Reactive high-spin iron(IV)-oxo sites through dioxygen activation in a metal-organic framework.

In nature, nonheme iron enzymes use dioxygen to generate high-spin iron(IV)=O species for a variety of oxygenation reactions. Although synthetic chemists have long sought to mimic this reactivity, the enzyme-like activation of O2 to form high-spin iron(IV) = O species remains an unrealized goal. Here, we report a metal-organic framework featuring iron(II) sites with a local structure similar to that in α-ketoglutarate-dependent dioxygenases. The framework reacts with O2 at low temperatures to form high-spin iron(IV) = O species that are characterized using in situ diffuse reflectance infrared Fourier transform, in situ and variable-field Mössbauer, Fe Kß x-ray emission, and nuclear resonance vibrational spectroscopies. In the presence of O2, the framework is competent for catalytic oxygenation of cyclohexane and the stoichiometric conversion of ethane to ethanol.

Cerebellar morphological differences and associations with extrinsic factors in bipolar disorder type I.

BACKGROUND: The neural underpinnings of bipolar disorder (BD) remain poorly understood. The cerebellum is ideally positioned to modulate emotional regulation circuitry yet has been understudied in BD. Literature suggests differences in cerebellar activity and metabolism in BD, however findings on structural differences remain contradictory. Potential reasons include combining BD subtypes, small sample sizes, and potential moderators such as genetics, adverse childhood experiences (ACEs), and pharmacotherapy. METHODS: We collected 3 T MRI scans from participants with (N = 131) and without (N = 81) BD type I, as well as blood and questionnaires. We assessed differences in cerebellar volumes and explored potentially influential factors. RESULTS: The cerebellar cortex was smaller bilaterally in participants with BD. Polygenic propensity score did not predict any cerebellar volumes, suggesting that non-genetic factors may have greater influence on the cerebellar volume difference we observed in BD. Proportionate cerebellar white matter volumes appeared larger with more ACEs, but this may result from reduced ICV. Time from onset and symptom burden were not associated with cerebellar volumes. Finally, taking sedatives was associated with larger cerebellar white matter and non-significantly larger cortical volume. LIMITATIONS: This study was cross-sectional, limiting interpretation of possible mechanisms. Most of our participants were White, which could limit the generalizability. Additionally, we did not account for potential polypharmacy interactions. CONCLUSIONS: These findings suggest that external factors, such as sedatives and childhood experiences, may influence cerebellum structure in BD and may mask underlying differences. Accounting for such variables may be critical for consistent findings in future studies.

A cooperative adsorbent for the switch-like capture of carbon dioxide from crude natural gas.

Natural gas constitutes a growing share of global primary energy due to its abundant supply and lower CO2 emission intensity compared to coal. For many natural gas reserves, CO2 contamination must be removed at the wellhead to meet pipeline specifications. Here, we demonstrate the potential of the diamine-appended metal-organic framework ee-2-Mg2(dobpdc) (ee-2 = N,N-diethylethylenediamine; dobpdc4- = 4,4'-dioxidobiphenyl-3,3'-dicarboxylate) as a next-generation CO2 capture material for high-pressure natural gas purification. Owing to a cooperative adsorption mechanism involving formation of ammonium carbamate chains, ee-2-Mg2(dobpdc) can be readily regenerated with a minimal change in temperature or pressure and maintains its CO2 capacity in the presence of water. Moreover, breakthrough experiments reveal that water enhances the CO2 capture performance of ee-2-Mg2(dobpdc) by eliminating "slip" of CO2 before full breakthrough. Spectroscopic characterization and multicomponent adsorption isobars suggest that the enhanced performance under humid conditions arises from preferential stabilization of the CO2-inserted phase in the presence of water. The favorable performance of ee-2-Mg2(dobpdc) is further demonstrated through comparison with a benchmark material for this separation, zeolite 13X, as well as extended pressure cycling. Overall, these results support continued development of ee-2-Mg2(dobpdc) as a promising adsorbent for natural gas purification.

Using Cg05575921 methylation to predict lung cancer risk: a potentially bias-free precision epigenetics approach.

The decision to engage in lung cancer screening (LCS) necessitates weighing benefits versus harms. Previously, clinicians in the United States have used the PLCOM2012 algorithm to guide LCS decision-making. However, that formula contains race and gender-based variables. Previously, using data from a European study, Bojesen and colleagues have suggested that cg05575921 methylation could guide decision-making. To test this hypothesis in a more diverse American population, we examined DNA and clinical data from 3081 subjects from the National Lung Screening Trial (NLST) study. Using survival analysis, we found a simple linear predictor consisting of age, pack-year consumption and cg05575921, to have the best predictive power among several alternatives (AUC = 0.66). Results showed that the highest quartile of risk was more than 2-fold more likely to develop lung cancer than those in the lowest quartile. Race, ethnicity, and gender had no effect on prediction with both cg05575921 and pack years contributing equally (both p < 0.003) to risk prediction. Current smokers had considerably lower methylation than former smokers (46% vs 67%; p < 0.001) with the average methylation of those who quit approaching 80% after 25 years of cessation. Finally, current male smokers had lower mean cg05575921 percentage than female smokers (46% vs 49%; p < 0.001). We conclude that cg05575921 (along with age and pack years) can be used to guide LCS decision-making, and additional studies might focus on how best to use methylation to inform decision-making.

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.

Predictors of Smoking in Older Adults and an Epigenetic Validation of Self-Report.

There are several established predictors of smoking, but it is unknown if these predictors operate similarly for young and old smokers. We examined clinical data from the National Lung Screening Trial (NLST) to determine the predictive ability of gender, body mass index (BMI), marital status, and race on smoking behavior, with emphasis on gender interactions. In addition, we validated the self-report of smoking behaviors for a subgroup that had available epigenetic data in the form of cg05575921 methylation. Participants were N=9572 current or former smokers from the NLST biofluids database, age 55-74, minimum of 30 pack years, and mostly White. A subgroup of N=3084 who had DNA were used for the self-report validation analysis. The predictor analysis was based on the larger group and used penalized logistic regression to predict the self-report of being a former or current smoker at baseline. Cg05575921 methylation showed a moderate ability to discriminate among former and current smokers, AUC = 0.85 (95% confidence interval = [0.83, 0.86]). The final selected variables for the prediction model were BMI, gender, BMI by gender, age, divorced (vs. married), education, and race. The gender by BMI interaction was such that males had a higher probability of current smoking for lower BMI, but this switched to females having higher current smoking for overweight to obese. There is evidence that the self-reported smoking behavior in NLST is moderately accurate. The results of the primary analysis are consistent with the general smoking literature, and our results provide additional specificity regarding the gender by BMI interaction. Body weight issues might play a role in smoking cessation for older established smokers in a similar manner as younger smokers. It could be that women have less success with cessation when their BMI increases.

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.

Isolation of a triplet benzene dianion.

Baird's rule predicts that molecules with 4n π electrons should be aromatic in the triplet state, but the realization of simple ring systems with such an electronic ground state has been stymied by these molecules' tendency to distort into structures bearing a large singlet-triplet gap. Here, we show that the elusive benzene diradical dianion can be stabilized through creation of a binucleating ligand that enforces a tightly constrained inverse sandwich structure and direct magnetic exchange coupling. Specifically, we report the compounds [K(18-crown-6)(THF)2]2[M2(BzN6-Mes)] (M = Y, Gd; BzN6-Mes = 1,3,5-tris[2',6'-(N-mesityl)dimethanamino-4'-tert-butylphenyl]benzene), which feature a trigonal ligand that binds one trivalent metal ion on each face of a central benzene dianion. Antiferromagnetic exchange in the Gd3+ compound preferentially stabilizes the triplet state such that it becomes the molecular ground state. Single-crystal X-ray diffraction data and nucleus-independent chemical shift calculations support aromaticity, in agreement with Baird's rule.

Enhancing Li-ion capacity and rate capability in cation-defective vanadium ferrite aerogels via aluminum substitution.

Cation-defective iron oxides have proven to be effective Li-ion charge-storage hosts in nonaqueous electrolytes, particularly when expressed in disordered, nanoscale forms such as aerogels. Replacing a fraction of Fe sites in ferrites with high-valent cations such as V5+ introduces cation-vacancy defects that increase Li-ion capacity. Herein, we show that compositional substitution with electroinactive Al3+ further increases Li-ion capacity by 30% when incorporated within a disordered VFe2Ox aerogel, as verified by electrochemical tests in a two-terminal Li half-cell. We use electroanalytical techniques to show that both Al-VFe2Ox and VFe2Ox aerogels exhibit many of the hallmarks of pseudocapacitive materials, including fast charge-discharge and surface-controlled charge-storage kinetics. These disordered, substituted ferrites also provide the high specific capacity expected from battery-type electrode materials, up to 130 mA h g-1 for Al-VFe2Ox. Our findings are discussed in the context of related Li-insertion hosts that blur the distinctions between battery-like and capacitor-like behavior.

A simple, rapid, interpretable, actionable and implementable digital PCR based mortality index.

Mortality assessments are conducted for both civil and commercial purposes. Recent advances in epigenetics have resulted in DNA methylation tools to assess risk and aid in this task. However, widely available array-based algorithms are not readily translatable into clinical tools and do not provide a good foundation for clinical recommendations. Further, recent work shows evidence of heritability and possible racial bias in these indices. Using a publicly available array data set, the Framingham Heart Study (FHS), we develop and test a five-locus mortality-risk algorithm using only previously validated methylation biomarkers that have been shown to be free of racial bias, and that provide specific assessments of smoking, alcohol consumption, diabetes and heart disease. We show that a model using age, sex and methylation measurements at these five loci outperforms the 513 probe Levine index and approximates the predictive power of the 1030 probe GrimAge index. We then show each of the five loci in our algorithm can be assessed using a more powerful, reference-free digital PCR approach, further demonstrating that it is readily clinically translatable. Finally, we show the loci do not reflect ethnically specific variation. We conclude that this algorithm is a simple, yet powerful tool for assessing mortality risk. We further suggest that the output from this or similarly derived algorithms using either array or digital PCR can be used to provide powerful feedback to patients, guide recommendations for additional medical assessments, and help monitor the effect of public health prevention interventions.

The Reversion of cg05575921 Methylation in Smoking Cessation: A Potential Tool for Incentivizing Healthy Aging.

Smoking is the largest preventable cause of mortality and the largest environmental driver of epigenetic aging. Contingency management-based strategies can be used to treat smoking but require objective methods of verifying quitting status. Prior studies have suggested that cg05575921 methylation reverts as a function of smoking cessation, but that it can be used to verify the success of smoking cessation has not been unequivocally demonstrated. To test whether methylation can be used to verify cessation, we determined monthly cg05575921 levels in a group of 67 self-reported smokers undergoing biochemically monitored contingency management-based smoking cessation therapy, as part of a lung imaging protocol. A total of 20 subjects in this protocol completed three months of cotinine verified smoking cessation. In these 20 quitters, the reversion of cg05575921 methylation was dependent on their initial smoking intensity, with methylation levels in the heaviest smokers reverting to an average of 0.12% per day over the 3-month treatment period. In addition, we found suggestive evidence that some individuals may have embellished their smoking history to gain entry to the study. Given the prominent effect of smoking on longevity, we conclude that DNA methylation may be a useful tool for guiding and incentivizing contingency management-based approaches for smoking cessation.

Metal-Ligand Cooperativity via Exchange Coupling Promotes Iron- Catalyzed Electrochemical CO2 Reduction at Low Overpotentials.

Biological and heterogeneous catalysts for the electrochemical CO2 reduction reaction (CO2RR) often exhibit a high degree of electronic delocalization that serves to minimize overpotential and maximize selectivity over the hydrogen evolution reaction (HER). Here, we report a molecular iron(II) system that captures this design concept in a homogeneous setting through the use of a redox non-innocent terpyridine-based pentapyridine ligand (tpyPY2Me). As a result of strong metal-ligand exchange coupling between the Fe(II) center and ligand, [Fe(tpyPY2Me)]2+ exhibits redox behavior at potentials 640 mV more positive than the isostructural [Zn(tpyPY2Me)]2+ analog containing the redox-inactive Zn(II) ion. This shift in redox potential is attributed to the requirement for both an open-shell metal ion and a redox non-innocent ligand. The metal-ligand cooperativity in [Fe(tpyPY2Me)]2+ drives the electrochemical reduction of CO2 to CO at low overpotentials with high selectivity for CO2RR (>90%) and turnover frequencies of 100 000 s-1 with no degradation over 20 h. The decrease in the thermodynamic barrier engendered by this coupling also enables homogeneous CO2 reduction catalysis in water without compromising selectivity or rates. Synthesis of the two-electron reduction product, [Fe(tpyPY2Me)]0, and characterization by X-ray crystallography, Mössbauer spectroscopy, X-ray absorption spectroscopy (XAS), variable temperature NMR, and density functional theory (DFT) calculations, support assignment of an open-shell singlet electronic structure that maintains a formal Fe(II) oxidation state with a doubly reduced ligand system. This work provides a starting point for the design of systems that exploit metal-ligand cooperativity for electrocatalysis where the electrochemical potential of redox non-innocent ligands can be tuned through secondary metal-dependent interactions.

Selective, High-Temperature O2 Adsorption in Chemically Reduced, Redox-Active Iron-Pyrazolate Metal-Organic Frameworks.

Developing O2-selective adsorbents that can produce high-purity oxygen from air remains a significant challenge. Here, we show that chemically reduced metal-organic framework materials of the type AxFe2(bdp)3 (A = Na+, K+; bdp2- = 1,4-benzenedipyrazolate; 0 < x ≤ 2), which feature coordinatively saturated iron centers, are capable of strong and selective adsorption of O2 over N2 at ambient (25 °C) or even elevated (200 °C) temperature. A combination of gas adsorption analysis, single-crystal X-ray diffraction, magnetic susceptibility measurements, and a range of spectroscopic methods, including 23Na solid-state NMR, Mössbauer, and X-ray photoelectron spectroscopies, are employed as probes of O2 uptake. Significantly, the results support a selective adsorption mechanism involving outer-sphere electron transfer from the framework to form superoxide species, which are subsequently stabilized by intercalated alkali metal cations that reside in the one-dimensional triangular pores of the structure. We further demonstrate O2 uptake behavior similar to that of AxFe2(bdp)3 in an expanded-pore framework analogue and thereby gain additional insight into the O2 adsorption mechanism. The chemical reduction of a robust metal-organic framework to render it capable of binding O2 through such an outer-sphere electron transfer mechanism represents a promising and underexplored strategy for the design of next-generation O2 adsorbents.

Computational Study of an Iron(II) Polypyridine Electrocatalyst for CO2 Reduction: Key Roles for Intramolecular Interactions in CO2 Binding and Proton Transfer.

A solar-driven conversion of CO2 into fuels by artificial photosynthesis would not only mitigate the greenhouse effect but also provide an alternative to obtain fuels in a renewable fashion. To this end, the new iron polypyridine catalyst [Fe(bpyNHEtPY2Me)L2]2+ (L = H2O, CH3CN) was recently developed for the electrochemical reduction of CO2 to CO. In this study, we performed density functional theory (DFT) electronic structure calculations to shed light on a possible pathway for CO2 reduction and the origin of the selectivity between CO2 reduction versus the hydrogen evolution reaction. The metal center remains Lewis acidic throughout the reduction process due to ligand loss and mainly ligand-based reduction stabilized by antiferromagnetic coupling to a high-spin Fe(II) center. This results in a high barrier for hydride formation but a facile addition and activation of CO2 via an η2 coordination and stabilizing hydrogen bonding by the amine group. The second unoccupied equatorial coordination site opens up the possibility for an intramolecular protonation with a coordinated water ligand. This facilitates protonation because not only CO2 but also the proton source H2O is activated and properly aligned for a proton transfer due to the Fe-OH2 bond; consequently, both protonation steps are facile. The moderate ligand field allows a rapid ligand exchange for a second intramolecular protonation step and facilitates an exergonic CO release. The lower selectivity of the related [Fe(bpyOHPY2Me)L2]2+ complex can be related to its more acidic second coordination sphere, which enables an intramolecular proton transfer that is kinetically competitive with CO2 addition.

Tuning Second Coordination Sphere Interactions in Polypyridyl-Iron Complexes to Achieve Selective Electrocatalytic Reduction of Carbon Dioxide to Carbon Monoxide.

The development of noble-metal-free catalysts capable of electrochemically converting carbon dioxide (CO2) selectively into value-added compounds remains one of the central challenges in catalysis research. Here, we present a systematic study of Fe(II) complexes of the functionalized ligands bpyRPY2Me (bpyPY2Me = 6-(1,1-bis(pyridin-2-yl)ethyl)-2,2'-bipyridine) in the pursuit of water-stable molecular Fe complexes that are selective for the catalytic formation of CO from CO2. Taking advantage of the inherently high degree of tunability of this ligand manifold, we followed a bioinspired approach by installing protic functional groups of varying acidities (-H, -OH, -OMe, -NHEt, and -NEt2) into the ligand framework to systematically modify the second coordination sphere of the Fe center. This family of [(bpyRPY2Me)FeII] complexes was characterized using single-crystal X-ray analysis, 1H NMR spectroscopy, and mass spectrometry. Comparative catalytic evaluation of this set of compounds via voltammetry and electrolysis experiments identified [(bpyNHEtPY2Me)Fe]2+ in particular as an efficient, iron-based, non-heme CO2 electroreduction catalyst that displays significant selectivity for the conversion of CO2 to CO in acetonitrile solution with 11 M H2O. We propose that the NH group acts as a local proton source for cleaving the C-O bond in CO2 to form CO. Interestingly, the complex with the most acidic functional group in the second coordination sphere, [(bpyOHPY2Me)Fe]2+, favors formation of H2 over CO. Our results correlate the selectivity of water versus carbon dioxide reduction to the acidity of the second coordination sphere functional group and emphasize the continued untapped potential that synthetic molecular chemistry offers in the pursuit of next-generation CO2 reduction electrocatalysts.

Biomimetic O2 adsorption in an iron metal-organic framework for air separation.

Bio-inspired motifs for gas binding and small molecule activation can be used to design more selective adsorbents for gas separation applications. Here, we report an iron metal-organic framework, Fe-BTTri (Fe3[(Fe4Cl)3(BTTri)8]2·18CH3OH, H3BTTri = 1,3,5-tris(1H-1,2,3-triazol-5-yl)benzene), that binds O2 in a manner similar to hemoglobin and therefore results in highly selective O2 binding. As confirmed by gas adsorption studies and Mössbauer and infrared spectroscopy data, the exposed iron sites in the framework reversibly adsorb substantial amounts of O2 at low temperatures by converting between high-spin, square-pyramidal Fe(ii) centers in the activated material to low-spin, octahedral Fe(iii)-superoxide sites upon gas binding. This change in both oxidation state and spin state observed in Fe-BTTri leads to selective and readily reversible O2 binding, with the highest reported O2/N2 selectivity for any iron-based framework.

Generalizing MRI Subcortical Segmentation to Neurodegeneration.

Many neurodegenerative diseases like Huntington's disease (HD) affect the subcortical structures of the brain, especially the caudate and the putamen. Automated segmentation of subcortical structures from MRI scans is thus important in HD studies. LiviaNET [2] is the state-of-the-art deep learning approach for subcortical segmentation. As all learning-based models, this approach requires appropriate training data. While annotated healthy control images are relatively easy to obtain, generating such annotations for each new disease population can be prohibitively expensive. In this work, we explore LiviaNET variants using well-known strategies for improving performance, to make it more generalizable to patients with substantial neurodegeneration. Specifically, we explored Res-blocks in our convolutional neural network, and we also explored manipulating the input to the network as well as random elastic deformations for data augmentation. We tested our method on images from the PREDICT-HD dataset, which includes control and HD subjects. We trained on control subjects and tested on both controls and HD patients. Compared to the original LiviaNET, we improved the accuracy of most structures, both for controls and for HD patients. The caudate has the most pronounced improvement in HD subjects with the proposed modifications to LiviaNET, which is noteworthy since caudate is known to be severely atrophied in HD. This suggests our extensions may improve the generalization ability of LiviaNET to cohorts where significant neurodegeneration is present, without needing to be retrained.

AHRR methylation predicts smoking status and smoking intensity in both saliva and blood DNA.

Many existing DNA repositories do not have robust characterizations of smoking, while for many currently ongoing studies, the advent of vaping has rendered traditional cotinine-based methods of determining smoking status unreliable. Previously, we have shown that methylation status at cg05575921 in whole blood DNA can reliably predict cigarette consumption. However, whether methylation status in saliva can be used similarly has yet to be established. Herein, we use DNA from 418 biochemically confirmed smokers or nonsmokers to compare and contrast the utility of cg05575921 in classifying and quantifying cigarette smoking. Using whole blood DNA, a model incorporating age, gender, and methylation status had a receiver operating characteristic (ROC) area under the curve (AUC) for predicting smoking status of 0.995 with a nonlinear demethylation response to smoking. Using saliva DNA, the ROC AUC for predicting smoking was 0.971 with the plot of the relationship of DNA methylation to daily cigarette consumption being very similar to that seen for whole blood DNA. The addition of information from another methylation marker designed to correct for cellular heterogeneity improved the AUC for saliva DNA to 0.981. Finally, in 31 subjects who reported quitting smoking 10 or more years previously, cg05575921 methylation was nonsignificantly different from controls. We conclude that DNA methylation status at cg05575921 in DNA from whole blood or saliva predicts smoking status and daily cigarette consumption. We suggest these epigenetic assessments for objectively ascertaining smoking status will find utility in research, clinical, and civil applications.

A Four Marker Digital PCR Toolkit for Detecting Heavy Alcohol Consumption and the Effectiveness of Its Treatment.

Background.-Heavy alcohol consumption (HAC) is a shared concern of the forensic, medical and insurance underwriting communities. Unfortunately, there is a relative lack of clinically employable tools for detecting HAC and monitoring treatment response. Building on the results of 3 genome wide methylation studies, we have previously shown in a small group of samples that methylation sensitive digital PCR assays (MSdPCR) have the potential to accurately classify individuals with respect to HAC in a small set of individuals. Objective.-We now expand on those earlier findings using data and biomaterials from 143 participants with current HAC and 200 abstinent controls. Results.-We show that a set of 4 digital PCR assays that have a receiver operating characteristic (ROC) area under the curve (AUC) of 0.96 for detecting those with HAC. After a mean of 21 days of inpatient enforced abstinence, methylation status at one of these markers, cg04987734, began to revert to baseline values. Re-examination of methylation data from our smaller 2014 study with respect to this locus demonstrated a similarly significant reversion pattern at cg04987734 in association with treatment enforced abstinence. Conclusions.-We conclude that clinically implementable dPCR tools can sensitively detect the presence of HAC and that they show promise for monitoring alcohol treatment results. These dPCR tools could be useful to clinicians and researchers in monitoring those enrolled in substance use disorder treatment, employee wellness programs and insurance underwriting.

AHRR Methylation is a Significant Predictor of Mortality Risk in Framingham Heart Study.

Background.-The ability to predict mortality is useful to clinicians, policy makers and insurers. At the current time, prediction of future mortality is still an inexact process with some proposing that epigenetic assessments could play a role in improving prognostics. In past work, we and others have shown that DNA methylation status at cg05575921, a well-studied measure of smoking intensity, is also a predictor of mortality. However, the exact extent of that predictive capacity and its independence of other commonly measured mortality risk factors are unknown. Objective.-To determine the capacity of methylation to predict mortality. Method.-We analyzed the relationship of methylation at cg05575921 and cg04987734, a recently described quantitative marker of heavy alcohol consumption, to mortality in the Offspring Cohort of the Framingham Heart Study using proportional hazards survival analysis. Results.-In this group of participants (n = 2278) whose average age was 66 ± 9 years, we found that the inclusion of both cg05575921 and cg04987734 methylation to a base model consisting of age and sex only, or to a model containing 11 commonly used mortality risk factors, improved risk prediction. What is more, prediction accuracy for the base model plus methylation data was increased compared to the base model plus known predictors of mortality (CHD, COPD, or stroke). Conclusion.-Cg05575921, and to a smaller extent cg04987734, are strong predictors of mortality risk in older Americans and that incorporation of DNA methylation assessments to these and other loci may be useful to population scientists, actuaries and policymakers to better understand the relationship of environmental risk factors, such as smoking and drinking, to mortality.