Individual Phenotypes Research Articles

Variability of longitudinal triglyceride phenotype in patients heterozygous for pathogenic APOA5 variants

Biallelic pathogenic variants in APOA5 are an infrequent cause of familial chylomicronemia syndrome characterized by severe, refractory hypertriglyceridemia (HTG), and fasting plasma triglyceride (TG) >10mmol/L (>875mg/dL). The TG phenotype of heterozygous individuals with one copy of a pathogenic APOA5 variant is less familiar. We evaluated the longitudinal TG phenotype of individuals with a single pathogenic APOA5 variant allele. Medically stable outpatients from Ontario, Canada were selected for study based on having: 1) a rare pathogenic APOA5 variant in a single allele; and 2) at least three serial fasting TG measurements obtained over >1.5 years of follow-up. Seven patients were followed for a mean of 5.3±3.7 years. Fasting TG levels varied widely both within and between patients. Three patients displayed at least one normal TG measurement (<2.0mmol/L or <175mg/dL). All patients displayed mild-to-moderate HTG (2 to 9.9mmol/L or 175 to 875mg/dL) at multiple time points. Five patients displayed at least one severe HTG measurement. 10%, 54%, and 36% of all TG measurements were in normal, mild-to-moderate, and severe HTG ranges, respectively. Heterozygosity for pathogenic variants in APOA5 is associated with highly variable TG phenotypes both within and between patients. Heterozygosity confers susceptibility to elevated TG levels, with secondary factors likely modulating the phenotypic severity.

Sex difference contributes to phenotypic diversity in individuals with neurodevelopmental disorders.

Gain a better understanding of sex-specific differences in individuals with global developmental delay (GDD), with a focus on phenotypes and genotypes. Using the Deciphering Developmental Disorders (DDD) dataset, we extracted phenotypic information from 6,588 individuals with GDD and then identified statistically significant variations in phenotypes and genotypes based on sex. We compared genes with pathogenic variants between sex and then performed gene network and molecular function enrichment analysis and gene expression profiling between sex. Finally, we contrasted individuals with autism as an associated condition. We identified significantly differentially expressed phenotypes in males vs. females individuals with GDD. Autism and macrocephaly were significantly more common in males whereas microcephaly and stereotypies were more common in females. Importantly, 66% of GDD genes with pathogenic variants overlapped between both sexes. In the cohort, males presented with only slightly increased X-linked genes (9% vs. 8%, respectively). Individuals from both sexes harbored a similar number of pathogenic variants overall (3) but females presented with a significantly higher load for GDD genes with high intolerance to loss of function. Sex difference in gene expression correlated with genes identified in a sex specific manner. While we identified sex-specific GDD gene mutations, their pathways overlapped. Interestingly, individuals with GDD but also co-morbid autism phenotypes, we observed distinct mutation load, pathways and phenotypic presentation. Our study shows for the first time that males and females with GDD present with significantly different phenotypes. Moreover, while most GDD genes overlapped, some genes were found uniquely in each sex. Surprisingly they shared similar molecular functions. Sorting genes by predicted tolerance to loss of function (pLI) led to identifying an increased mutation load in females with GDD, suggesting potentially a tolerance to GDD genes of higher pLI compared to overall GDD genes. Finally, we show that considering associated conditions (for instance autism) may influence the genomic underpinning found in individuals with GDD and highlight the importance of comprehensive phenotyping.

COMPARISON OF CELL DEATH RATE IN VARIOUS CHICKEN LYMPHOCYTES POPULATIONS IN A RESPONSE TO THREE TEMPERATURE TREATMENTS

The goal of the experiment was to evaluate susceptibility of lymphocytes populations derived from bursa of Fabricius, spleen, thymus, and blood to temperature treatments in vitro. Temperatures used in study was 37 °C (thermoneutral), 41 °C (mild heat stress) and 45 °C (severe heat stress). Cells were incubated for 8 hours and after 3 and 8 hours were measured numbers of apoptotic, necrotic and CellROX positive cells by flow cytometry. Representation of live lymphocyte phenotypes (CD3, CD4, CD8, BU1) in cell populations were also measured. At all temperature treatments, thymus lymphocytes population had the lowest (p &lt; 0.05) percentage of apoptotic cells. On the other hand, significantly highest numbers (p &lt; 0.05) of apoptotic cells were found in bursal lymphocytes after 8 hours of incubation. Differences in numbers of necrotic cells were more pronounced at 45 °C, where after 3 and 8 hours of incubation were significantly highest numbers (p &lt; 0.05) of necrotic cells in spleen. Increasing temperature induce production of reactive oxygen species (ROS) in cells and highest proportion (p &lt; 0.05) of ROS-positive cells were found in bursal and spleen cell population after 8 hours of incubation. Transmission electron microscopy showed loss of mitochondrial matrix and disrupted mitochondrial membrane in mitochondria of lymphocytes at 45 °C as initial damage caused by ROS. From individual cell phenotypes, there were significantly decreased (p &lt; 0.05) B lymphocytes in bursa of Fabricius, CD4+ and CD8+ lymphocytes in thymus and whole T lymphocytes population in spleen at 45 °C. Various susceptibility to temperature can be predictive factor of worse function in some organs in stress conditions where body temperature increase.

Weight Loss and Sleep, Current Evidence in Animal Models and Humans.

Sleep is a vital process essential for survival. The trend of reduction in the time dedicated to sleep has increased in industrialized countries, together with the dramatic increase in the prevalence of obesity and diabetes. Short sleep may increase the risk of obesity, diabetes and cardiovascular disease, and on the other hand, obesity is associated with sleep disorders, such as obstructive apnea disease, insomnia and excessive daytime sleepiness. Sleep and metabolic disorders are linked; therefore, identifying the physiological and molecular pathways involved in sleep regulation and metabolic homeostasis can play a major role in ameliorating the metabolic health of the individual. Approaches aimed at reducing body weight could provide benefits for both cardiometabolic risk and sleep quality, which indirectly, in turn, may determine an amelioration of the cardiometabolic phenotype of individuals. We revised the literature on weight loss and sleep, focusing on the mechanisms and the molecules that may subtend this relationship in humans as in animal models.

Phenotypes of undiagnosed adults with actionable OTC and GLA variants

Inherited metabolic disorders (IMDs) are variably expressive, complicating identification of affected individuals. A genotype-first approach can identify individuals at risk for morbidity and mortality from undiagnosed IMDs and can lead to protocols that improve clinical detection, counseling, and management. Using data from 57,340 participants in two hospital biobanks, we assessed the frequency and phenotypes of individuals with pathogenic/likely pathogenic variants (PLPVs) in two IMD genes: GLA, associated with Fabry disease, and OTC, associated with ornithine transcarbamylase deficiency. Approximately 1 in 19,100 participants harbored an undiagnosed PLPV in GLA or OTC. We identified three individuals (2 male, 1 female) with PLPVs in GLA, all of whom were undiagnosed, and three individuals (3 female) with PLPVs in OTC, two of whom were undiagnosed. All three individuals with PLPVs in GLA (100%) had symptoms suggestive of mild Fabry disease, and one individual (14.2%) had an ischemic stroke at age 33, likely indicating the presence of classic disease. No individuals with PLPVs in OTC had documented hyperammonemia despite exposure to catabolic states, but all (100%) had chronic symptoms suggestive of attenuated disease, including mood disorders and migraines. Our findings suggest that GLA and OTC variants identified via a genotype-first approach are of high penetrance and that population screening of these genes can be used to facilitate stepwise phenotyping and appropriate care.

Epidemiological and clinical profile of amyotrophic lateral sclerosis in Ethiopia: a 5-year multicenter retrospective study

Background Amyotrophic lateral sclerosis (ALS) is a fatal neurodegenerative disease that results in progressive weakness of skeletal muscles including respiratory muscles. Epidemiological and clinical aspects of ALS are derived from a few world regions with very little representation of low- and middle-income countries. We therefore set out to determine the epidemiological and clinical phenotype of individuals with ALS in Ethiopia. Methods Multicenter retrospective analysis was conducted using clinical records from ALS patients seen in Ethiopia at Tikur Anbessa Specialized Hospital and Yehuleshet specialty clinic between January 2016 and August 2021. The data collected included clinical characteristics, disease-related symptoms, a revised ALS functional rating scale, and medications. Results Patients in Ethiopia had a younger age of onset with a mean age of disease onset of 51.9 years. 2.9% of patients had juvenile ALS, and the male-to-female ratio was almost 2:1. 4.9% had a positive family history of the disease. 68% of patients had spinal region involvement at onset, while 32% had bulbar region involvement at onset. Riluzole was used by 31% of ALS patients. 20.6% of patients had some respiratory symptoms, but none received a standard respiratory function assessment. 33.3% of patients were wheelchair-bound. Conclusion In this retrospective study spanning 5 years, we examined the clinical phenotype of ALS in Ethiopian patients. Our findings suggest that most patients had clinically definite ALS with spinal region involvement. Further research, including genetic and epigenetic information, is necessary to understand the early onset of the disease in Ethiopia.

Investigating Adiposity-Related Metabolic Health Phenotypes in Patients with Hidradenitis Suppurativa: A Cross-Sectional Study.

Obesity and hidradenitis suppurativa (HS) are related through meta-inflammation and are both associated with increased cardiometabolic risk. Notwithstanding, cardiometabolic pathology is not uniform in obesity and a subset of individuals with excess adiposity exhibit a healthy metabolic profile. Whilst the incidence of cardiometabolic endpoints and transitions across different adiposity-related body composition phenotypes within several populations and across different ethnicities have been investigated, data regarding metabolic health (MetH) and body composition phenotypes in individuals with HS are lacking. The objective of this study was to evaluate the relationship between different body composition phenotypes in individuals with HS. This was a cross-sectional study of 632 individuals with and without HS from a population with a high prevalence of both obesity and HS. A total of four body composition phenotypes were generated based on BMI and metabolic status (defined using either the metabolic syndrome definition or the homeostasis model of insulin resistance (HOMA-IR)): metabolically healthy overweight/obese (MHOWOB), metabolically unhealthy overweight/obese (MUOWOB), metabolically healthy normal weight (MHNW), and metabolically unhealthy normal weight (MUNW). Generally, subjects with HS exhibited a worse metabolic profile with higher levels of indices of central adiposity measures (including Visceral Adiposity Index and waist circumference), systolic blood pressure and markers of insulin resistance, as well as a higher prevalence of the metabolic syndrome. Moreover, when sub-stratified into the different body composition phenotypes, individuals with HS typically also demonstrated adverse metabolic characteristics relative to controls matched for both adiposity and metabolic health, particularly in the normal weight category and despite being classified as metabolically healthy. Being metabolically unhealthy in addition to being overweight/obese increases an individual's risk of HS. Metabolic risk-assessment should be prioritized in the clinical management of individuals with HS even in those who are lean. Patients attending HS clinics provide a valuable opportunity for targeted cardiovascular risk reduction with respect to the management of both obesity and metabolic health.

Internal Consistency of the Serbian Translation of the Stanford Social Dimensions Scale and Association to Strengths and Difficulties Questionnaire Scores in Male and Female Individuals on the Autism Spectrum and Non-autistic Individuals.

We aimed to evaluate the internal consistency of Stanford Social Dimensions Scale (SSDS) translated to Serbian and to test it against the Strengths and Difficulties Questionnaire (SDQ). The sample consisted of 200 patients (32% ASD) of the Institute of Mental Health in Belgrade, Serbia (68 females, 132 males, Mage=9.61, SDage=4.06). Internal consistency coefficients were within good/acceptable range for Social Motivation, Affiliation, Recognition and Unusual Approach subscales and below acceptable for Expressive Social Communication subscale. The non-autistic group scored higher on all subscales compared to the ASD group. All SSDS subscales positively correlated with SDQ Prosocial Behaviors scale. The SSDS is a valuable instrument for accessing sociobehavioral phenotype in both individuals on the autism spectrum and non-autistic individuals.

The STROMICS genome study: deep whole-genome sequencing and analysis of 10K Chinese patients with ischemic stroke reveal complex genetic and phenotypic interplay

Ischemic stroke is a leading cause of global mortality and long-term disability. However, there is a paucity of whole-genome sequencing studies on ischemic stroke, resulting in limited knowledge of the interplay between genomic and phenotypic variations among affected patients. Here, we outline the STROMICS design and present the first whole-genome analysis on ischemic stroke by deeply sequencing and analyzing 10,241 stroke patients from China. We identified 135.59 million variants, > 42% of which were novel. Notable disparities in allele frequency were observed between Chinese and other populations for 89 variants associated with stroke risk and 10 variants linked to response to stroke medications. We investigated the population structure of the participants, generating a map of genetic selection consisting of 31 adaptive signals. The adaption of the MTHFR rs1801133-G allele, which links to genetically evaluated VB9 (folate acid) in southern Chinese patients, suggests a gene-specific folate supplement strategy. Through genome-wide association analysis of 18 stroke-related traits, we discovered 10 novel genetic-phenotypic associations and extensive cross-trait pleiotropy at 6 lipid-trait loci of therapeutic relevance. Additionally, we found that the set of loss-of-function and cysteine-altering variants present in the causal gene NOTCH3 for the autosomal dominant stroke disorder CADASIL displayed a broad neuro-imaging spectrum. These findings deepen our understanding of the relationship between the population and individual genetic layout and clinical phenotype among stroke patients, and provide a foundation for future efforts to utilize human genetic knowledge to investigate mechanisms underlying ischemic stroke outcomes, discover novel therapeutic targets, and advance precision medicine.

Identification of transcriptional programs using dense vector representations defined by mutual information with GeneVector

Deciphering individual cell phenotypes from cell-specific transcriptional processes requires high dimensional single cell RNA sequencing. However, current dimensionality reduction methods aggregate sparse gene information across cells, without directly measuring the relationships that exist between genes. By performing dimensionality reduction with respect to gene co-expression, low-dimensional features can model these gene-specific relationships and leverage shared signal to overcome sparsity. We describe GeneVector, a scalable framework for dimensionality reduction implemented as a vector space model using mutual information between gene expression. Unlike other methods, including principal component analysis and variational autoencoders, GeneVector uses latent space arithmetic in a lower dimensional gene embedding to identify transcriptional programs and classify cell types. In this work, we show in four single cell RNA-seq datasets that GeneVector was able to capture phenotype-specific pathways, perform batch effect correction, interactively annotate cell types, and identify pathway variation with treatment over time.

Profiling Immunological Phenotypes in Individuals During the First Year After Traumatic Spinal Cord Injury: A Longitudinal Analysis.

Abstract Individuals with SCI are severely affected by immune system changes, resulting in increased risk of infections and persistent systemic inflammation. While recent data support that immunological changes after SCI differ in the acute and chronic phases of living with SCI, only limited immunological phenotyping in humans is available. To characterize dynamic molecular and cellular immune phenotypes over the first year, we assess RNA (bulk-RNA sequencing), protein, and flow cytometry (FACS) profiles of blood samples from 12 individuals with SCI at 0-3 days and at 3, 6, and 12 months post injury (MPI) compared to 23 uninjured individuals (controls). We identified 967 differentially expressed (DE) genes in individuals with SCI (FDR <0.001) compared to controls. Within the first 6 MPI we detected a reduced expression of NK cell genes, consistent with reduced frequencies of CD56bright, CD56dim NK cells present at 12 MPI. Over 6MPI, we observed increased and prolonged expression of genes associated with inflammation (e.g. HMGB1, Toll-like receptor signaling) and expanded frequencies of monocytes acutely. Canonical T-cell related DE genes (e.g. FOXP3, TCF7, CD4) were upregulated during the first 6 MPI and increased frequencies of activated T cells at 3-12 MPI. Neurological injury severity was reflected in distinct whole blood gene expression profiles at any time after SCI, verifying a persistent 'neurogenic' imprint. Overall, 2876 DE genes emerge when comparing motor complete to motor incomplete SCI (ANOVA, FDR <0.05), including those related to neutrophils, inflammation, and infection. In summary, we identify a dynamic immunological phenotype in humans, including molecular and cellular changes which may provide potential targets to reduce inflammation, improve immunity, or serve as candidate biomarkers of injury severity.

Monocyte phenotype and extracellular vesicles in HIV-1, HIV-2, and HIV-1/2 dual infection.

AIDS-defining illness develops at higher CD4 + T-cell counts in individuals infected with HIV-2 compared with HIV-1-infected, which suggests that the two types of HIV may have different effects on other compartments of the immune system. We here investigate monocyte phenotype, activation and macrophage-derived extracellular vesicles in individuals with different HIV types. Cross-sectional. ART-naive HIV-1 ( n = 83), HIV-2 ( n = 63), and HIV-1/2 dually positive ( n = 27) participants were recruited in Bissau, Guinea-Bissau, together with HIV-negative controls ( n = 26). Peripheral blood mononuclear cells (PBMCs) were isolated and analyzed by flow cytometry for monocyte phenotype and activation, and plasma was analyzed for extracellular vesicle forms of CD163 and CD206. Compared with HIV-negative controls, all groups of HIV-positive participants had a skewed monocyte phenotype with a higher proportion of intermediate monocytes, increased CD163 expression and elevated serum levels of the inflammatory biomarkers soluble (s)CD163 and sCD206. HIV-2-positive participants had lower CD163 monocyte expression than HIV-1-positive participants, regardless of HIV RNA or CD4 + cell count. Levels of sCD206 extracellular vesicles were increased in all HIV groups, and higher in HIV-1 compared with HIV-2-positive participants. The monocyte phenotype of HIV-2-positive participants deviated less from healthy controls than did HIV-1 participants. HIV-2-positive participants also had a lower concentration of extracellular CD206 vesicles compared with HIV-1-positive participants. This does not explain the difference in AIDS development.

Inferring sparse structure in genotype-phenotype maps.

Correlation among multiple phenotypes across related individuals may reflect some pattern of shared genetic architecture: individual genetic loci affect multiple phenotypes (an effect known as pleiotropy), creating observable relationships between phenotypes. A natural hypothesis is that pleiotropic effects reflect a relatively small set of common "core" cellular processes: each genetic locus affects one or a few core processes, and these core processes in turn determine the observed phenotypes. Here, we propose a method to infer such structure in genotype-phenotype data. Our approach, sparse structure discovery (SSD) is based on a penalized matrix decomposition designed to identify latent structure that is low-dimensional (many fewer core processes than phenotypes and genetic loci), locus-sparse (each locus affects few core processes), and/or phenotype-sparse (each phenotype is influenced by few core processes). Our use of sparsity as a guide in the matrix decomposition is motivated by the results of a novel empirical test indicating evidence of sparse structure in several recent genotype-phenotype datasets. First, we use synthetic data to show that our SSD approach can accurately recover core processes if each genetic locus affects few core processes or if each phenotype is affected by few core processes. Next, we apply the method to three datasets spanning adaptive mutations in yeast, genotoxin robustness assay in human cell lines, and genetic loci identified from a yeast cross, and evaluate the biological plausibility of the core process identified. More generally, we propose sparsity as a guiding prior for resolving latent structure in empirical genotype-phenotype maps.

"Mens Sana in Cute Sana"-A State of the Art of Mutual Etiopathogenetic Influence and Relevant Pathophysiological Pathways between Skin and Mental Disorders: An Integrated Approach to Contemporary Psychopathological Scenarios.

The negative socioeconomic impact of mental health disorders and skin diseases has increased in part due to the conflict between Russia and Ukraine, which has been a fertile ground for the emergence of psychopathologies. It is firmly established that there is a direct thread of etiopathogenetic communication between skin diseases and neuropsychiatric disorders, and the literature has tried to reveal the pathophysiological mechanisms governing such bidirectionality. This paper discusses this complex network of molecular pathways that are targeted by conventional and biological pharmacological agents that appear to impact two pathological spheres that previously seemed to have little connection. This molecular discussion is supplemented with a literature review, from a clinical viewpoint, regarding skin-brain etiopathogenetic bidirectionality. We focus on post-traumatic stress disorder (PTSD), which can be considered for all intents and purposes a systemic inflammatory disease that also affects the skin. A brief overview is also provided on the diagnostic-therapeutic and follow-up potential of oxidative and inflammatory markers potentially involved in the pathophysiological mechanisms treated. The aim is to clarify how these mechanisms may be useful in defining different stress-coping strategies and thus individual phenotypes of stress sensitivity/resistance in order to promote personalized medicine in the field of psychodermatology.

Long-term effects of incubation temperature on growth and thermal physiology in a small ectotherm.

Thermal conditions in the developmental environment can substantially affect an individual's phenotype, particularly in egg-laying ectotherms. However, whether these effects persist into adulthood is rarely examined. To investigate this, we incubated delicate skink, Lampropholis delicata, eggs at either cool (22°C), mild (26°C) or hot (30°C) temperatures. After hatching, we measured growth, thermal performance curves of locomotor activity, and thermal sensitivity of resting metabolic rate of offspring as juveniles (4-6 weeks of age), sub-adults (approx. 200 days of age), and adults (approx. 2 years of age), and then measured developmental temperature impacts on male fertility. Incubation temperature had a lasting effect on growth and locomotor performance, with cool and hot incubation temperatures resulting in faster growth and larger maximum size, and hot incubation temperatures reducing locomotor performance at all timepoints. Effects on resting metabolic rate were only present in sub-adults, with a higher metabolic rate at high and average body mass and negative metabolic scaling exponent in cool-incubated lizards. Additionally, cool and hot incubation treatments resulted in shorter sperm midpieces and heads. Incubation temperature did not affect testis mass or sperm count. Overall, our results demonstrate that incubation temperature can have lasting effects on later life stages, highlighting the importance of maternal nest-site selection, but that some effects are age dependent. This article is part of the theme issue 'The evolutionary ecology of nests: a cross-taxon approach'.

Novel approaches to characterize individual drug metabolism and advance precision medicine.

Interindividual variability in drug metabolism can significantly affect drug concentrations in the body and subsequent drug response. Understanding an individual's drug metabolism capacity is important for predicting drug exposure and developing precision medicine strategies. The goal of precision medicine is to individualize drug treatment for patients to maximize efficacy and minimize drug toxicity. While advances in pharmacogenomics have improved our understanding of how genetic variations in drug-metabolizing enzymes (DMEs) affect drug response, non-genetic factors are also known to influence drug metabolism phenotypes. This minireview will discuss approaches beyond pharmacogenetic testing to phenotype DMEs- particularly the cytochrome P450 enzymes- in clinical settings. Several phenotyping approaches have been proposed: traditional approaches include phenotyping with exogenous probe substrates and the use of endogenous biomarkers; newer approaches include evaluating circulating non-coding RNAs (ncRNAs) and liquid biopsy-derived markers relevant to DME expression and function. The goals of this minireview are to: 1) provide a high-level overview of traditional and novel approaches to phenotype individual drug metabolism capacity; 2) describe how these approaches are being applied or can be applied to pharmacokinetic studies; and 3) discuss perspectives on future opportunities to advance precision medicine in diverse populations. Significance Statement This minireview provides an overview of recent advances in approaches to characterize individual drug metabolism phenotypes in clinical settings. Herein, we highlight the integration of existing pharmacokinetic biomarkers with novel approaches; also discussed are current challenges and existing knowledge gaps. The article concludes with perspectives on the future deployment of a liquid biopsy-informed physiologically based pharmacokinetic (PBPK) strategy for patient characterization and precision dosing.

Connectomic insight into unique stroke patient recovery after rTMS treatment.

An improved understanding of the neuroplastic potential of the brain has allowed advancements in neuromodulatory treatments for acute stroke patients. However, there remains a poor understanding of individual differences in treatment-induced recovery. Individualized information on connectivity disturbances may help predict differences in treatment response and recovery phenotypes. We studied the medical data of 22 ischemic stroke patients who received MRI scans and started repetitive transcranial magnetic stimulation (rTMS) treatment on the same day. The functional and motor outcomes were assessed at admission day, 1 day after treatment, 30 days after treatment, and 90 days after treatment using four validated standardized stroke outcome scales. Each patient underwent detailed baseline connectivity analyses to identify structural and functional connectivity disturbances. An unsupervised machine learning (ML) agglomerative hierarchical clustering method was utilized to group patients according to outcomes at four-time points to identify individual phenotypes in recovery trajectory. Differences in connectivity features were examined between individual clusters. Patients were a median age of 64, 50% female, and had a median hospital length of stay of 9.5 days. A significant improvement between all time points was demonstrated post treatment in three of four validated stroke scales utilized. ML-based analyses identified distinct clusters representing unique patient trajectories for each scale. Quantitative differences were found to exist in structural and functional connectivity analyses of the motor network and subcortical structures between individual clusters which could explain these unique trajectories on the Barthel Index (BI) scale but not on other stroke scales. This study demonstrates for the first time the feasibility of using individualized connectivity analyses in differentiating unique phenotypes in rTMS treatment responses and recovery. This personalized connectomic approach may be utilized in the future to better understand patient recovery trajectories with neuromodulatory treatment.

Recent advances in understanding brain cancer metabolomics: a review.

Regardless of the significant progress made in surgical techniques and adjuvant therapies, brain tumors are a major contributor to cancer-related morbidity and mortality in both pediatric and adult populations. Gliomas represent a significant proportion of cerebral neoplasms, exhibiting diverse levels of malignancy. The etiology and mechanisms of resistance of this malignancy are inadequately comprehended, and the optimization of patient diagnosis and prognosis is a challenge due to the diversity of the disease and the restricted availability of therapeutic options. Metabolomics refers to the comprehensive analysis of endogenous and exogenous small molecules, both in a targeted and untargeted manner, that enables the characterization of an individual's phenotype and offers valuable insights into cellular activity, particularly in the context of cancer biology, including brain tumor biology. Metabolomics has garnered attention in current years due to its potential to facilitate comprehension of the dynamic spatiotemporal regulatory network of enzymes and metabolites that enables cancer cells to adapt to their environment and foster the development of tumors. Metabolic changes are widely acknowledged as a significant characteristic for tracking the advancement of diseases, treatment efficacy, and identifying novel molecular targets for successful medical management. Metabolomics has emerged as an exciting area for personalized medicine and drug discovery, utilizing advanced analytical techniques such as nuclear magnetic resonance spectroscopy (MRS) and mass spectrometry (MS) to achieve high-throughput analysis. This review examines and highlights the latest developments in MRS, MS, and other technologies in studying human brain tumor metabolomics.

CYP3A genetic variation and taxane-induced peripheral neuropathy: a systematic review, meta-analysis, and candidate gene study.

Background: Taxane-induced peripheral neuropathy (TIPN) is an important cause of premature treatment cessation and dose-limitation in cancer therapy. It also reduces quality of life and survivorship in affected patients. Genetic polymorphisms in the CYP3A family have been investigated but the findings have been inconsistent and contradictory. Methods: A systematic review identified 12 pharmacogenetic studies investigating genetic variation in CYP3A4*22 and CYP3A5*3 and TIPN. In our candidate gene study, 288 eligible participants (211 taxane participants receiving docetaxel or paclitaxel, and 77 control participants receiving oxaliplatin) were successfully genotyped for CYP3A4*22 and CYP3A5*3. Genotyping data was transformed into a combined CYP3A metaboliser phenotype: Poor metabolisers, intermediate metabolisers and extensive metabolisers. Individual genotypes and combined CYP3A metaboliser phenotypes were assessed in relation to neurotoxicity, including by meta-analysis where possible. Results: In the systematic review, no significant association was found between CYP3A5*3 and TIPN in seven studies, with one study reporting a protective association. For CYP3A4*22, one study has reported an association with TIPN, while four other studies failed to show an association. Evaluation of our patient cohort showed that paclitaxel was found to be more neurotoxic than docetaxel (p < 0.001). Diabetes was also significantly associated with the development of TIPN. The candidate gene analysis showed no significant association between either SNP (CYP3A5*3 and CYP3A4*22) and the development of TIPN overall, or severe TIPN. Meta-analysis showed no association between these two variants and TIPN. Transformed into combined CYP3A metaboliser phenotypes, 30 taxane recipients were poor metabolisers, 159 were intermediate metabolisers, and 22 were extensive metabolisers. No significant association was observed between metaboliser status and case-control status. Summary: We have shown that the risk of peripheral neuropathy during taxane chemotherapy is greater in patients who have diabetes. CYP3A genotype or phenotype was not identified as a risk factor in either the candidate gene analysis or the systematic review/meta-analysis, although we cannot exclude the possibility of a minor contribution, which would require a larger sample size.

The mitochondrial genome as a modifier of autism versus cancer phenotypes in PTEN hamartoma tumor syndrome.

Cancer and autism spectrum disorder/developmental delay (ASD/DD) are two common clinical phenotypes in individuals with germline PTEN variants (PTEN hamartoma tumor syndrome, PHTS). Burgeoning studies have shown that genomic and metabolomic factors may act as modifiers of ASD/DD versus cancer in PHTS. Recently, we showed copy number variations to be associated with ASD/DD versus cancer in these PHTS individuals. We also found that mitochondrial complex II variants occurring in 10% of PHTS individuals modify breast cancer risk and thyroid cancer histology. These studies suggest that mitochondrial pathways could act as important factors in PHTS phenotype development. However, the mitochondrial genome (mtDNA) has never been systematically studied in PHTS. We therefore investigated the mtDNA landscape extracted from whole-genome sequencing data from 498 PHTS individuals, including 164 with ASD/DD (PHTS-onlyASD/DD), 184 with cancer (PHTS-onlyCancer), 132 with neither ASD/DD nor cancer (PHTS-neither), and 18 with both ASD/DD and cancer (PHTS-ASDCancer). We demonstrate that PHTS-onlyASD/DD has significantly higher mtDNA copy number than PHTS-onlyCancer group (p= 9.2×10-3 in all samples; p= 4.2×10-3 in the H haplogroup). PHTS-neither group has significantly higher mtDNA variant burden than PHTS-ASDCancer group (p= 4.6×10-2); the PHTS-noCancer group (PHTS-onlyASD/DD and PHTS-neither groups) also shows higher variant burden than the PHTS-Cancer group (PHTS-onlyCancer and PHTS-ASD/Cancer groups; p=3.3×10-2). Our study implicates the mtDNA as a modifier of ASD/DD versus cancer phenotype development in PHTS.