Acupressure to Reduce Treatment-Related Symptoms for Children With Cancer and Recipients of Hematopoietic Stem Cell Transplant: Protocol for a Randomized Controlled Trial.

BackgroundWe describe the study design and protocol of a pragmatic randomized controlled trial (RCT) Acupressure for Children in Treatment for a Childhood Cancer (ACT-CC).ObjectiveTo describe the feasibility and effectiveness of an acupressure intervention to decrease treatment-related symptoms in children in treatment for cancer or recipients of a chemotherapy-based hematopoietic stem cell transplant (HSCT).DesignTwo-armed RCTs with enrollment of 5 to 30 study days.SettingTwo pediatric teaching hospitals.PatientsEighty-five children receiving cancer treatment or a chemotherapy-based HSCT each with 1 parent or caregiver.InterventionPatients are randomized 1:1 to receive either usual care plus daily professional acupressure and caregiver delivered acupressure versus usual care alone for symptom management. Participants receive up to 20 professional treatments.Main outcomeA composite nausea/vomiting measure for the child.Secondary outcomesChild's nausea, vomiting, pain, fatigue, depression, anxiety, and positive affect.Parent outcomesDepression, anxiety, posttraumatic stress symptoms, caregiver self-efficacy, and positive affect. Feasibility of delivering the semistandardized intervention will be described. Linear mixed models will be used to compare outcomes between arms in children and parents, allowing for variability in diagnosis, treatment, and age.DiscussionTrial results could help childhood cancer and HSCT treatment centers decide about the regular inclusion of trained acupressure providers to support symptom management

Guidelines for Genome-Scale Analysis of Biological Rhythms

Genome biology approaches have made enormous contributions to our understanding of biological rhythms, particularly in identifying outputs of the clock, including RNAs, proteins, and metabolites, whose abundance oscillates throughout the day. These methods hold significant promise for future discovery, particularly when combined with computational modeling. However, genome-scale experiments are costly and laborious, yielding “big data” that are conceptually and statistically difficult to analyze. There is no obvious consensus regarding design or analysis. Here we discuss the relevant technical considerations to generate reproducible, statistically sound, and broadly useful genome-scale data. Rather than suggest a set of rigid rules, we aim to codify principles by which investigators, reviewers, and readers of the primary literature can evaluate the suitability of different experimental designs for measuring different aspects of biological rhythms. We introduce CircaInSilico, a web-based application for generating synthetic genome biology data to benchmark statistical methods for studying biological rhythms. Finally, we discuss several unmet analytical needs, including applications to clinical medicine, and suggest productive avenues to address them

Guidelines for Genome-Scale Analysis of Biological Rhythms

Genome biology approaches have made enormous contributions to our understanding of biological rhythms, particularly in identifying outputs of the clock, including RNAs, proteins, and metabolites, whose abundance oscillates throughout the day. These methods hold significant promise for future discovery, particularly when combined with computational modeling. However, genome-scale experiments are costly and laborious, yielding ‘big data’ that is conceptually and statistically difficult to analyze. There is no obvious consensus regarding design or analysis. Here we discuss the relevant technical considerations to generate reproducible, statistically sound, and broadly useful genome scale data. Rather than suggest a set of rigid rules, we aim to codify principles by which investigators, reviewers, and readers of the primary literature can evaluate the suitability of different experimental designs for measuring different aspects of biological rhythms. We introduce CircaInSilico, a web-based application for generating synthetic genome biology data to benchmark statistical methods for studying biological rhythms. Finally, we discuss several unmet analytical needs, including applications to clinical medicine, and suggest productive avenues to address them

Deletion of the KH1 Domain of Fmr1 Leads to Transcriptional Alterations and Attentional Deficits in Rats

Fragile X syndrome (FXS) is a neurodevelopmental disorder caused by mutations in the FMR1 gene. It is a leading monogenic cause of autism spectrum disorder and inherited intellectual disability and is often comorbid with attention deficits. Most FXS cases are due to an expansion of CGG repeats leading to suppressed expression of fragile X mental retardation protein (FMRP), an RNA-binding protein involved in mRNA metabolism. We found that the previously published Fmr1 knockout rat model of FXS expresses an Fmr1 transcript with an in-frame deletion of exon 8, which encodes for the K-homology (KH) RNA-binding domain, KH1. Notably, 3 pathogenic missense mutations associated with FXS lie in the KH domains. We observed that the deletion of exon 8 in rats leads to attention deficits and to alterations in transcriptional profiles within the medial prefrontal cortex (mPFC), which map to 2 weighted gene coexpression network modules. These modules are conserved in human frontal cortex and enriched for known FMRP targets. Hub genes in these modules represent potential therapeutic targets for FXS. Taken together, these findings indicate that attentional testing might be a reliable cross-species tool for investigating FXS and identify dysregulated conserved gene networks in a relevant brain region

The dystrophin gene and cognitive function in the general population

The aim of our study is to investigate whether single-nucleotide dystrophin gene (DMD) variants associate with variability in cognitive functions in healthy populations. The study included 1240 participants from the Erasmus Rucphen family (ERF) study and 1464 individuals from the Rotterdam Study (RS). The participants whose exomes were sequenced and who were assessed for various cognitive traits were included in the analysis. To determine the association between DMD variants and cognitive ability, linear (mixed) modeling with adjustment for age, sex and education was used. Moreover, Sequence Kernel Association Test (SKAT) was used to test the overall association of the rare genetic variants present in the DMD with cognitive traits. Although no DMD variant surpassed the prespecified significance threshold (PG showed strong association (beta = 1.786, P-value = 2.56 x 10(-4)) with block-design test in the ERF study, while another variant rs1800273: G>A showed suggestive association (beta = -0.465, P-value = 0.002) with Mini-Mental State Examination test in the RS. Both variants are highly conserved, although rs147546024: A>G is an intronic variant, whereas rs1800273: G>A is a missense variant in the DMD which has a predicted damaging effect on the protein. Further gene-based analysis of DMD revealed suggestive association (P-values = 0.087 and 0.074) with general cognitive ability in both cohorts. In conclusion, both single variant and gene-based analyses suggest the existence of variants in the DMD which may affect cognitive functioning in the general populations