EWAS) were replicated, we aggregated significant findings across studies and identified 184 genes and 15 gene ontological pathways that were differentially methylated in at least two studies and four genes and three gene ontological pathways that were differentially methylated in three studies. These genes and pathways repeatedly found enrichment of immune processes, which is in line with recent developments suggesting that the immune system may be altered in AUD. Finally, we assess the current limitations of studies of DNA methylation and AUD and make recommendations on how to design future studies to resolve outstanding questions. [ABSTRACT FROM AUTHOR]

The prevalence of type 2 diabetes (T2D) varies among populations of different race/ethnicity. The influence of genetically-proxied lipoprotein cholesterol (LDL-C) lowering through proprotein convertase subtilisin/kexin 9 (PCSK9) and HMG-CoA Reductase (HMGCR) on T2D in non-European populations is not well established.A drug-target Mendelian randomization (MR) approach was used to assess the effects of PCSK9 and HMGCR inhibition on T2D risk and glycemic traits in five populations: East Asian (EAS), South Asian (SAS), Hispanic (HISP), African (AFR), and European (EUR). Our study did not find relationships between genetically-proxied PCSK9 inhibition and T2D risk in EAS (odds ratio [OR]=1.02, [0.95-1.10]), SAS (OR=1.05, [0.97-1.14]), HISP (OR=1.03, [0.94-1.12]), or EUR (OR=1.04, [0.98-1.11]). However, in AFR, primary analyses suggested an increased risk of T2D due to PCSK9 inhibition (OR=1.53, [1.058-2.22], P-value=0.024), although this was not supported in sensitivity analyses. Genetically-proxied HMGCR inhibition was associated with an increased risk of T2D in SAS (OR=1.44, [1.30-1.61], P-value=9.8×10-12), EAS (OR=1.36, [1.22-1.51], P-value=4.2×10-10), and EUR (OR=1.52, [1.21-1.90], P-value=3.3×10-4). These results were consistent across various sensitivity analyses, including colocalization, indicating a robust finding. The findings indicate a neutral impact of long-term PCSK9 inhibition on T2D and glycemic markers in most non-European populations, with a potential increased risk in AFR cohorts. By contrast, HMGCR inhibition increased the risk of T2D in South Asian, East Asian, and European cohorts, underscoring the need to consider diversity in genetic research on metabolic diseases., (© 2024 by the American Diabetes Association.)

Human genetic and transgenic mouse studies have highlighted a potential liver-adipose tissue endocrine axis, involving activin C (Act-C) and/or Act-E and ALK7, influencing fat distribution and systemic metabolism. We investigated the bidirectional effects between circulating INHBC, which homodimerizes into Act-C, and adiposity traits, insulin resistance, inflammation, and cardiometabolic disease risk. Additionally, we examined if Act-C is an ALK7 ligand in human adipocytes. We used Mendelian randomization and in vitro studies in immortalized human abdominal and gluteal adipocytes. Circulating INHBC was causally linked to reduced lower-body fat, dyslipidaemia, and increased risks of coronary artery disease (CAD) and non-alcoholic fatty liver disease (NAFLD). Conversely, upper-body fat distribution, obesity, hypertriglyceridemia, subclinical inflammation, and type 2 diabetes positively impacted plasma INHBC levels. Mechanistically, an atherogenic lipid profile may partly explain the INHBC-CAD link, while inflammation and hypertriglyceridemia may partly explain how adiposity traits affect circulating INHBC. Phenome-wide Mendelian randomization showed weak causal relationships between higher plasma INHBC and impaired kidney function and higher gout risk. In human adipocytes, recombinant Act-C activated SMAD2/3 signaling via ALK7 and suppressed lipolysis. In summary, INHBC influences systemic metabolism by activating ALK7 in adipose tissue and may serve as a drug target for atherogenic dyslipidemia, CAD, and NAFLD., (© 2024 by the American Diabetes Association.)

Background: Lithium is regarded as a first-line treatment for bipolar disorder (BD), but partial response and non-response commonly occurs. There exists a need to identify lithium non-responders prior to initiating treatment. The Pharmacogenomics of Bipolar Disorder (PGBD) Study was designed to identify predictors of lithium response., Methods: The PGBD Study was an eleven site prospective trial of lithium treatment in bipolar I disorder. Subjects were stabilized on lithium monotherapy over 4 months and gradually discontinued from all other psychotropic medications. After ensuring a sustained clinical remission (defined by a score of ≤3 on the CGI for 4 weeks) had been achieved, subjects were followed for up to 2 years to monitor clinical response. Cox proportional hazard models were used to examine the relationship between clinical measures and time until failure to remit or relapse., Results: A total of 345 individuals were enrolled into the study and included in the analysis. Of these, 101 subjects failed to remit or relapsed, 88 achieved remission and continued to study completion, and 156 were terminated from the study for other reasons. Significant clinical predictors of treatment failure (p < 0.05) included baseline anxiety symptoms, functional impairments, negative life events and lifetime clinical features such as a history of migraine, suicidal ideation/attempts, and mixed episodes, as well as a chronic course of illness., Conclusions: In this PGBD Study of lithium response, several clinical features were found to be associated with failure to respond to lithium. Future validation is needed to confirm these clinical predictors of treatment failure and their use clinically to distinguish who will do well on lithium before starting pharmacotherapy., (© 2021 The Authors. Bipolar Disorders published by John Wiley & Sons Ltd.)