KNeXT: a NetworkX-based topologically relevant KEGG parser.

Automating the recreation of gene and mixed gene-compound networks from Kyoto Encyclopedia of Genes and Genomes (KEGG) Markup Language (KGML) files is challenging because the data structure does not preserve the independent or loosely connected neighborhoods in which they were originally derived, referred to here as its topological environment. Identical accession numbers may overlap, causing neighborhoods to artificially collapse based on duplicated identifiers. This causes current parsers to create misleading or erroneous graphical representations when mixed gene networks are converted to gene-only networks. To overcome these challenges we created a python-based KEGG NetworkX Topological (KNeXT) parser that allows users to accurately recapitulate genetic networks and mixed networks from KGML map data. The software, archived as a python package index (PyPI) file to ensure broad application, is designed to ingest KGML files through built-in APIs and dynamically create high-fidelity topological representations. The utilization of NetworkX's framework to generate tab-separated files additionally ensures that KNeXT results may be imported into other graph frameworks and maintain programmatic access to the original x-y axis positions to each node in the KEGG pathway. KNeXT is a well-described Python 3 package that allows users to rapidly download and aggregate specific KGML files and recreate KEGG pathways based on a range of user-defined settings. KNeXT is platform-independent, distinctive, and it is not written on top of other Python parsers. Furthermore, KNeXT enables users to parse entire local folders or single files through command line scripts and convert the output into NCBI or UniProt IDs. KNeXT provides an ability for researchers to generate pathway visualizations while persevering the original context of a KEGG pathway. Source code is freely available at https://github.com/everest-castaneda/knext.

Long-term drinking stability in the open-access self-administration monkey model.

The Non-Human Primate (NHP) model for the study of Alcohol Use Disorders (AUD) as developed in our laboratories is critical to our understanding of the pathophysiology of voluntary, chronic, ethanol consumption. Previous work in this model established categories of ethanol consumption that parallel reported categories of human consumption across a spectrum spanning low drinking, binge drinking, heavy drinking, and very heavy drinking, albeit at generally higher daily intakes across categories than documented in people. Original categories assigned to ethanol consumption patterns were established using a limited cohort of rhesus macaques. This study revisits the validity of categorical drinking using an additional 28 monkeys. In addition to finding categorical representations consistent with the original 2014 report, our findings demonstrate that drinking categories remain stable across the observed 12 months of nearly consistent access to ethanol (22 h/day), termed "open access". Animals occupying the two ends of the spectrum, "low" and "very heavy" drinkers, exhibit the largest stability. The findings also indicate a slight escalatory drift over time, with very heavy drinking animals experiencing fatigue near the end of open access.

Waco COVID Survey: A Community-Based SARS-CoV-2 Serological Surveillance Study in Central Texas.

In early-2020, the epidemiology of the SARS-CoV-2 virus was still in discovery and initial reports about the role of asymptomatic individuals were developing. The Waco COVID Survey was implemented in mid-2020 with targeted serological surveillance to assess relationships among risk factors and asymptomatic transmission in McLennan County, Texas, USA. Because large-scale random sampling of the population was not feasible, a targeted and repeated sampling of specific clustered groups of asymptomatic individuals was employed. This included four waves (initial intake [n = 495], two follow-ups separated by a month [n = 348; n = 287], and a final follow-up one year later [n = 313]) of sampling participants in different risk categories: (a) healthcare workers (e.g., physicians, nurses, etc.) and first responders, (b) essential service employees (e.g., convenience and grocery stores, restaurants focused on delivery and carry-out), (c) employees whose businesses began reopening on May 1 (e.g., dine-in restaurants, churches, etc.) including church attendees, and (d) individuals that practiced intensive isolation. The survey collected information on demographics, compliance with public health recommendations, satisfaction with government responses, health history, attitudes regarding the SARS-CoV-2 virus and COVID-19 disease, health behaviors, personality, stress, and general affect. Results illustrate pandemic fatigue over time, the influence of political leniency on opinions and behaviors, the importance of face coverings in preventing infection, and the positive impact of vaccination in the community. This project remains one of the largest longitudinal SARS-CoV-2 antibody seroprevalence surveys in the US, and details for successful implementation and community involvement are discussed.

Exploring links between pathogen avoidance motivation, COVID-19 case counts, and immune function.

OBJECTIVES: The selection pressures exerted by pathogens have played important roles in shaping the biology and behavior of animals, including humans. Immune systems recognize and respond to cues of infection or damage by coordinating cellular, humoral, and metabolic shifts that promote recovery. Moreover, animals also possess a repertoire of behavioral tools to help combat the threat of pathogens, often referred to as the behavioral immune system. Recently, researchers have begun to examine how cognitive, affective, and behavioral disease avoidance mechanisms interact with the biological immune system. METHODS: The present study explored relationships among individual differences in behavioral immune system activity (e.g., pathogen disgust), shifts in SARS-CoV-2 infection risk (i.e., 7-day case averages), and immune function in a community cohort from McLennan County, Texas, USA (n = 387). RESULTS: Levels of disease concern were not consistently associated with immune markers. However, serum levels of IFN-γ, TNF-α, IL-2, and IL-8, as well as serum killing ability of Escherichia coli, each varied with case counts. Additional analyses found that case counts also predicted changes in stress physiology, but not subjective measures of distress. However, follow-up mediation models did not provide evidence that relationships between case counts and immunological outcomes were mediated through levels of stress. CONCLUSIONS: The present project provides initial evidence that markers of immune function may be sensitive to changes in infection risk during the COVID-19 pandemic. This adds to the growing body of research finding relationships among behavioral and biological pathogen management mechanisms.

Ethanol alters the relationship between IGF-1 and bone turnover in male macaques.

Insulin-like growth factor 1 (IGF-1) influences bone turnover. Transient decreases in IGF-I levels and/or bioavailability may contribute to the detrimental effects of alcohol on bone. The goals of this non-human primate study were to i) evaluate the 20-h response of bone turnover markers to ethanol consumption and ii) assess how ethanol consumption influences the relationship between IGF-1 and these markers. Osteocalcin (bone formation), carboxyterminal cross-linking telopeptide of type 1 collagen (CTX, bone resorption), IGF-1, and IGF binding protein 1 (IGFBP-1) were measured in plasma from male rhesus macaques (N = 10, 8.4 ± 0.3 years) obtained at 12:00, 16:00, and 06:00 h during two phases: pre-ethanol (alcohol-naïve) and ethanol access. During the ethanol access phase, monkeys consumed 1.5 g/kg/day ethanol (4% w/v) beginning at 10:00 h. Osteocalcin and CTX were lower, and the ratio of osteocalcin to CTX was higher at each time point during ethanol access compared to the pre-ethanol phase. Pre-ethanol marker levels did not vary across time points, but markers varied during ethanol access. IGF-1 levels, but not IGFBP-1 levels, varied during the pre-ethanol phase. In contrast, IGF-1 levels were stable during ethanol access but IGFBP-1 levels varied. There were positive relationships between IGF-1 and turnover markers during the pre-ethanol phase, but not during ethanol access. In conclusion, chronic ethanol consumption reduces levels of bone turnover markers and blocks the normal positive relationship between IGF-1 and turnover markers and alters the normal relationship between IGF-1 and IGFBP-1. These findings support the hypothesis that chronic alcohol consumption leads to growth hormone/IGF-1 resistance.

Longitudinal changes in COVID-19 concern and stress: Pandemic fatigue overrides individual differences in caution.

Background: Pandemic fatigue describes a phenomenon whereby individuals experience a decrease in COVID-19 concern over time, despite their risk for infection remaining stable, or even increasing. Individual differences in the experience of pandemic fatigue may have important implications for people's adherence to public health recommendations. Design and methods: Using data collected from a large community cohort in McLennan County, TX, longitudinal changes in COVID-19-related concern, stress, and affect across three appointments separated by approximately 4 weeks (July-November 2020) were examined. About 495, 349, and 286 participants completed one, two, and three appointments, respectively. Changes to stress physiology and local travel over time were also analyzed. Results: Results of a latent class growth analysis revealed four distinct classes of individuals: (a) low concern, low stress, (b) moderate concern, moderate stress, (c) moderate concern, low stress, and (d) high concern, high stress. Despite differences between latent classes in initial levels of concern, stress, and negative affect, levels of each variable decreased over time for all groups. While this reduction of concern did not coincide with changes in local travel, it was reflected in heart rate and blood pressure. Conclusions: Together, these results suggest a general trend of pandemic fatigue in the sample, even for those with moderate-to-high levels of initial COVID-19 stress and concern. Such findings may provide insights into the expected challenges of promoting compliance with public health recommendations as the pandemic continues.

Establishment, Persistence, and Reactivation of Latent HIV-1 Infection in Renal Epithelial Cells.

HIV-1 persistence in different cell types presents the main obstacle to an HIV-1 cure. We have previously shown that the renal epithelium is a site of HIV-1 infection and that the kidney represents a separate viral compartment from blood. Whether renal cells can harbor latent virus that can be reactivated upon treatment with latency reversing agents (LRAs) is unknown. To address this question, we developed an in vitro HIV-1 latency model in renal tubule epithelial (RTE) cells using a dual color HIV-1 reporter virus, R7/E-/GFP/EF1a-mCherry (R7GEmC), and evaluated the effect of LRAs, both as single agents and in combination, on viral reactivation. Our data show that HIV-1 can establish latency in RTE cells early postinfection. While the pool of latently infected cells expanded overtime, the percentage of productively infected cells declined. Following LRA treatment only a small fraction of latently infected cells, both T cells and RTE cells, could be reactivated, and the drug combinations more effective in reactivating HIV transcription in RTE cells differed from those more active in T cells. Our study demonstrates that HIV can establish latency in RTE cells and that current LRAs are only marginally effective in inducing HIV-1 reactivation. This suggests that further study of LRA dynamics in non-T cells may be warranted to assess the suitability of LRAs as a sterilizing cure strategy. IMPORTANCE Anti-retroviral therapy (ART) has dramatically reduced HIV-related morbidity and mortality. Despite this success, a number of challenges remain, including the long-term persistence of multiple, clinically latent viral reservoirs capable of reactivation in the absence of ART. As efforts proceed toward HIV eradication or functional cure, further understanding of the dynamics of HIV-1 replication, establishment of latency and mechanisms of reactivation in reservoirs harboring the virus throughout the body is necessary. HIV-1 can infect renal epithelial cells and the expression of viral genes in those cells contributes to the development of HIV associated nephropathy (HIVAN) in untreated individuals. The significance of our work is in developing the first model of HIV-1 latency in renal epithelial cells. This model enhances our understanding of HIV-1 latency and persistence in the kidney and can be used to screen candidate latency reversing agents.

Dose-response effects of alcohol on biochemical markers of bone turnover in non-human primates: Effects of species, sex and age of onset of drinking.

PURPOSE: Alcohol consumption suppressed bone turnover in male non-human primates; however, it is unclear the extent to which this effect depends upon biological variables. Using archived plasma samples, we investigated whether sex, age of onset of alcohol intake, and species influence the effects of graded increases in alcohol consumption on bone turnover markers. METHODS: 91 male and female macaques (rhesus and cynomolgus), ranging in age from 4 years (adolescent) to 10 years (adult) were required to increase their consumption of ethanol in 30-day increments: 0 g/kg/day, followed by 0.5 g/kg/day, 1.0 g/kg/day, and, finally, 1.5 g/kg/day. Plasma osteocalcin (formation), plasma CTX (resorption) and osteocalcin to CTX ratio (turnover balance) were measured during these intervals to assess the dose-response effects of alcohol. RESULTS: We detected no relationship between dose and osteocalcin when all monkeys were combined, but there was a significant effect of sex (lower levels in females) and interactions between alcohol dose and sex (osteocalcin levels increased with dose in rhesus females). In contrast, we detected a negative linear dose-response relationship for ethanol and CTX. We did not detect a relationship between dose and osteocalcin to CTX ratio overall, but there was a significant positive relationship detected in females (no change in males). Increased age predicted lower biomarker levels for both osteocalcin and CTX. Species was a significant predictor for osteocalcin and the osteocalcin to CTX ratio in these models. CONCLUSION: These findings indicate that age, sex, and species influence bone turnover and support the concept that factors beyond quantity of alcohol affect skeletal response to alcohol consumption.

Pairing food and drink: A physiological model of blood ethanol levels for a variety of drinking behaviors.

We present a blood ethanol concentration compartment model which utilizes an animal's ethanol intake, food intake, and weight to predict the animal's blood ethanol concentration at any given time. By incorporating the food digestion process into the model we can predict blood ethanol concentration levels over time for a variety of drinking and eating scenarios. The model is calibrated and validated using data from cohorts of male monkeys, and is able to capture blood ethanol concentration kinetics of the monkeys from a variety of drinking behavior classifications.

Using hierarchical similarity to examine the genetics of Behçet's disease.

OBJECTIVE: Behçet's disease (BD) is a multisystem inflammatory disease that affects patients along the historic silk road. Thus far, the pathogenesis of the disease has proved elusive due to the complex genetic interactions of the disease. In this paper, we seek to clarify the genetic factors of the disease while also uncovering other diseases of interest that present with a similar genotype as BD. RESULTS: To do this, we employ a convergent functional genomics approach by leveraging the hierarchical similarity tool available in Geneweaver. Through our analysis, we were able to ascertain 7 BD consensus genes and 16 autoimmune diseases with genetic overlap with BD. The results of our study will inform further research into the pathogenesis of Behçet's disease.

Unrealistic Optimism and Risk for COVID-19 Disease.

Risk perception and consequently engagement in behaviors to avoid illness often do not match actual risk of infection, morbidity, and mortality. Unrealistic optimism occurs when individuals falsely believe that their personal outcomes will be more favorable than others' in the same risk category. Natural selection could favor overconfidence if its benefits, such as psychological resilience, outweigh its costs. However, just because optimism biases may have offered fitness advantages in our evolutionary past does not mean that they are always optimal. The current project examined relationships among personal risk for severe COVID-19, risk perceptions, and preventative behaviors. We predicted that those with higher risk of severe COVID-19 would exhibit unrealistic optimism and behave in ways inconsistent with their elevated risk of morbidity and mortality. Clinical risk scores for severe COVID-19 were calculated and compared with COVID-19 threat appraisal, compliance with shelter-in-place orders (March 13-May 22, 2020) and travel restrictions, compliance with public health recommendations, and potential covariates like self-rated knowledge about COVID-19 in a robust dataset including 492 participants from McLennan County, TX, USA. While those with high clinical risk acknowledged their greater likelihood of experiencing severe illness if infected, they actually reported lower perceived likelihood of becoming infected in the first place. While it is possible that those with higher clinical risk scores truly are less likely to become infected, the pattern and significance of these results held after controlling for possible occupational exposure, household size, and other factors related to infection probability. Higher clinical risk also predicted more recent travel within Texas and lower distress during the pandemic (i.e., feeling less stressed, depressed, and helpless). Additional behavioral data suggested that those with higher clinical risk scores did not generally behave differently than those with lower scores during the shelter-in-place order. While unrealistic optimism may provide some short-term psychological benefits, it could be dangerous due to improper assessment of hazardous situations; inferring that optimism bias has evolutionary origins does not mean that unrealistic optimism is "optimal" in every situation. This may be especially true when individuals face novel sources (or scales) of risk, such as a global pandemic.

Interpretation of psychiatric genome-wide association studies with multispecies heterogeneous functional genomic data integration.

Genome-wide association studies and other discovery genetics methods provide a means to identify previously unknown biological mechanisms underlying behavioral disorders that may point to new therapeutic avenues, augment diagnostic tools, and yield a deeper understanding of the biology of psychiatric conditions. Recent advances in psychiatric genetics have been made possible through large-scale collaborative efforts. These studies have begun to unearth many novel genetic variants associated with psychiatric disorders and behavioral traits in human populations. Significant challenges remain in characterizing the resulting disease-associated genetic variants and prioritizing functional follow-up to make them useful for mechanistic understanding and development of therapeutics. Model organism research has generated extensive genomic data that can provide insight into the neurobiological mechanisms of variant action, but a cohesive effort must be made to establish which aspects of the biological modulation of behavioral traits are evolutionarily conserved across species. Scalable computing, new data integration strategies, and advanced analysis methods outlined in this review provide a framework to efficiently harness model organism data in support of clinically relevant psychiatric phenotypes.

Immunogenicity, safety, and efficacy of sequential immunizations with an SIV-based IDLV expressing CH505 Envs.

A preventative HIV-1 vaccine is an essential intervention needed to halt the HIV-1 pandemic. Neutralizing antibodies protect against HIV-1 infection in animal models, and thus an approach toward a protective HIV-1 vaccine is to induce broadly cross-reactive neutralizing antibodies (bnAbs). One strategy to achieve this goal is to define envelope (Env) evolution that drives bnAb development in infection and to recreate those events by vaccination. In this study, we report the immunogenicity, safety, and efficacy in rhesus macaques of an SIV-based integrase defective lentiviral vector (IDLV) expressing sequential gp140 Env immunogens derived from the CH505 HIV-1-infected individual who made the CH103 and CH235 bnAb lineages. Immunization with IDLV expressing sequential CH505 Envs induced higher magnitude and more durable binding and neutralizing antibody responses compared to protein or DNA +/- protein immunizations using the same sequential envelopes. Compared to monkeys immunized with a vector expressing Envs alone, those immunized with the combination of IDLV expressing Env and CH505 Env protein demonstrated improved durability of antibody responses at six months after the last immunization as well as lower peak viremia and better virus control following autologous SHIV-CH505 challenge. There was no evidence of vector mobilization or recombination in the immunized and challenged monkeys. Although the tested vaccines failed to induce bnAbs and to mediate significant protection following SHIV-challenge, our results show that IDLV proved safe and successful at inducing higher titer and more durable immune responses compared to other vaccine platforms.

Therapeutic vaccination with IDLV-SIV-Gag results in durable viremia control in chronically SHIV-infected macaques.

Despite incredible scientific efforts, there is no cure for HIV infection. While antiretroviral treatment (ART) can help control the virus and prevent transmission, it cannot eradicate HIV from viral reservoirs established before the initiation of therapy. Further, HIV-infected individuals reliably exhibit viral rebound when ART is interrupted, suggesting that the host immune response fails to control viral replication in persistent reservoirs. Therapeutic vaccines are one current approach to improving antiviral host immune responses and enhance long term virus control. In the present study, we used an integrase defective lentiviral vector (IDLV) expressing SIV-Gag to boost anti-Gag specific immune responses in macaques chronically infected with the tier-2 SHIV-1157(QNE)Y173H. A single immunization with IDLV-SIV-Gag induced durable (>20 weeks) virus control in 55% of the vaccinated macaques, correlating with an increased magnitude of SIV-Gag specific CD8+ T-cell responses. IDLV-based therapeutic vaccines are therefore an effective approach to improve virus specific CD8+ T-cell responses and mediate virus control.

Cisplatin-resistant triple-negative breast cancer subtypes: multiple mechanisms of resistance.

BACKGROUND: Understanding mechanisms underlying specific chemotherapeutic responses in subtypes of cancer may improve identification of treatment strategies most likely to benefit particular patients. For example, triple-negative breast cancer (TNBC) patients have variable response to the chemotherapeutic agent cisplatin. Understanding the basis of treatment response in cancer subtypes will lead to more informed decisions about selection of treatment strategies. METHODS: In this study we used an integrative functional genomics approach to investigate the molecular mechanisms underlying known cisplatin-response differences among subtypes of TNBC. To identify changes in gene expression that could explain mechanisms of resistance, we examined 102 evolutionarily conserved cisplatin-associated genes, evaluating their differential expression in the cisplatin-sensitive, basal-like 1 (BL1) and basal-like 2 (BL2) subtypes, and the two cisplatin-resistant, luminal androgen receptor (LAR) and mesenchymal (M) subtypes of TNBC. RESULTS: We found 20 genes that were differentially expressed in at least one subtype. Fifteen of the 20 genes are associated with cell death and are distributed among all TNBC subtypes. The less cisplatin-responsive LAR and M TNBC subtypes show different regulation of 13 genes compared to the more sensitive BL1 and BL2 subtypes. These 13 genes identify a variety of cisplatin-resistance mechanisms including increased transport and detoxification of cisplatin, and mis-regulation of the epithelial to mesenchymal transition. CONCLUSIONS: We identified gene signatures in resistant TNBC subtypes indicative of mechanisms of cisplatin. Our results indicate that response to cisplatin in TNBC has a complex foundation based on impact of treatment on distinct cellular pathways. We find that examination of expression data in the context of heterogeneous data such as drug-gene interactions leads to a better understanding of mechanisms at work in cancer therapy response.

On Finding and Enumerating Maximal and Maximum k-Partite Cliques in k-Partite Graphs.

Let k denote an integer greater than 2, let G denote a k-partite graph, and let S denote the set of all maximal k-partite cliques in G. Several open questions concerning the computation of S are resolved. A straightforward and highly-scalable modification to the classic recursive backtracking approach of Bron and Kerbosch is first described and shown to run in O(3 n/3) time. A series of novel graph constructions is then used to prove that this bound is best possible in the sense that it matches an asymptotically tight upper limit on |S|. The task of identifying a vertex-maximum element of S is also considered and, in contrast with the k = 2 case, shown to be NP-hard for every k ≥ 3. A special class of k-partite graphs that arises in the context of functional genomics and other problem domains is studied as well and shown to be more readily solvable via a polynomial-time transformation to bipartite graphs. Applications, limitations, potentials for faster methods, heuristic approaches, and alternate formulations are also addressed.

Time for a Drink? A Mathematical Model of Non-human Primate Alcohol Consumption.

We simulate a non-human primate's alcohol drinking pattern in order to better understand temporal patterning of alcoholic drinks that can lead to the excessive intakes associated with alcohol use disorder. A stochastic mathematical model of alcohol consumption pattern is developed, where model parameters are calibrated to an individual monkey's drinking history. The model predicts a time series that simulates a monkey's alcohol intake in time, and we analyze this drinking pattern to understand the variations in day and night drinking, the lengths of drinks (intake in 5 or more consecutive secs), and lengths of bouts (1 or more drinks per 5 min occasion). This time series can predict a lifetime categorical drinking level (light, binge, heavy, or very heavy), thus correlating an individual monkey's parameters with distinct long term drinking classifications.

Integration of heterogeneous functional genomics data in gerontology research to find genes and pathway underlying aging across species.

Understanding the biological mechanisms behind aging, lifespan and healthspan is becoming increasingly important as the proportion of the world's population over the age of 65 grows, along with the cost and complexity of their care. BigData oriented approaches and analysis methods enable current and future bio-gerontologists to synthesize, distill and interpret vast, heterogeneous data from functional genomics studies of aging. GeneWeaver is an analysis system for integration of data that allows investigators to store, search, and analyze immense amounts of data including user-submitted experimental data, data from primary publications, and data in other databases. Aging related genome-wide gene sets from primary publications were curated into this system in concert with data from other model-organism and aging-specific databases, and applied to several questions in genrontology using. For example, we identified Cd63 as a frequently represented gene among aging-related genome-wide results. To evaluate the role of Cd63 in aging, we performed RNAi knockdown of the C. elegans ortholog, tsp-7, demonstrating that this manipulation is capable of extending lifespan. The tools in GeneWeaver enable aging researchers to make new discoveries into the associations between the genes, normal biological processes, and diseases that affect aging, healthspan, and lifespan.

Curating gene sets: challenges and opportunities for integrative analysis.

Genomic data interpretation often requires analyses that move from a gene-by-gene focus to a focus on sets of genes that are associated with biological phenomena such as molecular processes, phenotypes, diseases, drug interactions or environmental conditions. Unique challenges exist in the curation of gene sets beyond the challenges in curation of individual genes. Here we highlight a literature curation workflow whereby gene sets are curated from peer-reviewed published data into GeneWeaver (GW), a data repository and analysis platform. We describe the system features that allow for a flexible yet precise curation procedure. We illustrate the value of curation by gene sets through analysis of independently curated sets that relate to the integrated stress response, showing that sets curated from independent sources all share significant Jaccard similarity. A suite of reproducible analysis tools is provided in GW as services to carry out interactive functional investigation of user-submitted gene sets within the context of over 150 000 gene sets constructed from publicly available resources and published gene lists. A curation interface supports the ability of users to design and maintain curation workflows of gene sets, including assigning, reviewing and releasing gene sets within a curation project context.

Chronic ethanol drinking increases during the luteal menstrual cycle phase in rhesus monkeys: implication of progesterone and related neurosteroids.

RATIONALE: Sporadic reports of alcohol consumption being linked to menstrual cycle phase highlight the need to consider hormonally characterized menstrual cycle phase in understanding the sex-specific effects of risk for alcohol drinking in women. OBJECTIVES: We investigated the association between menstrual cycle phase, characterized by circulating progesterone and menses, with accurate daily alcohol intakes in rhesus monkeys, and the contribution of progesterone derived neuroactive steroids to cycle-related alcohol drinking. METHODS: Menses (daily) and progesterone (2-3×/week) were obtained in female monkeys (n = 8, 5 ethanol, 3 control) for 12-18 months. Ethanol monkeys were then induced to drink ethanol (4% w/v; 3 months) and given 22 h/day access to ethanol and water for approximately 1 year. In selected cycles, a panel of neuroactive steroids were assayed during follicular and luteal phases from pre-ethanol and ethanol exposure. RESULTS: There were minimal to no effects of ethanol on menstrual cycle length, progesterone levels, and follicular or luteal phase length. The monkeys drank more ethanol during the luteal phase, compared to the follicular phase, and ethanol intake was highest in the late luteal phase when progesterone declines rapidly. Two neuroactive steroids were higher during the luteal phase versus the follicular phase, and several neuroactive steroids were higher in the pre- vs. post-ethanol drinking menstrual cycles. CONCLUSIONS: This is the first study to show that normal menstrual cycle fluctuations in progesterone, particularly during the late luteal phase, can modulate ethanol intake. Two of 11 neuroactive steroids were selectively associated with the effect of cycle progesterone on ethanol drinking, suggesting possible links to CNS mechanisms of ethanol intake control.