ZSCAN25 methylation predicts seizures and severe alcohol withdrawal syndrome.

Currently, clinicians use their judgement and indices such as the Prediction of Alcohol Withdrawal Syndrome Scale (PAWSS) to determine whether patients are admitted to hospitals for consideration of withdrawal syndrome (AWS). However, only a fraction of those admitted will experience severe AWS. Previously, we and others have shown that epigenetic indices, such as the Alcohol T-Score (ATS), can quantify recent alcohol consumption. However, whether these or other alcohol biomarkers, such as carbohydrate deficient transferrin (CDT), could identify those at risk for severe AWS is unknown. To determine this, we first conducted genome-wide DNA methylation analyses of subjects entering and exiting alcohol treatment to identify loci whose methylation quickly reverted as a function of abstinence. We then tested whether methylation at a rapidly reverting locus, cg07375256, or other existing metrics including PAWSS scores, CDT levels, or ATS, could predict outcome in 125 subjects admitted for consideration of AWS. We found that PAWSS did not significantly predict severe AWS nor seizures. However, methylation at cg07375256 (ZSCAN25) and CDT strongly predicted severe AWS with ATS (p < 0.007) and cg07375256 (p < 6 × 10-5) methylation also predicting AWS associated seizures. We conclude that epigenetic methods can predict those likely to experience severe AWS and that the use of these or similar Precision Epigenetic approaches could better guide AWS management.

Building multi-system nexuses in low-carbon transitions: Conflicts and asymmetric adjustments in Norwegian ferry electrification.

While nexus research in sustainability science has investigated the consequences of connected systems, it has paid less attention to the processes of building nexuses which is becoming increasingly important in low-carbon transitions because these often require the creation of new connections between multiple consumption-production systems. Building on multi-system research in the sustainability transitions literature, this paper introduces a conceptual system interface perspective on nexus-building which considers four dimensions (technology, actors, institutions, and resources) that are useful for analyzing nexus-building dynamics. We apply our framework to the case of electrification of ferries in Norway which requires the building of a new interface between the electricity system and the maritime transport system. The case study shows that the system interface was initially characterized by conflicts and tensions in all dimensions, which actors then attempted to resolve through cross-system intermediation and adjustment activities. These activities were asymmetrical because of differences in external pressures, urgency, unequal power relationships, and different degrees of interest in cross-system nexus building. Because important tensions remained unresolved, ferry actors started implementing sub-optimal workaround solutions in the diffusion phase.

Epigenetic biomarkers for smoking cessation.

Cigarette smoking has been associated with epigenetic alterations that may be reversible upon cessation. As the most-studied epigenetic modification, DNA methylation is strongly associated with smoking exposure, providing a potential mechanism that links smoking to adverse health outcomes. Here, we reviewed the reversibility of DNA methylation in accessible peripheral tissues, mainly blood, in relation to cigarette smoking cessation and the utility of DNA methylation as a biomarker signature to differentiate current, former, and never smokers and to quantify time since cessation. We summarized thousands of differentially methylated Cytosine-Guanine (CpG) dinucleotides and regions associated with smoking cessation from candidate gene and epigenome-wide association studies, as well as the prediction accuracy of the multi-CpG predictors for smoking status. Overall, there is robust evidence for DNA methylation signature of cigarette smoking cessation. However, there are still gaps to fill, including (1) cell-type heterogeneity in measuring blood DNA methylation; (2) underrepresentation of non-European ancestry populations; (3) limited longitudinal data to quantitatively measure DNA methylation after smoking cessation over time; and (4) limited data to study the impact of smoking cessation on other epigenetic features, noncoding RNAs, and histone modifications. Epigenetic machinery provides promising biomarkers that can improve success in smoking cessation in the clinical setting. To achieve this goal, larger and more-diverse samples with longitudinal measures of a broader spectrum of epigenetic marks will be essential to developing a robust DNA methylation biomarker assay, followed by meeting validation requirements for the assay before being implemented as a clinically useful tool.

DNA methylation differentiates smoking from vaping and non-combustible tobacco use.

Increasing use of non-combusted forms of nicotine such as e-cigarettes poses important public health questions regarding their specific risks relative to combusted tobacco products such as cigarettes. To fully delineate these risks, improved biomarkers that can distinguish between these forms of nicotine use are needed. Prior work has suggested that methylation status at cg05575921 may serve as a specific biomarker of combusted tobacco smoke exposure. We hypothesized combining this epigenetic biomarker with conventional metabolite assays could classify the type of nicotine product consumption. Therefore, we determined DNA methylation and serum cotinine values in samples from 112 smokers, 35 e-cigarette users, 19 smokeless tobacco users, and 269 controls, and performed mass spectroscopy analyses of urine samples from all nicotine users and 22 verified controls to determine urinary levels of putatively nicotine product-specific substances; propylene glycol, 2-cyanoethylmercapturic acid (CEMA), and anabasine. 1) Cigarette smoking was associated with a dose dependent demethylation of cg05575921 and increased urinary CEMA and anabasine levels, 2) e-cigarette use did not demethylate cg05575921, 3) smokeless tobacco use also did not demethylate cg05575921 but was positively associated with anabasine levels 4) CEMA and cg05575921 levels were highly correlated and 5) propylene glycol levels did not reliably distinguish use groups. Cg05575921 assessments distinguish exposure to tobacco smoke from smokeless sources of nicotine including e-cigarettes and smokeless tobacco, neither of which are associated with cg05575921 demethylation. A combination of methylomic and metabolite profiling may allow for accurate classification use status of a variety of nicotine containing products.

Epigenetic Analyses of Alcohol Consumption in Combustible and Non-Combustible Nicotine Product Users.

Alcohol and tobacco use are highly comorbid and exacerbate the associated morbidity and mortality of either substance alone. However, the relationship of alcohol consumption to the various forms of nicotine-containing products is not well understood. To improve this understanding, we examined the relationship of alcohol consumption to nicotine product use using self-report, cotinine, and two epigenetic biomarkers specific for smoking (cg05575921) and drinking (Alcohol T Scores (ATS)) in n = 424 subjects. Cigarette users had significantly higher ATS values than the other groups (p < 2.2 × 10-16). Using the objective biomarkers, the intensity of nicotine and alcohol consumption was correlated in both the cigarette and smokeless users (R = -0.66, p = 3.1 × 10-14; R2 = 0.61, p = 1.97 × 10-4). Building upon this idea, we used the objective nicotine biomarkers and age to build and test a Balanced Random Forest classification model for heavy alcohol consumption (ATS > 2.35). The model performed well with an AUC of 0.962, 89.3% sensitivity, and 85% specificity. We conclude that those who use non-combustible nicotine products drink significantly less than smokers, and cigarette and smokeless users drink more with heavier nicotine use. These findings further highlight the lack of informativeness of self-reported alcohol consumption and suggest given the public and private health burden of alcoholism, further research into whether using non-combustible nicotine products as a mode of treatment for dual users should be considered.

The relationship of smoking to cg05575921 methylation in blood and saliva DNA samples from several studies.

Numerous studies have shown that cg05575921 methylation decreases in response to smoking. However, secondary to methodological issues, the magnitude and dose dependency of that response is as of yet unclear. This lack of certainty is a barrier to the use of DNA methylation clinically to assess and monitor smoking status. To better define this relationship, we conducted a joint analysis of methylation sensitive PCR digital (MSdPCR) assessments of cg05575921 methylation in whole blood and/or saliva DNA to smoking using samples from 421 smokers and 423 biochemically confirmed non-smokers from 4 previously published studies. We found that cg05575921 methylation manifested a curvilinear dose dependent decrease in response to increasing cigarette consumption. In whole blood DNA, the Receiver Operating Characteristic (ROC) Area Under the Curve (AUC) of cg05575921 methylation for predicting daily smoking status was 0.98. In saliva DNA, the gross AUC was 0.91 with correction for cellular heterogeneity improving the AUC to 0.94. Methylation status was significantly associated with the Fagerstrom Test for Nicotine Dependence score, but with significant sampling heterogeneity. We conclude that MSdPCR assessments of cg05575921 methylation are a potentially powerful, clinically implementable tool for the assessment and management of smoking.

An Examination of Risk Factors for Tobacco and Cannabis Smoke Exposure in Adolescents Using an Epigenetic Biomarker.

Objective: Evolving patterns of nicotine and cannabis use by adolescents require new tools to understand the changing epidemiology of these substances. Here we describe the use of a novel epigenetic biomarker sensitive to both tobacco and cannabis smoke in a longitudinal sample of high-risk adolescents. We examine risk factors for positivity for this epigenetic biomarker in comparison to positivity for conventional serum biomarkers of nicotine and cannabis use. Method: Eastern Iowa 10th graders who had a friend or family member who smoked were eligible to participate in a longitudinal study over 10-12th grades. Subjects provided self-report data on nicotine, tobacco, and cannabis use patterns as well as blood samples that were used for serum cotinine and THC assays. DNA was prepared for analysis of methylation at the CpG cg05575921, a sensitive indicator of smoke exposure. Relationships between positivity for each these biomarkers and a variety of risk factors, including demographics, family and peer relationships, psychopathology, willingness to smoke, and perceptions of typical cigarette and cannabis users, were examined at the 10th (n = 442), 11th (n = 376), and 12th (n = 366) grade timepoints. Results: A increasing proportion of subjects were positive for cotinine (5-16%), THC (3-10%), and cg05575921 methylation (5-7%) across timepoints, with some overlap. Self-reported combusted tobacco and cannabis use was strongly correlated with all biomarkers, whereas cg05575921 methylation was not correlated with reported e-cigarette use. Dual users, defined as those positive for nicotine and THC in the 12th grade showed the greatest cumulative smoke exposure, indicated by cg05575921 methylation. Subjects reported more positive attitudes toward cannabis users than cigarette smokers, and willingness to smoke and positive perceptions of tobacco and cannabis smokers were significant risk factors for biomarker positivity across timepoints. Conclusion: We conclude that measurement of cg05575921 methylation in adolescents is a useful tool in detecting tobacco smoking in adolescents, and may be a novel tool for the detection of cannabis smoking and cannabis and tobacco co-use, though non-combusted forms of nicotine use do not appear to be detectable by this method.

Alcohol Use Intensity Decreases in Response to Successful Smoking Cessation Therapy.

Smokers frequently drink heavily. However, the effectiveness of smoking cessation therapy for those with comorbid alcohol abuse is unclear, and the content of smoking cessation programs often does not address comorbid alcohol consumption. In order to achieve a better understanding of the relationship between changes in rate of smoking to the change in intensity of alcohol consumption, and the necessity for alcohol-specific programming for dual users, we quantified cigarette and alcohol consumption in 39 subjects undergoing a 3-month contingency management smoking cessation program using recently developed DNA methylation tools. Intake alcohol consumption, as quantified by the Alcohol T Score (ATS), was highly correlated with cg05575921 smoking intensity (adjusted R2 = 0.49) with 19 of the 39 subjects having ATS scores indicative of Heavy Alcohol Consumption. After 90 days of smoking cessation therapy, ATS values decreased with the change in ATS score being highly correlated with change in cg05575921 smoking intensity (adjusted R2 = 0.60), regardless of whether or not the subject managed to completely quit smoking. We conclude that alcohol consumption significantly decreases in response to successful smoking cessation. Further studies to determine whether targeted therapy focused on comorbid alcohol use increases the success of smoking cessation in those with dual use should be explored.

Inflammatory biomarker relationships with helper T cell GPR15 expression and cannabis and tobacco smoking.

OBJECTIVE: Smoking is associated with numerous inflammatory and autoimmune conditions. The goal of this study was to examine whether increased expression of G-protein-coupled receptor 15 (GPR15) on helper T cells in smokers could predispose to these conditions through its relationship with inflammatory biomarkers. METHODS: We used flow cytometric measurement of GPR15+CD3+CD4+ helper T cells and serum assays for C-reactive protein (CRP) and 17 cytokines drawn from peripheral blood samples from a cohort of n = 62 primarily African American young adults (aged 27-35 years). These variables were examined cross-sectionally in conjunction with serum biomarkers of tobacco (cotinine) and cannabis (tetrahydrocannabinol) use and lifestyle factors potentially impacting immune function in correlational analyses and linear regression models. RESULTS: Tobacco and cannabis smoking were strongly associated with increased GPR15 expression on helper T cells (p < 0.001), which was in turn was strongly associated with the ratio of pro-inflammatory to anti-inflammatory cytokines (p < 0.001). Mediation analyses indicated increased GPR15 expression accounted for roughly half of the relationship between smoking variables and pro-inflammatory to anti-inflammatory cytokine balance. CRP was not associated with cannabis or tobacco use or GPR15+ expression, but was associated with body mass index (p < 0.001). These relationships persisted after controlling for lifestyle and medical factors impacting immune function. CONCLUSIONS: Increased expression of GPR15 by helper T cells in smokers may mediate some of the relationship between smoking and a pro-inflammatory cytokine milieu. Better understanding of this relationship may help uncover how smoking increases the risk of inflammatory diseases.

Refinement of cg05575921 demethylation response in nascent smoking.

The initiation of adolescent smoking is difficult to detect using carbon monoxide or cotinine assays. Previously, we and others have shown that the methylation of cg05575921 is an accurate predictor of adult smoking status. But the dose and time dependency of the demethylation response to smoking initiation in adolescents is not yet well understood. To this end, we conducted three consecutive annual in-person interviews and biological samplings of 448 high school students (wave 1 (W1)-wave 3 (W3)). At W1 (n = 448), 62 subjects reported using tobacco and 72 subjects reported using cannabis at least once in their life-time with 38 and 20 subjects having a positive cotinine and cannabinoid levels, respectively, at W1 intake. At W3 (n = 383), 67 subjects reported using tobacco and 60 subjects reported using cannabis at least once with 75 and 60 subjects having positive cotinine and cannabinoid levels, respectively, at W3. Subjects with undetectable cotinine levels at all three-time waves had stable levels of cg05575921 methylation throughout the study (88.7% at W1 and 88.8% at W3, n = 149), while subjects with positive cotinine levels at all 3 time points manifested a steady decrease in cg05575921 methylation (81.8% at W1 and 71.3% at the W3, n = 12). In those subjects with an affirmative smoking self-report at W3 (n = 17), the amount of demethylation at cg05575921 was correlated with time and intensity of smoking. We conclude that cg05575921 methylation is a sensitive, dose-dependent indicator of early stages of smoking, and may help to identify smokers in the early stages of smoking.

Cigarette and Cannabis Smoking Effects on GPR15+ Helper T Cell Levels in Peripheral Blood: Relationships with Epigenetic Biomarkers.

Background: Smoking causes widespread epigenetic changes that have been linked with an increased risk of smoking-associated diseases and elevated mortality. Of particular interest are changes in the level of T cells expressing G-protein-coupled receptor 15 (GPR15), a chemokine receptor linked with multiple autoimmune diseases, including inflammatory bowel disease, multiple sclerosis and psoriasis. Accordingly, a better understanding of the mechanisms by which smoking influences variation in the GPR15+ helper T cell subpopulation is of potential interest. Methods: In the current study, we used flow cytometry and digital PCR assays to measure the GPR15+CD3+CD4+ populations in peripheral blood from a cohort of n = 62 primarily African American young adults (aged 27-35 years) with a high rate of tobacco and cannabis use. Results: We demonstrated that self-reported tobacco and cannabis smoking predict GPR15+CD3+CD4+ helper T cell levels using linear regression models. Further, we demonstrated that methylation of two candidate CpGs, cg19859270, located in GPR15, and cg05575921, located in the gene Aryl Hydrocarbon Receptor Repressor (AHRR), were both significant predictors of GPR15+CD3+CD4+ cell levels, mediating the relationship between smoking habits and increases in GPR15+CD3+CD4+ cells. As hypothesized, the interaction between cg05575921 and cg19859270 was also significant, indicating that low cg05575921 methylation was more strongly predictive of GPR15+CD3+CD4+ cell levels for those who also had lower cg19859270 methylation. Conclusions: Smoking leads changes in two CpGs, cg05575921 and cg19859270, that mediate 38.5% of the relationship between tobacco and cannabis smoking and increased GPR15+ Th levels in this sample. The impact of cg19859270 in amplifying the association between cg05575921 and increased GPR15+ Th levels is of potential theoretical interest given the possibility that it reflects a permissive interaction between different parts of the adaptive immune system.

Elopement Patterns and Caregiver Strategies.

The Interactive Autism Network (IAN) administered a survey to caregivers of children with Autism Spectrum Disorder (ASD) on their interventions for elopement behavior (EB). Data from 526 respondents were analyzed. Most families reported multiple interventions for EB and rated interventions overall as effective but burdensome. Several interventions such as fencing and window locks had favorable effectiveness/burden profiles. Tracking devices were used infrequently and rated as having low effectiveness. Behavioral specialists were commonly used, rated as effective, and most often provided by insurance. Medications were rated as having low effectiveness for EB, whether taken off-label for EB or for other reasons. Further study is needed to identify EB interventions that are effective, affordable, and easy to implement are needed.

Saliva DNA Methylation Detects Nascent Smoking in Adolescents.

Objectives: Early identification of smoking, essential for the successful implementation of interventions, arrests the escalation of smoking and smoking-associated risk behaviors in adolescents. However, because nascent smoking is typically episodic and infrequent, enzyme-linked immunoassay reagent-based approaches that detect cotinine, a key nicotine metabolite, are not effective in identifying adolescents in the earliest stages of smoking. Epigenetic methods may offer an alternative approach for detecting early-stage smokers. In prior work, we and others have shown that the methylation status of cg05575921 of whole-blood DNA accurately predicts smoking status in regularly smoking adults and is sensitive to nascent smoking. Yet, the blood draws necessary to obtain DNA for this method may be poorly accepted by adolescents. Saliva could be an alternative source of DNA. However, the ability of saliva DNA methylation status to predict smoking status among adolescents is unknown. Methods: To explore the possibility of using salivary DNA for screening purposes, we examined the DNA methylation status at cg05575921 in saliva DNA samples from 162 high school aged subjects for whom we also had paired serum cotinine values. Results: Overall, the reliability of self-report of nicotine/tobacco use in these adolescents was poor with 67% of all subjects whose serum levels of cotinine was ≥2 ng/mL (n = 75) denying any use of nicotine-containing products in the past 6 months. However, the correspondence of the two biological measures of smoking was high, with serum cotinine positivity being strongly correlated with cg05575921 methylation (p < 0.0001). Receiver operating characteristic (ROC) analyses showed that cg05575921 methylation status could be used to classify those with positive serum cotinine values (≥2 ng/mL) from those denying smoking and have undetectable levels of cotinine. Conclusions: We conclude that saliva DNA methylation assessments hold promise as a means of detecting nascent smoking.

Methylation of MTHFR Moderates the Effect of Smoking on Genomewide Methylation Among Middle Age African Americans.

Differential methylation at MTHFR (mMTHFR) has been examined previously as a moderator of changes in methylation among nascent smokers, but the effects of mMTHFR on genomewide patterns of methylation among established smokers in middle age are unknown. In the current investigation we examined a sample of 180 African American middle-aged smokers and non-smokers to test for patterns indicative of three different potential mechanisms of impact on epigenetic remodeling in response to long-term smoking. We found that mMTHFR moderated the association between smoking and changes in methylation for more than 25% of the 909 loci previously identified as being associated with smoking at a genomewide level of significance in middle-aged African Americans. Observed patterns of effect indicated amplification of both hyper and hypo methylating responses to smoking among those with lower mMTHFR. Moderating effects were robust to controls for sex, age, diet, and cell-type variation. Implications for potential mechanisms conferring effects are discussed. Of particular potential practical importance was a strong effect of mMTHFR on hypomethylation at GPR15 in response to smoking, indicative of the differential impact of MTHFR activity on changes in a specific cell population linked to inflammatory disease in smokers.

A Droplet Digital PCR Assay for Smoking Predicts All-Cause Mortality.

OBJECTIVES: -Determine whether an epigenetic assay for smoking predicts all-cause mortality in adults participating in a longitudinal study of Iowa adoptees. BACKGROUND: -Improved biomarkers for smoking are needed given its large public health impact and significant limitations of both self-report and current biomarkers, such as cotinine in detecting smoking. In the past 5 years, multiple epigenome-wide association studies of smoking have identified loci suitable for translation as epigenetic biomarkers for smoking, in particular the CpG cg05575921. Digital polymerase chain reaction methods hold promise for the development of this and other epigenetic biomarkers. METHODS: -Participants in the Iowa Adoption Studies were interviewed regarding their smoking habits. DNA was prepared from whole blood and bisulfite-converted for methylation analysis and digital droplet polymerase chain reaction assay of methylation at cg05575921 was performed. National Death Index records were requested for 584 study participants, resulting in 24 complete matches, 210 partial matches and 350 non-matching records. Complete matches were coded as deceased while the remainder were coded as alive (ie, censored). In total, methylation data and vital status information were available for a total of N = 193 subjects, including 15 deceased and 178 non-deceased. Cox regression was used to examine the ability of cg05575921 methylation as a continuous value to predict the timing of mortality with and without the inclusion of age, sex, race, BMI, marital status, educational status, socioeconomic status, cardiovascular risk factors, and a history of cancer as covariates. RESULTS: -Methylation at cg05575921 predicted the hazard of mortality as the sole predictor and after accounting for major demographic and clinical risk factors. The fitted model showed the hazard ratio increased by 3.5% for every 1% decrease in methylation. CONCLUSIONS: -Decreased methylation at cg05575921, an emerging epigenetic biomarker for smoking, was associated with early mortality in a longitudinal study of adults after accounting for the impact of major demographic and clinical risk factors for all-cause mortality. This approach may be useful in clinical research or actuarial assessments.

Accuracy and utility of an epigenetic biomarker for smoking in populations with varying rates of false self-report.

Better biomarkers to detect smoking are needed given the tremendous public health burden caused by smoking. Current biomarkers to detect smoking have significant limitations, notably a short half-life for detection and lack of sensitivity for light smokers. These limitations may be particularly problematic in populations with less accurate self-reporting. Prior epigenome-wide association studies indicate that methylation status at cg05575921, a CpG residue located in the aryl hydrocarbon receptor repressor (AHRR) gene, may be a robust indicator of smoking status in individuals with as little as half of a pack-year of smoking. In this study, we show that a novel droplet digital PCR assay for measuring methylation at cg05575921 can reliably detect smoking status, as confirmed by serum cotinine, in populations with different demographic characteristics, smoking histories, and rates of false-negative self-report of smoking behavior. Using logistic regression models, we show that obtaining maximum accuracy in predicting smoking status depends on appropriately weighting self-report and cg05575921 methylation according to the characteristics of the sample being tested. Furthermore, models using only cg05575921 methylation to predict smoking perform nearly as well as those also including self-report across populations. In conclusion, cg05575921 has significant potential as a clinical biomarker to detect smoking in populations with varying rates of accuracy in self-report of smoking behavior.

Polygenic Scores for Major Depressive Disorder and Risk of Alcohol Dependence.

Importance: Major depressive disorder (MDD) and alcohol dependence (AD) are heritable disorders with significant public health burdens, and they are frequently comorbid. Common genetic factors that influence the co-occurrence of MDD and AD have been sought in family, twin, and adoption studies, and results to date have been promising but inconclusive. Objective: To examine whether AD and MDD overlap genetically, using a polygenic score approach. Design, Settings, and Participants: Association analyses were conducted between MDD polygenic risk score (PRS) and AD case-control status in European ancestry samples from 4 independent genome-wide association study (GWAS) data sets: the Collaborative Study on the Genetics of Alcoholism (COGA); the Study of Addiction, Genetics, and Environment (SAGE); the Yale-Penn genetic study of substance dependence; and the National Health and Resilience in Veterans Study (NHRVS). Results from a meta-analysis of MDD (9240 patients with MDD and 9519 controls) from the Psychiatric Genomics Consortium were applied to calculate PRS at thresholds from P < .05 to P ≤ .99 in each AD GWAS data set. Main Outcomes and Measures: Association between MDD PRS and AD. Results: Participants analyzed included 788 cases (548 [69.5%] men; mean [SD] age, 38.2 [10.8] years) and 522 controls (151 [28.9.%] men; age [SD], 43.9 [11.6] years) from COGA; 631 cases (333 [52.8%] men; age [SD], 35.0 [7.7] years) and 756 controls (260 [34.4%] male; age [SD] 36.1 [7.7] years) from SAGE; 2135 cases (1375 [64.4%] men; age [SD], 39.4 [11.5] years) and 350 controls (126 [36.0%] men; age [SD], 43.5 [13.9] years) from Yale-Penn; and 317 cases (295 [93.1%] men; age [SD], 59.1 [13.1] years) and 1719 controls (1545 [89.9%] men; age [SD], 64.5 [13.3] years) from NHRVS. Higher MDD PRS was associated with a significantly increased risk of AD in all samples (COGA: best P = 1.7 × 10-6, R2 = 0.026; SAGE: best P = .001, R2 = 0.01; Yale-Penn: best P = .035, R2 = 0.0018; and NHRVS: best P = .004, R2 = 0.0074), with stronger evidence for association after meta-analysis of the 4 samples (best P = 3.3 × 10-9). In analyses adjusted for MDD status in 3 AD GWAS data sets, similar patterns of association were observed (COGA: best P = 7.6 × 10-6, R2 = 0.023; Yale-Penn: best P = .08, R2 = 0.0013; and NHRVS: best P = .006, R2 = 0.0072). After recalculating MDD PRS using MDD GWAS data sets without comorbid MDD-AD cases, significant evidence was observed for an association between the MDD PRS and AD in the meta-analysis of 3 GWAS AD samples without MDD cases (best P = .007). Conclusions and Relevance: These results suggest that shared genetic susceptibility contributes modestly to MDD and AD comorbidity. Individuals with elevated polygenic risk for MDD may also be at risk for AD.

Current and Future Prospects for Epigenetic Biomarkers of Substance Use Disorders.

Substance abuse has an enormous impact on economic and quality of life measures throughout the world. In more developed countries, overutilization of the most common forms of substances of abuse, alcohol and tobacco, is addressed primarily through prevention of substance use initiation and secondarily through the treatment of those with substance abuse or dependence. In general, these therapeutic approaches to substance abuse are deemed effective. However, there is a broad consensus that the development of additional tools to aid diagnosis, prioritize treatment selection and monitor treatment response could have substantial impact on the effectiveness of both substance use prevention and treatment. The recent demonstrations by a number of groups that substance use exposure is associated with robust changes in DNA methylation signatures of peripheral blood cells suggests the possibility that methylation assessments of blood or saliva could find broad clinical applications. In this article, we review recent progress in epigenetic approaches to substance use assessment with a particular emphasis on smoking (and alcohol) related applications. In addition, we highlight areas, such as the epigenetics of psychostimulant, opioid and cannabis abuse, which are markedly understudied and could benefit from intensified collaborative efforts to define epigenetic biomarkers of abuse and dependence.

[Analysis of medical short-term admissions of elderly patients with focus on alternatives to hospitalization]. / Analyse af medicinske korttidsindlæggelser af ældre patienter med fokus på alternative løsninger

By a retrospective medical record review it is studied if 334 admissions of acute short-term hospitalization (< 24 hours) of elderly medical patients could have been substituted by alternative solutions. 27% of these admissions were evaluated as substitutable. This study cannot confirm that the number of medical short-term admissions of elderly patients could be reduced by one or more specific interventions, nor that the medical short-term hospitalization generally is inappropriate.

Binary classification of ¹8F-flutemetamol PET using machine learning: comparison with visual reads and structural MRI.

(18)F-flutemetamol is a positron emission tomography (PET) tracer for in vivo amyloid imaging. The ability to classify amyloid scans in a binary manner as 'normal' versus 'Alzheimer-like', is of high clinical relevance. We evaluated whether a supervised machine learning technique, support vector machines (SVM), can replicate the assignments made by visual readers blind to the clinical diagnosis, which image components have highest diagnostic value according to SVM and how (18)F-flutemetamol-based classification using SVM relates to structural MRI-based classification using SVM within the same subjects. By means of SVM with a linear kernel, we analyzed (18)F-flutemetamol scans and volumetric MRI scans from 72 cases from the (18)F-flutemetamol phase 2 study (27 clinically probable Alzheimer's disease (AD), 20 amnestic mild cognitive impairment (MCI), 25 controls). In a leave-one-out approach, we trained the (18)F-flutemetamol based classifier by means of the visual reads and tested whether the classifier was able to reproduce the assignment based on visual reads and which voxels had the highest feature weights. The (18)F-flutemetamol based classifier was able to replicate the assignments obtained by visual reads with 100% accuracy. The voxels with highest feature weights were in the striatum, precuneus, cingulate and middle frontal gyrus. Second, to determine concordance between the gray matter volume- and the (18)F-flutemetamol-based classification, we trained the classifier with the clinical diagnosis as gold standard. Overall sensitivity of the (18)F-flutemetamol- and the gray matter volume-based classifiers were identical (85.2%), albeit with discordant classification in three cases. Specificity of the (18)F-flutemetamol based classifier was 92% compared to 68% for MRI. In the MCI group, the (18)F-flutemetamol based classifier distinguished more reliably between converters and non-converters than the gray matter-based classifier. The visual read-based binary classification of (18)F-flutemetamol scans can be replicated using SVM. In this sample the specificity of (18)F-flutemetamol based SVM for distinguishing AD from controls is higher than that of gray matter volume-based SVM.