ABSTRACT
Introduction: Tobacco smoking is the leading preventable cause of death, causing more than six million deaths annually worldwide, mainly due to cardiovascular disease and cancer. Many habitual smokers try to stop smoking but only about 7% are successful, despite widespread knowledge of the risks. Development of addiction to a range of substances is associated with progressive blunting of brain reward responses and sensitisation of stress responses, as described by the allostasis theory of addiction. There is pre-clinical evidence from rodents for a dramatic decrease in brain reward function during nicotine withdrawal. Methods: Here we tested the hypothesis that habitual smokers would also exhibit blunted reward function during nicotine withdrawal using a decision-making task and fMRI. Results: Our findings supported this hypothesis, with midbrain reward-related responses particularly blunted. We also tested the hypothesis that smokers with a longer duration of smoking would have more pronounced abnormalities. Contrary to expectations, we found that a shorter duration of smoking in younger smokers was associated with the most marked abnormalities, with blunted midbrain reward related activation including the dopaminergic ventral tegmental area. Discussion: Given the substantial mortality associated with smoking, and the small percent of people who manage to achieve sustained abstinence, further translational studies on nicotine addiction mechanisms are indicated.
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To create a radiogenomics map and evaluate the correlation between molecular and imaging phenotypes in localized prostate cancer (PCa), using radical prostatectomy histopathology as a reference standard. Radiomic features were extracted from T2-weighted (T2WI) and Apparent Diffusion Coefficient (ADC) images of clinically localized PCa patients (n = 15) across different Gleason score-based risk categories. DNA extraction was performed on formalin-fixed, paraffin-embedded (FFPE) samples. Gene expression analysis of androgen receptor expression, apoptosis, and hypoxia was conducted using the Chromosome Analysis Suite (ChAS) application and OSCHIP files. The relationship between gene expression alterations and textural features was assessed using Pearson's correlation analysis. Receiver operating characteristic (ROC) analysis was utilized to evaluate the predictive accuracy of the model. A significant correlation was observed between radiomic texture features and copy number variation (CNV) of genes associated with apoptosis, hypoxia, and androgen receptor (p-value ≤ 0.05). The identified radiomic features, including Sum Entropy ADC, Inverse Difference ADC, Sum Variance T2WI, Entropy T2WI, Difference Variance T2WI, and Angular Secondary Moment T2WI, exhibited potential for predicting cancer grade and biological processes such as apoptosis and hypoxia. Incorporating radiomics and genomics into a prediction model significantly improved the prediction of prostate cancer grade (clinically significant prostate cancer), yielding an AUC of 0.95. Radiomic texture features significantly correlate with genotypes for apoptosis, hypoxia, and androgen receptor expression in localised prostate cancer. Integration of these into the prediction model improved prediction accuracy of clinically significant prostate cancer.
Subject(s)
Prostatic Neoplasms , Male , Humans , Prostatic Neoplasms/genetics , Prostatic Neoplasms/pathology , Prostatic Neoplasms/diagnostic imaging , Middle Aged , Aged , Receptors, Androgen/genetics , Neoplasm Grading , Magnetic Resonance Imaging/methods , Biopsy , Phenotype , ROC Curve , DNA Copy Number Variations/geneticsABSTRACT
BACKGROUND: Renal cancers are among the top ten causes of cancer-specific mortality, of which the ccRCC subtype is responsible for most cases. The grading of ccRCC is important in determining tumour aggressiveness and clinical management. OBJECTIVES: The objectives of this research were to predict the WHO/ISUP grade of ccRCC pre-operatively and characterise the heterogeneity of tumour sub-regions using radiomics and ML models, including comparison with pre-operative biopsy-determined grading in a sub-group. METHODS: Data were obtained from multiple institutions across two countries, including 391 patients with pathologically proven ccRCC. For analysis, the data were separated into four cohorts. Cohorts 1 and 2 included data from the respective institutions from the two countries, cohort 3 was the combined data from both cohort 1 and 2, and cohort 4 was a subset of cohort 1, for which both the biopsy and subsequent histology from resection (partial or total nephrectomy) were available. 3D image segmentation was carried out to derive a voxel of interest (VOI) mask. Radiomics features were then extracted from the contrast-enhanced images, and the data were normalised. The Pearson correlation coefficient and the XGBoost model were used to reduce the dimensionality of the features. Thereafter, 11 ML algorithms were implemented for the purpose of predicting the ccRCC grade and characterising the heterogeneity of sub-regions in the tumours. RESULTS: For cohort 1, the 50% tumour core and 25% tumour periphery exhibited the best performance, with an average AUC of 77.9% and 78.6%, respectively. The 50% tumour core presented the highest performance in cohorts 2 and 3, with average AUC values of 87.6% and 76.9%, respectively. With the 25% periphery, cohort 4 showed AUC values of 95.0% and 80.0% for grade prediction when using internal and external validation, respectively, while biopsy histology had an AUC of 31.0% for the classification with the final grade of resection histology as a reference standard. The CatBoost classifier was the best for each of the four cohorts with an average AUC of 80.0%, 86.5%, 77.0% and 90.3% for cohorts 1, 2, 3 and 4 respectively. CONCLUSIONS: Radiomics signatures combined with ML have the potential to predict the WHO/ISUP grade of ccRCC with superior performance, when compared to pre-operative biopsy. Moreover, tumour sub-regions contain useful information that should be analysed independently when determining the tumour grade. Therefore, it is possible to distinguish the grade of ccRCC pre-operatively to improve patient care and management.
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Apathy is a common and disabling complication of Parkinson's disease characterized by reduced goal-directed behaviour. Several studies have reported dysfunction within prefrontal cortical regions and projections from brainstem nuclei whose neuromodulators include dopamine, serotonin and noradrenaline. Work in animal and human neuroscience have confirmed contributions of these neuromodulators on aspects of motivated decision-making. Specifically, these neuromodulators have overlapping contributions to encoding the value of decisions, and influence whether to explore alternative courses of action or persist in an existing strategy to achieve a rewarding goal. Building upon this work, we hypothesized that apathy in Parkinson's disease should be associated with an impairment in value-based learning. Using a four-armed restless bandit reinforcement learning task, we studied decision-making in 75 volunteers; 53 patients with Parkinson's disease, with and without clinical apathy, and 22 age-matched healthy control subjects. Patients with apathy exhibited impaired ability to choose the highest value bandit. Task performance predicted an individual patient's apathy severity measured using the Lille Apathy Rating Scale (R = -0.46, P < 0.001). Computational modelling of the patient's choices confirmed the apathy group made decisions that were indifferent to the learnt value of the options, consistent with previous reports of reward insensitivity. Further analysis demonstrated a shift away from exploiting the highest value option and a reduction in perseveration, which also correlated with apathy scores (R = -0.5, P < 0.001). We went on to acquire functional MRI in 59 volunteers; a group of 19 patients with and 20 without apathy and 20 age-matched controls performing the Restless Bandit Task. Analysis of the functional MRI signal at the point of reward feedback confirmed diminished signal within ventromedial prefrontal cortex in Parkinson's disease, which was more marked in apathy, but not predictive of their individual apathy severity. Using a model-based categorization of choice type, decisions to explore lower value bandits in the apathy group activated prefrontal cortex to a similar degree to the age-matched controls. In contrast, Parkinson's patients without apathy demonstrated significantly increased activation across a distributed thalamo-cortical network. Enhanced activity in the thalamus predicted individual apathy severity across both patient groups and exhibited functional connectivity with dorsal anterior cingulate cortex and anterior insula. Given that task performance in patients without apathy was no different to the age-matched control subjects, we interpret the recruitment of this network as a possible compensatory mechanism, which compensates against symptomatic manifestation of apathy in Parkinson's disease.
Subject(s)
Apathy , Parkinson Disease , Humans , Parkinson Disease/complications , Parkinson Disease/diagnostic imaging , Apathy/physiology , Dopamine , Motivation , Neurotransmitter AgentsABSTRACT
BACKGROUND: Multiple brain imaging studies of negative emotional bias in major depressive disorder (MDD) have used images of fearful facial expressions and focused on the amygdala and the prefrontal cortex. The results have, however, been inconsistent, potentially due to small sample sizes (typically N<50). It remains unclear if any alterations are a characteristic of current depression or of past experience of depression, and whether there are MDD-related changes in effective connectivity between the two brain regions. METHODS: Activations and effective connectivity between the amygdala and dorsolateral prefrontal cortex (DLPFC) in response to fearful face stimuli were studied in a large population-based sample from Generation Scotland. Participants either had no history of MDD (N=664 in activation analyses, N=474 in connectivity analyses) or had a diagnosis of MDD during their lifetime (LMDD, N=290 in activation analyses, N=214 in connectivity analyses). The within-scanner task involved implicit facial emotion processing of neutral and fearful faces. RESULTS: Compared to controls, LMDD was associated with increased activations in left amygdala (PFWE=0.031,kE=4) and left DLPFC (PFWE=0.002,kE=33), increased mean bilateral amygdala activation (ß=0.0715,P=0.0314), and increased inhibition from left amygdala to left DLPFC, all in response to fearful faces contrasted to baseline. Results did not appear to be attributable to depressive illness severity or antidepressant medication status at scan time. LIMITATIONS: Most studied participants had past rather than current depression, average severity of ongoing depression symptoms was low, and a substantial proportion of participants were receiving medication. The study was not longitudinal and the participants were only assessed a single time. CONCLUSIONS: LMDD is associated with hyperactivity of the amygdala and DLPFC, and with stronger amygdala to DLPFC inhibitory connectivity, all in response to fearful faces, unrelated to depression severity at scan time. These results help reduce inconsistency in past literature and suggest disruption of 'bottom-up' limbic-prefrontal effective connectivity in depression.
Subject(s)
Depressive Disorder, Major , Humans , Depressive Disorder, Major/diagnostic imaging , Depression , Fear/physiology , Emotions/physiology , Prefrontal Cortex/diagnostic imaging , Brain Mapping , Magnetic Resonance Imaging/methods , Facial ExpressionABSTRACT
Motivational (i.e., Pavlovian) values interfere with instrumental responding and can lead to suboptimal decision-making. In humans, task-based neuroimaging studies have only recently started illuminating the functional neuroanatomy of Pavlovian biasing of instrumental control. To provide a mechanistic understanding of the neural dynamics underlying the Pavlovian and instrumental valuation systems, analysis of neuroimaging data has been informed by computational modeling of conditioned behavior. Nonetheless, because of collinearities in Pavlovian and instrumental predictions, previous research failed to tease out hemodynamic activity that is parametrically and dynamically modulated by coexistent Pavlovian and instrumental value expectations. Moreover, neural correlates of Pavlovian to instrumental transfer effects have so far only been identified in extinction (i.e., in the absence of learning). In this study, we devised a modified version of the orthogonalized go/no-go paradigm, which introduced Pavlovian-only catch trials to better disambiguate trial-by-trial Pavlovian and instrumental predictions in both sexes. We found that hemodynamic activity in the ventromedial pFC covaried uniquely with the model-derived Pavlovian value expectations. Notably, modulation of neural activity encoding for instrumental predictions in the supplementary motor cortex was linked to successful action selection in conflict conditions. Furthermore, hemodynamic activity in regions pertaining to the limbic system and medial pFC was correlated with synergistic Pavlovian and instrumental predictions and improved conditioned behavior during congruent trials. Altogether, our results provide new insights into the functional neuroanatomy of decision-making and corroborate the validity of our variant of the orthogonalized go/no-go task as a behavioral assay of the Pavlovian and instrumental valuation systems.
Subject(s)
Conditioning, Classical , Learning , Male , Female , Humans , Motivation , Magnetic Resonance Imaging , Conditioning, OperantABSTRACT
BACKGROUND: Individuals with non-small cell lung cancer (NSCLC) are burdened by long-lasting symptoms (e.g., dyspnea and fatigue) post-treatment. These symptoms often reduce physical activity levels and increase the risk of functional decline. Though we have previously proposed cluster-set resistance training to mitigate symptom burden in lung cancer, there is currently no data on the feasibility or acceptability of this mode of exercise in cancer. Therefore, the purpose of this study was to investigate the feasibility and acceptability of a hybrid-delivery home-based cluster-set resistance training program in individuals with NSCLC stages I-III (i.e., early stage). METHODS: This study aimed to recruit individuals with NSCLC stages I-III post-treatment to participate in 8 weeks of home-based resistance training, 3 days per week. The program included supervised sessions in the participants' homes and virtual supervision via videoconferencing. The primary outcome measure of feasibility was evaluated through recruitment, retention, and intervention fidelity (i.e., proportion of exercise completed, relative to what was prescribed). Intervention acceptability (i.e., ease and quality of virtual delivery, level of difficulty, and home-based approach) was assessed using a 4-point Likert-type scale from "strongly disagree" to "strongly agree". RESULTS: Fourteen participants were recruited over a 6-month period, with 11 completing the intervention (2 withdrew due to unrelated illness, 1 withdrew due to requiring active treatment), yielding a retention rate of 79%. Characteristics of the participants who completed the intervention (n = 11) were as follows: mean age: 71 ± 10 years, mean BMI: 29.1 ± 6.5, and average time since diagnosis was 62 ± 51 months. Of completers, 27% were male, and 36% were Black; 10 were stage I (91%), and one was stage II (9%). Mean session attendance was 86.4 ± 9.5%. Mean intervention fidelity was 83.1 ± 13.1%. With regard to acceptability, > 90% of participants positively rated all aspects of the intervention delivery. No adverse events related to exercise were recorded. CONCLUSIONS: The hybrid delivery of a home-based resistance exercise program for individuals previously treated for early-stage NSCLC was found to be safe and feasible. Adaptations to the program for future interventions are required, particularly surrounding resistance exercise programming, and intervention delivery with home visits. TRIAL REGISTRATION: ClinicalTrials.gov: NCT05014035 . Registered January 20, 2021.
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BACKGROUND: Multiple reports have described myopericarditis following mRNA COVID-19 vaccination. However, data on the persistence of subclinical myocardial injury assessed by left ventricular (LV) longitudinal strain (LVLS) is limited. OBJECTIVES: Our aim was to assess LV function longitudinally in our cohort of COVID-19 vaccine-related myopericarditis using ejection fraction (EF), fractional shortening (FS), LVLS, and diastolic parameters. METHODS: Retrospective, single-center review of demographic, laboratory, and management data was performed on 20 patients meeting diagnostic criteria for myopericarditis after mRNA COVID-19 vaccination. Echocardiographic images were obtained on initial presentation (time 0), at a median of 12 days (7.5, 18.5; time 1), and at a median of 44 days (29.5, 83.5; time 2). FS was calculated by M-mode, EF by 5/6 area-length methods, LVLS by utilization of TOMTEC software, and diastolic function by tissue Doppler. All parameters were compared across pairs of these time points using Wilcoxon signed-rank test. RESULTS: Our cohort consisted predominantly of adolescent males (85%) with mild presentation of myopericarditis. The median EF was 61.6% (54.6, 68.0), 63.8% (60.7, 68.3), 61.4% (60.1, 64.6) at times 0, 1, and 2, respectively. Upon initial presentation, 47% of our cohort had LVLS < -18%. The median LVLS was -18.6% (-16.9, -21.0) at time 0, -21.2% at time 1 (-19.4, -23.5) (p = 0.004) and -20.8% (-18.7, -21.7) at time 2 (p = 0.004, as compared to time 0). CONCLUSIONS: Though many of our patients had abnormal strain during acute illness, LVLS improved longitudinally, indicating myocardial recovery. LVLS can be used as marker of subclinical myocardial injury and risk stratification in this population.
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BACKGROUND: Adverse childhood experiences have been linked to increased multimorbidity, with physical and mental health consequences throughout life. Chronic pain is often associated with mood disorders, such as major depressive disorder (MDD); both have been linked to adverse childhood experiences. It is unclear how the effect of adverse childhood experiences on neural processing impacts on vulnerability to chronic pain, MDD, or both, and whether there are shared mechanisms. We aimed to assess evidence for central neural changes associated with adverse childhood experiences in subjects with chronic pain, MDD, or both using systematic review and meta-analysis. METHODS: Electronic databases were systematically searched for neuroimaging studies of adverse childhood experiences, with chronic pain, MDD, or both. Two independent reviewers screened title, abstracts, and full text, and assessed quality. After extraction of neuroimaging data, activation likelihood estimate meta-analysis was performed to identify significant brain regions associated with these comorbidities. RESULTS: Forty-nine of 2414 studies were eligible, of which 43 investigated adverse childhood experiences and MDD and six investigated adverse childhood experiences and chronic pain. None investigated adverse childhood experiences, chronic pain, and MDD together. Functional and structural brain abnormalities were identified in the superior frontal, lingual gyrus, hippocampus, insula, putamen, superior temporal, inferior temporal gyrus, and anterior cerebellum in patients with MDD exposed to adverse childhood experiences. In addition, brain function abnormalities were identified for patients with MDD or chronic pain and exposure to adverse childhood experiences in the cingulate gyrus, inferior parietal lobule, and precuneus in task-based functional MRI studies. CONCLUSIONS: We found that adverse childhood experiences exposure can result in different functional and structural brain alterations in adults with MDD or chronic pain compared with those without adverse childhood experiences. SYSTEMATIC REVIEW PROTOCOL: PROSPERO CRD42021233989.
Subject(s)
Adverse Childhood Experiences , Chronic Pain , Depressive Disorder, Major , Adult , Humans , Depressive Disorder, Major/complications , Depression , Likelihood Functions , Magnetic Resonance Imaging/methods , BrainABSTRACT
Every decision that we make involves a conflict between exploiting our current knowledge of an action's value or exploring alternative courses of action that might lead to a better, or worse outcome. The sub-cortical nuclei that make up the basal ganglia have been proposed as a neural circuit that may contribute to resolving this explore-exploit 'dilemma'. To test this hypothesis, we examined the effects of neuromodulating the basal ganglia's output nucleus, the globus pallidus interna, in patients who had undergone deep brain stimulation (DBS) for isolated dystonia. Neuromodulation enhanced the number of exploratory choices to the lower value option in a two-armed bandit probabilistic reversal-learning task. Enhanced exploration was explained by a reduction in the rate of evidence accumulation (drift rate) in a reinforcement learning drift diffusion model. We estimated the functional connectivity profile between the stimulating DBS electrode and the rest of the brain using a normative functional connectome derived from heathy controls. Variation in the extent of neuromodulation induced exploration between patients was associated with functional connectivity from the stimulation electrode site to a distributed brain functional network. We conclude that the basal ganglia's output nucleus, the globus pallidus interna, can adaptively modify decision choice when faced with the dilemma to explore or exploit.
Subject(s)
Deep Brain Stimulation , Dystonia , Humans , Globus Pallidus/physiology , Basal Ganglia , BrainABSTRACT
Alcohol-related morbidities and mortality are highly prevalent, increasing the burden to societies and health systems with 3 million deaths globally each year in young adults directly attributable to alcohol. Cue-induced alcohol craving has been formulated as a type of aberrant associative learning, modeled using temporal difference theory with an expected reward value (ERV) linked to craving. Clinically, although harmful use of alcohol is associated with increased time spent obtaining and using alcohol, it is also associated with self-neglect. The latter implies that the motivational aspects of nonalcohol stimuli are blunted. Using an instrumental learning task with non-alcohol-related stimuli, here, we tested hypotheses that the encoding of cue signals (ERV) predicting reward delivery would be blunted in binge alcohol drinkers in both sexes. We also predicted that for the binge drinking group alone, ratings of problematic alcohol use would correlate with abnormal ERV signals consistent with between groups (i.e., binge drinkers vs controls) abnormalities. Our results support our hypotheses with the ERV (nonalcohol cue) signal blunted in binge drinkers and with the magnitude of the abnormality correlating with ratings of problematic alcohol use. This implies that consistent with hypotheses, the motivational aspects of non-alcohol-related stimuli are blunted in binge drinkers. A better understanding of the mechanisms of harmful alcohol use will, in time, facilitate the development of more effective interventions, which should aim to decrease the motivational value of alcohol and increase the motivational value of non-alcohol-related stimuli.SIGNIFICANCE STATEMENT Allostasis theory predicts specific abnormalities in brain function and subjective experiences that occur when people develop drug problems including addiction. Cue-induced alcohol craving has been formulated as a type of aberrant associative learning, modeled using temporal difference theory with ERV linked to craving. Here, we used an instrumental learning task with non-alcohol-associated stimuli to test hypotheses that the encoding of nonalcohol cue signals (ERV) and reward prediction error signals showed blunting in binge alcohol drinkers. We conclude that fMRI can be used to noninvasively test allostasis and associative learning theory predictions in binge drinkers.
Subject(s)
Binge Drinking , Male , Female , Young Adult , Humans , Alcohol Drinking , Ethanol , Reward , CravingABSTRACT
BACKGROUND: Major depressive disorder (MDD) was previously associated with negative affective biases. Evidence from larger population-based studies, however, is lacking, including whether biases normalise with remission. We investigated associations between affective bias measures and depressive symptom severity across a large community-based sample, followed by examining differences between remitted individuals and controls. METHODS: Participants from Generation Scotland (N = 1109) completed the: (i) Bristol Emotion Recognition Task (BERT), (ii) Face Affective Go/No-go (FAGN), and (iii) Cambridge Gambling Task (CGT). Individuals were classified as MDD-current (n = 43), MDD-remitted (n = 282), or controls (n = 784). Analyses included using affective bias summary measures (primary analyses), followed by detailed emotion/condition analyses of BERT and FAGN (secondary analyses). RESULTS: For summary measures, the only significant finding was an association between greater symptoms and lower risk adjustment for CGT across the sample (individuals with greater symptoms were less likely to bet more, despite increasingly favourable conditions). This was no longer significant when controlling for non-affective cognition. No differences were found for remitted-MDD v. controls. Detailed analysis of BERT and FAGN indicated subtle negative biases across multiple measures of affective cognition with increasing symptom severity, that were independent of non-effective cognition [e.g. greater tendency to rate faces as angry (BERT), and lower accuracy for happy/neutral conditions (FAGN)]. Results for remitted-MDD were inconsistent. CONCLUSIONS: This suggests the presence of subtle negative affective biases at the level of emotion/condition in association with depressive symptoms across the sample, over and above those accounted for by non-affective cognition, with no evidence for affective biases in remitted individuals.
Subject(s)
Depression , Depressive Disorder, Major , Humans , Depressive Disorder, Major/psychology , Emotions , Happiness , BiasABSTRACT
Electroconvulsive therapy (ECT) is the most effective treatment for severe treatment-resistant depression but concern about cognitive side-effects, particularly memory loss, limits its use. Recent observational studies on large groups of patients who have received ECT report that cognitive side-effects were associated with electric field (EF) induced increases in hippocampal volume, whereas therapeutic efficacy was associated with EF induced increases in sagittal brain structures. The aim in the present study was to determine whether a novel fronto-medial (FM) ECT electrode placement would minimize electric fields in bilateral hippocampi (HIP) whilst maximizing electric fields in dorsal sagittal cortical regions. An anatomically detailed computational head model was used with finite element analysis, to calculate ECT-induced electric fields in specific brain regions identified by translational neuroimaging studies of treatment-resistant depressive illness, for a range of electrode placements. As hypothesized, compared to traditional bitemporal (BT) electrode placement, a specific FM electrode placement reduced bilateral hippocampal electric fields two-to-three-fold, whilst the electric fields in the dorsal anterior cingulate (dAC) were increased by approximately the same amount. We highlight the clinical relevance of this specific FM electrode placement for ECT, which may significantly reduce cognitive and non-cognitive side-effects and suggest a clinical trial is indicated.
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BACKGROUND: DNA methylation is an epigenetic mark associated with the repression of gene promoters. Its pattern in the genome is disrupted with age and these changes can be used to statistically predict age with epigenetic clocks. Altered rates of aging inferred from these clocks are observed in human disease. However, the molecular mechanisms underpinning age-associated DNA methylation changes remain unknown. Local DNA sequence can program steady-state DNA methylation levels, but how it influences age-associated methylation changes is unknown. RESULTS: We analyze longitudinal human DNA methylation trajectories at 345,895 CpGs from 600 individuals aged between 67 and 80 to understand the factors responsible for age-associated epigenetic changes at individual CpGs. We show that changes in methylation with age occur at 182,760 loci largely independently of variation in cell type proportions. These changes are especially apparent at 8322 low CpG density loci. Using SNP data from the same individuals, we demonstrate that methylation trajectories are affected by local sequence polymorphisms at 1487 low CpG density loci. More generally, we find that low CpG density regions are particularly prone to change and do so variably between individuals in people aged over 65. This differs from the behavior of these regions in younger individuals where they predominantly lose methylation. CONCLUSIONS: Our results, which we reproduce in two independent groups of individuals, demonstrate that local DNA sequence influences age-associated DNA methylation changes in humans in vivo. We suggest that this occurs because interactions between CpGs reinforce maintenance of methylation patterns in CpG dense regions.
Subject(s)
DNA Methylation , Epigenesis, Genetic , Aged , Aged, 80 and over , Aging/genetics , CpG Islands , Epigenomics , HumansABSTRACT
Characterising associations between the methylome, proteome and phenome may provide insight into biological pathways governing brain health. Here, we report an integrated DNA methylation and phenotypic study of the circulating proteome in relation to brain health. Methylome-wide association studies of 4058 plasma proteins are performed (N = 774), identifying 2928 CpG-protein associations after adjustment for multiple testing. These are independent of known genetic protein quantitative trait loci (pQTLs) and common lifestyle effects. Phenome-wide association studies of each protein are then performed in relation to 15 neurological traits (N = 1,065), identifying 405 associations between the levels of 191 proteins and cognitive scores, brain imaging measures or APOE e4 status. We uncover 35 previously unreported DNA methylation signatures for 17 protein markers of brain health. The epigenetic and proteomic markers we identify are pertinent to understanding and stratifying brain health.
Subject(s)
Genome-Wide Association Study , Proteome , Biomarkers/metabolism , Brain/metabolism , CpG Islands/genetics , DNA Methylation/genetics , Epigenome , Proteome/genetics , Proteome/metabolism , ProteomicsABSTRACT
BACKGROUND: Younger women (defined as those < 50 years who are likely pre-menopausal at time of diagnosis) with breast cancer often experience persistent treatment-related side effects that adversely affect their physical and psychological wellbeing. The Women's Wellness After Cancer Program (WWACP) was adapted and piloted in Australia to address these outcomes in younger women. The aims of this feasibility study are to determine (1) the potential to translate the Younger WWACP (YWWACP) intervention to a broader population base in Aotearoa/New Zealand and Australia, and (2) the potential for success of a larger, international, phase ΙΙΙ, randomised controlled trial. METHODS: This bi-national, randomised, single-blinded controlled trial involves two main study sites in Aotearoa/New Zealand (Kowhai study) and Australia (EMERALD study). Young women aged 18 to 50 years who completed intensive treatment (surgery, chemotherapy, and/or radiotherapy) for breast cancer in the previous 24 months are eligible. The potential to translate the YWWACP to women in these two populations will be assessed according to several feasibility outcomes. These include examining intervention accessibility, acceptability and uptake; intervention sustainability and adherence; the prevalence components of the intervention in the control group; intervention efficacy; participants' perception of measurement burden; the effectiveness of planned recruitment strategies; and trial methods and procedures. The studies collectively aim to enrol 60 participants in the intervention group and 60 participants in the control group (total = 120 participants). DISCUSSION: Ethical approval has been received from the Southern Health and Disability Ethics Committee (Kowhai ref: 19/STH/215), and UnitingCare Human Research Ethics Committee (EMERALD ref: 202103). This study will provide important data on the feasibility of the refined YWWACP in the trans-Tasman context. This study will account for and harmonise cross-country differences to ensure the success of a proposed international grant application for a phase ΙΙΙ randomised controlled trial of this program to improve outcomes in younger women living with breast cancer. TRIAL REGISTRATION: Australian New Zealand Clinical Trials Registry (ANZCTR): Kowhai ACTRN12620000260921 , registered on 27 February 2020. EMERALD ACTRN12621000447853 , registered on 19 April 2021.
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Background: ChRCC and RO are two types of rarely occurring renal tumors that are difficult to distinguish from one another based on morphological features alone. They differ in prognosis, with ChRCC capable of progressing and metastasizing, but RO is benign. This means discrimination of the two tumors is of crucial importance. Objectives: The purpose of this research was to develop and comprehensively evaluate predictive models that can discriminate between ChRCC and RO tumors using Computed Tomography (CT) scans and ML-Radiomics texture analysis methods. Methods: Data were obtained from 78 pathologically confirmed renal masses, scanned at two institutions. Data from the two institutions were combined to form a third set resulting in three data cohorts, i.e., cohort 1, 2 and combined. Contrast-enhanced scans were used and the axial cross-sectional slices of each tumor were extracted from the 3D data using a semi-automatic segmentation technique for both 2D and 3D scans. Radiomics features were extracted before and after applying filters and the dimensions of the radiomic features reduced using the least absolute shrinkage and selection operator (LASSO) method. Synthetic minority oversampling technique (SMOTE) was applied to avoid class imbalance. Five ML algorithms were used to train models for predictive classification and evaluated using 5-fold cross-validation. Results: The number of selected features with good model performance was 20, 40 and 6 for cohorts 1, 2 and combined, respectively. The best model performance in cohorts 1, 2 and combined had an excellent Area Under the Curve (AUC) of 1.00 ± 0.000, 1.00 ± 0.000 and 0.87 ± 0.073, respectively. Conclusions: ML-based radiomics signatures are potentially useful for distinguishing ChRCC and RO tumors, with a reliable level of performance for both 2D and 3D scanning.
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Background: Automated brain tumor identification facilitates diagnosis and treatment planning. We evaluate the performance of traditional machine learning (TML) and deep learning (DL) in brain tumor detection and segmentation, using MRI. Methods: A systematic literature search from January 2000 to May 8, 2021 was conducted. Study quality was assessed using the Checklist for Artificial Intelligence in Medical Imaging (CLAIM). Detection meta-analysis was performed using a unified hierarchical model. Segmentation studies were evaluated using a random effects model. Sensitivity analysis was performed for externally validated studies. Results: Of 224 studies included in the systematic review, 46 segmentation and 38 detection studies were eligible for meta-analysis. In detection, DL achieved a lower false positive rate compared to TML; 0.018 (95% CI, 0.011 to 0.028) and 0.048 (0.032 to 0.072) (P < .001), respectively. In segmentation, DL had a higher dice similarity coefficient (DSC), particularly for tumor core (TC); 0.80 (0.77 to 0.83) and 0.63 (0.56 to 0.71) (P < .001), persisting on sensitivity analysis. Both manual and automated whole tumor (WT) segmentation had "good" (DSC ≥ 0.70) performance. Manual TC segmentation was superior to automated; 0.78 (0.69 to 0.86) and 0.64 (0.53 to 0.74) (P = .014), respectively. Only 30% of studies reported external validation. Conclusions: The comparable performance of automated to manual WT segmentation supports its integration into clinical practice. However, manual outperformance for sub-compartmental segmentation highlights the need for further development of automated methods in this area. Compared to TML, DL provided superior performance for detection and sub-compartmental segmentation. Improvements in the quality and design of studies, including external validation, are required for the interpretability and generalizability of automated models.
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BACKGROUND: Symptom burden remains a critical concern for individuals with non-small cell lung cancer (NSCLC) following the completion of treatment. The most common symptom clusters, dyspnea (shortness of breath) and fatigue, can contribute to physical decline, reductions in quality of life, and a higher risk of comorbidities and mortality. Dyspnea is a primary limiter of exercise capacity in individuals with lung cancer, resulting in exercise avoidance and an accelerated physical decline. As such, designing resistance training with cluster sets to mitigate symptoms of dyspnea and fatigue may result in improved exercise tolerance. Thus, maintaining the exercise stimulus via cluster sets, combined with improved tolerance of the exercise, could result in the maintenance of physical function and quality of life. The purpose of this study is to investigate the feasibility and preliminary efficacy of a hybrid-delivery home-based cluster-set resistance training program in individuals with NSCLC. METHODS: Individuals with NSCLC (n = 15), within 12 months of completion of treatment, will be recruited to participate in this single-arm feasibility trial. Participants will complete 8 weeks of home-based resistance training designed to minimize dyspnea and fatigue. The hybrid delivery of the program will include supervised sessions in the participants' home and virtual supervision via video conferencing. The primary outcome of feasibility will be quantified by recruitment rates, retention, acceptability, and intervention fidelity. Exploratory outcomes (dyspnea, fatigue, quality of life, physical function, and body composition) will be assessed pre- and post-intervention. DISCUSSION: This study will provide important data on the feasibility of delivering this intervention and inform procedures for a future randomized controlled trial. TRIAL REGISTRATION: Record not yet public.