Search

Substance use disparities among sexual and gender minority (SGM) people are attributed to minority stress, but few studies have examined minority stress and cannabis use over time or investigated differences in cannabis use trajectories by less-studied gender subgroups. We examined if longitudinal cannabis use trajectories are related to baseline minority stressors and if gender differences persisted after accounting for minority stress. Cannabis use risk was measured annually over four years (2017-2021) within a longitudinal cohort study of SGM adults in the United States (N = 11,813). Discrimination and victimization, internalized stigma, disclosure and concealment, and safety and acceptance comprised minority stress (n = 5,673). Latent class growth curve mixture models identified five cannabis use trajectories: 'low or no risk', 'low moderate risk', 'high moderate risk', 'steep risk increase', and 'highest risk'. Participants who reported past-year discrimination and/or victimization at baseline had greater odds of membership in any cannabis risk category compared to the 'low risk' category (odds ratios [OR] 1.17-1.33). Internalized stigma was related to 'high moderate' and 'highest risk' cannabis use (ORs 1.27-1.38). After accounting for minority stress, compared to cisgender men, gender expansive people and transgender men had higher odds of 'low moderate risk' (ORs 1.61, 1.67) or 'high moderate risk' (ORs 2.09, 1.99), and transgender men had higher odds of 'highest risk' (OR 2.36) cannabis use. This study indicates minority stress is related to prospective cannabis use risk trajectories among SGM people, and transgender men and gender expansive people have greater odds of trajectories reflecting cannabis use risk.

Objective: Circulating microRNAs show cross-sectional associations with overweight and obesity. Few studies provided data to differentiate between a snapshot perspective on these associations versus how microRNAs characterize prodromal risk from disease pathology and complications. This study assessed longitudinal relationships between circulating microRNAs and weight at multiple time-points in the Diabetes Prevention Program trial. Research design and methods: A subset of participants (n=150) from the Diabetes Prevention Program were included. MicroRNAs were measured from banked plasma using a Fireplex Assay. We used generalized linear mixed models to evaluate relationships between microRNAs and changes in weight at baseline, year-1, and year-2. Logistic regression was used to evaluate whether microRNAs at baseline were associated with weight change after 2 years. Results: In fully adjusted models that included relevant covariates, seven miRs (i.e., miR-126, miR-15a, miR-192, miR-23a, and miR-27a) were statistically associated with weight over 2 years. MiR-197 and miR-320a remained significant after adjustment for multiple comparisons. Baseline levels of let-7f, miR-17, and miR-320c were significantly associated with 3% weight loss after 2 years in fully adjusted models. Discussion: This study provided evidence for longitudinal relationships between circulating microRNAs and weight. Because microRNAs characterize the combined effects of genetic determinants and responses to behavioral determinants, they may provide insights about the etiology of overweight and obesity in the context or risk for common, complex diseases. Additional studies are needed to validate the potential genes and biological pathways that might be targeted by these microRNA biomarkers and have mechanistic implications for weight loss and disease prevention.

Purpose: Sexual and gender minority (SGM) people are at greater risk for substance use than heterosexual and cisgender people, but most prior work is limited by cross-sectional analyses or the examination of single substance use. This study examined substance use over time among SGM people to identify patterns of polysubstance use at the intersection of sex and gender. Methods: Data were collected annually over 4 years from SGM respondents (n = 11,822) in The Population Research in Identity and Disparities for Equality (PRIDE) Study. Differences in substance use patterns (any prior 30-day use of 15 substances) by gender subgroup were examined with latent class analysis, and multinomial regression models tested relationships between gender subgroup and substance use. Results: Eight classes of substance use were observed. The three most common patterns were low substance use (49%), heavy episodic alcohol use (≥5 alcoholic drinks on one occasion) with some cannabis and tobacco use (14%), and cannabis use with some tobacco and declining heavy episodic alcohol use (13%). Differences observed included lower odds of patterns defined by heavy episodic alcohol use with some cannabis and tobacco use in all gender subgroups relative to cisgender men and persons with low substance use (odds ratios [ORs] 0.26-0.60). Gender expansive people assigned female at birth, gender expansive people assigned male at birth, and transgender men had greater odds of reporting cannabis use with small percentages of heavy episodic alcohol and tobacco use (ORs: 1.41-1.60). Conclusion: This study suggests that there are unique patterns of polysubstance use over time among gender subgroups of SGM people.

Introduction: Metabolic syndrome (MetS) is a prominent risk factor for both cardiovascular disease (CVD) and type 2 diabetes (T2D). MicroRNAs (miRs) are small noncoding RNA molecules that target messenger RNAs to alter gene expression. Circulating miRs have been studied as potential clinically meaningful biomarkers of risk for MetS as they are readily measured from blood. Though associations among MetS components and social constructs of race, ethnicity, and gender have previously been established, grouping according to these constructs alone may conflate genetic ancestry with the environmental/behavioral effects of being characterized as a particular gender, race, or ethnicity. The purpose of this study was to identify differences in circulating miRs associated with demographic factors and MetS components to better illuminate the nuanced health impacts of race, ethnicity and gender. Methods: This was a secondary analysis of a subset of participants (N=1000) from the Diabetes Prevention Program (DPP). A custom Fireplex assay was used to quantify miRs from banked plasma collected at baseline. Correlations between miRs and metabolic syndrome components were assessed by Pearson’s correlation coefficient. Multivariable linear models adjusted for age and weight were used to analyze associations between gender, race, ethnicity, and miR expression. The Benjamini-Hochberg false discovery rate (FDR) method was applied. Results: The sample was 68% female, 19% Black, 15% Hispanic, and mean age was 52 ± 10 years. After adjusting for multiple comparisons (FDR

BackgroundCervical cancer oncogenesis starts with human papillomavirus (HPV) cell entry after binding to host cell surface receptors; however, the mechanism is not fully known. We examined polymorphisms in receptor genes hypothesized to be necessary for HPV cell entry and assessed their associations with clinical progression to precancer.MethodsAfrican American women (N = 1,728) from the MACS/WIHS Combined Cohort Study were included. Two case-control study designs were used-cases with histology-based precancer (CIN3+) and controls without; and cases with cytology-based precancer [high-grade squamous intraepithelial lesions (HSIL)] and controls without. SNPs in candidate genes (SDC1, SDC2, SDC3, SDC4, GPC1, GPC2, GPC3, GPC4, GPC5, GPC6, and ITGA6) were genotyped using an Illumina Omni2.5-quad beadchip. Logistic regression was used to assess the associations in all participants and by HPV genotypes, after adjusting for age, human immunodeficiency virus serostatus, CD4 T cells, and three principal components for ancestry.ResultsMinor alleles in SNPs rs77122854 (SDC3), rs73971695, rs79336862 (ITGA6), rs57528020, rs201337456, rs11987725 (SDC2), rs115880588, rs115738853, and rs9301825 (GPC5) were associated with increased odds of both CIN3+ and HSIL, whereas, rs35927186 (GPC5) was found to decrease the odds for both outcomes (P value ≤ 0.01). Among those infected with Alpha-9 HPV types, rs722377 (SDC3), rs16860468, rs2356798 (ITGA6), rs11987725 (SDC2), and rs3848051 (GPC5) were associated with increased odds of both precancer outcomes.ConclusionsPolymorphisms in genes that encode binding receptors for HPV cell entry may play a role in cervical precancer progression.ImpactOur findings are hypothesis generating and support further exploration of mechanisms of HPV entry genes that may help prevent progression to cervical precancer.

MicroRNAs (miRs) may contribute to disease etiology by influencing gene expression. Numerous databases are available for miR target prediction and validation, but their functionality is varied, and outputs are not standardized. The purpose of this review is to identify and describe databases for cataloging validated miR targets. Using Tools4miRs and PubMed, we identified databases with experimentally validated targets, human data, and a focus on miR-messenger RNA (mRNA) interactions. Data were extracted about the number of times each database was cited, the number of miRs, the target genes, the interactions per database, experimental methodology and key features of each database. The search yielded 10 databases, which in order of most cited to least were: miRTarBase, starBase/The Encyclopedia of RNA Interactomes, DIANA-TarBase, miRWalk, miRecords, miRGator, miRSystem, miRGate, miRSel and targetHub. Findings from this review suggest that the information presented within miR target validation databases can be enhanced by adding features such as flexibility in performing queries in multiple ways, downloadable data, ongoing updates and integrating tools for further miR-mRNA target interaction analysis. This review is designed to aid researchers, especially those new to miR bioinformatics tools, in database selection and to offer considerations for future development and upkeep of validation tools. Database URL http://mirtarbase.cuhk.edu.cn/.

BackgroundType 2 diabetes (T2D) has an immense disease burden, affecting millions of people worldwide and costing billions of dollars in treatment. As T2D is a multifactorial disease with both genetic and nongenetic influences, accurate risk assessments for patients are difficult to perform. Machine learning has served as a useful tool in T2D risk prediction, as it can analyze and detect patterns in large and complex data sets like that of RNA sequencing. However, before machine learning can be implemented, feature selection is a necessary step to reduce the dimensionality in high-dimensional data and optimize modeling results. Different combinations of feature selection methods and machine learning models have been used in studies reporting disease predictions and classifications with high accuracy.ObjectiveThe purpose of this study was to assess the use of feature selection and classification approaches that integrate different data types to predict weight loss for the prevention of T2D.MethodsThe data of 56 participants (ie, demographic and clinical factors, dietary scores, step counts, and transcriptomics) were obtained from a previously completed randomized clinical trial adaptation of the Diabetes Prevention Program study. Feature selection methods were used to select for subsets of transcripts to be used in the selected classification approaches: support vector machine, logistic regression, decision trees, random forest, and extremely randomized decision trees (extra-trees). Data types were included in different classification approaches in an additive manner to assess model performance for the prediction of weight loss.ResultsAverage waist and hip circumference were found to be different between those who exhibited weight loss and those who did not exhibit weight loss (P=.02 and P=.04, respectively). The incorporation of dietary and step count data did not improve modeling performance compared to classifiers that included only demographic and clinical data. Optimal subsets of transcripts identified through feature selection yielded higher prediction accuracy than when all available transcripts were included. After comparison of different feature selection methods and classifiers, DESeq2 as a feature selection method and an extra-trees classifier with and without ensemble learning provided the most optimal results, as defined by differences in training and testing accuracy, cross-validated area under the curve, and other factors. We identified 5 genes in two or more of the feature selection subsets (ie, CDP-diacylglycerol-inositol 3-phosphatidyltransferase [CDIPT], mannose receptor C type 2 [MRC2], PAT1 homolog 2 [PATL2], regulatory factor X-associated ankyrin containing protein [RFXANK], and small ubiquitin like modifier 3 [SUMO3]).ConclusionsOur results suggest that the inclusion of transcriptomic data in classification approaches for prediction has the potential to improve weight loss prediction models. Identification of which individuals are likely to respond to interventions for weight loss may help to prevent incident T2D. Out of the 5 genes identified as optimal predictors, 3 (ie, CDIPT, MRC2, and SUMO3) have been previously shown to be associated with T2D or obesity.Trial registrationClinicalTrials.gov NCT02278939; https://clinicaltrials.gov/ct2/show/NCT02278939.

IntroductionIntegrated transcriptome and microRNA differential gene expression (DEG) analyses may help to explain type 2 diabetes (T2D) pathogenesis in at-risk populations. The purpose of this study was to characterize DEG in banked biospecimens from underactive adult participants who responded to a randomized clinical trial measuring the effects of lifestyle interventions on T2D risk factors. DEGs were further examined within the context of annotated biological pathways.MethodsParticipants (n = 52) in a previously completed clinical trial that assessed a 12-week behavioural intervention for T2D risk reduction were included. Participants who showed >6mg/dL decrease in fasting blood glucose were identified as responders. Gene expression was measured by RNASeq, and overrepresentation analysis within KEGG pathways and weighted gene correlation network analysis (WGCNA) were performed.ResultsNo genes remained significantly differentially expressed after correction for multiple comparisons. One module derived by WGCNA related to body mass index was identified, which contained genes located in KEGG pathways related to known mechanisms underlying risk for T2D as well as pathways related to neurodegeneration and protein misfolding. A network analysis showed indirect connections between genes in this module and islet amyloid polypeptide (IAPP), which has previously been hypothesized as a mechanism for T2D.DiscussionWe validated prior studies that showed pathways related to metabolism, inflammation/immunity, and endocrine/hormone function are related to risk for T2D. We identified evidence for new potential mechanisms that include protein misfolding. Additional studies are needed to determine whether these are potential therapeutic targets to decrease risk for T2D.

PurposeGestational diabetes (GDM) is associated with increased risk for preterm birth and related complications for both the pregnant person and newborn. Changes in gene expression have the potential to characterize complex interactions between genetic and behavioral/environmental risk factors for GDM. Our goal was to summarize the state of the science about changes in gene expression and GDM.DesignThe systematic review was conducted using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines.MethodsPubMed articles about humans, in English, from any date were included if they described mRNA transcriptome or microRNA findings from blood samples in adults with GDM compared with adults without GDM.ResultsSixteen articles were found representing 1355 adults (n=674 with GDM, n=681 controls) from 12 countries. Three studies reported transcriptome results and thirteen reported microRNA findings. Identified pathways described various aspects of diabetes pathogenesis, including glucose and insulin signaling, regulation, and transport; natural killer cell mediated cytotoxicity; and fatty acid biosynthesis and metabolism. Studies described 135 unique miRNAs that were associated with GDM, of which eight (miR-16-5p, miR-17-5p, miR-20a-5p, miR-29a-3p, miR-195-5p, miR-222-3p, miR-210-3p, and miR-342-3p) were described in 2 or more studies. Findings suggest that miRNA levels vary based on the time in pregnancy when GDM develops, the time point at which they were measured, sex assigned at birth of the offspring, and both the pre-pregnancy and gestational body mass index of the pregnant person.ConclusionsThe mRNA, miRNA, gene targets, and pathways identified in this review contribute to our understanding of GDM pathogenesis; however, further research is warranted to validate previous findings. In particular, longitudinal repeated-measures designs are needed that control for participant characteristics (e.g., weight), use standardized data collection methods and analysis tools, and are sufficiently powered to detect differences between subgroups. Findings may be used to improve early diagnosis, prevention, medication choice and/or clinical treatment of patients with GDM.

MicroRNAs (miRNAs) may be considered important regulators of risk for type 2 diabetes (T2D). The aim of the present study was to identify novel sets of miRNAs associated with T2D risk, as well as their gene and pathway targets. Circulating miRNAs (n=59) were measured in plasma from participants in a previously completed clinical trial (n=82). An agnostic statistical approach was applied to identify novel sets of miRNAs with optimal co‑expression patterns. In silico analyses were used to identify the messenger RNA and biological pathway targets of the miRNAs within each factor. A total of three factors of miRNAs were identified, containing 18, seven and two miRNAs each. Eight biological pathways were revealed to contain genes targeted by the miRNAs in all three factors, 38 pathways contained genes targeted by the miRNAs in two factors, and 55, 18 and two pathways were targeted by the miRNAs in a single factor, respectively (all q

Prior studies focused on circulating microRNAs and the risk for complex diseases have shown inconsistent findings. The majority of studies focused on European and East Asian racial or ethnic groups, however, ancestry was not typically reported. We evaluated the risk for type 2 diabetes as an exemplar to show that race and ethnic group may contribute to inconsistent validation of previous findings of associations with microRNAs.

BackgroundMicroRNAs may be important regulators of risk for type 2 diabetes. The purpose of this longitudinal observational study was to assess whether circulating microRNAs predicted improvements in fasting blood glucose, a major risk factor for type 2 diabetes, over 12 months.MethodsThe study included participants (n = 82) from a previously completed trial that tested the effect of restorative yoga on individuals with prediabetes. Circulating microRNAs were measured using a flow cytometry miRNA assay. Linear models were used to determine the optimal sets of microRNA predictors overall and by intervention group.ResultsSubsets of microRNAs were significant predictors of final fasting blood glucose after 12-months (R2 = 0.754, p

IntroductionMicroRNAs (miRs) may be important regulators of risk for type 2 diabetes (T2D). Circulating miRs may provide information about which individuals are at risk for T2D. The purpose of this study was to assess longitudinal associations between circulating miR expression and variability in fasting blood glucose (FBG) and to identify miR-targeted genes and biological pathways.MethodsVariability in FBG was estimated using standard deviation from participants (n = 20) in a previously completed yoga trial. Expression of 402 miRs was measured using hydrogel particle lithography. MirTarBase was used to identify mRNAs, and miRPathDB was used to identify pathways targeted by differentially expressed miRs.ResultsSix circulating miRs (miR-192, miR-197, miR-206, miR-424, miR-486, and miR-93) were associated with variability in FBG and targeted 143 genes and 23 Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways. Six mRNAs (AKT1, CCND1, ESR1, FASN, SMAD7, and VEGFA) were targeted by at least two miRs and four of those were located in miR-targeted KEGG pathways.ConclusionsCirculating miRs are associated with variability in FBG in individuals at risk for T2D. Further studies are needed to determine whether miRs may be prodromal biomarkers that can identify which individuals are at greatest risk to progress to T2D and which biological pathways underlie this risk.

BackgroundGlobally, type 2 diabetes is highly prevalent in individuals of Latino ancestry. The reasons underlying this high prevalence are not well understood, but both genetic and lifestyle factors are contributors. Circulating microRNAs are readily detectable in blood and are promising biomarkers to characterize biological responses (i.e., changes in gene expression) to lifestyle factors. Prior studies identified relationships between circulating microRNAs and risk for type 2 diabetes, but Latinos have largely been under-represented in these study samples.Aims/hypothesisThe aim of this study was to assess for differences in expression levels of three candidate microRNAs (miR-126, miR-146, miR-15) between individuals who had prediabetes compared to normal glycemic status and between individuals who self-identified with Latino ancestry in the United States (US) and native Mexicans living in or near Leon, Mexico.MethodsThis was a cross-sectional study that included 45 Mexicans and 21 Latino participants from the US. Prediabetes was defined as fasting glucose 100-125 mg/dL or 2-h post-glucose challenge between 140 and 199 mg/dL. Expression levels of microRNAs from plasma were measured by qPCR. Linear and logistic regression models were used to assess relationships between individual microRNAs and glycemic status or geographic site.ResultsNone of the three microRNAs was associated with risk for type 2 diabetes. MiR-146a and miR-15 were significantly lower in the study sample from Mexico compared to the US. There was a significant interaction between miR-146a and BMI associated with fasting blood glucose.Conclusions/interpretationThis study did not replicate in Latinos prior observations from other racial groups of associations between miR-126, miR-146a, and miR-15 and risk for type 2 diabetes. Future studies should consider other microRNAs related to different biological pathways as possible biomarkers for type 2 diabetes in Latinos.

BackgroundData on the prevalence and correlates of restless legs syndrome (RLS) in people with HIV are limited. This study sought to determine the prevalence of RLS, associated clinical correlates, and characterize sleep-related differences in men with and without HIV.MethodsSleep-related data were collected in men who have sex with men participating in the Multicenter AIDS Cohort Study (MACS). Demographic, health behaviors, HIV status, comorbidities, and serological data were obtained from the MACS visit coinciding with sleep assessments. Participants completed questionnaires, home polysomnography, and wrist actigraphy. RLS status was determined with the Cambridge-Hopkins RLS questionnaire. RLS prevalence was compared in men with and without HIV. Multinomial logistic regression was used to examine correlates of RLS among all participants and men with HIV alone. Sleep-related differences were examined in men with and without HIV by RLS status.ResultsThe sample consisted of 942 men (56% HIV+; mean age 57 years; 69% white). The prevalence of definite RLS was comparable in men with and without HIV (9.1% vs 8.7%). In multinomial regression, HIV status was not associated with RLS prevalence. However, white race, anemia, depression, and antidepressant use were each independently associated with RLS. HIV disease duration was also associated with RLS. Men with HIV and RLS reported poorer sleep quality, greater sleepiness, and had worse objective sleep efficiency/fragmentation than men without HIV/RLS.ConclusionsThe prevalence of RLS in men with and without HIV was similar. Screening for RLS may be considered among people with HIV with insomnia and with long-standing disease.

SORCS2 rs73208473 was recently associated with decreased atazanavir (ATV) concentration in the hair of women with seropositive HIV. Herein, we report on a pharmacogenetic study of women with seropositive HIV demonstrating a similar association between rs73208473 and dose-adjusted plasma ATV concentration in African Americans.

Background: Cocaine—one of the most frequently abused illicit drugs among persons living with HIV [people living with HIV (PLWH)]—slows the decline of viral production after antiretroviral therapy and is associated with higher HIV viral load, more rapid HIV progression, and increased mortality. Setting: We examined the impact of cocaine use on the CD4+ T-cell HIV latent reservoir (HLR) in virally suppressed PLWH participating in a national, longitudinal cohort study of the natural and treated history of HIV in the United States. Methods: CD4+ T-cell genomic DNA from 434 women of diverse ancestry (ie, 75% Black, 14% Hispanic, 12% White) who self-reported cocaine use (ie, 160 cocaine users, 59 prior users, 215 non-users) was analyzed using the Intact Proviral HIV DNA Assay, measuring intact provirus per 106 CD4+ T cells. Findings: HIV latent reservoir size differed by cocaine use (ie, median [interquartile range]: 72 [14–193] for never users, 165 [63– 387] for prior users, 184 [28–502] for current users), which was statistically significantly larger in both prior (P = 0.023) and current (P = 0.001) cocaine users compared with never users. Conclusions: Cocaine use may contribute to a larger replication competent HLR in CD4+ T cells among virologically suppressed women living with HIV. Our findings are important because women are underrepresented in HIV reservoir studies and in studies of the impact of cocaine use on outcomes among PLWH. [ABSTRACT FROM AUTHOR]

Stimulant use may accelerate HIV disease progression through biological and behavioral pathways. However, scant research with treated HIV-positive persons has examined stimulant-associated alterations in pathophysiologic processes relevant to HIV pathogenesis. In a sample of 55 HIV-positive, methamphetamine-using sexual minority men with a viral load less than 200 copies/mL, we conducted RNA sequencing to examine patterns of leukocyte gene expression in participants who had a urine sample that was reactive for stimulants (n = 27) as compared to those who tested non-reactive (n = 28). Results indicated differential expression of 32 genes and perturbation of 168 pathways in recent stimulant users. We observed statistically significant differential expression of single genes previously associated with HIV latency, cell cycle regulation, and immune activation in recent stimulant users (false discovery rate p

Sexual minority (i.e., non-heterosexual) individuals experience poorer mental and physical health, accounted for in part by the additional burden of sexual minority stress occurring from being situated in a culture favoring heteronormativity. Informed by previous research, the purpose of this study was to identify the relationship between sexual minority stress and leukocyte gene expression related to inflammation, cancer, immune function, and cardiovascular function. Sexual minority men living with HIV who were on anti-retroviral medication, had viral load

Since the completion of the Human Genome Project, there have been pitched debates about its implications and the research it enables. One prominent thread of concern focuses on the role of post-genomic science on technically enabling and generating interest in genetic ancestry testing (GAT). Critical analyses of GAT have pointed to multiple issues, raising the alarm on consumers' experiences with such technologies. This paper describes the results of a pilot study in which we tracked women's experiences receiving their genetic ancestry results, and their understandings of, reactions to, and valuing of this information over time. Overwhelmingly, our participants reported a curious combination of anticipation and satisfaction yet no discernable impact on their sense of self or racial identity. We elaborate on the effects and non-effects of GAT for the women in our study, and how we make sense of their simultaneous experiences of 'knowing something' but not 'feeling different.'

Cancer patients in pain require high doses of opioids and quickly become opioid-tolerant. Previous studies have shown that chronic cancer pain as well as high-dose opioid use lead to mu-opioid receptor downregulation. In this study we explore downregulation of the mu-opioid receptor gene (OPRM1), as a mechanism for opioid tolerance in the setting of opioid use for cancer pain. We demonstrate in a cohort of 84 cancer patients that high-dose opioid use correlates with OPRM1 hypermethylation in peripheral leukocytes of these patients. We then reverse-translate our clinical findings by creating a mouse cancer pain model; we create opioid tolerance in the mouse cancer model to mimic opioid tolerance in the cancer patients. Using this model we determine the functional significance of OPRM1 methylation on cancer pain and opioid tolerance. We focus on 2 main cells within the cancer microenvironment: the cancer cell and the neuron. We show that targeted re-expression of mu-opioid receptor on cancer cells inhibits mechanical and thermal hypersensitivity, and prevents opioid tolerance, in the mouse model. The resultant analgesia and protection against opioid tolerance are likely due to preservation of mu-opioid receptor expression on the cancer-associated neurons.PerspectiveWe demonstrate that epigenetic regulation of OPRM1 contributes to opioid tolerance in cancer patients, and that targeted gene therapy could treat cancer-induced nociception and opioid tolerance in a mouse cancer model.

Objective/backgroundDaytime napping longer than one hour has been associated with an increased risk for all-cause mortality. Associations between cytokine polymorphisms and daytime napping in chronic illnesses such as HIV, however, have not been well described. The purpose of this study was to examine cytokine polymorphisms associated with long daytime napping in adults living with HIV.MethodsA cross-sectional analysis was conducted using a convenience sample of 257 adults living with HIV. Daytime napping was assessed with wrist actigraphy data collected over three days. Participants categorized as long nappers (≥60 min) were compared to short nappers and non-nappers (

Fatigue, a highly prevalent and distressing symptom during chemotherapy (CTX), demonstrates diurnal and interindividual variability in severity. Little is known about the associations between variations in genes involved in inflammatory processes and morning and evening fatigue severity during CTX. The purposes of this study, in a sample of oncology patients (N=543) with breast, gastrointestinal (GI), gynecological (GYN), or lung cancer who received two cycles of CTX, were to determine whether variations in genes involved in inflammatory processes were associated with inter-individual variability in initial levels as well as in the trajectories of morning and evening fatigue. Patients completed the Lee Fatigue Scale to determine morning and evening fatigue severity a total of six times over two cycles of CTX. Using a whole exome array, 309 single nucleotide polymorphisms SNPs among the 64 candidate genes that passed all quality control filters were evaluated using hierarchical linear modeling (HLM). Based on the results of the HLM analyses, the final SNPs were evaluated for their potential impact on protein function using two bioinformational tools. The following inflammatory pathways were represented: chemokines (3 genes); cytokines (12 genes); inflammasome (11 genes); Janus kinase/signal transducers and activators of transcription (JAK/STAT, 10 genes); mitogen-activated protein kinase/jun amino-terminal kinases (MAPK/JNK, 3 genes); nuclear factor-kappa beta (NFkB, 18 genes); and NFkB and MAP/JNK (7 genes). After controlling for self-reported and genomic estimates of race and ethnicity, polymorphisms in six genes from the cytokine (2 genes); inflammasome (2 genes); and NFkB (2 genes) pathways were associated with both morning and evening fatigue. Polymorphisms in six genes from the inflammasome (1 gene); JAK/STAT (1 gene); and NFkB (4 genes) pathways were associated with only morning fatigue. Polymorphisms in three genes from the inflammasome (2 genes) and the NFkB (1 gene) pathways were associated with only evening fatigue. Taken together, these findings add to the growing body of evidence that suggests that morning and evening fatigue are distinct symptoms.

Despite the high prevalence of nonalcoholic fatty liver disease (NAFLD), therapeutic options and noninvasive markers of disease activity and severity remain limited. We investigated the association between plasma biomarkers and liver histology in order to identify markers of disease activity and severity in patients with biopsy-proven NAFLD. Thirty-two plasma biomarkers chosen a priori as possible discriminators of NAFLD were measured in participants enrolled in the Nonalcoholic Steatohepatitis (NASH) Clinical Research Network. Dichotomized histologic outcomes were evaluated using centrally read biopsies. Biomarkers with statistically significant associations with NAFLD histology were evaluated in multivariable models adjusted for clinical factors. Of 648 participants (74.4% white, 61.7% female, mean age 47.7 years), 58.0% had definite NASH, 55.5% had mild/no fibrosis (stage 0-1), and 44.4% had significant fibrosis (stage 2-4). Increased activated plasminogen activator inhibitor 1 had a strong association with definite NASH compared to not NASH or borderline NASH in multivariable analysis (odds ratio = 1.20, 95% confidence interval 1.08-1.34, P < 0.001). Biomarkers associated with significant fibrosis (versus mild/no fibrosis) in multivariable analysis included higher levels of interleukin-8, monocyte chemoattractant protein-1, resistin, soluble interleukin-1 receptor I, soluble interleukin-2 receptor alpha, and tumor necrosis factor alpha and lower levels of insulin-like growth factor 2.ConclusionsSpecific plasma biomarkers are significantly associated with disease activity and severity of fibrosis in NAFLD and are potentially valuable tools for noninvasive stratification of patients with NAFLD and identification of targets for therapeutic intervention. (Hepatology 2017;65:65-77).

Aims: The purpose of this study was to assess the levels of cardiovascular health (CVH) of Black and Latino adults with type 2 diabetes (T2D) and examine the association of individual and microsystem level factors with their CVH score. Methods: This was a cross-sectional design in 60 Black and Latino Adults aged 18–40 with T2D. Data were collected on sociodemographic, individual (sociodemographic, diabetes self-management, sleep disturbance, depressive symptoms, quality of life, and the inflammatory biomarkers IL-6 and hs-CRP) and microsystem factors (family functioning), and American Heart Association's Life's Simple 7 metrics of CVH. Factors significantly associated with the CVH score in the bivariate analyses were entered into a linear regression model. Results: The sample had a mean age 34 ± 5 years and was primarily female (75%) with a mean CVH score was 8.6 ± 2.2 (possible range of 0–14). The sample achieved these CVH factors at ideal levels: body mass index <25 kg/m2 (8%); blood pressure <120/80 (42%); hemoglobin A1c < 7% (57%); total cholesterol <200 mg/dL (83%); healthy diet (18%); never or former smoker > one year (95%); and physical activity (150 moderate-to-vigorous minutes/week; 45%). In the multivariable model, two factors were significantly associated with cardiovascular health: hs-CRP (B = −0.11621, p <.0001) and the general health scale (B = 0.45127, p =.0013). Conclusions: This sample had an intermediate level of CVH, with inflammation and general health associated with overall CVH score. [ABSTRACT FROM AUTHOR]

PurposeNot all oncology patients and their family caregivers (FCs) experience the same quality of life (QOL). The purposes of this study were to identify latent classes of oncology patients (n = 168) and their FCs (n = 85) with distinct physical, psychological, social, and spiritual well-being trajectories from prior to through 4 months after the completion of radiation therapy and to evaluate for demographic, clinical, and genetic characteristics that distinguished between these latent classes.MethodsUsing growth mixture modeling, two latent classes were found for three (i.e., physical, psychological, and social well-being) of the four QOL domains evaluated.ResultsAcross these three domains, the largest percentage of participants reported relatively high well-being scores across the 6 months of the study. Across these three QOL domains, patients and FCs who were younger, female, belonged to an ethnic minority group, had children at home, had multiple comorbid conditions, or had a lower functional status, were more likely to be classified in the lower QOL class. The social well-being domain was the only domain that had a polymorphism in nuclear factor kappa beta 2 (NFKB2) associated with latent class membership. Carrying one or two doses of the rare allele for rs7897947 was associated with a 54 % decrease in the odds of belonging to the lower social well-being class [OR (95 % CI) = .46 (.21, .99), p = .049].ConclusionsThese findings suggest that a number of phenotypic and molecular characteristics contribute to differences in QOL in oncology patients and their FCs.

BackgroundPatients with colorectal cancer (CRC) rarely experience a single symptom associated with their disease and its treatment.ObjectivePurpose of this literature review was to summarize the current state of knowledge of multiple co-occurring symptoms in CRC patients who received chemotherapy (CTX) alone or CTX with targeted therapies.MethodsComprehensive literature search was conducted from 1990 to 2014. These studies were evaluated in terms of the occurrence of multiple co-occurring symptoms in CRC patients who received CTX alone or CTX with targeted therapies; the most common symptom assessment and quality of life (QOL) instruments used; and the associations identified between select demographic and treatment characteristics, QOL, and multiple co-occurring symptoms.ResultsOnly 5 studies met this review's inclusion criteria. Two studies compared symptoms in patients who received CTX alone or CTX with targeted therapies, and only 1 study reported on symptom occurrence. Of the 5 studies identified, only 2 used the same instrument to assess symptoms, and only 2 studies evaluated for associations between demographic and treatment characteristics and symptom burden, as well as QOL outcomes.ConclusionsGiven the larger number of patients with CRC, as well as the increased number of CRC patients who will receive targeted therapies with or without CTX, future studies need to describe the occurrence, severity, and distress of multiple co-occurring symptoms and their impact on CRC patients' QOL.Implications for practiceTo deliver effective symptom management interventions, the most common, severe, and distressing symptoms that CRC patients experience need to be identified.

ObjectiveThe purpose of this study was to evaluate trajectories of and predictors for changes in upper extremity (UE) function in women (n = 396) during the first year after breast cancer treatment.DesignProspective, longitudinal assessments of shoulder range of motion (ROM), grip strength, and perceived interference of function were performed before and for 1 year after surgery. Demographic, clinical, and treatment characteristics were evaluated as predictors of postoperative function.ResultsWomen had a mean (SD) age of 54.9 (11.6) years, and 64% were white. Small but statistically significant reductions in shoulder ROM were found on the affected side over 12 months (P < 0.001). Predictors of interindividual differences in ROM at the 1-month assessment were ethnicity, neoadjuvant chemotherapy, type of surgery, axillary lymph node dissection, and preoperative ROM. Predictors of interindividual differences in changes over time in postoperative ROM were living alone, type of surgery, axillary lymph node dissection, and adjuvant chemotherapy. Declines in mean grip strength from before through 1 month after surgery were small and not clinically meaningful. Women with greater preoperative breast pain interference scores had higher postoperative interference scores at all postoperative assessments.ConclusionSome of the modifiable risk factors identified in this study can be targeted for intervention to improve UE function in these women.

Moderate-to-severe fatigue occurs in up to 94% of oncology patients undergoing active treatment. Current interventions for fatigue are not efficacious. A major impediment to the development of effective treatments is a lack of understanding of the fundamental mechanisms underlying fatigue. In the current study, differences in phenotypic characteristics and gene expression profiles were evaluated in a sample of breast cancer patients undergoing chemotherapy (CTX) who reported low (n = 19) and high (n = 25) levels of evening fatigue. Compared to the low group, patients in the high evening fatigue group reported lower functional status scores, higher comorbidity scores, and fewer prior cancer treatments. One gene was identified as upregulated and 11 as downregulated in the high evening fatigue group. Gene set analysis found 24 downregulated and 94 simultaneously up- and downregulated pathways between the two fatigue groups. Transcript origin analysis found that differential expression (DE) originated primarily from monocytes and dendritic cell types. Query of public data sources found 18 gene expression experiments with similar DE profiles. Our analyses revealed that inflammation, neurotransmitter regulation, and energy metabolism are likely mechanisms associated with evening fatigue severity; that CTX may contribute to fatigue seen in oncology patients; and that the patterns of gene expression may be shared with other models of fatigue (e.g., physical exercise and pathogen-induced sickness behavior). These results suggest that the mechanisms that underlie fatigue in oncology patients are multifactorial.

ContextTo accurately investigate diurnal variations in fatigue, a measure needs to be psychometrically sound and demonstrate stable item function in relationship to time of day. Rasch analysis is a modern psychometric approach that can be used to evaluate these characteristics.ObjectivesTo evaluate, using Rasch analysis, the psychometric properties of the Lee Fatigue Scale (LFS) in a sample of oncology patients.MethodsThe sample comprised 587 patients (mean age 57.3 ± 11.9 years, 80% women) undergoing chemotherapy for breast, gastrointestinal, gynecological, or lung cancer. Patients completed the 13-item LFS within 30 minutes of awakening (i.e., morning fatigue) and before going to bed (i.e., evening fatigue). Rasch analysis was used to assess validity and reliability.ResultsIn initial analyses of differential item function, eight of the 13 items functioned differently depending on whether the LFS was completed in the morning or in the evening. Subsequent analyses were conducted separately for the morning and evening fatigue assessments. Nine of the morning fatigue items and 10 of the evening fatigue items demonstrated acceptable goodness-of-fit to the Rasch model. Principal components analyses indicated that both morning and evening assessments demonstrated unidimensionality. Person-separation indices indicated that both morning and evening fatigue scales were able to distinguish four distinct strata of fatigue severity.ConclusionExcluding four items from the morning fatigue scale and three items from the evening fatigue scale improved the psychometric properties of the LFS for assessing diurnal variations in fatigue severity in oncology patients.

PurposePurposes of this study were to identify subgroups of patients with distinct trajectories for morning and evening fatigue, evaluate for differences in demographic and clinical characteristics among these subgroups, and compare and contrast the predictors of subgroup membership for morning and evening fatigue.MethodsOutpatients with breast, gastrointestinal, gynecological, or lung cancer (n = 582) completed questionnaires, a total of six times over two cycles of chemotherapy (CTX). Morning and evening fatigue severity were evaluated using the Lee Fatigue Scale. Latent profile analysis (LPA) was used to identify distinct subgroups.ResultsThree latent classes were identified for morning fatigue (i.e., low (31.8 %), high (51.4 %), and very high (16.8 %)) and for evening fatigue (i.e., moderate (20.0 %), high (21.8 %), and very high (58.2 %)). Most of the disease and treatment characteristics did not distinguish among the morning and evening fatigue classes. Compared to the low class, patients in the high and very high morning fatigue classes were younger, had a lower functional status, and higher level of comorbidity. Compared to the moderate class, patients in the very high evening fatigue class were younger, more likely to be female, had child care responsibilities, had a lower functional status, and a higher level of comorbidity.ConclusionLPA allows for the identification of risk factors for more severe fatigue. Since an overlap was not observed across the morning and evening fatigue classes and unique predictors for morning and evening fatigue were identified, these findings suggest that morning and evening fatigue may have distinct underlying mechanisms.

BackgroundCA125, a tumor-associated antigen, is primarily used to monitor epithelial ovarian cancer. There is evidence that different species of CA125 exist; however, it is not known if any of these species are present in healthy women during the menstrual cycle and if they are associated with serum concentrations of CA125. The purpose of this study was to determine if the molecular species of CA125 differ across the three phases of the menstrual cycle in healthy women.MethodsHealthy, Caucasian women between the ages of 18 and 39 were enrolled using strict criteria to exclude factors known to contribute to CA125 fluctuations. Menstrual cycle regularity was determined using calendars maintained by participants for 3 months. After cycle regularity was established, blood was drawn at three time points for Western blot analysis.ResultsWestern blot analysis yielded 17 distinct profiles (i.e., patterns of species) of CA125, with 80% of the sample exhibiting 5 common profiles. No differences in demographic characteristics and serum CA125 values were found among the various CA125 profiles.ConclusionsDifferent molecular species of CA125 exist in healthy women with regular menstrual cycles. These data provide evidence that CA125 is not a homogeneous molecular species. Future research should evaluate the molecular composition and the clinical importance of these species.

Aims/hypothesisAsian Indians have a high incidence of type 2 diabetes, but factors associated with glycemic progression in this population are not understood. MicroRNAs are emerging as important mediators of glucose homeostasis and have not been previously studied in Asian Indians. We examined microRNA (miR) expression associated with glycemic impairment and progression in Asian Indians from the San Francisco Bay Area. We studied 128 Asian Indians age 45-84 years without known cardiovascular disease and not taking diabetes medications. Oral glucose tolerance tests were performed at baseline and after 2.5 years. We quantified circulating miRs from plasma collected during the enrollment visit using a flow cytometry-based assay.ResultsGlycemic impairment was present in 57 % (n = 73) at baseline. MiR-191 was positively associated with glycemic impairment (odds ratio (OR) 1.7 (95 % CI 1.2, 2.4), p