Genetic Tools Research Articles

Evolution of aromatic amino acid metabolism in plants: a key driving force behind plant chemical diversity in aromatic natural products.

A diverse array of plant aromatic compounds contributes to the tremendous chemical diversity in the plant kingdom that cannot be seen in microbes or animals. Such chemodiversity of aromatic natural products has emerged, occasionally in a lineage-specific manner, to adopt to challenging environmental niches, as various aromatic specialized metabolites play indispensable roles in plant development and stress responses (e.g. lignin, phytohormones, pigments and defence compounds). These aromatic natural products are synthesized from aromatic amino acids (AAAs), l-tyrosine, l-phenylalanine and l-tryptophan. While amino acid metabolism is generally assumed to be conserved between animals, microbes and plants, recent phylogenomic, biochemical and metabolomic studies have revealed the diversity of the AAA metabolism that supports efficient carbon allocation to downstream biosynthetic pathways of AAA-derived metabolites in plants. This review showcases the intra- and inter-kingdom diversification and origin of committed enzymes involved in plant AAA biosynthesis and catabolism and their potential application as genetic tools for plant metabolic engineering. I also discuss evolutionary trends in the diversification of plant AAA metabolism that expands the chemical diversity of AAA-derived aromatic natural products in plants. This article is part of the theme issue 'The evolution of plant metabolism'.

Exploring retinal degenerative diseases through CRISPR-based screening.

The CRISPR (Clustered regularly interspaced short palindromic repeats)/Cas9 (CRISPR-associated protein9) system has emerged as a powerful genetic tool, gaining global recognition as a versatile and efficient gene-editing technique. Its transformation into a high-throughput research platform, CRISPR Screening, has demonstrated wide applicability across various fields such as cancer biology, virology, and drug target discovery, resulting in significant advances. However, its potential in studying retinal degenerative diseases remains largely unexplored, despite the urgent need for effective treatments arising from an incomplete understanding of disease mechanisms. This review aims to present a comprehensive overview of the evolution and current state of CRISPR tools and CRISPR screening methodologies. Noteworthy pioneering studies utilizing these technologies are discussed, alongside experimental design guidelines, including positive and negative selection strategies and delivery methods for sgRNAs (single guide RNAs) and Cas proteins. Furthermore, we explore existing in vitro models appropriate for CRISPR screening in retinal research and identify relevant research questions that could be addressed through this approach. It is anticipated that this review will stimulate innovation in retinal research, facilitating a deeper comprehension of retinal pathophysiology and paving the way for groundbreaking therapeutic interventions and enhanced patient outcomes in the management of retinal degenerative disorders.

Caenorhabditis elegans as a Model to Study Aging and Photoaging.

Caenorhabditis elegans (C. elegans) has emerged as an outstanding model organism for investigating the aging process due to its shortened lifespan, well-defined genome, and accessibility of potent genetic tools. This review presents the current findings on chronological aging and photoaging in C. elegans, exploring the elaborate molecular pathways that control these processes. The progression of chronological aging is characterized by a gradual deterioration of physiological functions and is influenced by an interaction of genetic and environmental factors, including the insulin/insulin-like signaling (IIS) pathway. In contrast, photoaging is characterized by increased oxidative stress, DNA damage, and activation of stress response pathways induced by UV exposure. Although the genetic mechanisms of chronological aging in C. elegans have been characterized by extensive research, the pathways regulating photoaging are comparatively less well-studied. Here, we provide an overview of the current understanding of aging research, including the crucial genes and genetic pathways involved in the aging and photoaging processes of C. elegans. Understanding the complex interactions between these factors will provide invaluable insights into the molecular mechanisms underlying chronological aging and photoaging and may lead to novel therapeutic approaches and further studies for promoting healthy aging in humans.

Tissue resident memory CD4 + T cells are sustained by site-specific levels of self-renewal and replacement from precursors.

Tissue-resident memory T cells (T RM ) protect from repeated infections within organs and barrier sites. The breadth and duration of such protection is defined at minimum by three quantities; the rate at which new T RM are generated from precursors, their rate of self-renewal, and their loss rate through death, egress, or differentiation. Quantifying these processes in isolation is challenging. Here we combine genetic fate mapping tools and mathematical models to untangle these basic homeostatic properties of CD4 + T RM in skin and lamina propria (LP) of healthy adult mice. We show that CD69 + CD4 + T RM in skin reside for ∼ 24 days and self-renew more slowly, such that clones halve in size approximately every 5 weeks; and approximately 2% of cells are replaced daily from precursors. CD69 + CD4 + T RM in LP have shorter residencies ( ∼ 14 days) and are maintained largely by immigration (4-6% per day). We also find evidence that the constitutive replacement of CD69 + CD4 + T RM at both sites derives from circulating effectormemory CD4 + T cells, in skin possibly via a CD69 - intermediate. Our integrated approach maps the ontogeny of CD4 + T RM in skin and LP and exposes their dynamic and distinct behaviours, with continual seeding and erosion potentially impacting the duration of immunity at these sites.

Heat stress tolerance in wheat seedling: Clustering genotypes and identifying key traits using multivariate analysis

Elevated atmospheric heat is considered as one of the bottlenecks for global wheat production. Screening potential wheat genotypes against heat stress and selecting some suitable indicators to assist in understanding thermotolerance could be crucial for sustaining wheat cultivation. Accordingly, 80 diverse bread wheat genotypes were evaluated in controlled lab condition by imposing a week-long heat stress (35/25 °C D/N) at the seedling stage. The response of heat stress was evaluated using multivariate analysis techniques on 20 morpho-physiological traits. Results showed significant variations in the studied traits due to the imposition of heat stress. Eleven seedling traits that contributed significantly to the genotypic variability were identified using principal component analysis (PCA). A substantial correlation between most of the selected seedling attributes was observed. Hierarchical cluster analysis identified three distinct clusters among the tested wheat genotypes. Cluster 1, consisting of 33 genotypes, exhibited the highest tolerance to heat stress, followed by Cluster 2 (18 genotypes) with moderate tolerance and Cluster 3 (29 genotypes) showing susceptibility. Linear discriminant analysis (LDA) approved that nearly 93 % of the wheat genotypes were appropriately ascribed to each cluster. The squared distance analysis confirmed the distinct nature of the clusters. Using multi-trait genotype-ideotype distance index (MGIDI), all 12 identified tolerant genotypes (BG-30, BD-468, BG-24, BD-9908, BG-32, BD-476, BD-594, BD-553, BD-488, BG-33, BD-495, and AS-10627) originated from Cluster 1. Selection gain in MGIDI analysis, broad-sense heritability, and multiple linear regression analysis together identified shoot and root dry and fresh weights, chlorophyll contents (a and total), shoot tissue water content, root-shoot dry weight ratio, and efficiency of photosystem II (PS II) as the most vital discriminatory factors explaining heat stress tolerance of 80 wheat genotypes. The identified genotypes with superior thermotolerance would offer resourceful genetic tools for breeders to improve wheat yield in warmer regions. The traits found to have greater contribution in explaining heat stress tolerance will be equally important in prioritizing future research endeavors.

Tuft cells in the intestine, immunity and beyond.

Tuft cells have gained substantial attention over the past 10 years due to numerous reports linking them with type 2 immunity and microorganism-sensing capacity in many mucosal tissues. This heightened interest is fuelled by their unique ability to produce an array of biological effector molecules, including IL-25, allergy-related eicosanoids, and the neurotransmitter acetylcholine, enabling downstream responses in diverse cell types. Operating through G protein-coupled receptor-mediated signalling pathways reminiscent of type II taste cells in oral taste buds, tuft cells emerge as chemosensory sentinels that integrate luminal conditions, eliciting appropriate responses in immune, epithelial and neuronal populations. How tuft cells promote tissue alterations and adaptation to the variety of stimuli at mucosal surfaces has been explored in multiple studies in the past few years. Since the initial recognition of the role of tuft cells, the discovery of diverse tuft cell effector functions and associated feedback loops have also revealed the complexity of tuft cell biology. Although earlier work largely focused on extraintestinal tissues, novel genetic tools and recent mechanistic studies on intestinal tuft cells established fundamental concepts of tuft cell activation and functions. This Review is an overview of intestinal tuft cells, providing insights into their development, signalling and interaction modules in immunity and other states.

Knockout of rbm24a and rbm24b genes in zebrafish impairs skeletal and cardiac muscle integrity and function during development.

Skeletal and cardiac muscles are contractile tissues whose development and function are dependent on genetic programs that must be precisely orchestrated in time and space. In addition to transcription factors, RNA-binding proteins tightly regulate gene expression by controlling the fate of RNA transcripts, thus specific proteins levels within the cell. Rbm24 has been identified as a key player of myogenesis and cardiomyogenesis in several vertebrates, by controlling various aspects of post-transcriptional regulation, including pre-mRNA alternative splicing and mRNA stabilization. In zebrafish, knockdown of rbm24a or rbm24b also causes skeletal and cardiac muscle phenotypes, but how their combined loss affects muscle integrity and function remains elusive. By genome editing, we have generated rbm24a and rbm24b single mutants as well as double mutants. Structural analyses indicate that homozygous rbm24a and rbm24b double mutants exhibit severe somitic muscle and cardiac phenotypes, although rbm24b single mutants are obviously normal. We further show that the loss of rbm24a and rbm24b disrupts sarcomere organization, impairing functional contractility and motility of skeletal and cardiac muscles. The rbm24 mutant zebrafish represents a new genetic tool for in-depth studies of Rbm24-mediated post-transcriptional regulation of skeletal and cardiac muscle development, disease and regeneration.

A suite of enhancer AAVs and transgenic mouse lines for genetic access to cortical cell types.

The mammalian cortex is comprised of cells classified into types according to shared properties. Defining the contribution of each cell type to the processes guided by the cortex is essential for understanding its function in health and disease. We used transcriptomic and epigenomic cortical cell type taxonomies from mouse and human to define marker genes and putative enhancers and created a large toolkit of transgenic lines and enhancer AAVs for selective targeting of cortical cell populations. We report evaluation of fifteen new transgenic driver lines, two new reporter lines, and >800 different enhancer AAVs covering most subclasses of cortical cells. The tools reported here as well as the scaled process of tool creation and modification enable diverse experimental strategies towards understanding mammalian cortex and brain function.

Enhanced production, artificial intelligence optimized three-phase partitioning extraction, and in silico characterization of extracellular neutral Bacillus cereus proteinase

The present study applied atmospheric and room temperature plasma (ARTP) mutagenesis to improve Bacillus cereus strain for neutral proteinase production. The selected improved stable strain, Phe−Tyr-ARTP-60-E demonstrated a 2.88-fold enhanced proteinase yield and 2.81-fold enhanced proteinase activity with shortened fermentation time. An artificial neural network-embedded genetic algorithm (ANN-GA) was employed to optimize the enzyme's three-phase partitioning (TPP) recovery using Python software. The optimized solution of the hybrid model recommended 38.05% wv−1 (NH4)2SO4, 1.0:2.0 crude extract/tert-butanol ratio, pH 5.84 at 23.4 °C, for the exclusive partitioning of proteinase in the intermediate phase, with 202% recovery, 13-fold purity with specific activity of 922 Umg−1. Sensitivity analysis of the model revealed that enzyme recovery was most sensitive to crude extract/tert-butanol ratio with total sensitivity (ST) of 0.253 while purification factor was most sensitive to pH with an ST of 0.444. In silico analysis using Expasy ProtParam tool revealed that mutant proteinase had 3 amino acid substitutions; Val-to-Cys; Val-to-His and Ile-to-Lys, at positions 152, 288, and 292, respectively, and 39.2 kDa molecular weight, 6.42 isoelectric point, and 33.35 instability index. The 3-Dimensional structure of the enzyme predicted by ModWeb v r273 Server revealed 39% sequence identity with Pseudoalteromonas lipolytica thermolysin. The macromolecule increased transmittance in lysozyme-coated contact lenses by 99.6% in 45 min. We conclude that ARTP mutagenesis and ANN-GA optimized TPP are effective and efficient recalcitrant strain improvement and product recovery methods, respectively. Further genetic tools and analysis of the neutral proteinase-producing gene may be required for increased improvement toward sustainable application.

Nanogene editing drug delivery systems in the treatment of liver fibrosis.

Liver fibrosis is a group of diseases that seriously affect the health of the world's population. Despite significant progress in understanding the mechanisms of liver fibrogenesis, the technologies and drugs used to treat liver fibrosis have limited efficacy. As a revolutionary genetic tool, gene editing technology brings new hope for treating liver fibrosis. Combining nano-delivery systems with gene editing tools to achieve precise delivery and efficient expression of gene editing tools that can be used to treat liver fibrosis has become a rapidly developing field. This review provides a comprehensive overview of the principles and methods of gene editing technology and commonly used gene editing targets for liver fibrosis. We also discuss recent advances in common gene editing delivery vehicles and nano-delivery formulations in liver fibrosis research. Although gene editing technology has potential advantages in liver fibrosis, it still faces some challenges regarding delivery efficiency, specificity, and safety. Future studies need to address these issues further to explore the potential and application of liver fibrosis technologies in treating liver fibrosis.

Exploring the wild almond, Prunus arabica (Olivier), as a genetic source for almond breeding

During the process of almond (Prunus dulcis) domestication, essential traits, which gave plants the plasticity for facing unstable environmental conditions, were lost. In general, the domestication process often narrows the natural genetic diversity. Modern selections (i.e., breeding programs) dramatically accelerated this genetic bottleneck trend to a few successful almond cultivars, which are presently the founders of most commercial cultivars worldwide. The concept of utilizing wild species as a source for important traits and for the enrichment of the gene pool was deeply discussed in previous studies. However, in almonds and other Prunus species, deliberate utilization of wild species as a genetic resource for breeding programs is quite rare. To address these significant challenges, we generated an interspecific F1 population between the Israeli almond cultivar Um el Fahem (UEF) and a specimen of a local wild almond species, Prunus arabica (P. arabica), originating from the Judea desert. This interspecific F1 population possesses high phenotypic variability, and sixteen segregating traits were phenotyped. Among the segregating traits, we were able to genetically associate six agriculturally important traits, such as leaf chlorophyll content (LCC), flower size, and fruit size. The alleles for Self-Compatibility (SC) and kernel bitterness were previously mapped in almond and were reexamined on the background of the distinctive wild genetic material of P. arabica. Finally, phenotypic interactions between traits were suggested, such as rootstock perimeter and canopy area that were positively correlated with total yield in the F1 population. This study is a first step towards developing a well-characterized almond interspecies genetic population. The availability of such a genetic tool with detailed phenotypic analysis is crucial to address and explore the profound influence of almond wild species in Prunus genetic research and breeding. By using the interspecific population as the infrastructure, we show the advantages and importance of utilizing wild relatives.

AKT-mediated phosphorylation of TSC2 controls stimulus- and tissue-specific mTORC1 signaling and organ growth.

Mechanistic target of rapamycin (mTOR) complex 1 (mTORC1) integrates diverse intracellular and extracellular growth signals to regulate cell and tissue growth. How the molecular mechanisms regulating mTORC1 signaling established through biochemical and cell biological studies function under physiological states in specific mammalian tissues are unknown. Here, we characterize a genetic mouse model lacking the 5 phosphorylation sites on the tuberous sclerosis complex 2 (TSC2) protein through which the growth factor-stimulated protein kinase AKT can active mTORC1 signaling in cell culture models. These phospho-mutant mice (TSC2-5A) are developmentally normal but exhibit reduced body weight and the weight of specific organs, such as brain and skeletal muscle, associated with cell intrinsic decreases in growth factor-stimulated mTORC1 signaling. The TSC2-5A mouse model demonstrates that TSC2 phosphorylation is a primary mechanism of mTORC1 activation in some, but not all, tissues and provides a genetic tool to facilitate studies on the physiological regulation of mTORC1.

Prevalence and population genetic analyses of parasites in invasive Vespa velutina and native Hymenoptera

Invasive species pose a threat to the ecological balance of the ecosystems they invade by altering local host-pathogen dynamics. To investigate these relationships and their potential consequences, we examined the prevalence and genetic diversity patterns of Trypanosomatidae, Lipotrophidae, and Nosematidae in a collection of sympatric isolates of the invasive hornet Vespa velutina and local Hymenoptera from two recently colonized areas: Europe and South Korea. Data were gathered through PCR amplification and massive parallel sequencing, and analyses were conducted using population genetics tools. Parasite prevalences showed substantial variation depending on (i) the parasite family (Trypanosomatidae and Nosematidae were the most and less prevalent, respectively), (ii) location (e.g. Galicia displayed the highest pooled values), (iii) the season (highest in spring for Trypanosomatidae and Lipotrophidae), and (iv) the host. V. velutina exhibited significantly lower parasite occurrence than native Hymenoptera across all parasite families (consistent with the enemy release hypothesis), although this difference was less pronounced during the periods of heightened predatory activity, suggestive of trophic transmission. Parasite species displayed significant genetic differentiation between European and South Korean isolates, yet no differentiation was observed across hosts, suggesting that all Hymenoptera are exposed to a common local pathogen population. There was no indication that V. velutina acted as a carrier of foreign parasites to the invaded territories.

Evaluating Methods for the Prediction of Cell Type-Specific Enhancers in the Mammalian Cortex.

Identifying cell type-specific enhancers in the brain is critical to building genetic tools for investigating the mammalian brain. Computational methods for functional enhancer prediction have been proposed and validated in the fruit fly and not yet the mammalian brain. We organized the 'Brain Initiative Cell Census Network (BICCN) Challenge: Predicting Functional Cell Type-Specific Enhancers from Cross-Species Multi-Omics' to assess machine learning and feature-based methods designed to nominate enhancer DNA sequences to target cell types in the mouse cortex. Methods were evaluated based on in vivo validation data from hundreds of cortical cell type-specific enhancers that were previously packaged into individual AAV vectors and retro-orbitally injected into mice. We find that open chromatin was a key predictor of functional enhancers, and sequence models improved prediction of non-functional enhancers that can be deprioritized as opposed to pursued for in vivo testing. Sequence models also identified cell type-specific transcription factor codes that can guide designs of in silico enhancers. This community challenge establishes a benchmark for enhancer prioritization algorithms and reveals computational approaches and molecular information that are crucial for the identification of functional enhancers for mammalian cortical cell types. The results of this challenge bring us closer to understanding the complex gene regulatory landscape of the mammalian brain and help us design more efficient genetic tools and potential gene therapies for human neurological diseases.

Exploring Genetic Drug Targets in Acne Vulgaris: A Comprehensive Proteome-Wide Mendelian Randomization Study.

Acne vulgaris presents a substantial clinical challenge due to its complex pathophysiology and significant impact on quality of life. Identification of novel therapeutic targets for acne using genetic tools can guide the development of more effective treatments. Utilizing a dataset comprising 35 559 Icelandic individuals, we performed proteomic analyses to quantify 4709 circulating proteins. We integrated these data with acne-specific genome-wide association studies (GWAS) encompassing 34 422 acne patients and 364 991 controls. Mendelian randomization (MR) analyses employed the TwoSampleMR tool and Summary-data-based Mendelian Randomization (SMR) to estimate the causal effects of identified proteins on acne risk. Colocalization analyses assessed the likelihood of shared genetic etiology between protein levels and acne using the "coloc" R package. Our proteome-wide MR analysis initially identified 128 proteins potentially associated with acne risk. Following multiple testing corrections using the Benjamini-Hochberg method, fatty acid synthase (FASN) and tissue inhibitor of metalloproteinases 4 (TIMP4) remained significantly associated with acne risk. FASN exhibited a protective effect against acne (OR = 0.768, 95% CI: 0.676-0.872, p = 4.685E-05), while TIMP4 was associated with an increased risk (OR = 1.169, 95% CI: 1.103-1.241, p = 1.956E-07). Colocalization analysis supported a shared genetic basis for these protein-acne associations, with posterior probabilities indicating strong evidence of shared causal variants. Our findings highlight the utility of integrative genomic approaches in identifying potential therapeutic targets for acne. FASN and TIMP4, in particular, demonstrate strong potential as targets for therapeutic intervention, pending further validation through clinical research. These results offer a foundation for targeted acne treatment development, aligning with personalized medicine principles.

Traffic Classification in Software-Defined Networking Using Genetic Programming Tools

The classification of Software-Defined Networking (SDN) traffic is an essential tool for network management, network monitoring, traffic engineering, dynamic resource allocation planning, and applying Quality of Service (QoS) policies. The programmability nature of SDN, the holistic view of the network through SDN controllers, and the capability for dynamic adjustable and reconfigurable controllersare fertile ground for the development of new techniques for traffic classification. Although there are enough research works that have studied traffic classification methods in SDN environments, they have several shortcomings and gaps that need to be further investigated. In this study, we investigated traffic classification methods in SDN using publicly available SDN traffic trace datasets. We apply a series of classifiers, such as MLP (BFGS), FC2 (RBF), FC2 (MLP), Decision Tree, SVM, and GENCLASS, and evaluate their performance in terms of accuracy, detection rate, and precision. Of the methods used, GenClass appears to be more accurate in separating the categories of the problem than the rest, and this is reflected in both precision and recall. The key element of the GenClass method is that it can generate classification rules programmatically and detect the hidden associations that exist between the problem features and the desired classes. However, Genetic Programming-based techniques require significantly higher execution time compared to other machine learning techniques. This is most evident in the feature construction method where at each generation of the genetic algorithm, a set of learning models is required to be trained to evaluate the generated artificial features.

Engineering ethanologenicity into the extremely thermophilic bacterium Anaerocellum (f. Caldicellulosiriuptor) bescii

The anaerobic bacterium Anaerocellum (f. Caldicellulosiruptor) bescii natively ferments the carbohydrate content of plant biomass (including microcrystalline cellulose) into predominantly acetate, H2, and CO2, and smaller amounts of lactate, alanine and valine. While this extreme thermophile (growth Topt 78 °C) is not natively ethanologenic, it has been previously metabolically engineered with this property, albeit initially yielding low solvent titers (∼15 mM). Herein we report significant progress on improving ethanologenicity in A. bescii, such that titers above 130 mM have now been achieved, while concomitantly improving selectivity by minimizing acetate formation. Metabolic engineering progress has benefited from improved molecular genetic tools and better understanding of A. bescii growth physiology. Heterologous expression of a mutated thermophilic alcohol dehydrogenase (AdhE) modified for co-factor requirement, coupled with bioreactor operation strategies related to pH control, have been key to enhanced ethanol generation and fermentation product specificity. Insights gained from metabolic modeling of A. bescii set the stage for its further improvement as a metabolic engineering platform.

A New Frontier in Cystic Fibrosis Pathophysiology: How and When Clock Genes Can Affect the Inflammatory/Immune Response in a Genetic Disease Model.

Cystic fibrosis (CF) is a monogenic syndrome caused by variants in the CF Transmembrane Conductance Regulator (CFTR) gene, affecting various organ and systems, in particular the lung, pancreas, sweat glands, liver, gastrointestinal tract, vas deferens, and vascular system. While for some organs, e.g., the pancreas, a strict genotype-phenotype occurs, others, such as the lung, display a different pathophysiologic outcome in the presence of the same mutational asset, arguing for genetic and environmental modifiers influencing severity and clinical trajectory. CFTR variants trigger a pathophysiological cascade of events responsible for chronic inflammatory responses, many aspects of which, especially related to immunity, are not ascertained yet. Although clock genes expression and function are known modulators of the innate and adaptive immunity, their involvement in CF has been only observed in relation to sleep abnormalities. The aim of this review is to present current evidence on the clock genes role in immune-inflammatory responses at the lung level. While information on this topic is known in other chronic airway diseases (chronic obstructive pulmonary disease and asthma), CF lung disease (CFLD) is lacking in this knowledge. We will present the bidirectional effect between clock genes and inflammatory factors that could possibly be implicated in the CFLD. It must be stressed that besides sleep disturbance and its mechanisms, there are not studies directly addressing the exact nature of clock genes' involvement in inflammation and immunity in CF, pointing out the directions of new and deepened studies in this monogenic affection. Importantly, clock genes have been found to be druggable by means of genetic tools or pharmacological agents, and this could have therapeutic implications in CFLD.

An 8-SNP LDL Cholesterol Polygenic Score: Associations with Cardiovascular Risk Traits, Familial Hypercholesterolemia Phenotype, and Premature Coronary Heart Disease in Central Romania.

Familial hypercholesterolemia (FH) is the most significant inherited risk factor for coronary heart disease (CHD). Current guidelines focus on monogenic FH, but the polygenic form is more common and less understood. This study aimed to assess the clinical utility of an 8-SNP LDLC polygenic score in a central Romanian cohort. The cohort included 97 healthy controls and 125 patients with premature (P)CHD. The weighted LDLC polygenic risk score (wPRS) was analyzed for associations with relevant phenotypic traits, PCHD risk, and clinical FH diagnosis. The wPRS positively correlated with LDLC and DLCN scores, and LDLC concentrations could be predicted by wPRS. A trend of increasing LDLC and DLCN scores with wPRS deciles was observed. A +1 SD increase in wPRS was associated with a 36% higher likelihood of having LDLC > 190 mg/dL and increases in LDLC (+0.20 SD), DLCN score (+0.16 SD), and BMI (+0.15 SD), as well as a decrease in HDLC (-0.14 SD). Although wPRS did not predict PCHD across the entire spectrum of values, individuals above the 90th percentile were three times more likely to have PCHD compared to those within the 10th or 20th percentiles. Additionally, wPRS > 45th percentile identified "definite" clinical FH (DLCN score > 8) with 100% sensitivity and 45% specificity. The LDLC polygenic score correlates with key phenotypic traits, and individuals with high scores are more likely to have PCHD. Implementing this genetic tool may enhance risk prediction and patient stratification. These findings, the first of their kind in Romania, are consistent with the existing literature.

Exploring the Link Between Genetic Predictors of Cardiovascular Disease and Psoriasis.

The epidemiological link between immune-mediated diseases (IMIDs) and cardiovascular disease has often been attributed to systemic inflammation. However, the direction of causality and the biological mechanisms linking cardiovascular disease with IMIDs are incompletely understood. Given the robust epidemiological association and the growing body of supportive mechanistic evidence, psoriasis is an exemplary IMID model for exploring this relationship. To assess the bidirectional relationships between genetic predictors of psoriasis and the 2 major forms of cardiovascular disease, coronary artery disease (CAD) and stroke, and to evaluate the association between genetic predictors of cardiovascular disease with 9 other IMIDs. This was a genetic association study using mendelian randomization (MR), a powerful genetic tool to help distinguish causation from associations observed in epidemiological studies, to provide supportive evidence for causality between traits. The study conducted 2-sample MR analyses using summary-level data from large-scale genome-wide association meta-analysis studies (GWAS) for each trait. The analysis focused on individuals of European descent from GWAS meta-analyses, involving CAD, stroke, psoriasis, and 9 other IMIDs. Data were analyzed from January 2023 to May 2024. Genetic predictors of CAD, stroke, psoriasis, and 9 other IMIDs. The primary outcomes were the associations of genetic predictors of CAD and stroke with the risk of psoriasis and 9 other IMIDs, determined using inverse-variance weighted (IVW) MR estimates. This study included 181 249 cases and 1 165 690 controls with CAD, 110 182 cases and 1 503 898 controls with stroke, 36 466 cases and 458 078 controls with psoriasis, for a total of approximately 3 400 000 individuals, and 9 other IMIDs. In contrast to previous assumptions, genetic predictors of psoriasis were found to have no association with CAD or stroke. In the reverse direction, genetic predictors of both CAD (MR estimate IVW odds ratio [OR], 1.07; 95% CI, 1.04-1.10; P = .003) and stroke (IVW OR, 1.22; 95% CI, 1.05-1.41; P = .01) were found to have risk-increasing associations with psoriasis. Adjusting for stroke rendered the associations of genetically predicted CAD with psoriasis risk nonsignificant (and vice versa), suggesting that a shared effect underlying genetic risk for CAD and stroke associates with increased psoriasis risk. No risk-increasing associations were observed for genetic predictors of cardiovascular disease with other common IMIDs, including rheumatoid arthritis and inflammatory bowel disease. Findings of this mendelian randomization study indicate that genetic predictors of cardiovascular disease were associated with increased psoriasis risk with no reciprocal effect or association with other IMIDs. Elucidating mechanisms underpinning this association could lead to novel therapeutic approaches in both diseases.