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Subgrouping autism and ADHD based on structural MRI population modelling centiles.
BACKGROUND: Autism and attention deficit hyperactivity disorder (ADHD) are two highly heterogeneous neurodevelopmental conditions with variable underlying neurobiology. Imaging studies have yielded varied results, and it is now clear that there is unlikely to be one characteristic neuroanatomical profile of either condition. Parsing this heterogeneity could allow us to identify more homogeneous subgroups, either within or across conditions, which may be more clinically informative. This has been a pivotal goal for neurodevelopmental research using both clinical and neuroanatomical features, though results thus far have again been inconsistent with regards to the number and characteristics of subgroups. METHODS: Here, we use population modelling to cluster a multi-site dataset based on global and regional centile scores of cortical thickness, surface area and grey matter volume. We use HYDRA, a novel semi-supervised machine learning algorithm which clusters based on differences to controls and compare its performance to a traditional clustering approach. RESULTS: We identified distinct subgroups within autism and ADHD, as well as across diagnosis, often with opposite neuroanatomical alterations relatively to controls. These subgroups were characterised by different combinations of increased or decreased patterns of morphometrics. We did not find significant clinical differences across subgroups. LIMITATIONS: Crucially, however, the number of subgroups and their membership differed vastly depending on chosen features and the algorithm used, highlighting the impact and importance of careful method selection. CONCLUSIONS: We highlight the importance of examining heterogeneity in autism and ADHD and demonstrate that population modelling is a useful tool to study subgrouping in autism and ADHD. We identified subgroups with distinct patterns of alterations relative to controls but note that these results rely heavily on the algorithm used and encourage detailed reporting of methods and features used in future studies.
Inherited retinal disease pathway in the UK: a patient perspective and the potential of AI.
BACKGROUND: Inherited retinal diseases (IRDs) are the leading cause of blindness in young people in the UK. Despite significant improvements in genomics medicine, the diagnosis of these conditions remains challenging, and around 40% do not receive a definite genetic diagnosis after extensive genetic testing. This survey aims to investigate the experience of individuals affected by IRDs, their relatives, friends and caregivers, focusing on their care and diagnostic journey. Additionally, it explores the potential acceptability of artificial intelligence (AI) technologies, such as Eye2Gene, that predict causative genes from retinal images of patients with IRDs. METHODS: This cross-sectional survey included Likert scale and open-ended questions and was distributed electronically using the Qualtrics platform between April and August 2024. The survey included questions on respondent demographics; their journey to receive specialist care and genetic testing; their information needs and their attitude towards AI-augmented diagnosis. Descriptive statistics and content analysis were used to interpret the survey responses. RESULTS: The survey had 247 responses, of which 242 were analysed after removing four duplicates and one without consent; 80.2% were patients and the remainder were relatives, friends or caregivers. There was substantial variability in patient diagnostic journeys in terms of waiting times to see a specialist (IQR, 1-4 years), commute required (IQR, 10-74 miles) and number of visits to reach a diagnosis (IQR, 2-4). A substantial proportion of patients (35.8%) had a change in diagnosis. The majority of respondents (>90%) were overwhelmingly in favour of the integration of AI into the IRD pathway to accelerate genetic diagnosis and improve care. CONCLUSION: This survey identifies several key gaps and disparities in the IRD care pathway which may potentially be bridged with AI. The survey also reveals a favourable attitude towards incorporating AI into diagnostic testing of IRDs.
Investigating heterogeneity across autism, ADHD, and typical development using measures of cortical thickness, surface area, cortical/subcortical volume, and structural covariance.
INTRODUCTION: Attention-deficit/hyperactivity disorder (ADHD) and autism are multi-faceted neurodevelopmental conditions with limited biological markers. The clinical diagnoses of autism and ADHD are based on behavioural assessments and may not predict long-term outcomes or response to interventions and supports. To address this gap, data-driven methods can be used to discover groups of individuals with shared biological patterns. METHODS: In this study, we investigated measures derived from cortical/subcortical volume, surface area, cortical thickness, and structural covariance investigated of 565 participants with diagnoses of autism [n = 262, median(IQR) age = 12.2(5.9), 22% female], and ADHD [n = 171, median(IQR) age = 11.1(4.0), 21% female] as well neurotypical children [n = 132, median(IQR) age = 12.1(6.7), 43% female]. We integrated cortical thickness, surface area, and cortical/subcortical volume, with a measure of single-participant structural covariance using a graph neural network approach. RESULTS: Our findings suggest two large clusters, which differed in measures of adaptive functioning (χ 2 = 7.8, P = 0.004), inattention (χ 2 = 11.169, P
Research assistants' experiences recruiting patients with psychosis into clinical trials: a qualitative study.
OBJECTIVES: Treatments for patients diagnosed with psychosis need to be improved. Clinical trials are an important way of assessing the efficacy of new treatments. However, recruiting patients into trials is challenging. This study sought to better understand the reasons for this from the perspective of research assistants. DESIGN: A qualitative study underpinned by a critical realist ontology and contextualist epistemology. METHODS: Research assistants who had recruited patients with psychosis into trials, primarily of psychological interventions, were interviewed. Reflexive thematic analysis was used to identify themes. RESULTS: Overarching themes representing four types of factors influencing recruitment of patients with psychosis into clinical trials were generated: patient, clinical team, research team, and NHS infrastructure. Patients largely wished to take part in trials but needed time to build trust with research assistants. Clinical teams held the power in suggesting patients for trials; therefore, it was essential for research teams to build strong relationships with clinical staff. Research teams recruiting into trials benefited from lived experience expertise, support systems, and institutional knowledge. A key NHS infrastructure factor was that mental health staff had limited time to consider trials for their patients. CONCLUSIONS: Trial participation needs to be made more accessible to patients with psychosis, who often want to take part but lack opportunities. Methods of increasing accessibility could include identifying and addressing barriers to referral from clinical teams, employing multiple recruitment strategies, and flexible appointment formats. Qualitative research with clinical teams and patients will also help in developing the understanding of barriers to recruitment.
Dissecting metabolic dysfunction- and alcohol-associated liver disease (MetALD) using proteomic and metabolomic profiles.
BACKGROUND: & Aim, Metabolic dysfunction associated and alcohol associated liver disease (MetALD) is a poorly understood condition that bridges cardiometabolic and alcohol-related pathological characteristics. We aim to distinguish MetALD patients who share similar molecular signatures with alcohol-related liver disease (ALD) and those share signatures with metabolic dysfunction-associated steatotic liver disease (MASLD), and assess their prognostic risk for complications and mortality. METHODS: Our analysis involved 443,453 European participants from UK Biobank, including 34,147 with MetALD, 11,220 with ALD, and 124,034 with MASLD. We employed Elastic Net Regression to classify ALD and MASLD involving 249 plasma metabolites and/or 2,941 plasma proteins with various sensitivity analyses. We then used the selected concise model in MetALD patients to identify alcohol-predominant group (classified to ALD) and cardiometabolic-predominant group (classified to MASLD). Finally, we explored their 15-year risk of major outcomes (i.e., heart failure, myocardial infarction, stroke, cirrhosis, hepatocellular carcinoma and mortality) using Cox regression. RESULTS: The metabolome alone discriminated ALD from MASLD with an Area under the Curve (AUC) of 0.86, while the proteome alone achieved an AUC of 0.96. Adding age, sex, BMI, liver enzymes, or metabolome information did not enhance the AUC of the proteome model. A ten-protein model differentiated ALD and MASLD with an AUC of 0.93. This model identified that alcohol-predominant MetALD patients had significantly higher risks of mortality, and cirrhosis, along with elevated fibrosis scores and higher fibrosis stages, compared to cardiometabolic-predominant patients. CONCLUSIONS: This study emphasizes the importance of subtyping differentiation using proteome data for personalized treatment and improved prognostic outcomes in MetALD patients.
Early mucosal responses following a randomised controlled human inhaled infection with attenuated Mycobacterium bovis BCG.
The development of an effective vaccine against Mycobacterium tuberculosis is hampered by an incomplete understanding of immunoprotective mechanisms. We utilise an aerosol human challenge model using attenuated Mycobacterium bovis BCG, in BCG-naïve UK adults. The primary endpoint of this study (NCT03912207) was to characterise the early immune responses induced by aerosol BCG infection, the secondary endpoint was to identify immune markers associated with in-vitro protection. Blinded volunteers were randomised to inhale 1 × 107 CFU aerosolised BCG or 0.9% saline (20:6); and sequentially allocated to bronchoscopy at day 2 or 7 post-inhalation (10 BCG, 3 saline each timepoint). In the bronchoalveolar lavage post-aerosol BCG infection, there was an increase in frequency of eosinophils, neutrophils, NK cells and Donor-Unrestricted T cells at day 7, and the frequency of antigen presenting cells decreased at day 7 compared with day 2. The frequency of interferon-gamma+ BCG-specific CD4+ T cells increased in the BAL and peaked in the blood at day 7 post-BCG infection compared to day 2. BAL cells at day 2 and day 7 upregulated gene pathways related to phagocytosis, MHC-II antigen loading, T cell activation and proliferation. BCG's lack of key virulence factors and its failure to induce granulomas, may mean the observed immune responses do not fully recapitulate Mycobacterium tuberculosis infection. However, human infection models can provide unique insights into early immune mechanisms, informing vaccine design for complex pathogens.
The clockwork macrophage: timing in innate immunity.
The circadian clock enables organisms to predict daily environmental changes and synchronize their physiology and behaviour accordingly. Macrophages, key sensor cells in the innate immune system, exhibit cell-autonomous circadian rhythmicity. This circadian rhythmic behaviour is synchronised to the central clock in the hypothalamus as a result of neural, and hormonal signals. Macrophage rhythms and responses involve sensing temporal cues, integrating information from tissue-specific environments, and initiating context-appropriate, time-gated responses. On a broader scale, monocytes and macrophages communicate and synchronize with other immune cells, migrate throughout the body, and infiltrate tissues, collectively contributing to circadian regulation in both health and disease. While the field of macrophage circadian biology is rapidly advancing, it is equally important to reflect on its historical development, which has been shaped by over two centuries of accumulating knowledge and technological progress. This review traces key milestones in macrophage and circadian research, examining how recent discoveries have refined our understanding of early foundational questions and setting the stage for future inquiries. Notably, many intriguing questions remain unresolved, including the circadian regulation of macrophage function under steady-state conditions, the tissue-specific heterogeneity of macrophage circadian rhythms, and the role of macrophage circadian clocks in disease pathogenesis and their potential clinical implications.
A machine learning approach for multimodal data fusion for survival prediction in cancer patients.
Technological advancements of the past decade have transformed cancer research, improving patient survival predictions through genotyping and multimodal data analysis. However, there is no comprehensive machine-learning pipeline for comparing methods to enhance these predictions. To address this, a versatile pipeline using The Cancer Genome Atlas (TCGA) data was developed, incorporating various data modalities such as transcripts, proteins, metabolites, and clinical factors. This approach manages challenges like high dimensionality, small sample sizes, and data heterogeneity. By applying different feature extraction and fusion strategies, notably late fusion models, the effectiveness of integrating diverse data types was demonstrated. Late fusion models consistently outperformed single-modality approaches in TCGA lung, breast, and pan-cancer datasets, offering higher accuracy and robustness. This research highlights the potential of comprehensive multimodal data integration in precision oncology to improve survival predictions for cancer patients. The study provides a reusable pipeline for the research community, suggesting future work on larger cohorts.
Progression and life expectancy in primary lateral sclerosis
Objectives To characterise the clinical characteristics and longitudinal outcomes in primary lateral sclerosis (PLS), including median survival from symptom onset and age at death. Methods The authors retrospectively reviewed electronic health records of patients diagnosed with PLS referred to a specialised motor neuron disorders clinic from 2002 to 2024, analysed longitudinal Revised Amyotrophic Lateral Sclerosis Functional Rating Scale (ALSFRS-R) assessments using joint models and used Kaplan-Meier methods and life tables to calculate median survival and age at death compared with population-based values. Results Of 52 patients, 34 (65%) were male, 41 (79%) first noted symptoms in the lower limbs and 10 (19%) in corticobulbar function. Median age of symptom onset was 53 years. The mean annual rate of functional decline was -1.92 ALSFRS-R points (95% CI -3.03 to -0.78), with equal highest rates of decline in fine and gross motor subscores. Five patients (10%) received gastrostomy and three (6%) non-invasive ventilation. Median survival from symptom onset was 23.1 years (22.7 to not reached), and median age at death was 79.5 years (77.8 to not reached) compared with a population-based reference mean of 81.9 years (81.1 to 82.8). Discussion PLS may be commensurate with near-normal life expectancy. Significant disability arises from limb motor dysfunction, with a minority of patients requiring nutritional or respiratory support. This has important implications for counselling and trial design.
Blood pressure and its associations in 554 children and young people with CAH.
BACKGROUND: Congenital Adrenal Hyperplasia (CAH) due to 21-hydroxylase deficiency (21OHD) affects approximately 1 in 15,000 individuals. We leveraged the power of multicentre registry data to assess the trend and predictors of blood pressure (BP) within children and young persons with 21OHD to inform monitoring strategies. METHOD: Data from the International CAH Registry in patients younger than 20 years was compared to normative values. Values of BP were modelled to create reference curves, multiple change point analysis applied to quantify the difference with normative data. Covariate adjustment was informed by a directed acyclic graph, prior to joint outcome regression modelling to accurately assess predictors of BP. RESULTS: A total of 6436 visits within 554 patients (52.5% females) showed BP-Standard deviation scores (SDS) were higher at younger ages. Patients under five years had systolic BP-SDS of 1.6 (Q1:0.6-Q3:2.7) decreasing to 1.0 (Q1:0.2-Q3:1.8) over five years, equating to 31.0% over the 95th centile decreasing to 15.0%. Higher doses of fludrocortisone were associated with a small increase in systolic BP equivalent to 1.2mmHg with every 100 micrograms extra fludrocortisone. Renin of 100µU/ml was associated with 4.6mmHg lower systolic BP than a renin of 1µU/ml, higher 17OH-progesterone and androstenedione also predicted lower systolic and diastolic BP (p<0.05). CONCLUSION: Higher BP in children with 21OHD is common and particularly pronounced at a younger age, but may not be attributable to excessive mineralocorticoid replacement. There is a need to improve our understanding of the determinants of this raised BP as well as its long-term effects.
Dreaming of Better Treatments: Advances in Drug Development for Sleep Medicine and Chronotherapy.
Throughout history, the development of new sleep medicines has been driven by progress in our understanding of the mechanisms underlying sleep. Ancient civilisations used their understanding of the sedative nature of natural herbs and compounds to induce sleep. The discovery of barbiturates and bromides heralded a new era of synthetic sleep medicine in the 19th century. This was followed by the development of benzodiazepines that were used to inhibit signalling throughout the brain by promoting gamma-amino butyric acid release and thereby produce loss of consciousness. As our understanding of sleep has deepened, newer therapies have more specifically targeted the wake-inducing neurotransmitter orexin with fewer side effects. Given the newly highlighted role of kinases in sleep/wake regulation, we predict that the next breakthroughs in sleep medicine will likely target these kinases. Given the fundamental role that sleep plays in maintaining brain health through processes such as glymphatic clearance, sleep medicine has therapeutic potential beyond just sleep. Recent evidence suggests that sleep disruptions directly contribute to the build-up of pathological neuronal proteins in neurodegenerative disorders. Therefore, sleep medicine could improve prognosis in disorders such as these. Great attention must be paid to the mechanism of action of each sleep medicine, however, as sleep medicines which do not fully mimic sleep could actually worsen disease progression.
Tracing mitochondrial marks of neuronal aging in iPSCs-derived neurons and directly converted neurons
Abstract This study aims to determine if neurons derived from induced pluripotent stem cells (iPSCsNs) and directly converted neurons (iNs) from the same source cells exhibit changes in mitochondrial properties related to aging. This research addresses the uncertainty around whether aged iPSCsNs retain aging-associated mitochondrial impairments upon transitioning through pluripotency while direct conversion maintains these impairments. We observe that both aged models exhibit characteristics of aging, such as decreased ATP, mitochondrial membrane potential, respiration, NAD+/NADH ratio, and increased radicals and mitochondrial mass. In addition, both neuronal models show a fragmented mitochondrial network. However, aged iPSCsNs do not exhibit a metabolic shift towards glycolysis, unlike aged iNs. Furthermore, mRNA expression differed significantly between aged iPSCsNs and aged iNs. The study concludes that aged iPSCsNs may differ in transcriptomics and the aging-associated glycolytic shift but can be a valuable tool for studying specific feature of mitochondrial neuronal aging in vitro alongside aged iNs.
Severe Dietary Energy Restriction for Compensated Cirrhosis Due to Metabolic Dysfunction-Associated Steatotic Liver Disease: A Randomised Controlled Trial.
BACKGROUND: Compensated cirrhosis due to metabolic dysfunction-associated steatotic liver disease (CC-MASLD) increases morbidity and mortality risk but has no aetiology-specific treatment. We investigated the safety and efficacy signals of severe energy restriction. METHODS: In this randomised controlled trial, adults with CC-MASLD and obesity in a tertiary hepatology centre were randomised 2:1 to receive one-to-one remote dietetic support with a low-energy (880 kcal/day, 80 g protein/day) total diet replacement programme for 12 weeks and stepped food reintroduction for another 12 weeks or standard of care (SoC). Given the exploratory nature of the study, three pre-defined co-primary outcomes were used to assess safety and efficacy signals: severe increases in liver biochemistry, changes in iron-corrected T1, and changes in liver stiffness on magnetic resonance elastography. Changes in liver steatosis on magnetic resonance imaging, physical performance based on the physical performance test and liver frailty index, and changes in fat-free mass were secondary outcomes. Magnetic resonance outcomes were assessed blind. RESULTS: Between February 2022 and September 2023, 17 participants (36% female, median [IQR] age 58 [7.5] years) were randomised to SoC (n = 6) or intervention (n = 11). The trial stopped earlier than planned due to slow recruitment rate. 91% and 94% of participants completed the intervention and attended the 24-week follow-up, respectively. Compared with the SoC, the between-group weight change in the intervention was -11.9 kg (95% CI: -17.2, -6.6, p
The impact of dosage timing for inhaled corticosteroids in asthma: a randomised three-way crossover trial.
BACKGROUND: Asthma demonstrates a robust daily rhythm, with airflow obstruction and airway inflammation peaking overnight. Aligning the timing of drug administration with rhythms in disease (chronotherapy) may improve therapeutic efficacy. We aimed to evaluate the impact of dosage timing for inhaled corticosteroids in asthma. METHODS: This is a randomised three-way crossover trial. Participants with mild to moderate atopic asthma were randomised to beclometasone dipropionate: (1) 400 µg once daily between 08:00 and 09:00 (ODAM); (2) 400 µg once daily between 15:00 and 16:00 (ODPM); and (3) 200 µg twice daily between 08:00 and 09:00 and between 20:00 and 21:00 (BD) for 28 days, with a 2 week washout period in between treatment periods. Six-hourly spirometry and biomarkers were measured over 24 hours following the run-in period and at the end of each treatment period. RESULTS: Of 25 participants, 21 completed all regimens. ODPM was superior in improving 22:00 FEV1 (median (IQR): +160 (+70, +270) ml) compared with ODAM (-20 (-80, +230) ml) and BD (+80 (-20, +200) ml). ODPM resulted in better overnight (22:00 and 04:00) suppression in blood eosinophil counts compared with BD and ODAM. All regimens improved asthma control and reduced fractional exhaled nitric oxide and serum cortisol levels with no difference among dosing regimens. CONCLUSION: ODPM better suppresses the nocturnal dip in lung function and peak of blood eosinophil counts compared with BD and ODAM; this was without an increase in adverse events. Future trials are warranted to validate these findings in real-life settings and to determine which population may best benefit from chronotherapy.
In Vivo Quantification of Creatine Kinase Kinetics in Mouse Brain Using 31P-MRS at 7 T
31P-MRS is a method of choice for studying neuroenergetics in vivo, but its application in the mouse brain has been limited, often restricted to ultrahigh field (> 7 T) MRI scanners. Establishing its feasibility on more readily available preclinical 7-T scanners would create new opportunities to study metabolism and physiology in murine models of brain disorders. Here, we demonstrate that the apparent forward rate constant (kf) of creatine kinase (CK) can be accurately quantified using a progressive saturation-transfer approach in the mouse brain at 7 T. We also find that a 20% reduction in respiration of anesthetized mice can lead to 36% increase in kf attributable to a drop in cellular pH and mitochondrial ATP production. To achieve this, we used a test–retest analysis to assess the reliability and repeatability of 31P-MRS acquisition, analysis, and experimental design protocols. We report that many 31P-containing metabolites can be reliably measured using a localized 3D-ISIS sequence, which showed highest SNR amplitude, SNR consistency, and minimal T2 relaxation signal loss. Our study identifies key physiological factors influencing mouse brain energy homeostasis in vivo and provides a methodological basis to guide future studies interested in implementing 31P-MRS on preclinical 7-T scanners.