Concurrent cocaine and alcohol use in individuals presenting to an addiction treatment program

Occurrence and severity of cocaine-induced hallucinations: Two distinct phenotypes with shared clinical factors but specific genetic risk factors

Cocaine-induced transient hallucinations (CIH) are a frequent complication following cocaine intake that is associated with addiction severity.

METHODS

Two hundred and forty-two non-psychotic and Caucasian lifetime cocaine users were included in a French multicentric study. Clinical variables and dopamine pathway genotype data were extracted and tested with CIH scores using a zero-inflated binomial model, which allows for the exploration of factors associated with occurrence and severity separately.

RESULTS

Cocaine dependence (p_occurrence= 6.18 × 10^-5, p_severity= 9.25 × 10^-8), number of cocaine dependence DSM IV-Tr criteria (p_occurrence= 1.22 × 10^-7, p_severity= 5.09 × 10^-6), and frequency of intake during the worst period of misuse (p_occurrence= 8.51 × 10^-04, p_severity= 0.04) were associated with greater occurrence and higher severity of CIH. The genetic associations did not yield significant results after correction for multiple tests. However, some nominal associations of SNPs mapped to the VMAT2, DBH, DRD1, and DRD2 genes were significant. In the multivariate model, the significant variables were the number of cocaine dependence criteria, lifetime alcohol dependence, and the nominally associated SNPs.

CONCLUSION

Our study shows that CIH occurrence and severity are two distinct phenotypes, with shared clinical risk factors; however, they likely do not share the same genetic background.

Alcohol and Cocaine Combined Substance Use on Adult Hypothalamic Neural Stem Cells and Neurogenesis

Many advancements have been made over the years looking at the individual and combined effects of drugs of abuse on the brain, with one key area of research focusing on the effects on neurogenesis. An integral part of fetal brain development and, later, maintenance in the adult brain, neurogenesis occurs in three main regions: subventricularzone of the lateral ventricles (SVZ), subgranularzone of the dentate gyrus (SGZ), and the tanycyte layer in the hypothalamus (TL). We will review current literature on combined drugs of abuse and their effect on adult neurogenesis. More specifically, this review will focus on the effect of combining cocaine and alcohol. Additionally, the tanycyte layer will be explored in more depth and probed to look at the neurogenic properties of tanycytes and their role in neurogenesis.

Exploring functional data analysis and wavelet principal component analysis on ecstasy (MDMA) wastewater data

Background

Wastewater-based epidemiology (WBE) is a novel approach in drug use epidemiology which aims to monitor the extent of use of various drugs in a community. In this study, we investigate functional principal component analysis (FPCA) as a tool for analysing WBE data and compare it to traditional principal component analysis (PCA) and to wavelet principal component analysis (WPCA) which is more flexible temporally.

Methods

We analysed temporal wastewater data from 42 European cities collected daily over one week in March 2013. The main temporal features of ecstasy (MDMA) were extracted using FPCA using both Fourier and B-spline basis functions with three different smoothing parameters, along with PCA and WPCA with different mother wavelets and shrinkage rules. The stability of FPCA was explored through bootstrapping and analysis of sensitivity to missing data.

Results

The first three principal components (PCs), functional principal components (FPCs) and wavelet principal components (WPCs) explained 87.5-99.6 % of the temporal variation between cities, depending on the choice of basis and smoothing. The extracted temporal features from PCA, FPCA and WPCA were consistent. FPCA using Fourier basis and common-optimal smoothing was the most stable and least sensitive to missing data.

Conclusion

FPCA is a flexible and analytically tractable method for analysing temporal changes in wastewater data, and is robust to missing data. WPCA did not reveal any rapid temporal changes in the data not captured by FPCA. Overall the results suggest FPCA with Fourier basis functions and common-optimal smoothing parameter as the most accurate approach when analysing WBE data.

Electronic supplementary material

The online version of this article (doi:10.1186/s12874-016-0179-2) contains supplementary material, which is available to authorized users.

Wastewater-Based Epidemiology of Stimulant Drugs: Functional Data Analysis Compared to Traditional Statistical Methods

Background

Wastewater-based epidemiology (WBE) is a new methodology for estimating the drug load in a population. Simple summary statistics and specification tests have typically been used to analyze WBE data, comparing differences between weekday and weekend loads. Such standard statistical methods may, however, overlook important nuanced information in the data. In this study, we apply functional data analysis (FDA) to WBE data and compare the results to those obtained from more traditional summary measures.

Methods

We analysed temporal WBE data from 42 European cities, using sewage samples collected daily for one week in March 2013. For each city, the main temporal features of two selected drugs were extracted using functional principal component (FPC) analysis, along with simpler measures such as the area under the curve (AUC). The individual cities’ scores on each of the temporal FPCs were then used as outcome variables in multiple linear regression analysis with various city and country characteristics as predictors. The results were compared to those of functional analysis of variance (FANOVA).

Results

The three first FPCs explained more than 99% of the temporal variation. The first component (FPC1) represented the level of the drug load, while the second and third temporal components represented the level and the timing of a weekend peak. AUC was highly correlated with FPC1, but other temporal characteristic were not captured by the simple summary measures. FANOVA was less flexible than the FPCA-based regression, and even showed concordance results. Geographical location was the main predictor for the general level of the drug load.

Conclusion

FDA of WBE data extracts more detailed information about drug load patterns during the week which are not identified by more traditional statistical methods. Results also suggest that regression based on FPC results is a valuable addition to FANOVA for estimating associations between temporal patterns and covariate information.

Substitution and complementarity in the face of alcohol-specific policy interventions

AIM

Policy responses to the growing burden of alcohol-related disease fail to consider the interrelated nature of substance misuse and the potential for complex interactions in response to alcohol-specific interventions. This paper considers possible aggregate level responses to the alcohol policy and whether alcohol policy can be expected to reduce overall harm.

METHODS

A review and discussion of the relevant literature was conducted.

RESULTS

Evidence indicates that those at greatest risk consume stronger alcoholic beverages more frequently, that they are likely to complement their consumption with a range of intoxicants and that they are more likely to substitute alcohol with other substances.

CONCLUSIONS

Policies aimed at reducing alcohol consumption can be successful. However, evidence suggests a significant minority of consumers are likely to substitute or complement consumption with a range of intoxicants suggesting that policy is unlikely to reduce all-cause mortality and morbidity. Further research into the nature of substitution and complementarity is required.