Smoking-informed methylation and expression QTLs in human brain and colocalization with smoking-associated genetic loci.

Smoking is a leading cause of preventable morbidity and mortality. Smoking is heritable, and genome-wide association studies (GWASs) of smoking behaviors have identified hundreds of significant loci. Most GWAS-identified variants are noncoding with unknown neurobiological effects. We used genome-wide genotype, DNA methylation, and RNA sequencing data in postmortem human nucleus accumbens (NAc) to identify cis-methylation/expression quantitative trait loci (meQTLs/eQTLs), investigate variant-by-cigarette smoking interactions across the genome, and overlay QTL evidence at smoking GWAS-identified loci to evaluate their regulatory potential. Active smokers (N = 52) and nonsmokers (N = 171) were defined based on cotinine biomarker levels and next-of-kin reporting. We simultaneously tested variant and variant-by-smoking interaction effects on methylation and expression, separately, adjusting for biological and technical covariates and correcting for multiple testing using a two-stage procedure. We found >2 million significant meQTL variants (padj < 0.05) corresponding to 41,695 unique CpGs. Results were largely driven by main effects, and five meQTLs, mapping to NUDT12, FAM53B, RNF39, and ADRA1B, showed a significant interaction with smoking. We found 57,683 significant eQTL variants for 958 unique eGenes (padj < 0.05) and no smoking interactions. Colocalization analyses identified loci with smoking-associated GWAS variants that overlapped meQTLs/eQTLs, suggesting that these heritable factors may influence smoking behaviors through functional effects on methylation/expression. One locus containing MUSTN1 and ITIH4 colocalized across all data types (GWAS, meQTL, and eQTL). In this first genome-wide meQTL map in the human NAc, the enriched overlap with smoking GWAS-identified genetic loci provides evidence that gene regulation in the brain helps explain the neurobiology of smoking behaviors.

Trans-ancestry epigenome-wide association meta-analysis of DNA methylation with lifetime cannabis use.

Cannabis is widely used worldwide, yet its links to health outcomes are not fully understood. DNA methylation can serve as a mediator to link environmental exposures to health outcomes. We conducted an epigenome-wide association study (EWAS) of peripheral blood-based DNA methylation and lifetime cannabis use (ever vs. never) in a meta-analysis including 9436 participants (7795 European and 1641 African ancestry) from seven cohorts. Accounting for effects of cigarette smoking, our trans-ancestry EWAS meta-analysis revealed four CpG sites significantly associated with lifetime cannabis use at a false discovery rate of 0.05 [Formula: see text]: cg22572071 near gene ADGRF1, cg15280358 in ADAM12, cg00813162 in ACTN1, and cg01101459 near LINC01132. Additionally, our EWAS analysis in participants who never smoked cigarettes identified another epigenome-wide significant CpG site, cg14237301 annotated to APOBR. We used a leave-one-out approach to evaluate methylation scores constructed as a weighted sum of the significant CpGs. The best model can explain 3.79% of the variance in lifetime cannabis use. These findings unravel the DNA methylation changes associated with lifetime cannabis use that are independent of cigarette smoking and may serve as a starting point for further research on the mechanisms through which cannabis exposure impacts health outcomes.

Smoking-informed methylation and expression QTLs in human brain and colocalization with smoking-associated genetic loci.

Smoking is a leading cause of preventable morbidity and mortality. Smoking is heritable, and genome-wide association studies (GWAS) of smoking behaviors have identified hundreds of significant loci. Most GWAS-identified variants are noncoding with unknown neurobiological effects. We used genome-wide genotype, DNA methylation, and RNA sequencing data in postmortem human nucleus accumbens (NAc) to identify cis-methylation/expression quantitative trait loci (meQTLs/eQTLs), investigate variant-by-cigarette smoking interactions across the genome, and overlay QTL evidence at smoking GWAS-identified loci to evaluate their regulatory potential. Active smokers (N=52) and nonsmokers (N=171) were defined based on cotinine biomarker levels and next-of-kin reporting. We simultaneously tested variant and variant-by-smoking interaction effects on methylation and expression, separately, adjusting for biological and technical covariates and using a two-stage multiple testing approach with eigenMT and Bonferroni corrections. We found >2 million significant meQTL variants (padj<0.05) corresponding to 41,695 unique CpGs. Results were largely driven by main effects; five meQTLs, mapping to NUDT12, FAM53B, RNF39, and ADRA1B, showed a significant interaction with smoking. We found 57,683 significant eQTLs for 958 unique eGenes (padj<0.05) and no smoking interactions. Colocalization analyses identified loci with smoking-associated GWAS variants that overlapped meQTLs/eQTLs, suggesting that these heritable factors may influence smoking behaviors through functional effects on methylation/expression. One locus containing MUSTIN1 and ITIH4 colocalized across all data types (GWAS + meQTL + eQTL). In this first genome-wide meQTL map in the human NAc, the enriched overlap with smoking GWAS-identified genetic loci provides evidence that gene regulation in the brain helps explain the neurobiology of smoking behaviors.

Evaluation of pediatric epigenetic clocks across multiple tissues.

BACKGROUND: Epigenetic clocks are promising tools for assessing biological age. We assessed the accuracy of pediatric epigenetic clocks in gestational and chronological age determination. RESULTS: Our study used data from seven tissue types on three DNA methylation profiling microarrays and found that the Knight and Bohlin clocks performed similarly for blood cells, while the Lee clock was superior for placental samples. The pediatric-buccal-epigenetic clock performed the best for pediatric buccal samples, while the Horvath clock is recommended for children's blood cell samples. The NeoAge clock stands out for its unique ability to predict post-menstrual age with high correlation with the observed age in infant buccal cell samples. CONCLUSIONS: Our findings provide valuable guidance for future research and development of epigenetic clocks in pediatric samples, enabling more accurate assessments of biological age.

Multi-trait genome-wide association study of opioid addiction: OPRM1 and beyond.

Opioid addiction (OA) is moderately heritable, yet only rs1799971, the A118G variant in OPRM1, has been identified as a genome-wide significant association with OA and independently replicated. We applied genomic structural equation modeling to conduct a GWAS of the new Genetics of Opioid Addiction Consortium (GENOA) data together with published studies (Psychiatric Genomics Consortium, Million Veteran Program, and Partners Health), comprising 23,367 cases and effective sample size of 88,114 individuals of European ancestry. Genetic correlations among the various OA phenotypes were uniformly high (rg > 0.9). We observed the strongest evidence to date for OPRM1: lead SNP rs9478500 (p = 2.56 × 10-9). Gene-based analyses identified novel genome-wide significant associations with PPP6C and FURIN. Variants within these loci appear to be pleiotropic for addiction and related traits.

Evaluation of the GSP Creatine Kinase-MM Assay and Assessment of CK-MM Stability in Newborn, Patient, and Contrived Dried Blood Spots for Newborn Screening for Duchenne Muscular Dystrophy.

Duchenne Muscular Dystrophy (DMD) is a fatal X-linked disorder with a birth prevalence of 19.8:100,000 males worldwide. Elevated concentration of the muscle enzyme creatine kinase-MM (CK-MM) allows for presymptomatic screening of newborns using Dried Blood Spots (DBS). We evaluated imprecision and carryover of the FDA-approved PerkinElmer GSP Neonatal CK-MM kit over multiple runs, days, and operators, followed by quantification of CK-MM loss in stored newborn, contrived, and non-newborn patient DBS resulting from exposure to ambient versus low humidity (50-day trial), and high humidity and high temperature (8-day trial). Imprecision %CV was ≤14% for all verification comparisons and over 6 months of testing. On average, the mean CK-MM recovery after 50 days was >80% of initial concentration for all sample types stored in low humidity and <80% in ambient humidity. After 8 days of storage in high humidity and high temperature, the mean recovery for newborn samples was <80%. Verification results for the GSP Neonatal CK-MM assay were concordant with kit parameters and the assay performed consistently over 6 months. CK-MM degradation in ambient storage can be mitigated by reducing exposure to humidity. Assessment of DBS shipping and storage conditions is recommended prior to implementing DMD screening.

Diagnostic utility of exome sequencing in the evaluation of neuromuscular disorders.

OBJECTIVE: To evaluate the diagnostic yield and workflow of genome-scale sequencing in patients with neuromuscular disorders (NMDs). METHODS: We performed exome sequencing in 93 undiagnosed patients with various NMDs for whom a molecular diagnosis was not yet established. Variants on both targeted and broad diagnostic gene lists were identified. Prior diagnostic tests were extracted from the patient's medical record to evaluate the use of exome sequencing in the context of their prior diagnostic workup. RESULTS: The overall diagnostic yield of exome sequencing in our cohort was 12.9%, with one or more pathogenic or likely pathogenic variants identified in a causative gene associated with the patient's disorder. Targeted gene lists had the same diagnostic yield as a broad NMD gene list in patients with clear neuropathy or myopathy phenotypes, but evaluation of a broader set of disease genes was needed for patients with complex NMD phenotypes. Most patients with NMD had undergone prior testing, but only 10/16 (63%) of these procedures, such as muscle biopsy, were informative in pointing to a final molecular diagnosis. CONCLUSIONS: Genome-scale sequencing or analysis of a panel of relevant genes used early in the evaluation of patients with NMDs can provide or clarify a diagnosis and minimize invasive testing in many cases.

Local field potentials are local events in the mouse auditory cortex.

Local field potentials (LFPs) and spikes (SPKs) sampled at the thalamocortical recipient layers represent the inputs from the thalamus and outputs to other layers. Previous studies have shown that SPK-constructed receptive fields (RFSPK) of cortical neurons are much smaller than LFP-constructed RFs (RFLFP). The difference in cortical RFLFP and RFSPK is therefore a plausible indication of local networking. The presence of a boarder RFLFP appears due to contamination, to some degree, from remote sites. Our studies of the mouse primary auditory cortex show that the best frequencies and minimum thresholds of RFSPK and RFLFP were similar. We also observed that the RFLFP area was only slightly larger than the RFSPK area, a very different finding from previous reports. The bandwidth of RFLFP was slightly broader than that of RFSPK at all levels. These data do not support the explanation that bioelectrical signals from distant sites impact on cortical LFP through volume conduction. That the cortical LFP represents a local event is further supported by comparisons of RFSPK and RFLFP after cortical inhibition by muscimol and cortical disinhibition by bicuculine. We conclude that the difference between RFSPK (output of cortical neurons) and RFLFP (input of cortical neurons) results from intracortical processing, including cortical lateral inhibition and excitation.