Metabolites Associated With Fatigue and Physical Activity in Childhood Cancer

Untargeted analysis of psilocybin and non-psilocybin mushrooms using liquid chromatography quadrupole time of flight mass spectrometry

Psilocybin mushrooms, particularly those containing the psychoactive compounds psilocybin and psilocin, have attracted recent attention due to their potential therapeutic use for the treatment of psychological disorders. To use psilocybin mushrooms in a clinical context, it is important to understand their chemical composition more fully. An untargeted analysis using liquid chromatography (LC) quadrupole time-of-flight mass spectrometry was performed to explore the chemical diversity of various species of psilocybin mushrooms (PM) relative to edible non-psilocybin mushrooms (NPM). The analysis was performed using reversed phase LC with electrospray ionization in data independent acquisition mode. The study revealed the presence of several classes of compounds and their derivatives. The data was analyzed using multiple statistical methods. Principal component analysis showed that the psilocybin mushrooms and non-psilocybin mushrooms are compositionally very different from each other. These findings contribute to a deeper understanding of the chemical complexity of psilocybin mushrooms and lay groundwork for future research into their potential applications in medicine and psychology.

The Use of Biomarkers in Precision Health Symptom Science-Opportunities and Challenges

OBJECTIVES

Precision health symptom science applies person-centered approaches to elucidate interindividual differences in patients' symptom experiences and incorporates omics methods with social, societal, and environmental determinants of health to develop symptom management strategies. By filling scientific gaps related to patients' symptom experiences and their underlying mechanisms, interventions can be developed to improve quality of life and outcomes. The purposes of this article are to describe symptom phenotype development; review analytical approaches to identify a symptom phenotype; and discuss common and emerging methods for biomarker discovery and their implications in precision health symptom science.

METHODS

Peer-reviewed research studies, review articles, and scientific expertise were synthesized to provide a broad overview of several methods of biomarker discovery and their implications for precision health symptom science.

RESULTS

Approaches to symptom phenotype development and analytical methods for phenotype identification were reviewed. Common (ie, genomic, epigenomic, transcriptomic, proteomic, metabolomic, microbiome) and emerging (ie, polygenic risk scores, microRNA, epigenetic clocks, allostatic load, wearables) methods for biomarker discovery were described. Each method provides unique information to improve our understanding of the complex biological processes that underlie symptoms and may be used for risk prediction, screening, surveillance, and treatment response.

CONCLUSIONS

While the exemplar approaches to conducting precision health symptom science were shared through an oncology lens, they are generalizable across acute and chronic conditions.

IMPLICATIONS FOR NURSING PRACTICE

Symptom biomarker identification is inherently complex and the methods for biomarker collection, processing, measurement, and analysis are continually evolving. Therefore, symptom scientists need to form transdisciplinary teams with experts in omics methodologies and bioinformatics. Despite the challenges, symptom scientists are well suited to lead the way in precision health symptom science to reduce symptom burden and improve quality of life among patients with various chronic conditions.

Metabolomic Associations With Fatigue and Physical Function in Children With Cancer: A Pilot Study

Background: Fatigue is a frequently reported symptom in children undergoing cancer treatment. Prior research shows an inverse relationship between fatigue and physical activity. Less is known about fatigue's relationship with physical function or the underlying biological mechanisms of fatigue. This study explored associations among fatigue, physical function, and associated metabolites. Methods: Children (7-18 years) provided serum samples and self-reports of fatigue and lower extremity physical function (mobility) using Pediatric Patient-Reported Outcomes Measurement Information System (PROMIS) surveys at two timepoints during cancer therapy. PROMIS scores were categorized as high/low per established cut points (high fatigue T >47.5; high physical function T >51.5). High-resolution liquid chromatography-mass spectrometry extracted 29 metabolites hypothesized a priori to be associated with fatigue or physical function. Descriptive statistics summarized PROMIS scores, and linear mixed effect models estimated metabolite associations adjusting for age, gender and steroid use. Results: Forty children participated (female, 53%; 7-12 years, 38%; 13-18 years 62%; Hodgkins Lymphoma, 33%; Acute Lymphoblastic/Lymphocytic Leukemia, 40%; Osteosarcoma, 10%; Other, 17%). Physical function and fatigue were inversely related: T1 (r = -0.64; p < .001) and T2 (r = -0.63; p < .001). One metabolite (indole-3-latic acid) differentiated between low and high fatigue. Five metabolites differentiated significantly between low and high physical function (4-Hydroxybenzoic acid, m-Coumaric acid, myoinositol, tryptophan, and tyrosine). Conclusions:These findings substantiate prior studies showing metabolites, particularly amino acids, significantly associated with fatigue and physical function. All significant metabolites were associated with the gut microbiome. Physical function was inversely corelated with fatigue providing another potential intervention for fatigue management.

Association Between Systemic Immunity-Inflammation Index (SII) and Fatigue, Cancer, and Cancer-Related Fatigue: Insights From NHANES (2005-2018)

OBJECTIVE

To investigate the association between the systemic immunity-inflammation index (SII) and fatigue, cancer, and cancer-related fatigue (CRF) populations.

METHODS

The National Health and Nutrition Examination Survey (NHANES) from 2005 to 2018 provided data for this retrospective cross-sectional study. By dividing the platelet count by the neutrophil count and the lymphocyte count, SII was calculated. Participants were categorized into four groups: normal, fatigue, cancer, and cancer-related fatigue (CRF), with the normal group serving as the reference. Binary logistic regression was applied to assess the correlations. The dose-response relationship between SII and outcomes in the four groups was evaluated using restricted cubic splines. Use threshold effect analysis to determine the optimal SII value for each of the three groups. Stratified and subgroup analyses were performed based on sociodemographic factors and confounders, with specific attention to fatigue severity levels (mild, moderate, severe) in the fatigue and CRF groups.

RESULTS

Data analysis included a total of 32,491 participants, including 14,846 in the normal group, 14,581 in the fatigue group, 1520 in the cancer group, and 1544 in the CRF group. The results of binary logistic regression showed that SII was positively correlated with the fatigue group (1.43[1.33, 1.55]), cancer group (1.67 [1.43, 1.95]) and CRF group (1.93 [1.66, 2.25]). Restricted cubic spline analysis revealed a linear relationship between SII and outcomes. The threshold values (k) for each of these groups were identified as 464.78 × 103 cells/μL, 448.97 × 103 cells/μL, and 454.65 × 103 cells/μL, respectively. Stratified analysis indicates that most groups exhibit significant differences. The subgroup analysis indicated that fatigue severity increased with higher SII levels, with the CRF group exhibiting the highest rate of severe fatigue (171% increase).

CONCLUSION

SII is positively correlated with fatigue, cancer, and CRF in a linear way. Higher SII values are associated with greater fatigue, particularly in the CRF population.

Consumer-oriented (patient and family) outcomes from nursing in genomics: a scoping review of the literature (2012-2022)

Introduction

Genomics is a lifespan competency that is important for improving health outcomes for individuals, families, and communities. Nurses play a key role in genomic healthcare and realizing the potential of the genomic era.

Methods

We aimed to chart the current state of genomics in nursing by conducting a systematic scoping review of the literature in four databases (2012-2022). We categorized included articles using the Cochrane Collaboration outcome domains/sub-domains and identify key topical areas.

Results

Of 8532 retrieved articles, we identified 67 articles on 'consumer-oriented outcomes' (patient and family) for analysis. Identified articles primarily centered on themes of genetic testing and screening. Most studies reported non-interventional studies 39/67 (58%) and more than half were from the U.S.A. 34/67 (51%). Six of nine subdomains were reported on. The "patient involvement in care" subdomain was the most commonly reported subdomain (17/67, 25%) while "treatment outcomes" had the fewest reports (5/67, 8%). Overall, consumers (i.e., patients and families) had high satisfaction with nurse-led interventions.

Discussion

Synthesizing findings revealed key knowledge gaps and unmet patient informational needs around genetic testing and decision support. There are opportunities for interprofessional collaboration between nursing and genetic counseling to meet the mounting demand for genomic healthcare and develop more person-centered approaches to genetic counseling and decisional support. Findings support the need for interventional studies and enhanced focus on implementation for nurses to improve consumer-oriented outcomes.

Review of the microbiome and metabolic pathways associated with psychoneurological symptoms in children with cancer

Children with cancer often endure a range of psychoneurological symptoms (PNS), including pain, fatigue, cognitive impairment, anxiety, depressive symptoms, and sleep disturbance. Despite their prevalence, the underlying pathophysiology of PNS remains unclear. Hypotheses suggest an interplay between the gut microbiome and the functional metabolome, given the immune, neurological, and inflammatory influences these processes exert. This mini-review aims to provide a synopsis of the literature that examines the relationship between microbiome-metabolome pathways and PNS in children with cancer, drawing insights from the adult population when applicable. While there is limited microbiome research in the pediatric population, promising results in adult cancer patients include an association between lower microbial diversity and compositional changes, including decreased abundance of the beneficial microbes Fusicatenibacter, Ruminococcus, and Odoribacter, and more PNS. In pediatric patients, associations between peptide, tryptophan, carnitine shuttle, and gut microbial metabolism pathways and PNS outcomes were found. Utilizing multi-omics methods that combine microbiome and metabolome analyses provide insights into the functional capacity of microbiomes and their associated microbial metabolites. In children with cancer receiving chemotherapy, increased abundances of Intestinibacter and Megasphaera correlated with six metabolic pathways, notably carnitine shuttle and tryptophan metabolism. Interventions that target the underlying microbiome-metabolome pathway may be effective in reducing PNS, including the use of pre- and probiotics, fecal microbiome transplantation, dietary modifications, and increased physical activity. Future multi-omics research is needed to corroborate the associations between the microbiome, metabolome, and PNS outcomes in the pediatric oncology population.

Multi-omics analysis of the gut microbiome and metabolites associated with the psychoneurological symptom cluster in children with cancer receiving chemotherapy

BACKGROUND

Children with cancer receiving chemotherapy commonly report a cluster of psychoneurological symptoms (PNS), including pain, fatigue, anxiety, depression, and cognitive dysfunction. The role of the gut microbiome and its functional metabolites in PNS is rarely studied among children with cancer. This study investigated the associations between the gut microbiome-metabolome pathways and PNS in children with cancer across chemotherapy as compared to healthy children.

METHODS

A case-control study was conducted. Cancer cases were recruited from Children's Healthcare of Atlanta and healthy controls were recruited via flyers. Participants reported PNS using the Pediatric Patient-Reported Outcomes Measurement Information System. Data for cases were collected pre-cycle two chemotherapy (T0) and post-chemotherapy (T1), whereas data for healthy controls were collected once. Gut microbiome and its metabolites were measured using fecal specimens. Gut microbiome profiling was performed using 16S rRNA V4 sequencing, and metabolome was performed using an untargeted liquid chromatography-mass spectrometry approach. A multi-omics network integration program analyzed microbiome-metabolome pathways of PNS.

RESULTS

Cases (n = 21) and controls (n = 14) had mean ages of 13.2 and 13.1 years. For cases at T0, PNS were significantly associated with microbial genera (e.g., Ruminococcus, Megasphaera, and Prevotella), which were linked with carnitine shuttle (p = 0.0003), fatty acid metabolism (p = 0.001) and activation (p = 0.001), and tryptophan metabolism (p = 0.008). Megasphaera, clustered with aspartate and asparagine metabolism (p = 0.034), carnitine shuttle (p = 0.002), and tryptophan (p = 0.019), was associated with PNS for cases at T1. Gut bacteria with potential probiotic functions, along with fatty acid metabolism, tryptophan, and carnitine shuttle, were more clustered in cancer cases than the control network and this linkage with PNS needs further studies.

CONCLUSIONS

Using multi-omics approaches, this study indicated specific microbiome-metabolome pathways linked with PNS in children with cancer across chemotherapy. Due to limitations such as antibiotic use in cancer cases, these findings need to be further confirmed in a larger cohort.

Current State of Genomics in Nursing: A Scoping Review of Healthcare Provider Oriented (Clinical and Educational) Outcomes (2012-2022)

In the 20 years since the initial sequencing of the human genome, genomics has become increasingly relevant to nursing. We sought to chart the current state of genomics in nursing by conducting a systematic scoping review of the literature in four databases (2012-2022). The included articles were categorized according to the Cochrane Collaboration outcome domains/sub-domains, and thematic analysis was employed to identify key topical areas to summarize the state of the science. Of 8532 retrieved articles, we identified 232 eligible articles. The articles primarily reported descriptive studies from the United States and other high-income countries (191/232, 82%). More than half (126/232, 54.3%) aligned with the "healthcare provider oriented outcomes" outcome domain. Three times as many articles related to the "knowledge and understanding" sub-domain compared to the "consultation process" subdomain (96 vs. 30). Five key areas of focus were identified, including "nursing practice" (50/126, 40%), "genetic counseling and screening" (29/126, 23%), "specialist nursing" (21/126, 17%), "nurse preparatory education" (17/126, 13%), and "pharmacogenomics" (9/126, 7%). Only 42/126 (33%) articles reported interventional studies. To further integrate genomics into nursing, study findings indicate there is a need to move beyond descriptive work on knowledge and understanding to focus on interventional studies and implementation of genomics into nursing practice.

Mass Sportrometry: An annual look back at applications of mass spectrometry in sport and exercise science

Research in sport and exercise science (SES) is reliant on robust analyses of biomarker measurements to assist with the interpretation of physiological outcomes. Mass spectrometry (MS) is an analytical approach capable of highly sensitive, specific, precise, and accurate analyses of a range of biomolecules, many of which are of interest in SES including, but not limited to, endogenous metabolites, exogenously administered compounds (e.g. supplements), mineral ions, and circulating/tissue proteins. This annual review provides a summary of the applications of MS across studies investigating aspects related to sport or exercise in manuscripts published, or currently in press, in 2022. In total, 93 publications are included and categorized according to their methodologies including targeted analyses, metabolomics, lipidomics, proteomics, and isotope ratio/elemental MS. The advantageous analytical opportunities afforded by MS technologies are discussed across a selection of relevant articles. In addition, considerations for the future of MS in SES, including the need to improve the reporting of assay characteristics and validation data, are discussed, alongside the recommendation for selected current methods to be superseded by MS-based approaches where appropriate. The review identifies that a targeted, mostly quantitative, approach is the most commonly applied MS approach within SES, although there has also been a keen interest in the use of 'omics' to perform hypothesis-generating research studies. Nonetheless, MS is not commonplace in SES at this time, but its use to expand, and possibly improve, the analytical options should be continually considered to exploit the benefits of analytical chemistry in exercise/sports-based research. Overall, it is exciting to see the gradually increasing adoption of MS in SES and it is expected that the number, and quality, of MS-based assays in SES will increase over time, with the potential for 2023 to further establish this technique within the field.