Faculty Bibliography

Diverse environmental and biological systems interact to influence individual differences in response to environmental stress. Understanding the nature of these complex relationships can enhance the development of methods to: (1) identify risk, (2) classify individuals as healthy or ill, (3) understand mechanisms of change, and (4) develop effective treatments. The Research Domain Criteria (RDoC) initiative provides a theoretical framework to understand health and illness as the product of multiple inter-related systems but does not provide a framework to characterize or statistically evaluate such complex relationships. Characterizing and statistically evaluating models that integrate multiple levels (e.g. synapses, genes, environmental factors) as they relate to outcomes that a free from prior diagnostic benchmarks represents a challenge requiring new computational tools that are capable to capture complex relationships and identify clinically relevant populations. In the current review, we will summarize machine learning methods that can achieve these goals.

BACKGROUND:Cancers induce gene expression alterations in stroma surrounding tumors that supports cancer progression. However, it is actually not at all known the extent of altered stromal gene expression enacted by tumors nor the extent to which altered stromal gene expression penetrates the stromal tissue. Presently, post-surgical "tumor-free" stromal tissue is determined to be cancer-free based on solely on morphological normality-a criteria that has not changed in more than 100 years despite the existence of sophisticated gene expression data to the contrary. We therefore investigated the extent to which breast tumors alter stromal gene expression in three dimensions in women undergoing mastectomy with the intent of providing a genomic determination for development of future risk of recurrence criteria, and to inform the need for adjuvant full-breast irradiation. METHODS AND FINDINGS/RESULTS:Genome-wide gene expression changes were determined in histopathologically normal breast tissue in 33 women undergoing mastectomy for stage II and III primary invasive ductal carcinoma at serial distances in three dimensions from the tumor. Gene expression was determined by genome-wide mRNA analysis and subjected to metagene mRNA characterization. Tumor-like gene expression signatures in stroma were identified that surprisingly transitioned to a plastic, normalizing homeostatic signature with distance from tumor. Stroma closest to tumor displayed a pronounced tumor-like signature enriched in cancer-promoting pathways involved in disruption of basement membrane, cell migration and invasion, WNT signaling and angiogenesis. By 2 cm from tumor in all dimensions, stromal tissues were in transition, displaying homeostatic and tumor suppressing gene activity, while also expressing cancer supporting pathways. CONCLUSIONS:The dynamics of gene expression in the post-tumor breast stroma likely co-determines disease outcome: reversion to normality or transition to transformation in morphologically normal tissue. Our stromal genomic signature may be important for personalizing surgical and adjuvant therapeutic decisions and risk of recurrence.

Drug and alcohol use have been associated with increased risk for sexual violence, but there is little research on sexual violence within the context of drug use among young adult opioid users. The current mixed-methods study explores young adult opioid users' sexual experiences in the context of their drug use. Forty-six New York City young adults (ages 18-32) who reported lifetime nonmedical use of prescription opioids (POs) completed in-depth, semistructured interviews, and 164 (ages 18-29) who reported heroin and/or nonmedical PO use in the past 30 days completed structured assessments that inquired about their drug use and sexual behavior and included questions specific to sexual violence. Participants reported frequent incidents of sexual violence experienced both personally and by their opioid using peers. Participants described sexual violence, including sexual assault, as occurring within a context characterized by victimization of users who were unconscious as a result of substance use, implicit and explicit exchanges of sex for drugs and/or money that increased risk for sexual violence, negative sexual perceptions ascribed to drug users, and participants' own internalized stigma. Recommendations to reduce sexual violence among young adult opioid users include education for users and service providers on the risk of involvement in sexual violence within drug using contexts and efforts to challenge perceptions of acceptability regarding sexual violence.

Background: Multiple bacterial species are capable of degrading oxalate in vitro. Certain taxa degrade oxalate as their sole source of energy and carbon (e.g. Oxalobacter formigenes), whereas others use oxalate as an auxiliary carbon source. For oxalate metabolism, it is not yet well-understood how genomic potential relates to transcriptional regulation. We asked whether the human gut could have a community of oxalatedegrading taxa working synergistically to diminish the effects of this toxic metabolite. Our hypothesis is that oxalate metabolism is regulated by a multi-organism oxalatedegrading community (oxalobiome) that is dominated by specialist oxalate degraders.
Method(s): We used data from 2 public databases: (i)8 healthy subjects in the USA; and (ii)471 healthy subjects in the Netherlands as part of the Human Functional Genomic Project (HFGP). Both collected fecal samples for metagenomic and/or metatranscriptomic high throughput sequencing. Using HUMAnN2 with customized settings, we profiled the metabolic activity of oxalate-degrading bacterial species. Output from these analyses was expressed as Reads per Kilobase per Million mapped reads (RPKM).
Result(s): We identified the oxalate degradation pathway (ODP) in the metagenome and metatranscriptome of all 8 subjects. Mean ODP is 35.3+/-28.1 and 90.1+/-43.5 RPKM in the metagenome and the metatranscriptome, respectively, indicating active expression. O. formigenes, E. coli, and unclassified bacteria were present in metagenomic and metatranscriptomic reads. B. dentium had detectable ODP in its genome but was not transcribing it. In the HFGP database, we identified ODP in 328 subjects of the 471 tested (70%) (Mean=18.1+/-2.1 RPKM). ODP was detected in B. animalis, B. dentium, B. pseudocatenulatum, E.coli/Shigella, L. acidophilus, L. gasseri, L. mucosae, O. formigenes and unclassified bacteria. ODP was examined in the metagenome of 265 females (Mean ODP= 21.7+/-3.3) and 200 males (Mean ODP=13.3+/-1.9 RPKM; p=0.04 by unpaired t test).
Conclusion(s): We have identified a community of bacteria with the potential to degrade oxalate in healthy humans and species actively transcribing ODP. These include E.coli, which might be a common contributor of oxalate degradation in humans. The sex differences in ODP is consistent with the ~ 2:1 male/female incidence and prevalence of calcium oxalate stones

Increased intestinal permeability and translocation of gut bacteria trigger various polyaetiological diseases associated with chronic inflammation and underlie a variety of poorly treatable pathologies. Previous studies have established a primary role of the microbiota composition and intestinal permeability in such pathologies. Using a rat model, we examined the effects of exposure to a bacteriophage cocktail on intestinal permeability and relative abundance of taxonomic units in the gut bacterial community. There was an increase in markers of impaired gut permeability, such as the lactulose/mannitol ratio, plasma endotoxin concentrations, and serum levels of inflammation-related cytokines, following the bacteriophage challenge. We observed significant differences in the alpha diversity of faecal bacterial species and found that richness and diversity index values increased following the bacteriophage challenge. There was a reduction in the abundance of Blautia, Catenibacterium, Lactobacillus, and Faecalibacterium species and an increase in Butyrivibrio, Oscillospira and Ruminococcus after bacteriophage administration. These findings provide novel insights into the role of bacteriophages as potentially pathogenic for mammals and their possible implication in the development of diseases associated with increased intestinal permeability.

BACKGROUND: Benzodiazepines are a widely prescribed psychoactive drug; in the U.S., both medical and nonmedical use of benzodiazepines has increased markedly in the past 15 years. Long-term use can lead to tolerance and dependence, and abrupt withdrawal can cause seizures or other life-threatening symptoms. Benzodiazepines are often used nonmedically in conjunction with other drugs, and with opioids in particular-a combination that can increase the risk for fatal and non-fatal overdose. This mixed-methods study examines nonmedical use of benzodiazepines among young adults in New York City and its relationship with opioid use. METHODS: For qualitative analysis, 46 90-minute semi-structured interviews were conducted with young adult opioid users (ages 18-32). Interviews were transcribed and coded for key themes. For quantitative analysis, 464 young adult opioid users (ages 18-29) were recruited using Respondent-Driven Sampling and completed structured interviews. Benzodiazepine use was assessed via a self-report questionnaire that included measures related to nonmedical benzodiazepine and opioid use. RESULTS: Participants reported using benzodiazepines nonmedically for a wide variety of reasons, including: to increase the high of other drugs; to lessen withdrawal symptoms; and to come down from other drugs. Benzodiazepines were described as readily available and cheap. There was a high prevalence (93%) of nonmedical benzodiazepine use among nonmedical opioid users, with 57% reporting regular nonmedical use. In bivariate analyses, drug-related risk behaviours such as polysubstance use, drug binging, heroin injection and overdose were strongly associated with regular nonmedical benzodiazepine use. In multivariate analysis, growing up in a middle-income household (earning between $51,000 and $100,000 annually), lifetime overdose experience, having ever used cocaine regularly, having ever been prescribed benzodiazepines, recent drug binging, and encouraging fellow drug users to use benzodiazepines to cope with opioid withdrawal were consistently strong predictors of regular nonmedical benzodiazepine use. CONCLUSION: Nonmedical benzodiazepine use may be common among nonmedical opioid users due to its drug-related multi-functionality. Harm reduction messages should account for the multiple functions benzodiazepines serve in a drug-using context, and encourage drug users to tailor their endorsement of benzodiazepines to peers to include safer alternatives.

Bullying is an intentional act that can wreak havoc in the life of an individual. With more than 1 billion users, YouTubeTM is a powerful medium for disseminating information. The purpose of this study was to describe the extent to which content related to bullying is present on YouTubeTM with respect to source, content, number of views, length, and year uploaded. Collectively, the videos in this sample were viewed more than half a billion times. The source of the most widely viewed videos was consumers, and none of the most widely viewed videos was posted by a governmental agency or a professional organization. The most common content in the videos was describing or depicting violence (n = 89). Over one-half addressed getting help (n = 56). Suicide was mentioned in 38 of the videos. Additional investment by professional agencies is warranted to improve understanding about ways to increase the dissemination of positive messages about bullying prevention, and about helping adolescents who are bullied on social media.

To evaluate and characterize the structure of temporal patterns of depression, smoking, unhealthy alcohol use, and other substance use among individuals receiving medical care, and to inform discussion about whether integrated screening and treatment strategies for these conditions are warranted. Using the Veterans Aging Cohort Study (VACS) we measured depression, smoking, unhealthy alcohol use and other substance use (stimulants, marijuana, heroin, opioids) and evaluated which conditions tended to co-occur within individuals, and how this co-occurrence was temporally structured (i.e. concurrently, sequentially, or discordantly). Current depression was associated with current use of every substance examined with the exception of unhealthy alcohol use. Current unhealthy alcohol use and marijuana use were also consistently associated. Current status was strongly predicted by prior status (p < 0.0001; OR = 2.99-22.34) however, there were few other sequential relationships. Associations in the HIV infected and uninfected subgroups were largely the same with the following exceptions. Smoking preceded unhealthy alcohol use and current smoking was associated with current depression in the HIV infected subgroup only (p < 0.001; OR = 1.33-1.41 and p < 0.001; OR = 1.25-1.43). Opioid use and current unhealthy alcohol use were negatively associated only in the HIV negative subgroup (p = 0.01; OR = 0.75). Patterns of depression, smoking, unhealthy alcohol use, and other substance use were temporally concordant, particularly with regard to depression and substance use. These patterns may inform future development of more integrated screening and treatment strategies.

With combined technological advancements in high-throughput next-generation sequencing and deep mass spectrometry-based proteomics, proteogenomics, i.e., the integrative analysis of proteomic and genomic data, has emerged as a new research field. Early efforts in the field were focused on improving protein identification using sample-specific genomic and transcriptomic sequencing data. More recently, integrative analysis of quantitative measurements from genomic and proteomic studies have identified novel insights into gene expression regulation, cell signaling, and disease. Many methods and tools have been developed or adapted to enable an array of integrative proteogenomic approaches and in this article, we systematically classify published methods and tools into four major categories, (1) Sequence-centric proteogenomics; (2) Analysis of proteogenomic relationships; (3) Integrative modeling of proteogenomic data; and (4) Data sharing and visualization. We provide a comprehensive review of methods and available tools in each category and highlight their typical applications.