Genetic Data Research Articles

Utility of a Systolic Blood Pressure Polygenic Risk Score With Chlorthalidone Response

The clinical utility of polygenic risk scores (PRS) for blood pressure (BP) response to antihypertensive treatment (AHT) has not been elucidated. To investigate the ability of a systolic BP (SBP) PRS to predict AHT response and apparent treatment-resistant hypertension (aTRH). The Genetics of Hypertension Associated Treatments (GenHAT) study was an ancillary pharmacogenomic study to the Antihypertensive and Lipid-Lowering Treatment to Prevent Heart Attack Trial (ALLHAT). ALLHAT, which enrolled participants aged 55 years or older with hypertension (HTN) starting in February 1994, completed follow-up in March 2002. The current study was conducted from a subset of Black GenHAT participants randomized to the treatment groups of either chlorthalidone (n = 3745) or lisinopril (n = 2294), with genetic data available from a prior genetic association study. The current study's objective was to examine the association of the SBP PRS to AHT response over 6 months, as well as to examine the predictive accuracy of the SBP PRS with aTRH. The current analysis took place in February 2023, with additional analyses conducted in July 2024. An SBP PRS (comprising 1 084 157 genetic variants) stratified as quintiles and per SD. The primary outcome was change in SBP (ΔSBP) and diastolic BP (ΔDBP) over 6 months. aTRH was defined as the use of 3 AHTs with uncontrolled HTN at year 3 of follow-up or taking 4 or more AHTs at year 3 of follow-up, regardless of BP. Baseline demographics were compared across PRS quintiles using Kruskal-Wallis or χ2 tests as appropriate. The least-square means of BP response were calculated through multivariable adjusted linear regression, and multivariable adjusted logistic regression was used to calculate the odds ratios and 95% confidence intervals for aTRH. Among 3745 Black GenHAT participants randomized to chlorthalidone treatment, median (IQR) participant age was 65 (60-71) years, and 2064 participants (55.1%) were female. Each increasing quintile of the SBP PRS from 1 to 5 was associated with a reduced BP response to treatment over 6 months. Participants in the lowest quintile experienced a mean ΔSBP of -10.01 mm Hg (95% CI, -11.11 to -8.90) compared to -6.57 mm Hg (95% CI, -7.67 to -5.48) for participants in the median quintile. No associations were observed between the SBP PRS and BP response to lisinopril. Participants in the highest PRS quintile had 67% higher odds of aTRH compared to those in the median quintile (odds ratio, 1.67; 95% CI, 1.19-2.36). These associations were independently validated. In this genetic association study, Black individuals with HTN at a lower genetic risk of elevated BP experienced an approximately 3.5 mm Hg-greater response to chlorthalidone compared with those at an intermediate genetic risk of elevated BP. SBP PRS may also identify individuals with HTN harboring a higher risk of treatment-resistant HTN. Overall, SBP PRS demonstrates potential to identify those who may have greater benefit from chlorthalidone, but future research is needed to determine if PRS can inform initiation and choice of treatment among individuals with HTN.

A Feature-Fusion Technique-Based Alzheimer's Disease Classification Using Magnetic Resonance Imaging.

Early identification of Alzheimer's disease (AD) is essential for optimal treatment and management. Deep learning (DL) technologies, including convolutional neural networks (CNNs) and vision transformers (ViTs) can provide promising outcomes in AD diagnosis. However, these technologies lack model interpretability and demand substantial computational resources, causing challenges in the resource-constrained environment. Hybrid ViTs can outperform individual ViTs by visualizing key features with limited computational power. This synergy enhances feature extraction and promotes model interpretability. Thus, the authors present an innovative model for classifying AD using MRI images with limited computational resources. The authors improved the AD feature-extraction process by modifying the existing ViTs. A CatBoost-based classifier was used to classify the extracted features into multiple classes. The proposed model was generalized using the OASIS dataset. The model obtained an exceptional classification accuracy of 98.8% with a minimal loss of 0.12. The findings highlight the potential of the proposed AD classification model in providing an interpretable and resource-efficient solution for healthcare centers. To improve model robustness and applicability, subsequent research can include genetic and clinical data.

42 Clinical features and severity of COVID-19 with respiratory virus coinfections versus SARS-CoV-2 monoinfection in hospitalized children: A Canadian national surveillance study

Abstract Background The co-circulation of SARS-CoV-2 alongside other respiratory viruses has led to the risk of coinfections, potentially intensifying the severity of cases, especially in children. Objectives This study examined the epidemiology, clinical characteristics, and outcomes of SARS-CoV-2 respiratory virus coinfections in comparison to SARS-CoV-2 monoinfections in hospitalized children. Design/Methods A nationwide surveillance study was conducted to assess paediatric COVID-19-related hospitalizations across Canada from April 2020 to May 2022. Data were captured through two datasets covering ~90% of all Canadian tertiary-care paediatric beds: The Canadian Paediatric Surveillance Program and the Canadian Immunization Monitoring Program, ACTive. Coinfections were defined as the simultaneous detection of SARS-CoV-2 and ≥1 other respiratory virus. Severe infection was defined as intensive care, ventilatory, or hemodynamic support needs, organ systems complications, or death. Variables and outcomes were summarized and compared, and risk ratios were computed using Poisson regression, adjusting for age, gender, comorbid conditions, SARS-CoV-2 lineage, and vaccination status. Results Out of 1501 COVID-19-related hospitalizations, 163 (10.9%) had documented coinfections with 44/163 [27%] involving SARS-COV-2 plus ≥2 other respiratory viruses. The majority of SARS-CoV-2 monoinfections (1176/1501, 87.9%) and coinfections (139/163, 85.3%) belonged to the Omicron era (Figure A). RSV (66/163, 40.5%) and Enterovirus/rhinovirus (61/163, 37.4%) coinfections were the most common. Coinfection cases were significantly younger than monoinfection cases (median age 1.2 [IQR:0.3-3.3] vs 1.6 [IQR:0.3-7.0] years, p=0.04). Overall, severe disease was more common among cases with any coinfection (38.0%) than SARS-CoV-2 monoinfection (25.7%; adjusted risk ratio 1.45, 95% confidence interval 1.17-1.80) (Figure B). In particular, we observed that severe outcomes were significantly higher in SARS-CoV-2 coinfections compared to monoinfections during the Omicron era (Figure C-D). Overall, 26/61 (42.6%) Enterovirus/Rhinovirus and 20/66 (30.3%) RSV coinfections were associated with severe outcomes. Conclusion Children with documented coinfections had more severe respiratory disease compared to SARS-COV-2 monoinfections. However, children with severe COVID-19 may have been more likely tested for multiple viruses, leading to a risk of underestimation of coinfections among children with milder disease. Further work is needed to assess how different virus coinfections may affect children and which, if any, may be a predominant driver of disease severity. 1Severe disease was defined as intensive care, ventilatory, or hemodynamic support requirements, organ system complications, or death. 2Lineage was first assigned based on available genetic sequencing data. If missing, lineage was imputed based on the dominant circulating lineage at the provincial level according to the GISAID database.

A comprehensive framework for trans-ancestry pathway analysis using GWAS summary data from diverse populations.

As more multi-ancestry GWAS summary data become available, we have developed a comprehensive trans-ancestry pathway analysis framework that effectively utilizes this diverse genetic information. Within this framework, we evaluated various strategies for integrating genetic data at different levels-SNP, gene, and pathway-from multiple ancestry groups. Through extensive simulation studies, we have identified robust strategies that demonstrate superior performance across diverse scenarios. Applying these methods, we analyzed 6,970 pathways for their association with schizophrenia, incorporating data from African, East Asian, and European populations. Our analysis identified over 200 pathways significantly associated with schizophrenia, even after excluding genes near genome-wide significant loci. This approach substantially enhances detection efficiency compared to traditional single-ancestry pathway analysis and the conventional approach that amalgamates single-ancestry pathway analysis results across different ancestry groups. Our framework provides a flexible and effective tool for leveraging the expanding pool of multi-ancestry GWAS summary data, thereby improving our ability to identify biologically relevant pathways that contribute to disease susceptibility.

A tip of the iceberg: genome survey indicated a complex evolutionary history of Garuga Roxb. species

Background Garuga Roxb. is a genus endemic to southwest China and other tropical regions in Southeast Asia facing risk of extinction due to the loss of tropical forests and changes in land use. Conducting a genome survey of G. forrestii contribute to a deeper understanding and conservation of the genus.ResultsThis study utilized genome survey of G. forrestii generated approximately 54.56 GB of sequence data, with approximately 112 × coverage. K-mer analysis indicated a genome size of approximately 0.48 GB, smaller than 0.52GB estimated by flow cytometry. The heterozygosity is of about 0.54%, and a repeat rate of around 51.54%. All the shotgun data were assembled into 339,729 scaffolds, with an N50 of 17,344 bp. The average content of guanine and cytosine was approximately 35.16%. A total of 330,999 SSRs were detected, with mononucleotide repeats being the most abundant at 70.16%, followed by dinucleotide repeats at 20.40%. We conducted a preliminary ploidy assessment using Smudgeplot and observed a clear bimodal distribution in G. forrestii at 1/2 relative coverage depth and total coverage depth (2n), suggesting a potential diploid genome structure. A pseudo chromosome of G. forrestii and a gemone of Boswellia sacra were used as reference genome to perform a primer population resequencing analysis within three Garuga species. Principal component analysis (PCA) indicated three distinct groups, but genome wide phylogenetics represented conflicting both between the dataset of different reference genomes and between maternal and nuclear genome.ConclusionIn summary, the genome of G. forrestii is small, and the phylogenetic relationships within the Garuga genus are complex. The genetic data presented in this study holds significant value for comprehensive whole-genome analyses, the evaluation of population genetic diversity, investigations into adaptive evolution, the advancement of artificial breeding efforts, and the support of species conservation and restoration initiatives. Ultimately, this research contributes to reinforcing the conservation and management of natural ecosystems, promoting biodiversity conservation, and advancing sustainable development.

Discordance between preclinical and clinical testing of NaV1.7-selective inhibitors for pain.

The voltage-gated sodium channel NaV1.7 plays an important role in pain processing according to genetic data. Those data made NaV1.7 a popular drug target, especially since its relatively selective expression in nociceptors promised pain relief without the adverse effects associated with broader sodium channel blockade. Despite encouraging preclinical data in rodents, NaV1.7-selective inhibitors have not yet proven effective in clinical trials. Discrepancies between preclinical and clinical results should raise alarms. We reviewed preclinical and clinical reports on the analgesic efficacy of NaV1.7-selective inhibitors and found critical differences in several factors. Putting aside species differences, most preclinical studies tested young male rodents with limited genetic variability, inconsistent with the clinical population. Inflammatory pain was the most common preclinical chronic pain model whereas nearly all clinical trials focused on neuropathic pain despite some evidence suggesting NaV1.7 channels are not essential for neuropathic pain. Preclinical studies almost exclusively measured evoked pain whereas most clinical trials assessed average pain intensity without distinguishing between evoked and spontaneous pain. Nearly all preclinical studies gave a single dose of drug unlike the repeat dosing used clinically, thus precluding preclinical data from demonstrating whether tolerance or other slow processes occur. In summary, preclinical testing of NaV1.7-selective inhibitors aligned poorly with clinical testing. Beyond issues that have already garnered widespread attention in the pain literature, our results highlight the treatment regimen and choice of pain model as areas for improvement.

Assessing Variance in Male Reproductive Skew Based on Long-Term Data in Free-Ranging Rhesus Macaques.

The unequal share in male reproduction (male reproductive skew) has been reported across primate species. To explain the distribution of male reproduction within groups various skew models have been applied to primates, however the "dynamic tug-of-war" model first accounted for the specifics of primate sociality. This model assumes that an increase in the number of competing males, a high degree of female cycle synchrony and their interaction will result in a lower degree of male reproductive skew. Here, we first tested the predictors of this model in rhesus macaques (Macaca mulatta) using long-term demographic and genetic data (up to 9 groups over 22 seasons) of the Cayo Santiago population (Puerto Rico). We also tested an extended version including group size and sex ratio and their interaction with female cycle synchrony. Finally, we investigated which male attributes determine the probability to become a top sire (highest paternity share per group and season). Confirming studies, male rhesus macaques exhibited low to medium degrees of reproductive skew based on the multinomial index, M. Unlike predicted, reproductive skew was higher in groups with more males. The extended analysis suggested that reproductive skew increased with group size in more male-biased groups, but decreased with group size in female-biased groups indicating that the numbers of male and female group members matter. We detected no effect of female cycle synchrony on the variance of reproductive skew. Finally, only maternal rank predicted the probability to become a top sire as long as males resided in their natal group. Together, our results did not support predictions by the dynamic skew model in rhesus macaques, but strengthen studies suggesting that other factors in addition to male-male competition predict male reproductive output in rhesus macaques. Future skew studies should consider female choice and alternative male mating strategies.

Role of artificial intelligence in predicting neurological outcomes in post cardiac resuscitation

Being an extremely high mortality rate condition, cardiac arrest cases have rightfully been evaluated via various studies and scoring factors for effective resuscitative practices and neurological outcomes post resuscitation. This narrative review aims to explore the role of Artificial Intelligence (AI) in predicting neurological outcomes post cardiac resuscitation. Methodology involved detailed review of all relevant recent studies of AI, different machine learning algorithms, prediction tools and assessing their benefit in predicting neurological outcomes in post cardiac resuscitation cases as compared to more traditional prognostic scoring systems and tools. Previously, outcome determining clinical, blood and radiological factors were prone to other influencing factors like limited accuracy and time constraints. Studies conducted also emphasized that to predict poor neurological outcomes, a more multimodal approach helped adjust for confounding factors, interpret diverse datasets and provide a reliable prognosis which only demonstrates need for AI to help overcome challenges faced. Advanced machine learning algorithms like Artificial Neural Networks (ANN) using supervised learning by AI have improved accuracy of prognostic models outperforming conventional models. Several real-world cases of effective AI powered algorithm models have been cited here. Studies comparing machine learning tools like XGBoost, AI Watson, hyperspectral imaging, ChatGPT-4 and AI based gradient boosting have noted their beneficial uses. AI could help reduce workload, healthcare costs and help personalize care, process vast genetic and lifestyle data and help reduce side effects from treatments. Limitations of AI have been covered extensively in this article including data quality, bias, privacy issues and transparency. Our objectives should be to use more diverse data sources, use interpretable data output giving process explanation, validation method and implement policies to safeguard patient data. Despite the limitations, the advancements already made by AI and its potential in predicting neurological outcomes in post cardiac resuscitation cases has been quite promising and boosts a continually improving system, albeit requiring close human supervision with training and improving models, with plans to educate clinicians, the public and sharing collected data.

ParthenoGenius: A User-Friendly Heuristic for Inferring Presence and Mechanism of Facultative Parthenogenesis from Genetic and Genomic Data Sets.

Facultative parthenogenesis (FP), or asexual reproduction by sexually-reproducing female animals, has been reported across several clades of vertebrates and is increasingly being recognized as a reproductive mechanism with significant implications for the genetic variation of captive and wild populations. The definitive identification of parthenogens requires molecular confirmation, with large genomic data sets necessary to accurately parse the parthenogenetic mechanism (i.e., endoduplication, gametic duplication, terminal fusion automixis, or central fusion automixis). Current methods for inferring FP from large genomic data sets are statistically intensive, require competency in R scripting for their execution, and are not designed for detection of facultative parthenogenesis or screening of large numbers of mother/offspring pairs, whereas small data sets (i.e., microsatellites) that can be evaluated visually lack the power to discriminate among FP mechanisms. Here, we present the user-friendly software program, ParthenoGenius, that uses intuitive logic to infer presence and mechanism of FP from even large genomic data sets comprising many mothers and offspring. ParthenoGenius runs relatively quickly and does not require the researcher to have knowledge of R scripting or statistics. ParthenoGenius was tested on eight empirical data sets, and in each case identified parthenogens (and parthenogenic mechanism when present) consistent with results of previous studies or corroborating evidence. ParthenoGenius will facilitate the rapid screening of large genomic data sets comprising many mothers and offspring for the presence and mechanism of parthenogenesis, improving our understanding of the frequency and phylogenetic distribution of FP across the animal kingdom.

Ambient air pollution and risk of allergic respiratory diseases in European and East Asian populations: A Mendelian randomization study

BackgroundAmbient air pollution has become a challenging global health issue since industrialization, especially affecting respiratory diseases. However, the causal link between air pollution and allergic respiratory diseases (ARDs) remains unclear due to confounding factors in conventional epidemiological studies across different populations. Thus, we aimed to clarify the causal associations between air pollution and ARDs in European and East Asian populations using Mendelian randomization (MR). MethodsMR utilizes genetic variants and provides a satisfactory level of causal evidence. Genetic data for exposures (PM2.5, PM2.5 absorbance, PM10, PMcoarse, NO2 and NOx) and outcomes (allergic rhinitis, chronic rhinosinusitis, asthma, and obesity related asthma) were obtained from genome-wide association studies. Instrumental variables were strictly filtered based on core assumptions. Two-sample MR and sensitivity analyses were conducted separately for European and East Asian populations. ResultsPMcoarse was causally associated with an increased risk of chronic rhinosinusitis (OR = 1.588 [1.002–2.518]; p = 0.049) and obesity related asthma (OR = 1.956 [1.012–3.780]; p = 0.046) in European population, and PM10 was associated with a decreased risk of allergic rhinitis in East Asian population (OR = 0.882 [0.798–0.974]; p = 0.013). No heterogeneity or pleiotropy was detected in any significant causal association. ConclusionOur findings indicate that ambient air pollution has opposite impacts on the etiology of ARDs in European and East Asian populations, which provides evidence for decisions on public policies and suggests that different responses to environmental factors such as air pollution may contribute to racial heterogeneity of ARDs.

Applications of Primate Genetics for Conservation and Management

Conservation genetics is the use of genetics to understand and mitigate the threats caused by anthropogenic activities, including habitat loss and fragmentation, wildlife trafficking, and emerging diseases. In this review, we discuss the role of primate conservation genetics in the development of effective conservation strategies, emphasizing the importance of maintaining genetic diversity to enhance adaptive potential and prevent extinction. First, we discuss studies of various primate species that exemplify how genetic data have been instrumental in accurately assessing threat levels, identifying trafficked animals and tracing their geographic origin, and studying how habitat loss affects primate populations. Subsequently, we describe the various molecular tools and analytical approaches employed in these studies. Lastly, we provide a bibliographic review of research in conservation genetics over the last 20 years. We conclude with a brief discussion of the limitations and challenges in this field in developing countries and recommendations for future research.

DGRPool, a web tool leveraging harmonized Drosophila Genetic Reference Panel phenotyping data for the study of complex traits

Genome-wide association studies have advanced our understanding of complex traits, but studying how a GWAS variant can affect a specific trait in the human population remains challenging due to environmental variability. Drosophila melanogaster is in this regard an excellent model organism for studying the relationship between genetic and phenotypic variation due to its simple handling, standardized growth conditions, low cost, and short lifespan. The Drosophila Genetic Reference Panel (DGRP) in particular has been a valuable tool for studying complex traits, but proper harmonization and indexing of DGRP phenotyping data is necessary to fully capitalize on this resource. To address this, we created a web tool called DGRPool (dgrpool.epfl.ch), which aggregates phenotyping data of 1034 phenotypes across 135 DGRP studies in a common environment. DGRPool enables users to download data and run various tools such as genome-wide (GWAS) and phenome-wide (PheWAS) association studies. As a proof-of-concept, DGRPool was used to study the longevity phenotype and uncovered both established and unexpected correlations with other phenotypes such as locomotor activity, starvation resistance, desiccation survival, and oxidative stress resistance. DGRPool has the potential to facilitate new genetic and molecular insights of complex traits in Drosophila and serve as a valuable, interactive tool for the scientific community.

Expression-Driven Genetic Dependency Reveals Targets for Precision Medicine.

Cancer cells are heterogeneous, each harboring distinct molecular aberrations and are dependent on different genes for their survival and proliferation. While successful targeted therapies have been developed based on driver DNA mutations, many patient tumors lack druggable mutations and have limited treatment options. Here, we hypothesize that new precision oncology targets may be identified through "expression-driven dependency", whereby cancer cells with high expression of a targeted gene are more vulnerable to the knockout of that gene. We introduce a Bayesian approach, BEACON, to identify such targets by jointly analyzing global transcriptomic and proteomic profiles with genetic dependency data of cancer cell lines across 17 tissue lineages. BEACON identifies known druggable genes, e.g., BCL2, ERBB2, EGFR, ESR1, MYC , while revealing new targets confirmed by both mRNA- and protein-expression driven dependency. Notably, the identified genes show an overall 3.8-fold enrichment for approved drug targets and enrich for druggable oncology targets by 7 to 10-fold. We experimentally validate that the depletion of GRHL2 , TP63 , and PAX5 effectively reduce tumor cell growth and survival in their dependent cells. Overall, we present the catalog of express-driven dependency targets as a resource for identifying novel therapeutic targets in precision oncology.

DGRPool, a web tool leveraging harmonized Drosophila Genetic Reference Panel phenotyping data for the study of complex traits.

Genome-wide association studies have advanced our understanding of complex traits, but studying how a GWAS variant can affect a specific trait in the human population remains challenging due to environmental variability. Drosophila melanogaster is in this regard an excellent model organism for studying the relationship between genetic and phenotypic variation due to its simple handling, standardized growth conditions, low cost, and short lifespan. The Drosophila Genetic Reference Panel (DGRP) in particular has been a valuable tool for studying complex traits, but proper harmonization and indexing of DGRP phenotyping data is necessary to fully capitalize on this resource. To address this, we created a web tool called DGRPool (dgrpool.epfl.ch), which aggregates phenotyping data of 1034 phenotypes across 135 DGRP studies in a common environment. DGRPool enables users to download data and run various tools such as genome-wide (GWAS) and phenome-wide (PheWAS) association studies. As a proof-of-concept, DGRPool was used to study the longevity phenotype and uncovered both established and unexpected correlations with other phenotypes such as locomotor activity, starvation resistance, desiccation survival, and oxidative stress resistance. DGRPool has the potential to facilitate new genetic and molecular insights of complex traits in Drosophila and serve as a valuable, interactive tool for the scientific community.

Massive citizen science sampling and integrated taxonomic approach unravel Danish cryptogam-dwelling tardigrade fauna

Tardigrade diversity and distribution are enigmatic in most parts of the globe, and only some European countries can boast of a relatively well-studied water bear fauna. However, even these suffer from the lack of genetic data, which would substantiate faunistic data and make biogeographic comparisons easier. Denmark has never been intensively and systematically researched in this regard, thus a citizen science sampling of cryptogams (mosses, liverworts, and lichens) was launched in spring 2023, aiming at a comprehensive biodiversity survey across this insular country. Nearly 700 samples were selected out of 8.000 sent to NHMD, based on the quality of samples, representativeness of various regions of Denmark, and the type of substrate to allow unravelling of potential ecological associations between tardigrades and cryptogams. Importantly, a large fraction of morphological identifications was backed up by DNA barcode data based on ITS-2 (1001 sequences), and in some cases also on COI (93 sequences) and ITS-1 (22 sequences) molecular markers, which are recognised DNA fragments used in species delimitation. We quadruple the number of known Danish limno-terrestrial tardigrade species (55 spp. reported in this paper vs. 14 spp. reported in literature so far, most of which were contentious due to the insufficient knowledge on tardigrade taxonomy), demonstrating the power of integrative taxonomy. No fewer than nine spp. are new to science. This is the first case where tardigrade fauna of an entire country is examined both from morphological and DNA barcoding data perspective.

Integrative taxonomic revision of the grasshopper genera Parapetasia Bolívar, 1884, and Loveridgacris Rehn, 1954 (Orthoptera, Pyrgomorphidae), with description of a new species of Loveridgacris

The taxonomic status of the Pyrgomorphid genera Parapetasia Bolívar, 1884, and Loveridgacris Rehn, 1954 is complex and challenging. Here, we use a combination of morphological, distributional, and genetic data to revise the two genera and provide new information on their diversity. We describe a new species, Loveridgacris tectiferussp. nov., from Tanzania and formally resurrect the status of Parapetasia rammei as a valid species within Parapetasia, resulting in two species in Parapetasia (P. femorata and P. rammei) and two in Loveridgacris (L. impotens and L. tectiferussp. nov.). We also sequenced the COI and 16S genes of 10 Pyrgomorphidae species and provided the first phylogeny of the group. Our data show that all species are clearly distinct and represent molecular operational taxonomic units (mOTUs), with the exceptions of L. impotens and L. tectiferussp. nov., which are morphologically clearly distinct but for which the concatenated sequence alignments of the two individual gene datasets (COI and 16S) do not provide sufficient information. In addition, high interspecific distances were found between Parapetasia and Loveridgacris. Moreover, the complete mitogenomes of L. impotens and L. tectiferussp. nov. were sequenced using next-generation sequencing technology. The total lengths of the assembled mitogenomes were 15,592 bp and 15,737 bp, representing 13 protein-coding genes, 22 transfer RNA genes, two ribosomal RNA genes and one D-loop region, respectively. To aid in identification, we present a key for the two genera, including a key to species. This study provides insights into the morphology, distribution, and phylogeny of Pyrgomorphidae in Africa.

Morphological data and DNA barcoding reveal the presence of the alien freshwater leech Helobdella octatestisaca (Hirudinida: Glossiphoniformes) in North Africa (Tunisia).

We hereby report the first occurrence of Helobdella octatestisaca in North Africa, specifically in Tunisia, as a likely introduced species from the Neotropical Region. Historically, leeches bearing a prominent chitinous scute on their dorsal surface were commonly diagnosed as H. stagnalis. Most probably, H. octatestisaca had previously been misidentified as H. stagnalis in Tunisia. The identification was primarily based on morphological evidence, supplemented by genetic data obtained from COI DNA barcoding. The morphology of the examined specimens was consistent with the original species description, notably characterized by the presence of four pairs of testisacs. To support our findings, we conducted a phylogenetic analysis using the Maximum Likelihood method based on COI alignment constructed with the newly obtained sequence from Tunisian specimens and complete or nearly complete 'Folmer fragment' sequences of congeners sourced from the GenBank database. This study highlights the first identification of H. octatestisaca in North Africa and suggests that previous records of H. stagnalis in Tunisia likely misidentified this species.

Update on Inherited Pediatric Motor Neuron Diseases: Clinical Features and Outcome.

Inherited pediatric motor neuron diseases (MNDs) are a group of neurodegenerative disorders characterized by the degeneration of motor neurons in the brain and the spinal cord. These diseases can manifest as early as infancy and originate from inherited pathogenic mutations in known genes. Key clinical features of MNDs include muscle weakness, hypotonia, and atrophy due to the degeneration of lower motor neurons or spasticity, hypertonia, and hyperreflexia caused by upper motor neuron dysfunction. The course of the disease varies among individuals and is influenced by the specific subtype. We performed a non-systematic, narrative clinical review, employing a systematic methodology for the literature search and article selection to delineate the features of hereditary pediatric motor neuron diseases. The growing availability of advanced molecular testing, such as whole-exome sequencing (WES) and whole-genome sequencing (WGS), has expanded the range of identified genetic factors. These advancements provide insights into the genetic complexity and underlying mechanisms of these disorders. As more MND-related genes are discovered, the accumulating genetic data will help prioritize promising candidate genes for future research. In some cases, targeted treatments based on specific genetic mechanisms have already emerged, underscoring the critical role of early and timely diagnosis in improving patient outcomes. Common MNDs include amyotrophic lateral sclerosis, spinal muscular atrophy, and bulbar spinal muscular atrophy. This narrative clinical review covers the clinical presentation, genetics, molecular features, and pathophysiology of inherited pediatric MNDs.

Unraveling the causal association between lifestyle and metabolic factors with endometrial cancer: evidence from a Mendelian randomization study

BackgroundEndometrial carcinoma (EC) remain a malignancy with incompletely understood risk factors. To address this knowledge gap, we employed mendelian randomization study to investigate potential protective and risk elements associated with endometrial cancer.MethodsWe conducted a two-sample Mendelian randomization (MR) study using genetic association data for overall EC and its subtypes from a large-scale genome-wide association study (GWAS). This GWAS encompassed 12,906 EC patients and 108,979 healthy controls. The EC cases were further categorized into 8758 endometrioid and 1230 non-endometrioid subtypes. To serve as instrumental variables, we identified independent genetic variants strongly associated with 5 lifestyle factors and 14 metabolic factors from relevant GWASs. Subsequently, we conducted univariable Mendelian randomization (MR) analyses.ResultsOur study revealed the relationship among EC with lifetime smoking index (OR: 1.43; 95% CI 1.05–1.96), frequency of alcohol consumption (OR:1.23; 95% CI 1.04–1.45), body mass index (BMI) (OR:1.82; 95% CI 1.64–2.01), type 2 diabetes mellitus (T2DM) (OR:1.06; 95% CI 1.00–1.12), and fasting insulin (OR:1.97; 95% CI 1.30–2.98). Conversely, inverse associations with EC were observed for education level (OR:0.72, 95% CI 0.62–0.83), moderate-level physical exercise (OR 0.35, 95% CI 0.15–0.84), and low-density lipoproteins (LDL) (OR 0.91, 95% CI 0.84–0.99).ConclusionsOur findings underscore a causal association between genetically predicted lifetime smoking index, alcohol intake frequency, BMI, T2DM, and fasting insulin with EC risk. Furthermore, our study highlights the potential protective effects of a high education level, moderate-intensity physical exercise, and LDL reduction against EC risk. This MR analysis provided valuable insights into underlying EC risk mechanisms and paved new ways for EC prevention strategies.

Genomic Data Privacy and the Right to Science: Issues of Balance

The paper examines the confidentiality of genomic data. According to the author, genomic data is a special concept in the field of personal data and requires increased regulatory guarantees of legal protection and safeguards. In addition, the author considers the issue of the grounds for disclosure and use of this type of information. According to the researcher, this is possible only if there is a public interest in conducting scientific research that contributes to the implementation of the health function by the state. The right to science, enshrined in the Universal Declaration of Human Rights of 1948, can serve as a regulatory basis for this. The author notes that this right has not yet been established at the level of national legislation, which significantly complicates its understanding and definition of restrictions in its implementation. The paper also emphasizes the uniqueness of genomic information, which is characterized by features of identifiability and relative danger. These features are specified by the author in terms of the purpose and scope of the use of genetic data, their informational content, as well as the degree of their influence on the rights of the relevant person. In conclusion, the author puts forward am idea of one best way to balance the right to science and genomic data privacy, through which it will be possible to ensure both effective legal protection and a stable course of scientific evolution and progress.