NextGEM: Next-Generation Integrated Sensing and Analytical System for Monitoring and Assessing Radiofrequency Electromagnetic Field Exposure and Health

The evolution of emerging technologies that use Radio Frequency Electromagnetic Field (RF-EMF) has increased the interest of the scientific community and society regarding the possible adverse effects on human health and the environment. This article provides NextGEM’s vision to assure safety for EU citizens when employing existing and future EMF-based telecommunication technologies. This is accomplished by generating relevant knowledge that ascertains appropriate prevention and control/actuation actions regarding RF-EMF exposure in residential, public, and occupational settings. Fulfilling this vision, NextGEM commits to the need for a healthy living and working environment under safe RF-EMF exposure conditions that can be trusted by people and be in line with the regulations and laws developed by public authorities. NextGEM provides a framework for generating health-relevant scientific knowledge and data on new scenarios of exposure to RF-EMF in multiple frequency bands and developing and validating tools for evidence-based risk assessment. Finally, NextGEM’s Innovation and Knowledge Hub (NIKH) will offer a standardized way for European regulatory authorities and the scientific community to store and assess project outcomes and provide access to findable, accessible, interoperable, and reusable (FAIR) data

Genome-Wide and Abdominal MRI-Imaging Data Provides Evidence that a Genetically Determined Favourable Adiposity Phenotype is Characterized by Lower Ectopic Liver Fat and Lower Risk of Type 2 Diabetes, Heart Disease and Hypertension

Recent genetic studies have identified alleles associated with opposite effects on adiposity and risk of type 2 diabetes. We aimed to identify more of these variants and test the hypothesis that such favorable adiposity alleles are associated with higher subcutaneous fat and lower ectopic fat. We combined MRI data with genome-wide association studies of body fat percentage (%) and metabolic traits. We report 14 alleles, including 7 newly characterized alleles, associated with higher adiposity but a favorable metabolic profile. Consistent with previous studies, individuals carrying more favorable adiposity alleles had higher body fat % and higher BMI but lower risk of type 2 diabetes, heart disease, and hypertension. These individuals also had higher subcutaneous fat but lower liver fat and a lower visceral-to-subcutaneous adipose tissue ratio. Individual alleles associated with higher body fat % but lower liver fat and lower risk of type 2 diabetes included those in PPARG, GRB14, and IRS1, whereas the allele in ANKRD55 was paradoxically associated with higher visceral fat but lower risk of type 2 diabetes. Most identified favorable adiposity alleles are associated with higher subcutaneous and lower liver fat, a mechanism consistent with the beneficial effects of storing excess triglycerides in metabolically low-risk depots.</p

Trans-ancestry meta-analyses identify rare and common variants associated with blood pressure and hypertension

High blood pressure is a major risk factor for cardiovascular disease and premature death. However, there is limited knowledge on specific causal genes and pathways. To better understand the genetics of blood pressure, we genotyped 242,296 rare, low-frequency and common genetic variants in up to ~192,000 individuals, and used ~155,063 samples for independent replication. We identified 31 novel blood pressure or hypertension associated genetic regions in the general population, including three rare missense variants in RBM47, COL21A1 and RRAS with larger effects (>1.5mmHg/allele) than common variants. Multiple rare, nonsense and missense variant associations were found in A2ML1 and a low-frequency nonsense variant in ENPEP was identified. Our data extend the spectrum of allelic variation underlying blood pressure traits and hypertension, provide new insights into the pathophysiology of hypertension and indicate new targets for clinical intervention

Large-scale exome array summary statistics resources for glycemic traits to aid effector gene prioritization

Abstract Background: Genome-wide association studies for glycemic traits have identified hundreds of loci associated with these biomarkers of glucose homeostasis. Despite this success, the challenge remains to link variant associations to genes, and underlying biological pathways. Methods: To identify coding variant associations which may pinpoint effector genes at both novel and previously established genome-wide association loci, we performed meta-analyses of exome-array studies for four glycemic traits: glycated hemoglobin (HbA1c, up to 144,060 participants), fasting glucose (FG, up to 129,665 participants), fasting insulin (FI, up to 104,140) and 2hr glucose post-oral glucose challenge (2hGlu, up to 57,878). In addition, we performed network and pathway analyses. Results: Single-variant and gene-based association analyses identified coding variant associations at more than 60 genes, which when combined with other datasets may be useful to nominate effector genes. Network and pathway analyses identified pathways related to insulin secretion, zinc transport and fatty acid metabolism. HbA1c associations were strongly enriched in pathways related to blood cell biology. Conclusions: Our results provided novel glycemic trait associations and highlighted pathways implicated in glycemic regulation. Exome-array summary statistic results are being made available to the scientific community to enable further discoveries.Abstract Background: Genome-wide association studies for glycemic traits have identified hundreds of loci associated with these biomarkers of glucose homeostasis. Despite this success, the challenge remains to link variant associations to genes, and underlying biological pathways. Methods: To identify coding variant associations which may pinpoint effector genes at both novel and previously established genome-wide association loci, we performed meta-analyses of exome-array studies for four glycemic traits: glycated hemoglobin (HbA1c, up to 144,060 participants), fasting glucose (FG, up to 129,665 participants), fasting insulin (FI, up to 104,140) and 2hr glucose post-oral glucose challenge (2hGlu, up to 57,878). In addition, we performed network and pathway analyses. Results: Single-variant and gene-based association analyses identified coding variant associations at more than 60 genes, which when combined with other datasets may be useful to nominate effector genes. Network and pathway analyses identified pathways related to insulin secretion, zinc transport and fatty acid metabolism. HbA1c associations were strongly enriched in pathways related to blood cell biology. Conclusions: Our results provided novel glycemic trait associations and highlighted pathways implicated in glycemic regulation. Exome-array summary statistic results are being made available to the scientific community to enable further discoveries

Mendelian randomisation analyses of UK Biobank and published data suggest that increased adiposity lowers risk of breast and prostate cancer

AbstractBreast (BCa) and prostate (PrCa) cancer are the first and second most common types of cancer in women and men, respectively. We aimed to explore the causal effect of adiposity on BCa and PrCa risk in the UK Biobank and published data. We used Mendelian randomisation (MR) to assess the causal effect of body mass index (BMI), body fat percentage (BFP), waist circumference (WC), hip circumference (HC), and waist-to-hip ratio (WHR) on BCa and PrCa risk. We found that increased BMI, WC and HC decreased the risk of breast cancer (OR 0.70 per 5.14 kg/m2 [0.59–0.85, p = 2.1 × 10–4], 0.76 per 12.49 cm [60–0.97, p = 0.028] and 0.73 per 10.31 cm [0.59–0.90, p = 3.7 × 10–3], respectively) and increased WC and BMI decreased the risk of prostate cancer (0.68 per 11.32 cm [0.50–0.91, p = 0.01] and 0.76 per 10.23 kg/m2 [0.61–0.95, p = 0.015], respectively) in UK Biobank participants. We confirmed our results with a two-sample-MR of published data. In conclusion, our results suggest a protective effect of adiposity on the risk of BCa and PrCa highlighting the need to re-evaluate the role of adiposity as cancer risk factor.</jats:p

A risk and conformity assessment framework to ensure security and resilience of healthcare systems and medical supply chain

In recent years, the healthcare sector has undergone a significant digital transformation, driven by the rise of the Internet of Medical Things and the exponential use of connected medical devices in healthcare service delivery. This transformation offers numerous benefits, including enhanced patient data collection, processing, and informed treatment decisions. Despite these advantages, digital adoption brings several security challenges that pose considerable risks to overall healthcare service delivery. Additionally, connected medical devices must comply with sector-specific regulatory requirements to ensure trustworthiness and facilitate their broader adoption in the healthcare sector. There is, therefore, a pressing need to understand and manage these risks and compliance issues to secure and strengthen the resilience of healthcare systems. This work addresses these needs by introducing a novel Risk and Conformity Assessment Framework and Certification Scheme, implemented within an agile Information Security Management System context to enhance the security and resilience of healthcare systems. The framework leverages Artificial Intelligence (AI) in risk management practices, improving security assessments, risk prediction, security control implementation, and continuous monitoring. AI algorithms analyze large data volumes from various sources, enabling efficient processing and the identification of potential risk patterns. Additionally, AI-driven automation tools ensure consistent deployment of security controls, while continuous AI monitoring detects abnormal activities and enables rapid response to security incidents. The proposed Cybersecurity Certification Scheme incorporates AI-based security assessments into the certification process, facilitating efficient conformity assurance. This scheme also promotes a collaborative approach with relevant regulatory bodies to achieve compliance. While this work introduces a conceptual framework, its implementation and potential refinements remain subjects for future research. Further studies are necessary to validate its effectiveness, enhance its components, and evaluate its practical application in real-world healthcare environments.</p

NextGEM: Next-Generation Integrated Sensing and Analytical System for Monitoring and Assessing Radiofrequency Electromagnetic Field Exposure and Health

The evolution of emerging technologies that use Radio Frequency Electromagnetic Field (RF-EMF ) has increased the interest of the scientific community and society regarding the possible adverse effects on human health and the environment. This article provides NextGEM’s vision toassure safety for EU citizens when employing existing and future EMF-based telecommunication technologies. This is accomplished by generating relevant knowledge that ascertains appropriate prevention and control/actuation actions regarding RF-EMF exposure in residential, public, and occupational settings. Fulfilling this vision, NextGEM commits to the need for a healthy livingand working environment under safe RF-EMF exposure conditions that can be trusted by people and be in line with the regulations and laws developed by public authorities. NextGEM provides a framework for generating health-relevant scientific knowledge and data on new scenarios of exposure to RF-EMF in multiple frequency bands and developing and validating tools for evidence-based risk assessment. Finally, NextGEM’s Innovation and Knowledge Hub (NIKH) will offer a standardized way for European regulatory authorities and the scientific community to store and assess project outcomes and provide access to findable, accessible, interoperable, and reusable (FAIR) data.Electronic

Truncating Homozygous Mutation of Carboxypeptidase E (CPE) in a Morbidly Obese Female with Type 2 Diabetes Mellitus, Intellectual Disability and Hypogonadotrophic Hypogonadism

Carboxypeptidase E is a peptide processing enzyme, involved in cleaving numerous peptide precursors, including neuropeptides and hormones involved in appetite control and glucose metabolism. Exome sequencing of a morbidly obese female from a consanguineous family revealed homozygosity for a truncating mutation of the CPE gene (c.76_98del; p.E26RfsX68). Analysis detected no CPE expression in whole blood-derived RNA from the proband, consistent with nonsense-mediated decay. The morbid obesity, intellectual disability, abnormal glucose homeostasis and hypogonadotrophic hypogonadism seen in this individual recapitulates phenotypes in the previously described fat/fat and Cpe knockout mouse models, evidencing the importance of this peptide/hormone-processing enzyme in regulating body weight, metabolism, and brain and reproductive function in humans