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Potential benefits of precision medicine in cardiovascular disease (CVD) include more accurate phenotyping of individual patients with the same condition or presentation, using multiple clinical, imaging, molecular and other variables to guide diagnosis and treatment. An approach to realising this potential is the digital twin concept, whereby a virtual representation of a patient is constructed and receives real-time updates of a range of data variables in order to predict disease and optimise treatment selection for the real-life patient. We explored the term digital twin, its defining concepts, the challenges as an emerging field, and potentially important applications in CVD. A mapping review was undertaken using a systematic search of peer-reviewed literature. Industry-based participants and patent applications were identified through web-based sources. Searches of Compendex, EMBASE, Medline, ProQuest and Scopus databases yielded 88 papers related to cardiovascular conditions (28%, n  = 25), non-cardiovascular conditions (41%, n  = 36), and general aspects of the health digital twin (31%, n  = 27). Fifteen companies with a commercial interest in health digital twin or simulation modelling had products focused on CVD. The patent search identified 18 applications from 11 applicants, of which 73% were companies and 27% were universities. Three applicants had cardiac-related inventions. For CVD, digital twin research within industry and academia is recent, interdisciplinary, and established globally. Overall, the applications were numerical simulation models, although precursor models exist for the real-time cyber-physical system characteristic of a true digital twin. Implementation challenges include ethical constraints and clinical barriers to the adoption of decision tools derived from artificial intelligence systems.

The hippocampus is a key component of emotional and memory circuits and is broadly connected throughout the brain. We tracked the whole-brain connections of white matter fibres from the hippocampus using ultra-high angular resolution diffusion MRI in both a single 1150-direction dataset and a large normal cohort (n = 94; 391-directions). Using a connectomic approach, we identified six dominant pathways in terms of strength, length and anatomy, and characterised them by their age and gender variation. The strongest individual connection was to the ipsilateral thalamus. There was a strong age dependence of hippocampal connectivity to medial occipital regions. Overall, our results concur with preclinical and ex-vivo data, confirming that meaningful in vivo characterisation of hippocampal connections is possible in an individual. Our findings extend the collective knowledge of hippocampal anatomy, highlighting the importance of the spinal-limbic pathway and the striking lack of hippocampal connectivity with motor and sensory cortices.

Functional neuroimaging studies implicate anterior cingulate and limbic dysfunction in major depressive disorder (MDD) and responsiveness to antidepressants. Diffusion tensor imaging (DTI) enables characterisation of white matter tracts that relate to these regions. To examine whether DTI measures of anterior cingulate and limbic white matter are useful prognostic biomarkers for MDD. Of the 102 MDD out-patients from the International Study to Predict Optimized Treatment for Depression (iSPOT-D) who provided baseline magnetic resonance imaging (MRI) data, 74 completed an 8-week course of antidepressant medication (randomised to escitalopram, sertraline or extended-release venlafaxine) and were included in the present analyses. Thirty-four matched controls also provided DTI data. Fractional anisotropy was measured for five anterior cingulate-limbic white matter tracts: cingulum cingulate and hippocampus bundle, fornix, stria terminalis and uncinate fasciculus. (Trial registered at ClinicalTrials.gov: NCT00693849.) A cross-validated logistic regression model demonstrated that altered connectivity for the cingulum part of the cingulate and stria terminalis tracts significantly predicted remission independent of demographic and clinical measures with 62% accuracy. Prediction improved to 74% when age was added to this model. Anterior cingulate-limbic white matter is a useful predictor of antidepressant treatment outcome in MDD.

Although the cost of poor treatment outcomes of depression is staggering, we do not yet have clinically useful methods for selecting the most effective antidepressant for each depressed person. Emotional brain activation is altered in major depressive disorder (MDD) and implicated in treatment response. Identifying which aspects of emotional brain activation are predictive of general and specific responses to antidepressants may help clinicians and patients when making treatment decisions. We examined whether amygdala activation probed by emotion stimuli is a general or differential predictor of response to three commonly prescribed antidepressants, using functional magnetic resonance imaging (fMRI). A test-retest design was used to assess patients with MDD in an academic setting as part of the International Study to Predict Optimized Treatment in Depression. A total of 80 MDD outpatients were scanned prior to treatment and 8 weeks after randomization to the selective serotonin reuptake inhibitors escitalopram and sertraline and the serotonin-norepinephrine reuptake inhibitor, venlafaxine-extended release (XR). A total of 34 matched controls were scanned at the same timepoints. We quantified the blood oxygen level-dependent signal of the amygdala during subliminal and supraliminal viewing of facial expressions of emotion. Response to treatment was defined by ⩾50% symptom improvement on the 17-item Hamilton Depression Rating Scale. Pre-treatment amygdala hypo-reactivity to subliminal happy and threat was a general predictor of treatment response, regardless of medication type (Cohen's d effect size 0.63 to 0.77; classification accuracy, 75%). Responders showed hypo-reactivity compared to controls at baseline, and an increase toward 'normalization' post-treatment. Pre-treatment amygdala reactivity to subliminal sadness was a differential moderator of non-response to venlafaxine-XR (Cohen's d effect size 1.5; classification accuracy, 81%). Non-responders to venlafaxine-XR showed pre-treatment hyper-reactivity, which progressed to hypo-reactivity rather than normalization post-treatment, and hypo-reactivity post-treatment was abnormal compared to controls. Impaired amygdala activation has not previously been highlighted in the general vs differential prediction of antidepressant outcomes. Amygdala hypo-reactivity to emotions signaling reward and threat predicts the general capacity to respond to antidepressants. Amygdala hyper-reactivity to sad emotion is involved in a specific non-response to a serotonin-norepinephrine reuptake inhibitor. The findings suggest amygdala probes may help inform the personal selection of antidepressant treatments.

Increasing evidence suggests the presence of structural changes affecting the right ventricular outflow tract (RVOT) in patients with Brugada Syndrome (BrS). The aim of this study was to characterise the RV morphology in BrS and explore associations between morphologic, clinical, electrical, and genetic parameters using non-invasive multimodality testing. Consecutive BrS patients (recruited 2013-2015) underwent clinical assessment, dedicated RV imaging using cardiac magnetic resonance (CMR) imaging (unless contra-indicated), electrical assessment (electrocardiogram, Holter monitoring, signal-averaged ECG[SAECG]) and genotyping. Morphologic data were compared to matched control and unmatched ARVC (arrhythmogenic right ventricular cardiomyopathy) cohorts, and potential associations between morphologic parameters and other variables were explored. BrS patients (n = 42, male 86%, age 46±12 years) exhibited normal global RV volume and function, comparable to control, in contrast to significantly larger, impaired RVs in ARVC cohort (RVESV p = 0.0001; RVEDV p<0.0001, RVEF p = 0.002). Compared with control, BrS patients exhibited larger RVOT volumes (7.4 ± 0.7 vs 5.8 ± 0.7 mL/m2, p<0.0001) and wall motion abnormalities (RWMA) (31% vs 0%, p = 0.005); compared with ARVC cohort, the RVOT volumes were similar (7.4 ± 0.7 vs, 8.1 ± 1.7, p = 0.52) and there were less RWMA (31% vs 76%, p = 0.01). Overall 67% BrS patients had abnormal RVOT morphology. Patients with abnormal RVOT tended to be older (48 ± 12 y vs 41 ± 12y, p = 0.06). Rare genetic variants were only observed in patients with abnormal RVOT morphology (36% vs 0%, p = 0.02). Patients with BrS frequently exhibit structural abnormalities localised to the RVOT and these changes may be age- and gene-dependent.

Background As the average age of patients with severe aortic stenosis (AS) who receive procedural intervention continue to age, the need for non-invasive modalities that provide accurate diagnosis and operative planning is increasingly important. Advances in cardiovascular magnetic resonance (CMR) over the past two decades mean it is able to provide haemodynamic data at the aortic valve, along with high fidelity anatomical imaging. Methods Electronic databases were searched for studies comparing CMR to transthoracic echocardiography (TTE) and transoesophageal echocardiography (TEE) in the diagnosis of AS. Studies were included only if direct comparison was made on matched patients, and if diagnosis was primarily through measurement of aortic valve area (AVA). Results Twenty-three relevant, prospective articles were included in the meta-analysis, totalling 1040 individual patients. There was no significant difference in AVA measured as by CMR compared to TEE. CMR measurements of AVA size were larger compared to TTE by an average of 10.7% (absolute difference: + 0.14cm 2 , 95% CI 0.07–0.21, p  < 0.001). Reliability was high for both inter- and intra-observer measurements (0.03cm 2 +/− 0.04 and 0.02cm 2 +/− 0.01, respectively). Conclusions Our analysis demonstrates the equivalence of AVA measurements using CMR compared to those obtained using TEE. CMR demonstrated a small but significantly larger AVA than TTE. However, this can be attributed to known errors in derivation of left ventricular outflow tract size as measured by TTE. By offering additional anatomical assessment, CMR is warranted as a primary tool in the assessment and workup of patients with severe AS who are candidates for surgical or transcatheter intervention.

Liquid chromatography-mass spectrometry-based metabolomics studies are increasingly applied to large population cohorts, which run for several weeks or even years in data acquisition. This inevitably introduces unwanted intra- and inter-batch variations over time that can overshadow true biological signals and thus hinder potential biological discoveries. To date, normalisation approaches have struggled to mitigate the variability introduced by technical factors whilst preserving biological variance, especially for protracted acquisitions. Here, we propose a study design framework with an arrangement for embedding biological sample replicates to quantify variance within and between batches and a workflow that uses these replicates to remove unwanted variation in a hierarchical manner (hRUV). We use this design to produce a dataset of more than 1000 human plasma samples run over an extended period of time. We demonstrate significant improvement of hRUV over existing methods in preserving biological signals whilst removing unwanted variation for large scale metabolomics studies. Our tools not only provide a strategy for large scale data normalisation, but also provides guidance on the design strategy for large omics studies. Mass spectrometry-based metabolomics is a powerful method for profiling large clinical cohorts but batch variations can obscure biologically meaningful differences. Here, the authors develop a computational workflow that removes unwanted data variation while preserving biologically relevant information.

In the enduring challenge against disease, advancements in medical technology have empowered clinicians with novel diagnostic platforms. Whilst in some cases, a single test may provide a confident diagnosis, often additional tests are required. However, to strike a balance between diagnostic accuracy and cost-effectiveness, one must rigorously construct the clinical pathways. Here, we developed a framework to build multi-platform precision pathways in an automated, unbiased way, recommending the key steps a clinician would take to reach a diagnosis. We achieve this by developing a confidence score, used to simulate a clinical scenario, where at each stage, either a confident diagnosis is made, or another test is performed. Our framework provides a range of tools to interpret, visualize and compare the pathways, improving communication and enabling their evaluation on accuracy and cost, specific to different contexts. This framework will guide the development of novel diagnostic pathways for different diseases, accelerating the implementation of precision medicine into clinical practice.

Atherosclerotic coronary artery disease (CAD) remains a leading cause of death globally, and individual susceptibility is not fully explained by standard risk factors. The role of plasma fatty acid profiles in relation to imaging-defined CAD burden remains less well established. We performed a cross-sectional cohort analysis of 1,002 participants undergoing coronary computed tomographic angiography (CCTA), with blood samples collected immediately prior to contrast administration. Plasma fatty acids were quantified as a percentage of total plasma fatty acids and evaluated for associations with CAD burden, including coronary artery calcium score (CACS), CACS percentile, Gensini score, soft plaque score, and atrial fibrillation (AF). Associations were assessed using multivariate logistic regression, adjusting for age, sex, and cardiovascular risk factors. Higher plasma omega-6 levels were inversely associated with CACS (CAC+; odds ratio [OR] = 0.93, 95% confidence interval [CI] = 0.90–0.97) with similar inverse associations observed for Gensini and soft plaque scores. In contrast, monounsaturated (CAC + OR = 1.09, 95% CI = 1.03–1.15) and saturated fatty acids (CAC + OR = 1.08, 95% CI = 1.04–1.12) were positively associated with CAD burden. No consistent associations were observed with self-reported atrial fibrillation after multivariable adjustment. Plasma omega-6 fatty acids demonstrated inverse associations with imaging-defined CAD burden, suggesting a potential protective role that warrants investigation in longitudinal studies. Saturated and monounsaturated fatty acids were positively associated with CAD, aligning with prior evidence of their atherogenic potential.

The brainstem is the main region that innervates neurotransmitter release to the Hypothalamic-Pituitary Adrenal (HPA) axis and fronto-limbic circuits, two key brain circuits found to be dysfunctional in Major Depressive Disorder (MDD). However, the brainstem's role in MDD has only been evaluated in limited reports. Using Diffusion Tensor Imaging (DTI), we investigated whether major brainstem white matter tracts that relate to these two circuits differ in MDD patients compared to healthy controls. MDD patients (n = 95) and age- and gender-matched controls (n = 34) were assessed using probabilistic tractography of DTI to delineate three distinct brainstem tracts: the nigrostriatal tract (connecting brainstem to striatum), solitary tract (connecting brainstem to amygdala) and corticospinal tract (connecting brainstem to precentral cortex). Fractional anisotropy (FA) was used to measure the white matter integrity of these tracts, and measures were compared between MDD and control participants. MDD participants were characterized by a significant and specific decrease in white matter integrity of the right solitary tract (p<0.009 using independent t-test), which is a \"bottom up\" afferent pathway that connects the brainstem to the amygdala. This decrease was not related to symptom severity. The results provide new evidence to suggest that structural connectivity between the brainstem and the amygdala is altered in MDD. These results are interesting in light of predominant theories regarding amygdala-mediated emotional reactivity observed in functional imaging studies of MDD. The characterization of altered white matter integrity in the solitary tract in MDD supports the possibility of dysfunctional brainstem-amygdala connectivity impacting vulnerable circuits in MDD.