Establishing reference values for macro- and microvascular measurements in 4-to-5 year-old children of the ENVIRONAGE prospective birth cohort

Non-Invasive Retinal Vessel Analysis as a Predictor for Cardiovascular Disease

Cardiovascular disease (CVD) is the most frequent cause of death worldwide. The alterations in the microcirculation may predict the cardiovascular mortality. The retinal vasculature can be used as a model to study vascular alterations associated with cardiovascular disease. In order to quantify microvascular changes in a non-invasive way, fundus images can be taken and analysed. The central retinal arteriolar (CRAE), the venular (CRVE) diameter and the arteriolar-to-venular diameter ratio (AVR) can be used as biomarkers to predict the cardiovascular mortality. A narrower CRAE, wider CRVE and a lower AVR have been associated with increased cardiovascular events. Dynamic retinal vessel analysis (DRVA) allows the quantification of retinal changes using digital image sequences in response to visual stimulation with flicker light. This article is not just a review of the current literature, it also aims to discuss the methodological benefits and to identify research gaps. It highlights the potential use of microvascular biomarkers for screening and treatment monitoring of cardiovascular disease. Artificial intelligence (AI), such as Quantitative Analysis of Retinal vessel Topology and size (QUARTZ), and SIVA-deep learning system (SIVA-DLS), seems efficient in extracting information from fundus photographs and has the advantage of increasing diagnosis accuracy and improving patient care by complementing the role of physicians. Retinal vascular imaging using AI may help identify the cardiovascular risk, and is an important tool in primary cardiovascular disease prevention. Further research should explore the potential clinical application of retinal microvascular biomarkers, in order to assess systemic vascular health status, and to predict cardiovascular events.

Normal pediatric values of carotid artery intima-media thickness measured by B-mode ultrasound and radiofrequency echo tracking respecting the consensus: a systematic review

BACKGROUND

Carotid artery intima-media thickness (IMT) is a sub-clinical radiologic marker of atherosclerosis in children. It is associated with adult-onset vascular disease.

OBJECTIVE

To determine normal pediatric values of IMT from results observed in the literature.

METHODS

Our systematic review was conducted according to PRISMA guidelines. We reviewed 2298 English articles from inception to February 2023. Inclusion criteria included studies evaluating B-mode and radiofrequency (RF)-based IMT measurements based on the American Heart Association, the Association for European Pediatric Cardiology, the Mannheim Consensus, and the American Society of Echocardiography recommendations. A meta-analysis of aggregate data was conducted to obtain the confidence interval (CI) for IMT, using a 95% confidence level.

RESULTS

We obtained 88 B-mode-based IMT measurement studies with 6184 children and six radiofrequency echo-tracking-based studies with 766 children. Mean IMT in the pediatric population was 0.43 mm, 95% [CI] 0,42 to 0.44, using the B-mode technique, and 0.41 mm, 95% [CI] 0.36 to 0.45 using the radiofrequency technique. No significant relationship was detected between IMT and age (p value = 0.83). Finally, no significant effect of sex on IMT was found (p value = 0.82 for B-mode and p value = 0.62 for RF).

CONCLUSION

Based on the studies selected in this literature review, we were unable to conclude that there was a significant difference between the average IMT of boys and girls. No relationship was demonstrated between age and IMT. IMT is technique-specific, and normal values should be interpreted according to recommendations of recognized consensus to counteract the current heterogeneity in literature.

CLINICAL RELEVANCE STATEMENT

Technique and children-specific Intima media thickness measurements help clinicians and scientists to assess the risk of atherosclerosis in children.

KEY POINTS

• Intima-media thickness (IMT) does not correlate with age in children without risk factors. • According to current literature, there is no difference in IMT between healthy boys and girls. • There is heterogeneity, even with studies abiding by the official consensus.

Automated Retinal Vessel Analysis Based on Fundus Photographs as a Predictor for Non-Ophthalmic Diseases-Evolution and Perspectives

The study of retinal vessels in relation to cardiovascular risk has a long history. The advent of a dedicated tool based on digital imaging, i.e., the retinal vessel analyzer, and also other software such as Integrative Vessel Analysis (IVAN), Singapore I Vessel Assessment (SIVA), and Vascular Assessment and Measurement Platform for Images of the Retina (VAMPIRE), has led to the accumulation of a formidable body of evidence regarding the prognostic value of retinal vessel analysis (RVA) for cardiovascular and cerebrovascular disease (including arterial hypertension in children). There is also the potential to monitor the response of retinal vessels to therapies such as physical activity or bariatric surgery. The dynamic vessel analyzer (DVA) remains a unique way of studying neurovascular coupling, helping to understand the pathogenesis of cerebrovascular and neurodegenerative conditions and also being complementary to techniques that measure macrovascular dysfunction. Beyond cardiovascular disease, retinal vessel analysis has shown associations with and prognostic value for neurological conditions, inflammation, kidney function, and respiratory disease. Artificial intelligence (AI) (represented by algorithms such as QUantitative Analysis of Retinal vessel Topology and siZe (QUARTZ), SIVA-DLS (SIVA-deep learning system), and many others) seems efficient in extracting information from fundus photographs, providing prognoses of various general conditions with unprecedented predictive value. The future challenges will be integrating RVA and other qualitative and quantitative risk factors in a unique, comprehensive prediction tool, certainly powered by AI, while building the much-needed acceptance for such an approach inside the medical community and reducing the "black box" effect, possibly by means of saliency maps.

Association of indoor dust microbiota with cognitive function and behavior in preschool-aged children

BACKGROUND

Childhood cognitive development depends on neuroimmune interactions. Immunomodulation by early-life microbial exposure may influence neuropsychological function. In this study, we investigate the association between residential indoor microbiota and cognition and behavior among preschoolers.

RESULTS

Indoor-settled dust bacterial and fungal characteristics were assessed using 16S and ITS amplicon sequencing (microbial diversity) and qPCR measurements (microbial loads). Child behavior was assessed using four scales: peer relationship, emotional, conduct, and hyperactivity was assessed by the Strengths and Difficulties Questionnaire (SDQ). Cognitive function was assessed using four tasks of the Cambridge Neuropsychological Test Automated Battery (CANTAB) software. The first two tasks were designed to assess attention and psychomotor speed (Motor Screening (MOT) and Big/Little Circle (BLC)) and the last two to evaluate the child's visual recognition/working memory (Spatial Span (SSP) and Delayed Matching to Sample (DMS)). Among the 172 included children (age 4-6 years), we observed a 51% (95%CI;75%;9%) lower odds of children scoring not normal for hyperactivity and a decrease of 3.20% (95%CI, -6.01%; -0.30%) in BLC response time, for every IQR increase in fungal Shannon diversity. Contrarily, microbial loads were directly associated with SDQ scales and response time. For example, a 2-fold increase in Gram-positive bacterial load was associated with 70% (95%CI 18%; 156%) higher odds of scoring not normal for hyperactivity and an increase of 5.17% (95%CI 0.87%; 9.65%) in DMS response time.

CONCLUSIONS

Our findings show that early-life exposure to diverse indoor fungal communities is associated with better behavioral and cognitive outcomes, whereas higher indoor microbial load was associated with worse outcomes. Video Abstract.

Sex differences in pressure and flow waveform physiology across the life course

Cardiovascular disease (CVD) has long been deemed a disease of old men. However, in 2019 CVD accounted for 35% of all deaths in women and, therefore, remains the leading cause of death in both men and women. There is increasing evidence to show that risk factors, pathophysiology and health outcomes related to CVD differ in women compared with men, yet CVD in women remains understudied, underdiagnosed and undertreated. Differences exist between the sexes in relation to the structure of the heart and vasculature, which translate into differences in blood pressure and flow waveform physiology. These physiological differences between women and men may represent an important explanatory factor contributing to the sex disparity in CVD presentation and outcomes but remain understudied. In this review we aim to describe sex differences in arterial pressure and flow waveform physiology and explore how they may contribute to differences in CVD in women compared to men. Given that unfavourable alterations in the cardiovascular structure and function can start as early as in utero, we report sex differences in waveform physiology across the entire life course.

Residential green space can shape the indoor microbial environment

BACKGROUND

The influence of outdoor green space on microbial communities indoors has scarcely been investigated. Here, we study the associations between nearby residential green space and residential indoor microbiota.

METHODS

We collected settled dust from 176 living rooms of participants of the ENVIRONAGE birth cohort. We performed 16S and ITS amplicon sequencing, and quantitative PCR measurements of total bacterial and fungal loads to calculate bacterial and fungal diversity measures (Chao1 richness, Shannon and Simpson diversity indices) and relative abundance of individual taxa. Green spaces were estimated within 50m and 100m buffers around the residential address. We defined total residential green space using high-resolution land-cover data, further stratified in low-growing (height<3m) and high-growing green (height>3m). We used land-use data to calculate the residential nature. We ran linear regression models, adjusting for confounders and other potential determinants. Results are expressed as units change for an interquartile range (IQR) increase in residential green space and their 95% confidence intervals (CI).

RESULTS

After adjustment, we observed statistically significant associations between the indoor microbial diversity indices and nearby residential green space. For bacteria, the Shannon index was directly associated with residential nature (e.g. 0.08 units increase (CI:0.02,0.13) per IQR increase in nature within a 50m buffer). Fungal diversity was directly associated with high-growing residential green and inversely with low-growing green. For example, an IQR increase in high-growing green within a 50m buffer was associated with increases in 0.14 (CI:0.01,0.27) and 0.02 (CI:0.008,0.04) units in the Shannon and Simpson indices, respectively.

CONCLUSIONS

Nearby green space determines the diversity of indoor environment microbiota, and the type of green differently impacts bacterial and fungal diversity. Further research is needed to investigate in more detail possible microbial taxa compositions underlying the observed changes in indoor microbiota diversity and to explore their contribution to beneficial health effects associated with green space exposure.