Detection of Cocaine Use with Wireless Electrocardiogram Sensors

In recent years, the ability to continuously monitor activities, health, and lifestyles of individuals using sensor technologies has reached unprecedented levels. Such ubiquitous physiological sensing has the potential to profoundly improve our understanding of human behavior, leading to more targeted treatments for a variety of disorders. The long terms goal of this work is development of novel computational tools to support the study of addiction in the context of cocaine use. The current paper takes the first step in this important direction by posing a simple, but crucial question: Can cocaine use be reliably detected using wearable on-body sensors and current machine learning algorithms? We select wireless ECG as the most promising sensing modality for cocaine use detection. The main contributions in this paper include the presentation of a novel clinical study of cocaine use in which a unique set of wireless ECG data were collected, the description of a computational pipeline for inferring morphological features from noisy wireless ECG waveforms, and the evaluation of cocaine use detection algorithms based on data-driven and knowledge-based feature representations. Our results show that cocaine use can be detected with AUC levels above 0.9 in both the within-subjects and between-subjects cases at the 32mg/70kg dosage level

An exploratory examination of marijuana use, problem-gambling severity, and health correlates among adolescents

Abstract Background and aims Gambling is common in adolescents and at-risk and problem/pathological gambling (ARPG) is associated with adverse measures of health and functioning in this population. Although ARPG commonly co-occurs with marijuana use, little is known how marijuana use influences the relationship between problem-gambling severity and health- and gambling-related measures. Methods Survey data from 2,252 Connecticut high school students were analyzed using chi-square and logistic regression analyses. Results ARPG was found more frequently in adolescents with lifetime marijuana use than in adolescents denying marijuana use. Marijuana use was associated with more severe and a higher frequency of gambling-related behaviors and different motivations for gambling. Multiple health/functioning impairments were differentially associated with problem-gambling severity amongst adolescents with and without marijuana use. Significant marijuana-use-by-problem-gambling-severity-group interactions were observed for low-average grades (OR = 0.39, 95% CI = [0.20, 0.77]), cigarette smoking (OR = 0.38, 95% CI = [0.17, 0.83]), current alcohol use (OR = 0.36, 95% CI = [0.14, 0.91]), and gambling with friends (OR = 0.47, 95% CI = [0.28, 0.77]). In all cases, weaker associations between problem-gambling severity and health/functioning correlates were observed in the marijuana-use group as compared to the marijuana-non-use group. Conclusions Some academic, substance use, and social factors related to problem-gambling severity may be partially accounted for by a relationship with marijuana use. Identifying specific factors that underlie the relationships between specific attitudes and behaviors with gambling problems and marijuana use may help improve intervention strategies

Demographic changes and marker properties affect detection of human population differentiation

<p>Abstract</p> <p>Background</p> <p>Differentiating genetically between populations is valuable for admixture and population stratification detection and in understanding population history. This is easy to achieve for major continental populations, but not for closely related populations. It has been claimed that a large marker panel is necessary to reliably distinguish populations within a continent. We investigated whether empirical genetic differentiation could be accomplished efficiently among three Asian populations (Hmong, Thai, and Chinese) using a small set of highly variable markers (15 tetranucleotide and 17 dinucleotide repeats).</p> <p>Results</p> <p>Hmong could be differentiated from Thai and Chinese based on multi-locus genotypes, but Thai and Chinese were indistinguishable from each other. We found significant evidence for a recent population bottleneck followed by expansion in the Hmong that was not present in the Thai or Chinese. Tetranucleotide repeats were less useful than dinucleotide repeat markers in distinguishing between major continental populations (Asian, European, and African) while both successfully distinguished Hmong from Thai and Chinese.</p> <p>Conclusion</p> <p>Demographic history contributes significantly to robust detection of intracontinental population structure. Populations having experienced a rapid size reduction may be reliably distinguished as a result of a genetic drift -driven redistribution of population allele frequencies. Tetranucleotide markers, which differ from dinucleotide markers in mutation mechanism and rate, are similar in information content to dinucleotide markers in this situation. These factors should be considered when identifying populations suitable for gene mapping studies and when interpreting interpopulation relationships based on microsatellite markers.</p

Sequence variation and linkage disequilibrium in the GABA transporter-1 gene (SLC6A1) in five populations: implications for pharmacogenetic research

<p>Abstract</p> <p>Background</p> <p>GABA transporter-1 (GAT-1; genetic locus <it>SLC6A1</it>) is emerging as a novel target for treatment of neuropsychiatric disorders. To understand how population differences might influence strategies for pharmacogenetic studies, we identified patterns of genetic variation and linkage disequilibrium (LD) in <it>SLC6A1 </it>in five populations representing three continental groups.</p> <p>Results</p> <p>We resequenced 12.4 kb of <it>SLC6A1</it>, including the promoters, exons and flanking intronic regions in African-American, Thai, Hmong, Finnish, and European-American subjects (total n = 40). LD in <it>SLC6A1 </it>was examined by genotyping 16 SNPs in larger samples. Sixty-three variants were identified through resequencing. Common population-specific variants were found in African-Americans, including a novel 21-bp promoter region variable number tandem repeat (VNTR), but no such variants were found in any of the other populations studied. Low levels of LD and the absence of major LD blocks were characteristic of all five populations. African-Americans had the highest genetic diversity. European-Americans and Finns did not differ in genetic diversity or LD patterns. Although the Hmong had the highest level of LD, our results suggest that a strategy based on the use of tag SNPs would not translate to a major improvement in genotyping efficiency.</p> <p>Conclusion</p> <p>Owing to the low level of LD and presence of recombination hotspots, <it>SLC6A1 </it>may be an example of a problematic gene for association and haplotype tagging-based genetic studies. The 21-bp promoter region VNTR polymorphism is a putatively functional candidate allele for studies focusing on variation in GAT-1 function in the African-American population.</p

Identification of population substructure among Jews using STR markers and dependence on reference populations included

Background: Detecting population substructure is a critical issue for association studies of health behaviors and other traits. Whether inherent in the population or an artifact of marker choice, determining aspects of a population's genetic history as potential sources of substructure can aid in design of future genetic studies. Jewish populations, among which association studies are often conducted, have a known history of migrations. As a necessary step in understanding population structure to conduct valid association studies of health behaviors among Israeli Jews, we investigated genetic signatures of this history and quantified substructure to facilitate future investigations of these phenotypes in this population. Results: Using 32 autosomal STR markers and the program STRUCTURE, we differentiated between Ashkenazi (AJ, N = 135) and non-Ashkenazi (NAJ, N = 226) Jewish populations in the form of Northern and Southern geographic genetic components (AJ north 73%, south 23%, NAJ north 33%, south 60%). The ability to detect substructure within these closely related populations using a small STR panel was contingent on including additional samples representing major continental populations in the analyses. Conclusions: Although clustering programs such as STRUCTURE are designed to assign proportions of ancestry to individuals without reference population information, when Jewish samples were analyzed in the absence of proxy parental populations, substructure within Jews was not detected. Generally, for samples with a given grandparental country of birth, STRUCTURE assignment values to Northern, Southern, African and Asian clusters agreed with mitochondrial DNA and Y-chromosomal data from previous studies as well as historical records of migration and intermarriage

Cocaine and Sleep: Early Abstinence

Compulsive cocaine use is associated with a profound dysregulation of sleep. Perhaps the result of chronic use, a significant deterioration in sleep is apparent over the first 3 weeks of abstinence, with no indication of recovery. Interestingly, the diminished sleep is not accompanied by subjective reports of poor or worsening sleep. Rather, subjective reports actually improve over abstinence, while sleep-related cognitive performance declines. A mechanistic understanding of the apparent difference in objective and subjective measures is currently lacking. Here we review the relevant literature on cocaine use and sleep, and discuss the possible relevance of this sleep disturbance in relationship to the underlying disorder and its treatment

Detecting Cocaine Use with Wearable Electrocardiogram Sensors

Ubiquitous physiological sensing has the potential to profoundly improve our understanding of human behavior, leading to more targeted treatments for a variety of disorders. The long term goal of this work is development of novel computational tools to support the study of addiction in the context of cocaine use. The current paper takes the first step in this important direction by posing a simple, but crucial question: Can cocaine use be reliably detected using wearable electrocardiogram (ECG) sensors? The main contributions in this paper include the presentation of a novel clinical study of cocaine use, the development of a computational pipeline for inferring morphological features from noisy ECG waveforms, and the evaluation of feature sets for cocaine use detection. Our results show that 32mg/70kg doses of cocaine can be detected with the area under the receiver operating characteristic curve levels above 0.9 both within and between-subjects