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Porphyria is a group of rare metabolic disorders caused by mutations in the genes encoding crucial enzymes in the heme biosynthetic pathway. However, the lack of comprehensive genetic analysis of porphyria patients in the Chinese population makes identifying and diagnosing carriers of the condition challenging. Using the ChinaMAP database, we determined the frequencies of P/LP porphyria-associated gene variants according to the ACMG guidelines. We also calculated the carrier rates and prevalence of each type of porphyria in the Chinese population under Hardy–Weinberg equilibrium. Compared with the variants in the gnomAD database, the genetic spectrum of porphyria-related P/LP variants in the Chinese population is distinct. In the ChinaMAP database, we identified 23 variants. We estimated the carrier rates for autosomal dominant porphyrias (AIP, HCP, VP, PCT) in the Chinese population to be 1/1059, 1/1513, 1/10588, and 1/1765, respectively. For autosomal recessive porphyrias (ADP, EPP, HEP, CEP), the estimated carrier rates were 1/5294, 1/2117, 1/1765, and 1/2647, respectively, with predicted prevalence rates of 8.92 × 10−9, 7.51 × 10−5, 8.02 × 10−8, and 3.57 × 10−8, respectively. Notably, 12 of the variants we identified were unique to the Chinese population. The predicted prevalence rate of EPP was the highest among the various types of porphyria in the Chinese population, while the others were moderate to low. This is the first comprehensive genetic study on porphyria in the Chinese population. Clarifying the genetic characteristics of various porphyria types among the Chinese population provides scientifically sound reference data for both research and genetic screening to identify porphyria carriers. [ABSTRACT FROM AUTHOR]

Objective: This study examines the causal effects of varying exercise intensities on type 2 diabetes mellitus (T2D) through Mendelian randomization (MR) analysis, using genetic variants as instrumental variables. Methods: A two-sample MR analysis was performed, employing Inverse Variance Weighted (IVW) as the primary method, supported by weighted median, MREgger regression, MR-PRESSO, and MR robustness-adjusted contour scores. Data were obtained from the International Exercise Genetics Database (IEGD) and the Global Diabetes Research Consortium (GRC), encompassing over 150,000 individuals for exercise intensity and around 200,000 T2D patients and controls. SNPs linked to exercise intensity were selected based on genome-wide significance (P < 5 × 10^-8) and linkage disequilibrium criteria (distance >10,000 kb, r^2 < 0.001). Results: The IVW analysis suggested that high-intensity exercise might reduce T2D risk, but the association was not statistically significant (OR = 0.667, 95% CI = 0.104-4.255, P = 0.667). The wide confidence interval indicates uncertainty in the effect estimate. Low-intensity exercise showed no significant effect on T2D risk (OR ~ 1.0). Sensitivity analyses, including weighted median and MR-Egger regression, confirmed no significant association between high-intensity exercise and T2D risk. The MR-PRESSO analysis found no significant outliers, and the global test for pleiotropy was non-significant (P = 0.455). Cochran's Q test for heterogeneity in the IVW analysis was non-significant (Q = 12.45, P = 0.234), indicating consistency among SNP-derived estimates. Conclusion: High-intensity exercise potentially reduces T2D risk, but the association is not statistically significant. Further research is needed to understand the complex relationship between exercise intensity and T2D. [ABSTRACT FROM AUTHOR]

Summary Obesity is a major public health concern associated with a higher risk of various comorbidities. Some studies have explored the impact of obesity on cognitive function and, conversely, how lower intelligence might increase the risk of later obesity. The aim of this study is to analyze a complex relationship between body mass index (BMI) and intelligence quotient (IQ), employing a comprehensive approach, including a systematic review, meta‐analysis, and Mendelian randomization (MR). We extracted the data from Medline and Embase to identify relevant studies published since June 22, 2009. MR analysis relied on genetic databases such as the Genome‐Wide Association Study (GWAS) and the Genetic Investigation of Anthropometric Traits (GIANT) to explore potential causal relationships. The systematic review and meta‐analysis encompassed 34 and 17 studies, respectively. They revealed a substantial correlation between obesity and reduced IQ, particularly notable among school‐age children (mean difference −5.26; 95% CI: −7.44 to −3.09). Notably, within the IQ subgroup, verbal IQ also exhibited a significant association with a mean difference of −7.73 (95% CI: −14.70 to −0.77) in school‐age children. In contrast, the MR did not unveil a significant causal relationship between BMI and IQ, both in childhood and adulthood. This comprehensive analysis underscores a significant correlation between BMI and IQ, particularly in school‐age children. However, the MR analysis implies a potentially weaker causal relationship. Future large‐scale cohort studies should address potential confounding factors to provide further insights into the BMI‐IQ relationship. [ABSTRACT FROM AUTHOR]

The SETD1B gene, located on chromosome 12q24, is one of the chromatin‐modifying genes involved in epigenetic regulation of gene transcription. The phenotype of pathogenic variants in the SETD1B gene includes intellectual disability, seizures, and language delay (IDDSELD, OMIM 619000). In this study, we present a family consisting of consanguineous parents who died of cancer and their offspring. This family includes two cases diagnosed with autism spectrum disorder (ASD); six cases diagnosed with schizophrenia, bipolar disorder, or schizoaffective disorder; there cases diagnosed with cancer; and five cases who died of unknown causes in early childhood. Three affected members of this family agreed to genetic testing. We used whole exome sequencing. We report a novel in‐frame deletion variant of the SETD1B gene in a family with cases diagnosed with schizoaffective disorder and ASD without seizures and intellectual disability. It was found that the phenotypic features were inherited for at least three generations in the family we presented, and it was shown that the pathogenic variant of the SETD1B gene was transmitted from the affected parent to his affected children. In addition, the father was diagnosed with both schizoaffective disorder and leukemia. We proposed an association between rare variants of SETD1B and phenotypes of ASD and schizoaffective disorder without seizures and intellectual disability. The SETD1B gene is included in both the ASD genetic database of SFARI (https://gene.sfari.org/) and the cancer database of COSMIC (https://cancer.sanger.ac.uk/cosmic). However, there are very few reports of SETD1B gene variants as clinical entities. To our knowledge, the SETD1B gene variant has not been previously reported in an individual diagnosed with both a neuropsychiatric disorder and cancer. [ABSTRACT FROM AUTHOR]

Background: Despite being a major global cause of mortality, the exact underlying mechanisms of cardiovascular diseases (CVDs) remain uncertain. This study aimed to elucidate the possible pathological connection between circulating activated immune cell types and the advancement of CVD. Methods: A two-sample Mendelian randomization analysis was performed on publicly available genetic databases to examine the potential causal relationships among 731 immune phenotypes and CVD risks. The study focused on four distinct immune signatures: relative cell counts (RC), absolute cell counts (AC), morphological parameters (MP), and median fluorescence intensities (MFI). A sensitivity analysis was performed to assess the findings' consistency, robustness, and potential pleiotropic effects. Results: Significant associations between CVD and various immunophenotypes were observed in this study. Specifically, two phenotypes exhibited protective effects against CVD. The odds ratio (OR) for activated and secretory CD4+ regulatory T-cells (Tregs) was 0.757 [95% confidence interval (CI): 0.628–0.913; p = 0.004], whereas that for B-cell activating factor receptor on IgD−CD38+ memory B-cells was 0.654 (95% CI: 0.468–0.915; p = 0.013). Conversely, three major immunophenotypes were linked to heightened risks of CVD: CD80 on myeloid dendritic cells (OR: 1.181; 95% CI: 1.015–1.376; p = 0.032), the proportion of CD28+ CD45RA+ CD8+ T-cells in total T-cell population (OR: 1.064; 95% CI: 1.002–1.128; p = 0.041), and the proportion of CD28−CD45RA+ CD8+ T-cells in total T-cell population (OR: 1.005; 95% CI: 1.000–1.011; p = 0.045). Conclusion: This study underscores significant correlations between specific immune phenotypes and the risks associated with CVD onset, thus providing valuable perspectives for forthcoming clinical inquiries. [ABSTRACT FROM AUTHOR]

Autism spectrum disorder (ASD) is a neurodevelopmental condition characterized by social and communication difficulties, along with repetitive behaviors. While genetic factors play a significant role in ASD, the precise genetic landscape remains complex and not fully understood, particularly in non-syndromic cases. The study performed an in silico comparison of three genetic databases. ClinVar, SFARI Gene, and AutDB were utilized to identify relevant gene subset and genetic variations associated with non-syndromic ASD. Gene set enrichment analysis (GSEA) and protein–protein interaction (PPI) network analysis were conducted to elucidate the biological significance of the identified genes. The integrity of ASD-related gene subset and the distribution of their variations were statistically assessed. A subset of twenty overlapping genes potentially specific for non-syndromic ASD was identified. GSEA revealed enrichment of biological processes related to neuronal development and differentiation, synaptic function, and social skills, highlighting their importance in ASD pathogenesis. PPI network analysis demonstrated functional relationships among the identified genes. Analysis of genetic variations showed predominance of rare variants and database-specific distribution patterns. The results provide valuable insights into the genetic landscape of ASD and outline the genes and biological processes involved in the condition, while taking into account that the study relied exclusively on in silico analyses, which may be subject to biases inherent to database methodologies. Further research incorporating multi-omics data and experimental validation is warranted to enhance our understanding of non-syndromic ASD genetics and facilitate the development of targeted research, interventions and therapies. [ABSTRACT FROM AUTHOR]

The aim of this study was to describe the prenatal ultrasound findings of fetuses with skeletal dysplasia and to evaluate the genetic variations by molecular genetic analysis.Between August 1, 2018 and March 1, 2023, we conducted a retrospective case series at a tertiary referral center involving patients with fetal skeletal abnormalities. For cases referred for a possible diagnosis of fetal skeletal dysplasia, an ultrasound database and prenatal genetic counseling records were first searched. Terminated cases diagnosed with skeletal dysplasia by pathologic and radiologic findings and cases with skeletal dysplasia proven by postnatal clinical findings were included in the study.Between 2018 and 2023, a total of 64 cases were diagnosed as skeletal dysplasia based on radiologic findings, pathologic findings, and clinical features. The median week of the first ultrasound performed on patients is 19 0/7 weeks, while the median week of the ultrasound in which skeletal dysplasia is suspected is 21 3/7 weeks. Although micromelia was evaluated as a common feature in all cases, the most common concomitant anomaly was thoracic hypoplasia. Exome sequencing analysis was achieved in 31 (48 %) of cases. In 31 cases, in total of 35 pathogenic single gene mutations and 5 VUS (variants of uncertain significance) variants composing of 23 autosomal dominant, 10 autosomal recessive and 2 X linked recessive mutations were determined.Prenatal ultrasound findings can lead us to specific diagnoses, and with the appropriate molecular analysis method, a definitive diagnosis can be made without wasting time and money. [ABSTRACT FROM AUTHOR]

The therapeutic response to lithium in patients with bipolar disorder is highly variable and has a polygenic basis. Genome-wide association studies investigating lithium response have identified several relevant loci, though the precise mechanisms driving these associations are poorly understood. We aimed to prioritise the most likely effector gene and determine the mechanisms underlying an intergenic lithium response locus on chromosome 21 identified by the International Consortium on Lithium Genetics (ConLi+Gen). We conducted in-silico functional analyses by integrating and synthesising information from several publicly available functional genetic datasets and databases including the Genotype-Tissue Expression (GTEx) project and HaploReg. The findings from this study highlighted TMPRSS15 as the most likely effector gene at the ConLi+Gen lithium response locus. TMPRSS15 encodes enterokinase, a gastrointestinal enzyme responsible for converting trypsinogen into trypsin and thus aiding digestion. Convergent findings from gene-based lookups in human and mouse databases as well as co-expression network analyses of small intestinal RNA-seq data (GTEx) implicated TMPRSS15 in the regulation of intestinal nutrient absorption, including ions like sodium and potassium, which may extend to lithium. Although the findings from this study indicated that TMPRSS15 was the most likely effector gene at the ConLi+Gen lithium response locus, the evidence was circumstantial. Thus, the conclusions from this study need to be validated in appropriately designed wet-lab studies. The findings from this study are consistent with a model whereby TMPRSS15 impacts the efficacy of lithium treatment in patients with bipolar disorder by modulating intestinal lithium absorption. • TMPRSS15 is a novel regulator of lithium response in patients with bipolar disorder. • It is the most likely effector gene at a known lithium response locus. • The gene encodes enterokinase (ENTK), a key modulator of intestinal absorption. • ENTK likely impacts lithium response through the modulation of lithium absorption. [ABSTRACT FROM AUTHOR]

Simple Summary: In forensic entomology, insects are used to estimate the time since death and to answer other investigative questions, such as determining if the body was moved postmortem or identifying the season of death. In funerary archeoentomology, insects provide information related to the season of death, body transfer, and funerary practices. To obtain this information, the correct identification of specimens collected from the scene is fundamental. In old cases and archeological contexts, the majority of entomological evidence samples found are fly puparia, barrel-like structures formed from the third-instar larval cuticle where metamorphosis takes place. Despite recent publications of identification keys for certain fly larvae and adults, there is still a lack of tools for puparium identification. This problem is exacerbated by the scarcity of diagnostic features present on the puparia. This paper critically reviews the techniques available for puparium identification in addition to traditional morphological analysis. It describes DNA-based approaches and chemical analyses of cuticular lipids and hydrocarbons, highlighting the importance of using non-invasive methods to guarantee the repeatability of the analysis—a key element in forensic science—or to preserve precious and unique specimens from museum collections. Diptera identification is fundamental in forensic entomology as well as in funerary archeoentomology, where the challenge is exacerbated by the presence of immature stages such as larvae and puparia. In these two developmental stages, specimens possess a very limited number of diagnostic features, and for puparia, there is also a lack of identification tools such as descriptions and identification keys. Morphological analysis, DNA-based techniques, and cuticular chemical analyses all show good potential for species identification; however, they also have some limitations. DNA-based identification is primarily hindered by the incompleteness of genetic databases and the presence of PCR inhibitors often co-extracted from the puparial cuticle. Chemical analysis of the cuticle is showing promising results, but this approach is also limited by the insufficient profile database and requires specific, expensive equipment, as well as trained personnel. Additionally, to ensure the repeatability of the analysis—a critical aspect in forensic investigations—and to preserve precious and unique specimens from museum collections, non-invasive protocols and techniques must be prioritized for species identification. [ABSTRACT FROM AUTHOR]

Rhododendron williamsianum Rehder & E. H. Wilson 1913, is a plant with important horticultural value. Here we report its chloroplast genome. The total length of the chloroplast genome was 205,424 bp, with a GC content of 35.8%. It consisted of a 107,968 bp large single copy, a 2606 bp small single copy, and a pair of 47,425 bp inverted repeats separating them. Within the chloroplast genome, there were a total of 110 unique genes, which included 76 protein-coding genes, 4 rRNA genes, and 30 tRNA genes. Our phylogenetic analyses indicated that R. williamsianum was closely genetically related to R. sutchuenense and R. jingangshanicum. The findings from this study not only contribute to the genetic database of Rhododendron plants but also have implications for evolutionary research within the family Ericaceae. [ABSTRACT FROM AUTHOR]

The supervised machine learning method is often used for biomedical relationship extraction. The disadvantage is that it requires much time and money to manually establish an annotated dataset. Based on distant supervision, the knowledge base is combined with the corpus, thus, the training corpus can be automatically annotated. As many biomedical databases provide knowledge bases for study with a limited number of annotated corpora, this method is practical in biomedicine. The clinical significance of each patient's genetic makeup can be understood based on the healthcare provider's genetic database. Unfortunately, the lack of previous biomedical relationship extraction studies focuses on gene–gene interaction. The main purpose of this study is to develop extraction methods for gene–gene interactions that can help explain the heritability of human complex diseases. This study referred to the information on gene–gene interactions in the KEGG PATHWAY database, the abstracts in PubMed were adopted to generate the training sample set, and the graph kernel method was adopted to extract gene–gene interactions. The best assessment result was an F1-score of 0.79. Our developed distant supervision method automatically finds sentences through the corpus without manual labeling for extracting gene–gene interactions, which can effectively reduce the time cost for manual annotation data; moreover, the relationship extraction method based on a graph kernel can be successfully applied to extract gene–gene interactions. In this way, the results of this study are expected to help achieve precision medicine. [ABSTRACT FROM AUTHOR]

Motivation: Alignment of reads to a reference genome sequence is one of the key steps in the analysis of human whole-genome sequencing data obtained through Next-generation sequencing (NGS) technologies. The quality of the subsequent steps of the analysis, such as the results of clinical interpretation of genetic variants or the results of a genome-wide association study, depends on the correct identification of the position of the read as a result of its alignment. The amount of human NGS whole-genome sequencing data is constantly growing. There are a number of human genome sequencing projects worldwide that have resulted in the creation of large-scale databases of genetic variants of sequenced human genomes. Such information about known genetic variants can be used to improve the quality of alignment at the read alignment stage when analysing sequencing data obtained for a new individual, for example, by creating a genomic graph. While existing methods for aligning reads to a linear reference genome have high alignment speed, methods for aligning reads to a genomic graph have greater accuracy in variable regions of the genome. The development of a read alignment method that takes into account known genetic variants in the linear reference sequence index allows combining the advantages of both sets of methods. Results: In this paper, we present the minimap2_index_modifier tool, which enables the construction of a modified index of a reference genome using known single nucleotide variants and insertions/deletions (indels) specific to a given human population. The use of the modified minimap2 index improves variant calling quality without modifying the bioinformatics pipeline and without significant additional computational overhead. Using the PrecisionFDA Truth Challenge V2 benchmark data (for HG002 short-read data aligned to the GRCh38 linear reference (GCA_000001405.15) with parameters k = 27 and w = 14) it was demonstrated that the number of false negative genetic variants decreased by more than 9500, and the number of false positives decreased by more than 7000 when modifying the index with genetic variants from the Human Pangenome Reference Consortium. [ABSTRACT FROM AUTHOR]

Background: Observational studies have indicated that immune dysregulation in primary sclerosing cholangitis (PSC) primarily involves intestinal-derived immune cells. However, the causal relationship between peripheral blood immune cells and PSC remains insufficiently understood. Methods: A bidirectional two-sample Mendelian randomization (MR) analysis was implemented to determine the causal effect between PBC and 731 immune cells. All datasets were extracted from a publicly available genetic database. The standard inverse variance weighted (IVW) method was selected as the main method for the causality analysis. Cochran's Q statistics and MR-Egger intercept were performed to evaluate heterogeneity and pleiotropy. Results: In forward MR analysis, the expression ratios of CD11c on CD62L+ myeloid DC (OR = 1.136, 95% CI = 1.032-1.250, p = 0.009) and CD62L-myeloid DC AC (OR = 1.267, 95% CI = 1.086-1.477, p = 0.003) were correlated with a higher risk of PSC. Each one standard deviation increase of CD28 on resting regulatory T cells (Treg) (OR = 0.724, 95% CI = 0.630-0.833, p < 0.001) and CD3 on secreting Treg (OR = 0.893, 95% CI = 0.823-0.969, p = 0.007) negatively associated with the risk of PSC. In reverse MR analysis, PSC was identified with a genetic causal effect on EM CD8+ T cell AC, CD8+ T cell AC, CD28-CD127- CD25++ CD8+ T cell AC, CD28- CD25++ CD8+ T cell AC, CD28- CD8+ T cell/CD8+ T cell, CD28- CD8+ T cell AC, and CD45 RA- CD28- CD8+ T cell AC. Conclusion: Our study indicated the evidence of causal effects between PSC and immune cells, which may provide a potential foundation for future diagnosis and treatment of PSC. [ABSTRACT FROM AUTHOR]

Introduction: Immune cells are dynamic in the inflammatory environment and play a key role in eradicating periodontal pathogens, modulating immune responses, and instigating tissue destruction. Identifying specific immune cell phenotypes associated with periodontitis risk is essential for targeted immunotherapeutic interventions. However, the role of certain specific immune cell phenotypes in the development of periodontitis is unknown. Mendelian randomization offers a novel approach to reveal causality and address potential confounding factors through genetic instruments. Methods: This two-sample Mendelian randomization study assessed the causal relationship between 731 immune cell phenotypes and periodontitis using the inverse variance weighting method with the GWAS catalog genetic database. Methodological robustness was ensured through Cochran's Q test, MR-Egger regression, MR-PRESSO, and Leave-One-Out analysis. Results: 14 immune cell phenotypes showed potential positive causal associations with periodontitis risk (p < 0.05), suggesting an increased risk, while 11 immune cell phenotypes exhibited potential negative causal associations (p < 0.05), indicating a reduced risk. No significant heterogeneity or pleiotropy was observed. Conclusion: This study underscores certain immune cell types as potential periodontitis risk biomarkers, laying a theoretical foundation for future individualized treatment and precision medicine development. [ABSTRACT FROM AUTHOR]

This study was aimed at developing a molecular genetic database that allows the certification of the pecan cultivars planted in Brazil, based on reference cultivars from the USA. We used a set of 10 nSSR and 10 cpSSR markers for cultivar identification and characterization. The database developed is an instrument for certification of cultivars, characterization of potential new cultivars, and selection of material for pecan breeding. The CertiBase database is composed of genotypes and haplotypes characterized for 40 reference pecan cultivars, while the CertiBase algorithm for plant identification is implemented in a user-friendly free software. Varietal certification of cultivars will bring more security to the entire production chain, in addition to enabling the characterization of the ancestry of potential new cultivars and establishment of breeding programs of pecan in Brazil. [ABSTRACT FROM AUTHOR]

The article discusses the prevalence of lipodystrophy and lipodystrophy-like phenotypes, which are conditions characterized by altered adipose tissue distribution. The study found that lipodystrophy-like phenotypes are more common than the clinical or genetic prevalence of familial partial lipodystrophy (FPLD), a rare disease. The authors propose using a fat mass ratio (FMR) derived from DEXA scans to identify individuals with lipodystrophy-like phenotypes and potentially develop targeted therapies. However, they emphasize that a comprehensive clinical assessment is necessary for a definitive diagnosis of lipodystrophy syndromes. The article also highlights the challenges in accurately estimating the prevalence of lipodystrophy due to underdiagnosis and the involvement of unidentified genes. Overall, understanding and differentiating lipodystrophy and lipodystrophy-like phenotypes can improve personalized disease management and interventions. [Extracted from the article]

Introduction: CYP2C19 plays a major role in the metabolism of various drugs. The most common genetic variants were the CYP2C19*2 and *3 alleles (rs4244285 and rs4986893, non-functional variants). In previous studies, we found that genetic polymorphisms in CYP2C19 variants influenced the active metabolites of clopidogrel and caused major adverse cardiovascular and cerebrovascular effects. However, the distribution of CYP2C19 varies among ethnic groups and according to adverse drug reactions. This study aimed to investigate the frequency of CYP2C19 genetic polymorphisms in the Thai population and analyze the differences in the frequency of CYP2C19 genetic polymorphisms between Thai and other populations. Methods: This study enrolled 211 unrelated healthy Thai individuals in total. We performed a real-time polymerase chain reaction to genotype CYP2C19*2 (681G > A) and CYP2C19*3 (636G > A). Results: In the Thai population, the CYP2C19*1 allele was the most prevalent at 70.14%, while the CYP2C19*2 and *3 alleles were found at frequencies of 25.36% and 4.50%, respectively. Conversely, the CYP2C19*3 allele was not detected in Caucasian, Hispanic, African, Italian, Macedonian, Tanzanian, or North Indian populations. The phenotypic profile of this gene revealed that the frequency of intermediate metabolizers (IMs) is nearly equal to that of extensive metabolizers (EMs), at 42.65% and 48.82% respectively, with genotypes *1/*2 (36.02%) and *1/*3 (6.63%). Likewise, poor metabolizers (PMs) with genotypes *2/*2 (6.16%), *2/*3 (2.37%), and *3/*3 (< 1%) are more prevalent in our population as well. Conclusion: The distribution of CYP2C19 genotype and phenotype influenced by non-functional alleles has potential as a pharmacogenomics biomarker for precision medicine and is dependent on an ethnic-specific genetic variation database. [ABSTRACT FROM AUTHOR]

Background: Investigating novel therapeutic strategies for colorectal cancer (CRC) is imperative. However, there is limited research on the use of drugs to target peripheral blood immune cells in this context. To address this gap, we performed a two-sample Mendelian randomization (MR) analysis to identify potential therapeutic targets for CRC. Methods: We applied two-sample MR to identify the causal relationship between peripheral blood immune cells and CRC. GWAS data were obtained from the IEU OPEN GWAS project. Based on the implications from the MR results, we conducted a comprehensive database search and genetic analysis to explore potential underlying mechanisms. We predicted miRNAs for each gene and employed extensive research for potential therapeutic applications. Results: We have identified causal associations between two peripheral immune cells and colorectal cancer. Activated & resting Treg %CD4 + cell was positively associated with the risks of CRC, while DN (CD4-CD8-) %leukocyte cell exhibited a protective role in tumor progression. NEK7 (NIMA related kinase 7) and LHX9 (LIM homeobox 9) expressed in Treg cells were positively associated with CRC risks and may play a vital role in carcinogenesis. Conclusions: This study identified causal relationship between peripheral immune cell and CRC. Treg and DN T cells were implicated to own promoting and inhibiting effects on CRC progression respectively. NEK7 and LHX9 in Treg cells were identified as potential biotarget for antitumor therapies. [ABSTRACT FROM AUTHOR]

Background: The onset and progression of chronic kidney disease (CKD) has been linked to metabolic syndrome (MetS), with the results of recent observational studies supporting a potential link between renal failure and MetS. The causal nature of this relationship, however, remains uncertain. This study thus leveraged a Mendelian Randomization (MR) approach to probe the causal link of MetS with renal failure. Methods: A genetic database was initially used to identify SNPs associated with MetS and components thereof, after which causality was evaluated through the inverse variance weighted (IVW), MR-Egger regression, and weighted media techniques. Results were subsequently validated through sensitivity analyses. Results: IVW (OR = 1.48, 95% CI = 1.21–1.82, P =1.60E−04) and weighted median (OR = 1.58, 95% CI =1.15–2.17, P = 4.64E-03) analyses revealed that MetS was linked to an elevated risk of renal failure. When evaluating the specific components of MetS, waist circumference was found to be causally related to renal failure using the IVW (OR= 1.58, 95% CI = 1.39–1.81, P = 1.74e-11), MR-Egger (OR= 1.54, 95% CI = 1.03–2.29, P = 0.036), and weighted median (OR= 1.82, 95% CI = 1.48–2.24, P = 1.17e-8). The IVW method also revealed a causal association of hypertension with renal failure (OR= 1.95, 95% CI = 1.34–2.86, P = 5.42e-04), while renal failure was not causally related to fasting blood glucose, triglyceride levels, or HDL-C levels. Conclusion: These data offer further support for the existence of a causal association of MetS with kidney failure. It is thus vital that MetS be effectively managed in patients with CKD in clinical settings, particularly for patients with hypertension or a high waist circumference who are obese. Adequate interventions in these patient populations have the potential to prevent or delay the development of renal failure. [ABSTRACT FROM AUTHOR]

Rock abrasivity is one of the main factors affecting the wear of rock-cutting tools, which is usually quantified by the CERCHAR Abrasivity Index (CAI). Researchers and engineers study tool wear and predict tool life based on the CAI of rocks. However, there is still a lack of a dataset on rock properties, especially the abrasivity of various rocks. This paper reports the abrasive dataset of 10 kinds of rocks, including sedimentary rocks, metamorphic rocks, and igneous rocks, with the aid of the CERCHAR Abrasivity Test and digital measurement techniques. The dataset comprises rock abrasivity data, point cloud data for visualization, scratch photos, CERCHAR Abrasivity Test force data, and mechanical properties (uniaxial compressive strength) of rock samples. This dataset facilitates future research on rock abrasivity and rock-cutting tool wear. [ABSTRACT FROM AUTHOR]

Genes strictly regulate the development of teeth and their surrounding oral structures. Alteration of gene regulation leads to tooth disorders and developmental anomalies in tooth, oral, and facial regions. With the advancement of gene sequencing technology, genomic data is rapidly increasing. However, the large sets of genomic and proteomic data related to tooth development and dental disorders are currently dispersed in many primary databases and literature, making it difficult for users to navigate, extract, study, or analyze. We have curated the scattered genetic data on tooth development and created a knowledgebase called 'Bioinformatics for Dentistry' (https://dentalbioinformatics.com/). This database compiles genomic and proteomic data on human tooth development and developmental anomalies and organizes them according to their roles in different stages of tooth development. The database is built by systemically curating relevant data from the National Library of Medicine (NCBI) GenBank, OMIM: Online Mendelian Inheritance in Man, AlphaFold Protein Structure Database, Reactome pathway knowledgebase, Wiki Pathways, and PubMed. The accuracy of the included data was verified from supporting primary literature. Upon data curation and validation, a simple, easy-to-navigate browser interface was created on WordPress version 6.3.2, with PHP version 8.0. The website is hosted in a cloud hosting service to provide fast and reliable data transfer rate. Plugins are used to ensure the browser's compatibility across different devices. Bioinformatics for Dentistry contains four embedded filters for complex and specific searches and free-text search options for quick and simple searching through the datasets. Bioinformatics for Dentistry is made freely available worldwide, with the hope that this knowledgebase will improve our understanding of the complex genetic regulation of tooth development and will open doors to research initiatives and discoveries. This database will be expanded in the future by incorporating resources and built-in sequence analysis tools, and it will be maintained and updated annually. [ABSTRACT FROM AUTHOR]

Objectives: The Bengal tiger Panthera tigris tigris, is an emblematic animal for Bangladesh. Despite being the apex predator in the wild, their number is decreasing due to anthropogenic activities such as hunting, urbanization, expansion of agriculture and deforestation. By contrast, captive tigers are flourishing due to practical conservation efforts. Breeding within the small captive population can produce inbreeding depression and genetic bottlenecks, which may limit the success of conservation efforts. Despite past decades of research, a comprehensive database on genetic variation in the captive and wild Bengal tigers in Bangladesh still needs to be included. Therefore, this research aimed to investigate the White Bengal tiger genome to create a resource for future studies to understand variation underlying important functional traits. Data description: Blood samples from Chattogram Zoo were collected for three white Bengal tigers. Genomic DNA for all collected samples were extracted using a commercial DNA extraction kit. Whole genome sequencing was performed using a DNBseq platform. We generated 77 Gb of whole-genome sequencing (WGS) data for three white Bengal tigers (Average 11X coverage/sample). The data we generated will establish a paradigm for tiger research in Bangladesh by providing a genomic resource for future functional studies on the Bengal white tiger. [ABSTRACT FROM AUTHOR]

Objective: Few studies have been conducted on the association between gut microbes and gastric ulcers. This paper aims to investigate the causal relationship between gut flora and gastric ulcer development using a two-sample Mendelian randomization method. Methods: Relevant single nucleotide polymorphisms were screened as instrumental genetic variables (SNPs) from the genetic variation database of the gut microbiota (MiBioGen), and the weighted median estimator of random effects (WME), inverse variance weighting (IVW) and MR-Egger regression three Mendelian randomization methods were used to study the causal association between gut microbes and gastric ulcer development. Results and Discussion: Family Lachnospiraceae, genus Eubacterium ventriosum group, genus Olsenella were risk factors for gastric ulcer, while genus Butyrivibrio, genus Odoribacter, genus Sutterella had a suggestive protective effect on gastric ulcer, but the mechanism of intestinal flora and gastric ulcer needs to be further verified, but this study still provides some theoretical basis for future studies between gastric ulcer and intestinal flora. Conclusions: In this study, a potentially positive and negative causal relationship between intestinal flora and the gastric ulcer was derived by a two-sample Mendelian analysis, from which it was known that the family Lachnospiraceae, genus Eubacterium ventricose group, genus Olsenella are risk factors for gastric ulcer. In contrast, the genus Butyrivibrio, genus Odoribacter, and genus Sutterella had suggestive protective effects against gastric ulcers. [ABSTRACT FROM AUTHOR]

Taohong Siwu Decoction (THSWD), a traditional Chinese prescription renowned for its efficacy in promoting blood circulation and alleviating blood stasis, was investigated in this study to delineate its potential active components and discern the core targets (CTs) and signaling pathways implicated in the treatment of Alzheimer's disease (AD). Initially, 25 active compounds (ACs) and 478 corresponding active ingredient targets (AITs) of THSWD were meticulously identified by scrutinizing the active ingredients and their targets through the Traditional Chinese Medicine Systems Pharmacology (TCMSP) and Similarity Ensemble Approach (SEA) databases. Subsequently, a comprehensive compilation of 724 AD-related targets was assembled from the Therapeutic Target Database (TTD), DisGeNET, DrugBank, Genetic Association Database (GAD), and GeneCards databases. Through a meticulous alignment of AITs with disease-related targets, 64 overlapping targets (OTs) emerged as critical intersections. To distill the key compounds, an intricate analysis of the interrelationships among the 25 ACs and 64 OTs resulted in the identification of 21 first-level key compounds (FKCs). Further scrutiny through protein-protein interaction (PPI) analysis of the 64 OTs revealed 33 CTs. KEGG cluster analysis of these CTs yielded the top 73 pathways, forming the basis for constructing a network diagram encompassing "21 FKCs-33 CTs-73 pathways" using Cytoscape 3.7.2 software. Refining the network through the selection of topological parameters led to the identification of 19 second key components (SKCs). This information was then employed to construct a refined network, "19 SKCs-33 CTs-73 pathways", providing deeper insights into the intricate connections within the system. Further analyses culminated in the creation of a comprehensive network map, encapsulating "6 single drugs-8 potential active ingredients-13 core targets-54 signaling pathways", elucidating the multifaceted intervention of THSWD in AD. These results offered a novel perspective for understanding the pharmacodynamic material basis of THSWD and paved the way for in-depth investigations into its mechanisms of action and clinical applications in the context of AD. [ABSTRACT FROM AUTHOR]

Elasmobranchs (sharks and rays) are the most threatened marine vertebrates, particularly in tropical and subtropical areas. Their population status is often poorly understood due to insufficient information. Despite reportedly harbouring critical elasmobranch habitats, the Banc d'Arguin National Park (PNBA) in Mauritania lacks comprehensive and updated information on the diversity of elasmobranch species in the area. We developed a baseline inventory based on morphological and molecular identification and metabarcoding. DNA barcoding of tissue samples from elasmobranch processing sites and freshly sampled specimens was used to build a genetic reference database of local elasmobranch species. The richness and diversity of species in the PNBA were described via metabarcoding of seawater eDNA samples using an elasmobranch-specific assay and our reference database. We detected 27 species, including 12 new species records for the PNBA. We further uncover potentially undescribed species of Gymnura and Torpedo, while taxonomic corrections are noted for previously reported species. In particular, the reportedly abundant Mustelus mustelus was absent from tissue and eDNA samples, while M. punctulatus was detected instead. Taxa that have anecdotally become regionally extinct or rare (e.g., sawfishes, wedgefishes, lemon sharks) were not detected, highlighting local species diversity shifts within the last few decades. Results show that 67.9% of elasmobranch species in the PNBA are threatened with extinction according to the IUCN Red List of Threatened Species. This study emphasises the importance of taxonomic identification in support of species management and provides a baseline to inform future studies and conservation measures to avoid further species losses. [ABSTRACT FROM AUTHOR]

Background: Environmental stress factors, such as biotic and abiotic stress, are becoming more common due to climate variability, significantly affecting global maize yield. Transcriptome profiling studies provide insights into the molecular mechanisms underlying stress response in maize, though the functions of many genes are still unknown. To enhance the functional annotation of maize-specific genes, MaizeGDB has outlined a data-driven approach with an emphasis on identifying genes and traits related to biotic and abiotic stress. Results: We mapped high-quality RNA-Seq expression reads from 24 different publicly available datasets (17 abiotic and seven biotic studies) generated from the B73 cultivar to the recent version of the reference genome B73 (B73v5) and deduced stress-related functional annotation of maize gene models. We conducted a robust meta-analysis of the transcriptome profiles from the datasets to identify maize loci responsive to stress, identifying 3,230 differentially expressed genes (DEGs): 2,555 DEGs regulated in response to abiotic stress, 408 DEGs regulated during biotic stress, and 267 common DEGs (co-DEGs) that overlap between abiotic and biotic stress. We discovered hub genes from network analyses, and among the hub genes of the co-DEGs we identified a putative NAC domain transcription factor superfamily protein (Zm00001eb369060) IDP275, which previously responded to herbivory and drought stress. IDP275 was up-regulated in our analysis in response to eight different abiotic and four different biotic stresses. A gene set enrichment and pathway analysis of hub genes of the co-DEGs revealed hormone-mediated signaling processes and phenylpropanoid biosynthesis pathways, respectively. Using phylostratigraphic analysis, we also demonstrated how abiotic and biotic stress genes differentially evolve to adapt to changing environments. Conclusions: These results will help facilitate the functional annotation of multiple stress response gene models and annotation in maize. Data can be accessed and downloaded at the Maize Genetics and Genomics Database (MaizeGDB). [ABSTRACT FROM AUTHOR]

To detect environmental factors, which may be possible risk factors in the disease course of Fuchs' endothelial corneal dystrophy (FECD). Evaluation of patients with FECD registered in the FECD genetics database of the Center for Ophthalmology, University Hospital Cologne. For the evaluation, disease onset, central corneal thickness, best spectacle corrected visual acuity (BSCVA, logMAR), and modified Krachmer grading (grades 1–6) were correlated with the presence of diabetes mellitus (DM), body mass index (BMI), and smoking behavior. To put the age-related increase in Krachmer grading into perspective, a correction of grading were formed. Depending on the variables studied, differences between groups were examined by Mann–Whitney U test and chi-square test. The significance level was 5%. 403 patients with FECD were included in the analysis. The mean age of the patients was 70.0 ± 10.32 (range 28–96) years. The mean age at diagnosis of those patients was 63.1 ± 13.2 years. The female-to-male ratio was 1.46:1. Patients with a BMI > 30.0 kg/m2 developed FECD significantly earlier than patients with a BMI < 30 kg/m2, p = 0.001. Patients with DM showed significantly more often an Krachmer grade of 5, p = 0.015. Smoking had a negative effect on Krachmer grading (p = 0.024). Using the mediation analysis, the presence of DM correlated Krachmer Grade 5 (p = 0.015), and the presence of DM correlated with BMI > 30.0 kg/m2 (p = 0.012). In addition to smoking and DM our study shows for the first time that obesity may have a negative impact on the development of FECD. Whether dietary interventions and hormones can influence the development or progression of the disease needs to be investigated in future studies. [ABSTRACT FROM AUTHOR]

Single nucleotide polymorphisms are most common type of genetic variation in human genome. Analyzing genetic variants can help us better understand the genetic basis of diseases and develop predictive models which are useful to identify individuals who are at increased risk for certain diseases. Several SNP analysis tools have already been developed. For running these tools, the user needs to collect data from various databases. Secondly, often researchers have to use multiple variant analysis tools for cross validating their results and increase confidence in their findings. Extracting data from multiple databases and running multiple tools at a time, increases complexity and time required for analysis. There are some web-based tools that integrate multiple genetic variant databases and provide variant annotations for a few tools. These approaches have some limitations such as retrieving annotation information, filtering common pathogenic variants. The proposed web-based tool, namely IPSNP: An Integrated Platform for Predicting Impact of SNPs is written in Django which is a python-based framework. It uses RESTful API of MyVariant.info to extract annotation information of variants associated with a given gene, rsID, HGVS format variants specified in a VCF file for 29 tools. The results are in the form of a CSV file of predictions (1) derived from the consensus decision, (2) a file having annotations for the variants associated with the given gene, (3) a file showing variants declared as pathogenic commonly by the selected tools, and (4) a CSV file containing chromosome coordinates based on GRCh37 and GRCh38 genome assemblies, rsIDs and proteomic data, so that users may use tools of their choice and avoiding manual parameter collection for each tool. IPSNP is a valuable resource for researchers and clinicians and it can help to save time and effort in discovering the novel disease-associated variants and the development of personalized treatments. [ABSTRACT FROM AUTHOR]

Currently, the genus Zenopsis, also known as silver John Dory, comprises at least five valid species with a wide range of distribution. However, recent studies have proposed the existence of a new Zenopsis species inhabiting the Indian Ocean, and a preliminary search in the Barcode of Life Database reveals the presence of different barcode index numbers (BIN) for the nominal species Zenopsis conchifer. In the Southwest Atlantic Ocean (SWA), Z. conchifer is the only species reported so far. Therefore, the aim of this work was to evaluate, at the molecular level, the potential taxonomic diversity within the genus Zenopsis and to assess if the species occurring in the SWA corresponds with Z. conchifer. Using data available in worldwide genetic databases, a maximum likelihood tree, a BIN , and an automatic barcode gap discovery analysis were carried out. Additionally, specimens sampled from the SWA were morphologically compared with specimens from different parts of its distribution using available data. The specific identity at the molecular level of specimens occurring in the SWA was confirmed as Z. conchifer. The results of the molecular analysis highlight the existence of hidden specific diversity within the genus. [ABSTRACT FROM AUTHOR]

This document discusses the challenges of diagnosing the causes of unexplained child deaths and presents a study on the use of molecular autopsy to identify genetic variations associated with these deaths. Traditional autopsies are not always acceptable to parents due to religious and cultural beliefs, so molecular autopsy, which involves DNA sequencing, offers a promising alternative. The study used stored neonatal dried blood spots to conduct clinical exome sequencing and found that 88.9% of cases had genetic variations associated with the cause of death. The study suggests that molecular autopsies using clinical exome sequencing can be a feasible and effective method for investigating unexplained child deaths. [Extracted from the article]

The popularity of digital devices seems to provide a new observational variable for early identification and prevention of suicide with the development of the information technology era. Nevertheless, whether it is the use of digital devices that alters suicide risk or suicide risk manifests itself through change digital device use needs to be further explored. Bidirectional Mendelian randomization (MR) analysis was used to explore potential causal relationships in the perspective of genetic prediction. We collected publicly available digital device use and suicide risk summary statistics genome-wide association data from UK Biobank, Neale Lab and FinnGen genetic databases. We used inverse variance weighting methods to assess MR estimates. For robustness of the results, we performed further tests of heterogeneity and pleiotropy. In the Phase 1 results, we did not observe any effect of the length of digital device use on the suicide risk, while the results of Phase 2 suggested a significant positive association between suicide risk and the length of mobile phone use (IVW OR, 1.04; 95%CI, 1.01–1.06; P = 0.002), but this significance disappeared after adjusting for confounders of mental and affective disorders. In this bidirectional MR analysis, we observed that People at high risk of suicide may be more addicted to digital device use, but more detailed GWAS data and research methods to validate this finding are required. • This study is the first to explore the bidirectional causal relationship between digital device use and suicide risk. • Our study finds that length of use of digital devices does not change suicide risk. • People at high risk of suicide may be more addicted to digital device use. [ABSTRACT FROM AUTHOR]

OBJECTIVE: To identify the pathogenic alleles in primary congenital glaucoma patients for early cure of the disease METHODOLOGY: A cross-sectional descriptive study was carried out after approval from the ethical committee of SIOVS from December 2022 to November 2023 at Sindh Institute of Ophthalmology & Visual Sciences, Hyderabad. The consanguineous pedigree consisting of more than one affected was included, and the pedigree consists only one affected or secondary cause of vision loss was excluded. After getting informed consent, ten cc blood samples from all available participants in the pedigree were drawn, and DNA was extracted. The ARMS Assay and Sanger sequencing methods were adapted to analyze the CYP1B1 gen. RESULTS: In the present study, one novel c.1187C>T, p.Pro396Leu and one reported c.1169G>A, p.Arg390His allele in CYP1B1 gene were found in two isolated pedigrees enrolled from Sindh Pakistan. ARMS Assay method and the Sanger sequencing method were adopted to detect pathogenic variants. Bioinformatics tools were used to analyze the pathogenesis of identified alleles and compare phenotype -genotype correlation. CONCLUSION: The findings of novel and frequently reported mutations have a significant role in advancing genetic testing protocols, enabling more accurate targeting of diagnoses and identified alleles that may be added to existing repositories of the genetic database. [ABSTRACT FROM AUTHOR]

Case C‑205/21 VS v Ministerstvo na vatreshnite raboti, Glavna direktsia za borba s organiziranata prestapnost, Judgment of the Court of Justice of the European Union of 26 January 2023 The Court of Justice of the European Union (CJEU) decided that the systematic collection of biometric and genetic data of any accused individual in order for them to be entered in police records in an indiscriminate and generalised manner is not in compliance with the Union law. After summarising the judgment, this case note first questions whether the CJEU misclassified the personal data in question as genetic data. Then, it points out that the condition enshrined in Article 10 of the Law Enforcement Directive that allows sensitive data processing by law enforcement authorities only where strictly necessary is considered by the CJEU as a specific manifestation of lato sensu proportionality assessment. Considering that law enforcement authorities in the EU rely more and more on (biometric) technologies to prevent and fight against crimes, it concludes by speculating on some of the potential implications of this interpretation. [ABSTRACT FROM AUTHOR]

This article, published in the Egyptian Journal of Medical Human Genetics, discusses the identification of a novel ATR-X mutation in a myelofibrosis patient. ATR-X mutations have been associated with the onset of α-thalassemia in various hematological malignancies. The ATRX gene encodes a chromatin remodeling protein that regulates chromatin structure and function. The mutation identified in this study leads to a missense mutation in the PHD-like domain of the ATRX protein. The authors classified this mutation as potentially pathogenic based on computational predictions and its location in a mutational hot-spot region. This report contributes to the understanding of the ATRX gene mutational spectrum and may improve genetic screening and diagnosis of rare diseases. [Extracted from the article]

Background: Isolated growth hormone deficiency (IGHD) is a hereditary disorder that causes significant short stature. GHD has a reported incidence of 1/4000–1/10,000 births. It is caused by mutations in the major somatotroph axis genes, involving GH1, codes for growth hormone, GHSR, and GHRHR, codes for growth hormone secretagogue receptor and growth hormone-releasing hormone receptor, respectively. Aims of the study: The present study aims to examine the clinical phenotype and investigate the genetic etiology of ten Egyptian patients with type I isolated growth hormone insufficiency. Patients and methods: Patients recruited for the study were clinically diagnosed by two provocation tests and were subjected to a thorough history, clinical examination, and anthropometric measurements. Sanger sequencing and mutational analysis of the three genes, GH1, GHSR, and GHRHR, was our approach, performed in all enrolled IGHD patients. The variants identified were analyzed using the biological, population, sequence variants, and clinical genetics databases. Prediction of the pathogenicity of the novel variants was done by in silico prediction tools following the American College of Medical Genetics and Genomics (ACMG) guidelines. Results: Sanger sequencing revealed a previously reported pathogenic mutation (NM_000823.4: c.1069C > T; p.Arg357Cys) in the GHRHR gene in one patient and a novel frameshift variant (NM_198407.2: c.1043dup; Ser349Leu fs*6) in the GHSR gene in another patient. This is the fourth report highlighting the autosomal dominant inheritance of the GHSR mutation as a cause of isolated growth hormone deficiency. A number of previously reported variants, but of rare frequency, were identified in this study. In our IGHD cases, 90% of the patients were underweight, 50% had anemia, and 80% showed hypovitaminosis D. Conclusion: Our findings broaden the mutational spectrum underlying the IGHD in Egyptian patients and point out the importance of mutation screening of the GHSR and GHRHR genes. This study also acknowledges the autosomal dominant mode of inheritance of the GHSR mutation as a cause for dwarfism. [ABSTRACT FROM AUTHOR]

Cork oak (Quercus suber L.) is an essential species of the Mediterranean region. In Morocco, it represents a source of life and is a noble species for many populations. The Maâmora forest, situated in Morocco, is recognized as the largest forest in the Mediterranean basin and displays the highest diversity compared to other forests in its distribution area. This study aimed to establish a genetic database of 240 individuals from Maâmora forest using seven SSR markers. Through a series of statistical analyses, we determined the level of diversity and genetic structure and created a core collection. Statistical analysis of the data showed a high degree of allelic variation, generating 47 alleles with an average of 6.71 alleles per locus. Furthermore, a high percentage of polymorphisms and a high Shannon index were observed. Intra-population genetic diversity was found to be high (86%) compared to inter-population diversity (14%). A low level of genetic differentiation (Gst = 0.12) and high gene flow were identified, consistent with the results obtained from the analysis of molecular variance (AMOVA). This suggests a possible capacity for the species to adapt to environmental conditions. A core collection of 18 genotypes was constructed, which included all the private alleles that were detected in this study. This core collection exhibited similar and crucial diversity to that identified in the initial collection, as verified by a series of genetic diversity and structural analyses. This research advocates populations and individuals for further studies on adaptation in order to improve and conserve this valuable resource in the future. [ABSTRACT FROM AUTHOR]

Studies continue to uncover contributing risk factors for breast cancer (BC) development including genetic variants. Advances in machine learning and big data generated from genetic sequencing can now be used for predicting BC pathogenicity. However, it is unclear which tool developed for pathogenicity prediction is most suited for predicting the impact and pathogenicity of variant effects. A significant challenge is to determine the most suitable data source for each tool since different tools can yield different prediction results with different data inputs. To this end, this work reviews genetic variant databases and tools used specifically for the prediction of BC pathogenicity. We provide a description of existing genetic variants databases and, where appropriate, the diseases for which they have been established. Through example, we illustrate how they can be used for prediction of BC pathogenicity and discuss their associated advantages and disadvantages. We conclude that the tools that are specialized by training on multiple diverse datasets from different databases for the same disease have enhanced accuracy and specificity and are thereby more helpful to the clinicians in predicting and diagnosing BC as early as possible. [ABSTRACT FROM AUTHOR]

Peru ranks among the three countries with the highest bird species diversity globally and a majority of those species are found in the Peruvian Amazon. However, birds in this area are currently facing serious anthropogenic threats. Genetic and genomic methods are becoming important tools for avian biodiversity monitoring and conservation planning. Comprehensive molecular libraries that are publicly available are key to the effective deployment of these tools. We analyze the information gaps for four molecular markers in the most important genetic sequence databases, Barcode of Life Data Systems (BOLD) and NCBI GenBank, for bird species of the Peruvian Amazonia. We found that 64% of Peruvian Amazonian bird species have gene sequences for COI, 59.5% have CYTB sequences, 16.4% have 12S sequences, and only 0.6% have 18S sequences. However, these numbers decrease drastically to 4.3% for COI sequences when we only consider specimens sampled in Peru. Our data also showed that 43.8% of Peruvian Amazonian endemic species (n = 32) are missing sequences of any screened marker uploaded to GenBank or BOLD. Our results will encourage and guide efforts of the scientific community to complete reference libraries for Peruvian avian species that will be useful for future DNA-based monitoring projects that include birds. [ABSTRACT FROM AUTHOR]

DNA profiling has become a culturally ubiquitous technology. Its use, whether in forensic investigations, genetic databases, biomedical research, international border-making, or popular genealogy, has been familiarized through political debates, media and cultural representations and commercialization. DNA profiling has also attracted considerable scholarly attention across this terrain. However, scant attention has been paid to the key role played by legal migration in driving DNA profiling's initial translation from lab bench discovery to "truth machine" and identity token. Here, I discuss the first state-sponsored use of DNA profiling as a tool for establishing kinship relations among legal but racialized migrants on Britain's borders in the mid-1980s. I argue that this early "experiment" conditioned the commercialization and future uses of the technology at and beyond border zones. Reinstating migration as the origin context for DNA profiling, and retracing the postcolonial routes by which it entered the biopolitical sphere, sheds light on the conjoined naturalization and racialization of genetic technologies of identity and identification, whether at or beyond national borders. [ABSTRACT FROM AUTHOR]

In urban and agricultural streams, assessing aquatic ecosystem health is critical due to widespread pollution. Traditional methods for evaluating attached diatoms crucial for ecosystem monitoring face limitations such as species misidentification and sample damage. This study was conducted in the Miho River within the Geum River system and highlights the effectiveness of environmental DNA (eDNA) techniques for more accurate and efficient genetic-based analysis than conventional microscopic analysis methods. When eDNA-based assessments were compared with traditional microscopic methods, this study found that eDNA analysis often revealed poorer ecosystem health. Notably, eDNA assessments showed a stronger correlation with phosphorus concentrations, underlining their precision and importance in ecological studies. These findings suggest that eDNA has potential as a valuable tool for comprehensive biomonitoring. However, the use of international genetic barcode databases in eDNA analysis could lead to the identification of unrecorded species in Korea. Therefore, this study recommends developing a localized genetic barcode database and constructing eDNA information through meta-barcoding, focusing on native species. This approach is crucial for enhancing the accuracy and applicability of eDNA-based health assessments in national biomonitoring efforts. [ABSTRACT FROM AUTHOR]

INTRODUCTION: Alzheimer's disease (AD) is a complex disease influenced by genetics and environment. More than 75 susceptibility loci have been linked to late‐onset AD, but most of these loci were discovered in genome‐wide association studies (GWAS) exclusive to non‐Hispanic White individuals. There are wide disparities in AD risk across racially stratified groups, and while these disparities are not due to genetic differences, underrepresentation in genetic research can further exacerbate and contribute to their persistence. We investigated the racial/ethnic representation of participants in United States (US)‐based AD genetics and the statistical implications of current representation. METHODS: We compared racial/ethnic data of participants from array and sequencing studies in US AD genetics databases, including National Institute on Aging Genetics of Alzheimer's Disease Data Storage Site (NIAGADS) and NIAGADS Data Sharing Service (dssNIAGADS), to AD and related dementia (ADRD) prevalence and mortality. We then simulated the statistical power of these datasets to identify risk variants from non‐White populations. RESULTS: There is insufficient statistical power (probability <80%) to detect single nucleotide polymorphisms (SNPs) with low to moderate effect sizes (odds ratio [OR]<1.5) using array data from Black and Hispanic participants; studies of Asian participants are not powered to detect variants OR <= 2. Using available and projected sequencing data from Black and Hispanic participants, risk variants with OR = 1.2 are detectable at high allele frequencies. Sample sizes remain insufficiently powered to detect these variants in Asian populations. DISCUSSION: AD genetics datasets are largely representative of US ADRD burden. However, there is a wide discrepancy between proportional representation and statistically meaningful representation. Most variation identified in GWAS of non‐Hispanic White individuals have low to moderate effects. Comparable risk variants in non‐White populations are not detectable given current sample sizes, which could lead to disparities in future studies and drug development. We urge AD genetics researchers and institutions to continue investing in recruiting diverse participants and use community‐based participatory research practices. [ABSTRACT FROM AUTHOR]

A study published in Nature by Matt Nelson and colleagues provides evidence that human genetics is crucial for improving the success rates of drug development. The study found that less than 10% of drugs that enter clinical development succeed, resulting in high costs for drug developers. Drugs often fail due to lack of efficacy or adverse effects, which can be better understood through human genetics. By including human genetics evidence in the decision-making process, drug companies can double their success rate from 10% to 20%. The study also highlights the need for continued investment in human genetics research to further improve drug success rates. However, it is important to note that the identification of an association between a gene and a disease does not necessarily mean that the gene is a good drug target. The study has some limitations, such as hindsight and selection biases, but real-world experiences of drug companies implementing genetics-based drug target prioritization may offer further confirmation of the impact of human genetics on clinical success. [Extracted from the article]

This article discusses a case of dominant dystrophic epidermolysis bullosa pruriginosa (DDEB-Pr), a rare subtype of dystrophic epidermolysis bullosa (DEB) characterized by severe itching and prurigo-like lesions. The case involves a 28-year-old Japanese male with intractable prurigo-like lesions on his lower legs and dystrophic toenails. A skin biopsy confirmed the diagnosis of DDEB-Pr, and genetic analysis revealed a novel mutation in the COL7A1 gene. The article highlights the need for further research to understand the genotype-phenotype correlation and pathogenesis of DDEB-Pr. [Extracted from the article]

Zooplankton diversity in the deep "midnight zone" (>1000 m), where sunlight does not reach, remains largely unknown. Uncovering such diversity has been challenging because of the major difficulties in sampling deep pelagic fauna and identifying many (unknown) species that belong to these complex swimmer assemblages. In this study, we evaluated zooplankton diversity using two taxonomic marker genes: mitochondrial cytochrome oxidase subunit 1 (COI) and nuclear 18S ribosomal RNA (18S). We collected samples from plankton net tows, ranging from the surface to a depth of 5000 m above the Atacama Trench in the Southeast Pacific. Our study aimed to assess the zooplankton diversity among layers from the upper 1000 m to the ultra-deep abyssopelagic zone to test the hypothesis of decreasing diversity with depth resulting from limited carbon sources. The results showed unique, highly vertically structured communities within the five depth strata sampled, with maximal species richness observed in the upper bathypelagic layer (1000-2000 m). The high species richness of zooplankton (>750 OTUS) at these depths was higher than that found in the upper 1000 m. The vertical diversity trend exhibited a pattern similar to the well-known vertical pattern described for the benthic system. However, a large part of this diversity was either unknown (>50%) or could not be assigned to any known species in current genetic diversity databases. DNA analysis showed that the Calanoid copepods, mostly represented by Subeucalanus monachus, the Euphausiacea, Euphausia mucronata, and the halocypridade, Paraconchoecia dasyophthalma, dominated the community. Water column temperature, dissolved oxygen, particulate carbon, and nitrogen appeared to be related to the observed vertical diversity pattern. Our findings revealed rich and little-known zooplankton diversity in the deep sea, emphasizing the importance of further exploration of this ecosystem to conserve and protect its unique biota. [ABSTRACT FROM AUTHOR]

Abdominal aortic aneurysm (AAA), an extremely dangerous vascular disease with high mortality, causes massive internal bleeding due to aneurysm rupture. To boost the research on AAA, efforts should be taken to organize and link the information about AAA-related genes and their functions. Currently, most researchers screen through genetic databases manually, which is cumbersome and time-consuming. Here, we developed "AAAKB" a manually curated knowledgebase containing genes, SNPs and pathways associated with AAA. In order to facilitate researchers to further explore the mechanism network of AAA, AAAKB provides predicted genes that are potentially associated with AAA. The prediction is based on the protein interaction information of genes collected in the database, and the random forest algorithm (RF) is used to build the prediction model. Some of these predicted genes are differentially expressed in patients with AAA, and some have been reported to play a role in other cardiovascular diseases, illustrating the utility of the knowledgebase in predicting novel genes. Also, AAAKB integrates a protein interaction visualization tool to quickly determine the shortest paths between target proteins. As the first knowledgebase to provide a comprehensive catalog of AAA-related genes, AAAKB will be an ideal research platform for AAA. Database URL: http://www.lqlgroup.cn:3838/AAAKB/. [ABSTRACT FROM AUTHOR]

The article addresses privacy concerns arising from law enforcement's unconventional use of DNA, notably the San Francisco Police Department's use of a rape victim's DNA for an unrelated case. It explores diverse sources like commercial genetic databases, newborn blood samples, and state biobanks employed by law enforcement. It also discusses practices such as investigative genetic genealogy and DNA dragnets.

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Metabarcoding is revolutionizing fundamental research in ecology by enabling large‐scale detection of species and producing data that are rich with community context. However, the benefits of metabarcoding have yet to be fully realized in fields of applied ecology, especially those such as classical biological control (CBC) research that involve hyperdiverse taxa. Here, we discuss some of the opportunities that metabarcoding provides CBC and solutions to the main methodological challenges that have limited the integration of metabarcoding in existing CBC workflows. We focus on insect parasitoids, which are popular and effective biological control agents (BCAs) of invasive species and agricultural pests. Accurately identifying native, invasive and BCA species is paramount, since misidentification can undermine control efforts and lead to large negative socio‐economic impacts. Unfortunately, most existing publicly accessible genetic databases cannot be used to reliably identify parasitoid species, thereby limiting the accuracy of metabarcoding in CBC research. To address this issue, we argue for the establishment of authoritative genetic databases that link metabarcoding data to taxonomically identified specimens. We further suggest using multiple genetic markers to reduce primer bias and increase taxonomic resolution. We also provide suggestions for biological control‐specific metabarcoding workflows intended to track the long‐term effectiveness of introduced BCAs. Finally, we use the example of an invasive pest, Drosophila suzukii, in a reflective "what if" thought experiment to explore the potential power of community metabarcoding in CBC. [ABSTRACT FROM AUTHOR]