Long-term cardiometabolic health in people born after assisted reproductive technology: a multi-cohort analysis

Aims To examine associations of assisted reproductive technology (ART) conception (vs. natural conception: NC) with offspring cardiometabolic health outcomes and whether these differ with age. Methods and results Differences in systolic (SBP) and diastolic blood pressure (DBP), heart rate (HR), lipids, and hyperglycaemic/insulin resistance markers were examined using multiple linear regression models in 14 population-based birth cohorts in Europe, Australia, and Singapore, and results were combined using meta-analysis. Change in cardiometabolic outcomes from 2 to 26 years was examined using trajectory modelling of four cohorts with repeated measures. 35 938 (654 ART) offspring were included in the meta-analysis. Mean age ranged from 13 months to 27.4 years but was <10 years in 11/14 cohorts. Meta-analysis found no statistical difference (ART minus NC) in SBP (-0.53 mmHg; 95% CI:-1.59 to 0.53), DBP (-0.24 mmHg; -0.83 to 0.35), or HR (0.02 beat/min; -0.91 to 0.94). Total cholesterol (2.59%; 0.10-5.07), HDL cholesterol (4.16%; 2.52-5.81), LDL cholesterol (4.95%; 0.47-9.43) were statistically significantly higher in ART-conceived vs. NC offspring. No statistical difference was seen for triglycerides (TG), glucose, insulin, and glycated haemoglobin. Long-term follow-up of 17 244 (244 ART) births identified statistically significant associations between ART and lower predicted SBP/DBP in childhood, and subtle trajectories to higher SBP and TG in young adulthood; however, most differences were not statistically significant. Conclusion These findings of small and statistically non-significant differences in offspring cardiometabolic outcomes should reassure people receiving ART. Longer-term follow-up is warranted to investigate changes over adulthood in the risks of hypertension, dyslipidaemia, and preclinical and clinical cardiovascular disease.Acknowledgements We thank all cohort members and researchers who participated in the study. Cohort-specific acknowledgments can be found in Supplementary material online, Text S2. Data used in this study are available to bone fide researchers upon request to each cohort. Details of how to access the data are provided in Supplementary material online, Text S2. Please contact Professor Deborah Lawlor ([email protected]) and Dr Ahmed Elhakeem ([email protected]) if you have relevant data and would like to join the ART-Health Cohort Collaboration and contribute to future collaborations

Linking Symptom Inventories using Semantic Textual Similarity

An extensive library of symptom inventories has been developed over time to measure clinical symptoms, but this variety has led to several long standing issues. Most notably, results drawn from different settings and studies are not comparable, which limits reproducibility. Here, we present an artificial intelligence (AI) approach using semantic textual similarity (STS) to link symptoms and scores across previously incongruous symptom inventories. We tested the ability of four pre-trained STS models to screen thousands of symptom description pairs for related content - a challenging task typically requiring expert panels. Models were tasked to predict symptom severity across four different inventories for 6,607 participants drawn from 16 international data sources. The STS approach achieved 74.8% accuracy across five tasks, outperforming other models tested. This work suggests that incorporating contextual, semantic information can assist expert decision-making processes, yielding gains for both general and disease-specific clinical assessment

Genetic architecture of subcortical brain structures in 38,851 individuals

Subcortical brain structures are integral to motion, consciousness, emotions and learning. We identified common genetic variation related to the volumes of the nucleus accumbens, amygdala, brainstem, caudate nucleus, globus pallidus, putamen and thalamus, using genome-wide association analyses in almost 40,000 individuals from CHARGE, ENIGMA and UK Biobank. We show that variability in subcortical volumes is heritable, and identify 48 significantly associated loci (40 novel at the time of analysis). Annotation of these loci by utilizing gene expression, methylation and neuropathological data identified 199 genes putatively implicated in neurodevelopment, synaptic signaling, axonal transport, apoptosis, inflammation/infection and susceptibility to neurological disorders. This set of genes is significantly enriched for Drosophila orthologs associated with neurodevelopmental phenotypes, suggesting evolutionarily conserved mechanisms. Our findings uncover novel biology and potential drug targets underlying brain development and disease

The genetic architecture of the human cerebral cortex

The cerebral cortex underlies our complex cognitive capabilities, yet little is known about the specific genetic loci that influence human cortical structure. To identify genetic variants that affect cortical structure, we conducted a genome-wide association meta-analysis of brain magnetic resonance imaging data from 51,665 individuals. We analyzed the surface area and average thickness of the whole cortex and 34 regions with known functional specializations. We identified 199 significant loci and found significant enrichment for loci influencing total surface area within regulatory elements that are active during prenatal cortical development, supporting the radial unit hypothesis. Loci that affect regional surface area cluster near genes in Wnt signaling pathways, which influence progenitor expansion and areal identity. Variation in cortical structure is genetically correlated with cognitive function, Parkinson's disease, insomnia, depression, neuroticism, and attention deficit hyperactivity disorder

Variation in general supportive and preventive intensive care management of traumatic brain injury: a survey in 66 neurotrauma centers participating in the Collaborative European NeuroTrauma Effectiveness Research in Traumatic Brain Injury (CENTER-TBI) study

Abstract Background General supportive and preventive measures in the intensive care management of traumatic brain injury (TBI) aim to prevent or limit secondary brain injury and optimize recovery. The aim of this survey was to assess and quantify variation in perceptions on intensive care unit (ICU) management of patients with TBI in European neurotrauma centers. Methods We performed a survey as part of the Collaborative European NeuroTrauma Effectiveness Research in Traumatic Brain Injury (CENTER-TBI) study. We analyzed 23 questions focused on: 1) circulatory and respiratory management; 2) fever control; 3) use of corticosteroids; 4) nutrition and glucose management; and 5) seizure prophylaxis and treatment. Results The survey was completed predominantly by intensivists (n = 33, 50%) and neurosurgeons (n = 23, 35%) from 66 centers (97% response rate). The most common cerebral perfusion pressure (CPP) target was > 60 mmHg (n = 39, 60%) and/or an individualized target (n = 25, 38%). To support CPP, crystalloid fluid loading (n = 60, 91%) was generally preferred over albumin (n = 15, 23%), and vasopressors (n = 63, 96%) over inotropes (n = 29, 44%). The most commonly reported target of partial pressure of carbon dioxide in arterial blood (PaCO2) was 36–40 mmHg (4.8–5.3 kPa) in case of controlled intracranial pressure (ICP) < 20 mmHg (n = 45, 69%) and PaCO2 target of 30–35 mmHg (4–4.7 kPa) in case of raised ICP (n = 40, 62%). Almost all respondents indicated to generally treat fever (n = 65, 98%) with paracetamol (n = 61, 92%) and/or external cooling (n = 49, 74%). Conventional glucose management (n = 43, 66%) was preferred over tight glycemic control (n = 18, 28%). More than half of the respondents indicated to aim for full caloric replacement within 7 days (n = 43, 66%) using enteral nutrition (n = 60, 92%). Indications for and duration of seizure prophylaxis varied, and levetiracetam was mostly reported as the agent of choice for both seizure prophylaxis (n = 32, 49%) and treatment (n = 40, 61%). Conclusions Practice preferences vary substantially regarding general supportive and preventive measures in TBI patients at ICUs of European neurotrauma centers. These results provide an opportunity for future comparative effectiveness research, since a more evidence-based uniformity in good practices in general ICU management could have a major impact on TBI outcome

Joint analysis of area and thickness as a replacement for the analysis of cortical volume

Cortical surface area is an increasingly popular brain morphology metric that is ontogenetically and phylogenetically distinct from cortical thickness and offers a separate index of neurodevelopment and disease. However, the various existing methods for assessment of cortical surface area from magnetic resonance images have never been systematically compared. We show that the surface area method implemented in FreeSurfer corresponds closely to the exact, but computationally more demanding, mass-conservative (pycnophylactic) method, provided images are smoothed. Thus, the data produced by this method can be interpreted as estimates of cortical surface area, as opposed to areal expansion. In addition, focusing on the joint analysis of thickness and area, we compare an improved, analytic method for measuring cortical volume to a permutation based non-parametric combination (NPC) method. We analyze area, thickness and volume in young adults born preterm with very low birth weight, using both methods and show that NPC analysis is a more sensitive option for studying joint effects on area and thickness, giving equal weight to variation in both of these two morphological features

Predicting recovery in patients with mild traumatic brain injury and a normal CT using serum biomarkers and diffusion tensor imaging (CENTER-TBI): an observational cohort study

Background Even patients with normal computed tomography (CT) head imaging may experience persistent symptoms for months to years after mild traumatic brain injury (mTBI). There is currently no good way to predict recovery and triage patients who may benefit from early follow-up and targeted intervention . We aimed to assess if existing prognostic models can be improved by serum biomarkers or diffusion tensor imaging metrics (DTI) from MRI, and if serum biomarkers can identify patients for DTI. Methods We included 1025 patients aged >18 years with a Glasgow Coma Score >12 and normal CT from the Collaborative European NeuroTrauma Effectiveness Research in Traumatic Brain Injury (CENTER-TBI) study which recruited between December 19,2014 and December 17, 2017 (NCT02210221). Biomarkers (GFAP, NFL, S100B) were obtained at a median of 8·8h (Q1-Q3 4·2-16·7) and DTI at 13 days (3-19) after injury. DTI metrics were available in 153 patients for 48 white matter tracts (ICBM-DTI-81 atlas). Incomplete recovery at three months was defined as an extended Glasgow Outcome Scale score <8. Existing prognostic models were fitted with and without biomarkers, or with and without DTI, and internally validated using bootstrapping. Findings 385 (38%) patients had incomplete recovery. Adding biomarkers did not improve performance beyond the best existing clinical prognostic model [optimism-corrected AUC 0·69 (95% CI 0·65-0·72) and R2 17% (11-22)]. Adding DTI metrics significantly enhanced all models [best optimism-corrected AUC 0·82 (0·79-0·85) and R2 75% (39-100)]. The top three prognostic tracts were the left posterior thalamic radiation, left superior cerebellar peduncle and right uncinate fasciculus. Serum biomarkers could have avoided 1 in 5 DTI scans, with GFAP <12h and NFL 12-24h from injury performing best. Interpretation DTI substantially improved existing prognostic models for functional outcome in patients with mTBI and a normal CT, and biomarkers could help select patients for MRI. If validated, DTI could allow for targeted follow-up and enrichment of clinical trials of early interventions to improve outcome.The research leading to these results was supported by the European Union's Seventh Framework Programme (FP7/2007-2013) under grant agreement 602150 (CENTER-TBI). Additional funding was obtained from the Hannelore Kohl Stiftung (Germany), from OneMind (USA), from Integra LifeSciences (USA), from NeuroTrauma Sciences (US), the UK National Institute of Health and Care Research (NIHR) Biomedical Research Centre at Cambridge; the Technology Platform funding provided by the UK Department of Health. SR was supported by a Wellcome Trust PhD Fellowship (222213/Z/20/Z) and an NIHR Clinical Lectureship. EC was supported by project no. TKP2021-EGA-16 has been implemented with the support provided from the National Research, Development and Innovation Fund of Hungary, financed under the TKP2021-EGA funding scheme. JPP is supported by a grant from the Academy of Finland (Grant 17379). DKM was supported by an NIHR Senior Investigator award and by the TBI-REPORTER Grant (UK Research & Innovation (UKRI) Grant No: MR/Y008502/1), which is supported by a multi-funder consortium consisting of: Medical Research Council, UK; National institute for Health and Care Research, UK; UK Ministry of Defence, and Alzheimer’s Research UK. VFJN was supported by an Academy of Medical Sciences / The Health Foundation Clinician Scientist Fellowship and an NIHR Rosetrees Trust Advanced Fellowship NIHR302544, which is funded in partnership by the NIHR and Rosetrees Trust. The views expressed are those of the author(s) and not necessarily those of the NIHR, Rosetrees Trust or the Department of Health and Social Care. The funders of the study had no role in study design, data collection, data analysis, data interpretation, or writing of the report. We thank all patients and investigators who participated in the CENTER-TBI study