qSVA framework for RNA quality correction in differential expression analysis.

RNA sequencing (RNA-seq) is a powerful approach for measuring gene expression levels in cells and tissues, but it relies on high-quality RNA. We demonstrate here that statistical adjustment using existing quality measures largely fails to remove the effects of RNA degradation when RNA quality associates with the outcome of interest. Using RNA-seq data from molecular degradation experiments of human primary tissues, we introduce a method-quality surrogate variable analysis (qSVA)-as a framework for estimating and removing the confounding effect of RNA quality in differential expression analysis. We show that this approach results in greatly improved replication rates (>3×) across two large independent postmortem human brain studies of schizophrenia and also removes potential RNA quality biases in earlier published work that compared expression levels of different brain regions and other diagnostic groups. Our approach can therefore improve the interpretation of differential expression analysis of transcriptomic data from human tissue.

State variations in Medicaid enrollment and utilization of substance use services: Results from a National Longitudinal Study.

Medicaid enrollment varies considerably among states. This study examined the association of Medicaid enrollment with the use of substance health services in the longitudinal National Epidemiologic Survey on Alcohol and Related Conditions of 2001-2005. Instrumental variable methods were used to assess endogeneity of individual-level Medicaid enrollment using state-level data as instruments. Compared to the uninsured, Medicaid covered adults were more likely to use substance use disorder treatment services over the next three years. States that have opted to expand Medicaid enrollment under the Affordable Care Act will likely experience further increases in the use of these service over the coming years.

Transitions through stages of alcohol involvement: The potential role of mood disorders.

INTRODUCTION: Although prior clinical and population-based studies have demonstrated comorbidity between mood and alcohol use disorders (AUD), there is a paucity of research assessing whether mood disorders predict transition across stages of alcohol involvement. METHOD: Hypothesizing that mood disorders predict transition across sex-specific alcohol involvement stages, we used prospective data from the National Epidemiologic Survey on Alcohol and Related Conditions (NESARC), a nationally representative survey of US adults, which included male (n = 14,564) and female (n = 20,089) participants surveyed in 2001-2 and re-interviewed in 2004-5. Latent class (LCA) and latent transition analyses (LTA) were used to assess patterns of alcohol involvement in the US and the association of lifetime mood disorders at baseline with transition across stages of alcohol involvement during follow-up. RESULTS: A three-class model of AUD criteria was identified (No problems, Moderate problems and Severe problems) for both sexes. Positive cross-sectional associations between mood disorder and problem classes of alcohol involvement were found among both sexes, as were positive longitudinal associations. Propensity score adjustment mitigated the associations of baseline mood disorder with progressive transition for both sexes. However, among females, baseline mood disorder was consistently associated with reduction in remission from Severe to Moderate alcohol problems (aOR = 0.30, CI = 0.09-0.99, p = .048) over time. DISCUSSION: Our study provides evidence that mood disorders impact transition through stages of alcohol involvement and are most strongly associated with hindering remission among females. Findings advance our understanding of these comorbid relationships and have clinical implications for ongoing assessment of drinking patterns among individuals with mood disorders.

Trends in insurance coverage and treatment among persons with opioid use disorders following the Affordable Care Act.

PURPOSE: This short communication examines the impact of the Patient Protection and Affordable Care Act (PPACA) on insurance coverage and substance use treatment access among persons with opioid use disorders. METHODS: Data came from the 2010-2015 National Surveys on Drug Use and Health. Among persons with heroin and opioid pain-reliever use disorders, measures of insurance coverage and treatment access were compared before and after the implementation of major PPACA provisions that expanded access to insurance in 2014. RESULTS: The prevalence of uninsured persons among those with heroin use disorders declined dramatically following PPACA implementation (OR 0.59, 95% CI 0.39-0.89), largely due to an increase in the prevalence of Medicaid coverage (OR 1.96, 95% CI 1.21-3.18). There was no evidence of an increase in the prevalence of treatment, but among persons who received treatment, there was an increase in the proportion whose treatment was paid for by insurance (OR 3.75, 95% CI 2.13-3.18). By contrast, there was no evidence the uninsured rate declined among persons with pain-reliever use disorders. CONCLUSIONS: The PPACA Medicaid expansion increased insurance coverage among persons with heroin use disorders, and likely plays an essential role in protecting the health and financial security of this high-risk group. More research is needed on the relationship between insurance acquisition and utilization of substance use treatment.

The association of psychiatric comorbidity with treatment completion among clients admitted to substance use treatment programs in a U.S. national sample.

BACKGROUND: Psychiatric disorders are highly comorbid with substance use disorders and play an important role in their course and recovery. However, the impact of comorbidity on treatment outcomes has not been examined in a U.S. national sample. This study explores the impact of psychiatric comorbidity on treatment completion among individuals admitted to publicly funded substance use treatment facilities across the United States. METHODS: Using data on first-time treatment episodes in the U.S. from the Treatment Episode Dataset-Discharges (TEDS-D) for the years 2009-2011, logistic regression was used to assess the association between psychiatric comorbidity and treatment non-completion, and Cox proportional hazards regression was used to assess the association between comorbidity and rate of attrition. Analyses were performed for all substances together and then stratified by primary substance of abuse (alcohol, cannabis, stimulants, or opioids). RESULTS: Of 856,385 client treatment episodes included in our analysis, 28% had a psychiatric comorbidity and 38% did not complete treatment. After adjusting for socio-demographic and treatment characteristics, clients with psychiatric comorbidity had higher odds of not completing treatment relative to those without comorbidity [OR=1.28 (1.27-1.29)], and had an earlier time to attrition [HR=1.14 (1.13-1.15)]. Psychiatric comorbidity was most strongly associated with treatment non-completion and rate of attrition in those admitted primarily for alcohol [OR=1.37 (1.34-1.39); HR=1.19 (1.17-1.21), respectively]. CONCLUSIONS: Individuals with psychiatric comorbidities receiving treatment for substance use disorders face unique challenges that impact their ability to complete treatment. The findings call for further efforts to integrate treatment for psychiatric comorbidities in substance use treatment settings.