STepped exercise program for patients with knee OsteoArthritis (STEP-KOA): protocol for a randomized controlled trial

Background: Physical therapy (PT) and other exercise-based interventions are core components of care for knee osteoarthritis (OA), but both are underutilized, and some patients have limited access to PT services. This clinical trial is examining a STepped Exercise Program for patients with Knee OsteoArthritis (STEP-KOA). This model of care can help to tailor exercise-based interventions to patient needs and also conserve higher resource services (such as PT) for patients who do not make clinically relevant improvements after receiving less costly interventions. Methods / Design: Step-KOA is a randomized trial of 345 patients with symptomatic knee OA from two Department of Veterans Affairs sites. Participants are randomized to STEP-KOA and Arthritis Education (AE) Control groups with a 2:1 ratio, respectively. STEP-KOA begins with 3 months of access to an internet-based exercise program (Step 1). Participants not meeting response criteria for clinically meaningful improvement in pain and function after Step 1 progress to Step 2, which involves bi-weekly physical activity coaching calls for 3 months. Participants not meeting response criteria after Step 2 progress to in-person PT visits (Step 3). Outcomes will be assessed at baseline, 3, 6 and 9 months (primary outcome time point). The primary outcome is the Western Ontario and McMasters Universities Osteoarthritis Index (WOMAC), and secondary outcomes are objective measures of physical function. Linear mixed models will compare outcomes between the STEP-KOA and AE control groups at follow-up. We will also evaluate patient characteristics associated with treatment response and conduct a cost-effectiveness analysis of STEP-KOA. Discussion: STEP-KOA is a novel, efficient and patient-centered approach to delivering exercise-based interventions to patients with knee OA, one of the most prevalent and disabling health conditions. This trial will provide information on the effectiveness of STEP-KOA as a novel potential model of care for treatment of OA

Physiological Adaptations to Progressive Endurance Exercise Training in Adult and Aged Rats: Insights from the Molecular Transducers of Physical Activity Consortium (MoTrPAC)

While regular physical activity is a cornerstone of health, wellness, and vitality, the impact of endurance exercise training on molecular signaling within and across tissues remains to be delineated. The Molecular Transducers of Physical Activity Consortium (MoTrPAC) was established to characterize molecular networks underlying the adaptive response to exercise. Here, we describe the endurance exercise training studies undertaken by the Preclinical Animal Sites Studies component of MoTrPAC, in which we sought to develop and implement a standardized endurance exercise protocol in a large cohort of rats. To this end, Adult (6-mo) and Aged (18-mo) female (n = 151) and male (n = 143) Fischer 344 rats were subjected to progressive treadmill training (5 d/wk, ∼70%-75% VO2max) for 1, 2, 4, or 8 wk; sedentary rats were studied as the control group. A total of 18 solid tissues, as well as blood, plasma, and feces, were collected to establish a publicly accessible biorepository and for extensive omics-based analyses by MoTrPAC. Treadmill training was highly effective, with robust improvements in skeletal muscle citrate synthase activity in as little as 1-2 wk and improvements in maximum run speed and maximal oxygen uptake by 4-8 wk. For body mass and composition, notable age- and sex-dependent responses were observed. This work in mature, treadmill-trained rats represents the most comprehensive and publicly accessible tissue biorepository, to date, and provides an unprecedented resource for studying temporal-, sex-, and age-specific responses to endurance exercise training in a preclinical rat model

GWAS Meta-Analysis of Suicide Attempt: Identification of 12 Genome-Wide Significant Loci and Implication of Genetic Risks for Specific Health Factors

OBJECTIVE: Suicidal behavior is heritable and is a major cause of death worldwide. Two large-scale genome-wide association studies (GWASs) recently discovered and cross-validated genome-wide significant (GWS) loci for suicide attempt (SA). The present study leveraged the genetic cohorts from both studies to conduct the largest GWAS meta-analysis of SA to date. Multi-ancestry and admixture-specific meta-analyses were conducted within groups of significant African, East Asian, and European ancestry admixtures. METHODS: This study comprised 22 cohorts, including 43,871 SA cases and 915,025 ancestry-matched controls. Analytical methods across multi-ancestry and individual ancestry admixtures included inverse variance-weighted fixed-effects meta-analyses, followed by gene, gene-set, tissue-set, and drug-target enrichment, as well as summary-data-based Mendelian randomization with brain expression quantitative trait loci data, phenome-wide genetic correlation, and genetic causal proportion analyses. RESULTS: Multi-ancestry and European ancestry admixture GWAS meta-analyses identified 12 risk loci at p values \u3c5×10 CONCLUSIONS: This multi-ancestry analysis of suicide attempt identified several loci contributing to risk and establishes significant shared genetic covariation with clinical phenotypes. These findings provide insight into genetic factors associated with suicide attempt across ancestry admixture populations, in veteran and civilian populations, and in attempt versus death

GWAS Meta-Analysis of Suicide Attempt: Identification of 12 Genome-Wide Significant Loci and Implication of Genetic Risks for Specific Health Factors

Objective: Suicidal behavior is heritable and is a major cause of death worldwide. Two large-scale genome-wide association studies (GWASs) recently discovered and crossvalidated genome-wide significant (GWS) loci for suicide attempt (SA). The present study leveraged the genetic cohorts from both studies to conduct the largest GWAS metaanalysis of SA to date. Multi-ancestry and admixture-specific meta-analyses were conducted within groups of significant African, East Asian, and European ancestry admixtures. Methods: This study comprised 22 cohorts, including 43,871 SA cases and 915,025 ancestry-matched controls. Analytical methods across multi-ancestry and individual ancestry admixtures included inverse variance-weighted fixed-effects meta-analyses, followed by gene, gene-set, tissue-set, and drug-target enrichment, as well as summary-data-based Mendelian randomization with brain expression quantitative trait loci data, phenome-wide genetic correlation, and genetic causal proportion analyses. Results: Multi-ancestry and European ancestry admixture GWAS meta-analyses identified 12 risk loci at p values &lt;5×10-8. These loci were mostly intergenic and implicated DRD2, SLC6A9, FURIN, NLGN1, SOX5, PDE4B, and CACNG2. The multi-ancestry SNP-based heritability estimate of SA was 5.7% on the liability scale (SE=0.003, p=5.7×10-80). Significant brain tissue gene expression and drug set enrichment were observed. There was shared genetic variation of SA with attention deficit hyperactivity disorder, smoking, and risk tolerance after conditioning SA on both major depressive disorder and posttraumatic stress disorder. Genetic causal proportion analyses implicated shared genetic risk for specific health factors. Conclusions: This multi-ancestry analysis of suicide attempt identified several loci contributing to risk and establishes significant shared genetic covariation with clinical phenotypes. These findings provide insight into genetic factors associated with suicide attempt across ancestry admixture populations, in veteran and civilian populations, and in attempt versus death.</p

Dissecting the Shared Genetic Architecture of Suicide Attempt, Psychiatric Disorders, and Known Risk Factors

Background Suicide is a leading cause of death worldwide, and nonfatal suicide attempts, which occur far more frequently, are a major source of disability and social and economic burden. Both have substantial genetic etiology, which is partially shared and partially distinct from that of related psychiatric disorders. Methods We conducted a genome-wide association study (GWAS) of 29,782 suicide attempt (SA) cases and 519,961 controls in the International Suicide Genetics Consortium (ISGC). The GWAS of SA was conditioned on psychiatric disorders using GWAS summary statistics via multitrait-based conditional and joint analysis, to remove genetic effects on SA mediated by psychiatric disorders. We investigated the shared and divergent genetic architectures of SA, psychiatric disorders, and other known risk factors. Results Two loci reached genome-wide significance for SA: the major histocompatibility complex and an intergenic locus on chromosome 7, the latter of which remained associated with SA after conditioning on psychiatric disorders and replicated in an independent cohort from the Million Veteran Program. This locus has been implicated in risk-taking behavior, smoking, and insomnia. SA showed strong genetic correlation with psychiatric disorders, particularly major depression, and also with smoking, pain, risk-taking behavior, sleep disturbances, lower educational attainment, reproductive traits, lower socioeconomic status, and poorer general health. After conditioning on psychiatric disorders, the genetic correlations between SA and psychiatric disorders decreased, whereas those with nonpsychiatric traits remained largely unchanged. Conclusions Our results identify a risk locus that contributes more strongly to SA than other phenotypes and suggest a shared underlying biology between SA and known risk factors that is not mediated by psychiatric disorders.Peer reviewe

Large meta-analysis of genome-wide association studies identifies five loci for lean body mass

Lean body mass, consisting mostly of skeletal muscle, is important for healthy aging. We performed a genome-wide association study for whole body (20 cohorts of European ancestry with n = 38,292) and appendicular (arms and legs) lean body mass (n = 28,330) measured using dual energy X-ray absorptiometry or bioelectrical impedance analysis, adjusted for sex, age, height, and fat mass. Twenty-one single-nucleotide polymorphisms were significantly associated with lean body mass either genome wide (p < 5 x 10(-8)) or suggestively genome wide (p < 2.3 x 10(-6)). Replication in 63,475 (47,227 of European ancestry) individuals from 33 cohorts for whole body lean body mass and in 45,090 (42,360 of European ancestry) subjects from 25 cohorts for appendicular lean body mass was successful for five single-nucleotide polymorphisms in/ near HSD17B11, VCAN, ADAMTSL3, IRS1, and FTO for total lean body mass and for three single-nucleotide polymorphisms in/ near VCAN, ADAMTSL3, and IRS1 for appendicular lean body mass. Our findings provide new insight into the genetics of lean body mass

Drivers of the fungal spore bioaerosol budget: observational analysis and global modeling

Abstract. Bioaerosols are produced by biological processes and directly emitted into the atmosphere, where they contribute to ice nucleation and the formation of precipitation. Previous studies have suggested that fungal spores constitute a substantial portion of the atmospheric bioaerosol budget. However, our understanding of what controls the emission and burden of fungal spores on the global scale is limited. Here, we use a previously unexplored source of fungal spore count data from the American Academy of Allergy, Asthma, and Immunology (AAAAI) to gain insight into the drivers of their emissions. First, we derive emissions from observed concentrations at 66 stations by applying the boundary layer equilibrium assumption. We estimate an annual mean emission of 62 ± 31 m−2 s−1 across the USA. Based on these pseudo-observed emissions, we derive two models for fungal spore emissions at seasonal scales: a statistical model, which links fungal spore emissions to meteorological variables that show similar seasonal cycles (2 m specific humidity, leaf area index and friction velocity), and a population model, which describes the growth of fungi and the emission of their spores as a biological process that is driven by temperature and biomass density. Both models show better skill at reproducing the seasonal cycle in fungal spore emissions at the AAAAI stations than the model previously developed by Heald and Spracklen (2009) (referred to as HS09). We implement all three emissions models in the chemical transport model GEOS-Chem to evaluate global emissions and burden of fungal spore bioaerosol. We estimate annual global emissions of 3.7 and 3.4 Tg yr−1 for the statistical model and the population model, respectively, which is about an order of magnitude lower than the HS09 model. The global burden of the statistical and the population model is similarly an order of magnitude lower than that of the HS09 model. A comparison with independent datasets shows that the new models reproduce the seasonal cycle of fluorescent biological aerosol particle (FBAP) concentrations at two locations in Europe somewhat better than the HS09 model, although a quantitative comparison is hindered by the ambiguity in interpreting measurements of fluorescent particles. Observed vertical profiles of FBAP show that the convective transport of spores over source regions is captured well by GEOS-Chem, irrespective of which emission scheme is used. However, over the North Atlantic, far from significant spore sources, the model does not reproduce the vertical profiles. This points to the need for further exploration of the transport, cloud processing and wet removal of spores. In addition, more long-term observational datasets are needed to assess whether drivers of seasonal fungal spore emissions are similar across continents and biomes