Multi-environment QTL mixed models for drought stress adaptation in wheat

Many quantitative trait loci (QTL) detection methods ignore QTL-by-environment interaction (QEI) and are limited in accommodation of error and environment-specific variance. This paper outlines a mixed model approach using a recombinant inbred spring wheat population grown in six drought stress trials. Genotype estimates for yield, anthesis date and height were calculated using the best design and spatial effects model for each trial. Parsimonious factor analytic models best captured the variance-covariance structure, including genetic correlations, among environments. The 1RS.1BL rye chromosome translocation (from one parent) which decreased progeny yield by 13.8 g m(-2) was explicitly included in the QTL model. Simple interval mapping (SIM) was used in a genome-wide scan for significant QTL, where QTL effects were fitted as fixed environment-specific effects. All significant environment-specific QTL were subsequently included in a multi-QTL model and evaluated for main and QEI effects with non-significant QEI effects being dropped. QTL effects (either consistent or environment-specific) included eight yield, four anthesis, and six height QTL. One yield QTL co-located (or was linked) to an anthesis QTL, while another co-located with a height QTL. In the final multi-QTL model, only one QTL for yield (6 g m(-2)) was consistent across environments (no QEI), while the remaining QTL had significant QEI effects (average size per environment of 5.1 g m(-2)). Compared to single trial analyses, the described framework allowed explicit modelling and detection of QEI effects and incorporation of additional classification information about genotypes

Alcohol Use Patterns and Subsequent Sexual Behaviors Among Women, Men who have Sex with Men and Men who have Sex with Women Engaged in Routine HIV Care in the United States

Among people with HIV, alcohol use is associated with increased prevalence of sexual transmission behaviors. We examined associations between alcohol use in the prior year and sexual behaviors approximately six months later among 1857 women, 6752 men who have sex with men (MSM) and 2685 men who have sex with women (MSW). Any alcohol use was associated with increased risk of unsafe vaginal sex among women; anal sex and =>2 anal sex partners among MSM; and anal sex, =>2 anal or vaginal sex partners, and unsafe vaginal sex among MSW. In particular, among women >7 alcoholic drinks/week and among MSW =>5 alcoholic drinks/drinking day increased the likelihood of certain subsequent sexual behaviors. For all groups, especially women, the risk of sex under the influence of drugs/alcohol markedly increased with increases in quantity and frequency of alcohol consumption. These different patterns of drinking and sexual behaviors indicate the importance of tailored counseling messages to women, MSM and MSW

Do Symptoms of Depression Interact with Substance Use to Affect HIV Continuum of Care Outcomes?

Few studies examine how depression and substance use interact to affect HIV control. In 14,380 persons with HIV (PWH), we used logistic regression and generalized estimating equations to evaluate how symptoms of depression interact with alcohol, cocaine, opioid, and methamphetamine use to affect subsequent retention in care, maintaining an active prescription for ART, and consistent virologic suppression. Among PWH with no or mild depressive symptoms, heavy alcohol use had no association with virologic suppression (OR 1.00 [0.95–1.06]); among those with moderate or severe symptoms, it was associated with reduced viral suppression (OR 0.80 [0.74–0.87]). We found no interactions with heavy alcohol use on retention in care or maintaining ART prescription or with other substances for any outcome. These results highlight the importance of treating moderate or severe depression in PWH, especially with comorbid heavy alcohol use, and support multifaceted interventions targeting alcohol use and depression

The yields of r-process elements and chemical evolution of the Galaxy

The supernova yields of r-process elements are obtained as a function of the mass of their progenitor stars from the abundance patterns of extremely metal-poor stars on the left-side [Ba/Mg]-[Mg/H] boundary with a procedure proposed by Tsujimoto and Shigeyama. The ejected masses of r-process elements associated with stars of progenitor mass $M_{ms}\leq18M_{\odot}$ are infertile sources and the SNe II with 20$M_{\odot}\leq M_{ms}\leq 40M_{\odot}$are the dominant source of r-process nucleosynthesis in the Galaxy. The ratio of these stars 20$M_{\odot}\leq M_{ms}\leq40M_{\odot}$ with compared to the all massive stars is about $\sim$18%. In this paper, we present a simple model that describes a star's [r/Fe] in terms of the nucleosynthesis yields of r-process elements and the number of SN II explosions. Combined the r-process yields obtained by our procedure with the scatter model of the Galactic halo, the observed abundance patterns of the metal-poor stars can be well reproducedComment: 7 pages, 6 figures, Accepted for publication in Astrophysics and Space Scienc

Associations between At-Risk Alcohol Use, Substance Use, and Smoking with Lipohypertrophy and Lipoatrophy among Patients Living with HIV

To examine associations between lipohypertrophy and lipoatrophy and illicit drug use, smoking, and at-risk alcohol use among a large diverse cohort of persons living with HIV (PLWH) in clinical care. 7,931 PLWH at six sites across the United States completed 21,279 clinical assessments, including lipohypertrophy and lipoatrophy, drug/alcohol use, physical activity level, and smoking. Lipohypertrophy and lipoatrophy were measured using the FRAM body morphology instrument and associations were assessed with generalized estimating equations. Lipohypertrophy (33% mild, 4% moderate-to-severe) and lipoatrophy (20% mild, 3% moderate-to-severe) were common. Older age, male sex, and higher current CD4 count were associated with more severe lipohypertrophy (p values <.001-.03). Prior methamphetamine or marijuana use, and prior and current cocaine use, were associated with more severe lipohypertrophy (p values <.001-.009). Older age, detectable viral load, and low current CD4 cell counts were associated with more severe lipoatrophy (p values <.001-.003). In addition, current smoking and marijuana and opiate use were associated with more severe lipoatrophy (p values <.001-.03). Patients with very low physical activity levels had more severe lipohypertrophy and also more severe lipoatrophy than those with all other activity levels (p values <.001). For example, the lipohypertrophy score of those reporting high levels of physical activity was on average 1.6 points lower than those reporting very low levels of physical activity (-1.6, 95% CI:-1.8 to-1.4, p <.001). We found a high prevalence of lipohypertrophy and lipoatrophy among a nationally distributed cohort of PLWH. While low levels of physical activity were associated with both lipohypertrophy and lipoatrophy, associations with substance use and other clinical characteristics differed between lipohypertrophy and lipoatrophy. These results support the conclusion that lipohypertrophy and lipoatrophy are distinct, and highlight differential associations with specific illicit drug use

Application of a risk-management framework for integration of stromal tumor-infiltrating lymphocytes in clinical trials

Stromal tumor-infiltrating lymphocytes (sTILs) are a potential predictive biomarker for immunotherapy response in metastatic triple-negative breast cancer (TNBC). To incorporate sTILs into clinical trials and diagnostics, reliable assessment is essential. In this review, we propose a new concept, namely the implementation of a risk-management framework that enables the use of sTILs as a stratification factor in clinical trials. We present the design of a biomarker risk-mitigation workflow that can be applied to any biomarker incorporation in clinical trials. We demonstrate the implementation of this concept using sTILs as an integral biomarker in a single-center phase II immunotherapy trial for metastatic TNBC (TONIC trial, NCT02499367), using this workflow to mitigate risks of suboptimal inclusion of sTILs in this specific trial. In this review, we demonstrate that a web-based scoring platform can mitigate potential risk factors when including sTILs in clinical trials, and we argue that this framework can be applied for any future biomarker-driven clinical trial setting

Comprehensive analysis of epigenetic clocks reveals associations between disproportionate biological ageing and hippocampal volume

The concept of age acceleration, the difference between biological age and chronological age, is of growing interest, particularly with respect to age-related disorders, such as Alzheimer’s Disease (AD). Whilst studies have reported associations with AD risk and related phenotypes, there remains a lack of consensus on these associations. Here we aimed to comprehensively investigate the relationship between five recognised measures of age acceleration, based on DNA methylation patterns (DNAm age), and cross-sectional and longitudinal cognition and AD-related neuroimaging phenotypes (volumetric MRI and Amyloid-β PET) in the Australian Imaging, Biomarkers and Lifestyle (AIBL) and the Alzheimer’s Disease Neuroimaging Initiative (ADNI). Significant associations were observed between age acceleration using the Hannum epigenetic clock and cross-sectional hippocampal volume in AIBL and replicated in ADNI. In AIBL, several other findings were observed cross-sectionally, including a significant association between hippocampal volume and the Hannum and Phenoage epigenetic clocks. Further, significant associations were also observed between hippocampal volume and the Zhang and Phenoage epigenetic clocks within Amyloid-β positive individuals. However, these were not validated within the ADNI cohort. No associations between age acceleration and other Alzheimer’s disease-related phenotypes, including measures of cognition or brain Amyloid-β burden, were observed, and there was no association with longitudinal change in any phenotype. This study presents a link between age acceleration, as determined using DNA methylation, and hippocampal volume that was statistically significant across two highly characterised cohorts. The results presented in this study contribute to a growing literature that supports the role of epigenetic modifications in ageing and AD-related phenotypes

Uncovering the heterogeneity and temporal complexity of neurodegenerative diseases with Subtype and Stage Inference

The heterogeneity of neurodegenerative diseases is a key confound to disease understanding and treatment development, as study cohorts typically include multiple phenotypes on distinct disease trajectories. Here we introduce a machine-learning technique\u2014Subtype and Stage Inference (SuStaIn)\u2014able to uncover data-driven disease phenotypes with distinct temporal progression patterns, from widely available cross-sectional patient studies. Results from imaging studies in two neurodegenerative diseases reveal subgroups and their distinct trajectories of regional neurodegeneration. In genetic frontotemporal dementia, SuStaIn identifies genotypes from imaging alone, validating its ability to identify subtypes; further the technique reveals within-genotype heterogeneity. In Alzheimer\u2019s disease, SuStaIn uncovers three subtypes, uniquely characterising their temporal complexity. SuStaIn provides fine-grained patient stratification, which substantially enhances the ability to predict conversion between diagnostic categories over standard models that ignore subtype (p = 7.18 7 10 124 ) or temporal stage (p = 3.96 7 10 125 ). SuStaIn offers new promise for enabling disease subtype discovery and precision medicine