Shared Mechanisms Research Articles

Exploring the diversity and evolutionary strategies of prophages in Hyphomicrobiales, comparing animal-associated with non-animal-associated bacteria

The Hyphomicrobiales bacterial order (previously Rhizobiales) exhibits a wide range of lifestyle characteristics, including free-living, plant-association, nitrogen-fixing, and association with animals (Bartonella and Brucella). This study explores the diversity and evolutionary strategies of bacteriophages within the Hyphomicrobiales order, comparing animal-associated (AAB) with non-animal-associated bacteria (NAAB). We curated 560 high-quality complete genomes of 58 genera from this order and used the PHASTER server for prophage annotation and classification. For 19 genera with representative genomes, we curated 96 genomes and used the Defense-Finder server to summarize the type of anti-phage systems (APS) found in this order. We analyzed the genetic repertoire and length distributions of prophages, estimating evolutionary rates and comparing intact, questionable, and incomplete prophages in both groups. Analyses of best-fit parameters and bootstrap sensitivity were used to understand the evolutionary processes driving prophage gene content. A total of 1860 prophages distributed in Hyphomicrobiales were found, 695 in AAB and 1165 in the NAAB genera. The results revealed a similar number of prophages per genome in AAB and NAAB and a similar length distribution, suggesting shared mechanisms of genetic acquisition of prophage genes. Changes in the frequency of specific gene classes were observed between incomplete and intact prophages, indicating preferential loss or enrichment in both groups. The analysis of best-fit parameters and bootstrap sensitivity tests indicated a higher selection coefficient, induction rate, and turnover in NAAB genomes. We found 68 types of APS in Hyphomicrobiales; restriction modification (RM) and abortive infection (Abi) were the most frequent APS found for all Hyphomicrobiales, and within the AAB group. This classification of APS showed that NAAB genomes have a greater diversity of defense systems compared to AAB, which could be related to the higher rates of prophage induction and turnover in the latter group. Our study provides insights into the distributions of both prophages and APS in Hyphomicrobiales genomes, demonstrating that NAAB carry more defense systems against phages, while AAB show increased prophage stability and an increased number of incomplete prophages. These results suggest a greater role for domesticated prophages within animal-associated bacteria in Hyphomicrobiales.

Epidemiology, screening, and Co-management of type 2 diabetes mellitus and Metabolic-dysfunction associated steatotic liver disease.

Metabolic-dysfunction associated steatotic liver disease (MASLD), previously known as non-alcoholic fatty liver disease (NAFLD), is increasingly recognized as a prevalent global burden. Type 2 diabetes mellitus (T2DM), another important metabolic disease, is considered a major contributor to the development of MASLD. MASLD and T2DM have a strong association with each other due to shared pathogenic mechanisms. The co-existence of the two diseases increases the risk of liver-related adverse outcomes, and imposes a heavier burden on extrahepatic outcomes, representing a substantial public health issue. Effective assessment and management of T2DM combined with MASLD necessitate a multidisciplinary approach. The emergence of numerous randomized clinical trials has shed light on the treatment of T2DM combined with MASLD. This review uncovered the epidemiology of the intertwined T2DM and MASLD, offer insights into the evaluation of hepatic fibrosis in T2DM patients, glucose monitoring in MASLD population, and provide comprehensive co-management strategies for addressing both diseases.

Genetic association of inflammatory marker GlycA with lung function and respiratory diseases

Association of circulating glycoprotein acetyls (GlycA), a systemic inflammation biomarker, with lung function and respiratory diseases remain to be investigated. We examined the genetic correlation, shared genetics, and potential causality of GlycA (N = 115,078) with lung function and respiratory diseases (N = 497,000). GlycA showed significant genetic correlation with FEV1 (rg = −0.14), FVC (rg = −0.18), asthma (rg = 0.21) and COPD (rg = 0.31). We consistently identified ten shared loci (including chr3p21.31 and chr8p23.1) at both SNP and gene level revealing potential shared biological mechanisms involving ubiquitination, immune response, Wnt/β-catenin signaling, cell growth and differentiation in tissues or cells including blood, epithelium, fibroblast, fetal thymus, and fetal intestine. Genetically elevated GlycA was significantly correlated with lung function and asthma susceptibility (354.13 ml decrement of FEV1, 442.28 ml decrement of FVC, and 144% increased risk of asthma per SD increment of GlycA) from MR analyses. Our findings provide insights into biological mechanisms of GlycA in relating to lung function, asthma, and COPD.

A comprehensive genome-wide cross-trait analysis of sexual factors and uterine leiomyoma.

Age at first sexual intercourse (AFS) and lifetime number of sexual partners (NSP) may influence the pathogenesis of uterine leiomyoma (UL) through their associations with hormonal concentrations and uterine infections. Leveraging summary statistics from large-scale genome-wide association studies conducted in European ancestry for each trait (NAFS = 214,547; NNSP = 370,711; NUL = 302,979), we observed a significant negative genomic correlation for UL with AFS (rg = -0.11, P = 7.83×10-4), but not with NSP (rg = 0.01, P = 0.62). Four specific genomic regions were identified as contributing significant local genetic correlations to AFS and UL, including one genomic region further identified for NSP and UL. Partitioning SNP-heritability with cell-type-specific annotations, a close clustering of UL with both AFS and NSP was identified in immune and blood-related components. Cross-trait meta-analysis revealed 15 loci shared between AFS/NSP and UL, including 7 novel SNPs. Univariable two-sample Mendelian randomization (MR) analysis suggested no evidence for a causal association between genetically predicted AFS/NSP and risk of UL, nor vice versa. Multivariable MR adjusting for age at menarche or/and age at natural menopause revealed a significant causal effect of genetically predicted higher AFS on a lower risk of UL. Such effect attenuated to null when age at first birth was further included. Utilizing participant-level data from the UK Biobank, one-sample MR based on genetic risk scores yielded consistent null findings among both pre-menopausal and post-menopausal females. From a genetic perspective, our study demonstrates an intrinsic link underlying sexual factors (AFS and NSP) and UL, highlighting shared biological mechanisms rather than direct causal effects. Future studies are needed to elucidate the specific mechanisms involved in the shared genetic influences and their potential impact on UL development.

Switching off: disruptive TMS reveals distinct contributions of the posterior middle temporal gyrus and angular gyrus to bilingual speech production.

The role of the left temporoparietal cortex in speech production has been extensively studied during native language processing, proving crucial in controlled lexico-semantic retrieval under varying cognitive demands. Yet, its role in bilinguals, fluent in both native and second languages, remains poorly understood. Here, we employed continuous theta burst stimulation to disrupt neural activity in the left posterior middle-temporal gyrus (pMTG) and angular gyrus (AG) while Italian-Friulian bilinguals performed a cued picture-naming task. The task involved between-language (naming objects in Italian or Friulian) and within-language blocks (naming objects ["knife"] or associated actions ["cut"] in a single language) in which participants could either maintain (non-switch) or change (switch) instructions based on cues. During within-language blocks, cTBS over the pMTG entailed faster naming for high-demanding switch trials, while cTBS to the AG elicited slower latencies in low-demanding non-switch trials. No cTBS effects were observed in the between-language block. Our findings suggest a causal involvement of the left pMTG and AG in lexico-semantic processing across languages, with distinct contributions to controlled vs. "automatic" retrieval, respectively. However, they do not support the existence of shared control mechanisms within and between language(s) production. Altogether, these results inform neurobiological models of semantic control in bilinguals.

Distinct mechanisms of attentional suppression: exploration of trait factors underlying cued- and learned-suppression

Attention allows us to focus on relevant information while ignoring distractions. Effective suppression of distracting information is crucial for efficient visual search. Recent studies have developed two paradigms to investigate attentional suppression: cued-suppression which is based on top-down control, and learned-suppression which is based on selection history. While both types of suppression reportedly engage proactive control, it remains unclear whether they rely on shared mechanisms. This study aimed to determine the relationship between cued- and learned-suppression. In a within-subjects design, 54 participants performed a cued-suppression task where pre-cues indicated upcoming target or distractor colors, and a learned-suppression task where a salient color distractor was present or absent. No significant correlation emerged between performance in the two tasks, suggesting distinct suppression mechanisms. Cued-suppression correlated with visual working memory capacity, indicating reliance on explicit control. In contrast, learned-suppression correlated with everyday distractibility, suggesting implicit control based on regularities. These results provide evidence for heterogeneous proactive control mechanisms underlying cued- and learned-suppression. While both engage inhibition, cued-suppression relies on deliberate top-down control modulated by working memory, whereas learned-suppression involves implicit suppression shaped by selection history and distractibility traits.

Depression and Type 2 Diabetes: Dissecting the Causal Mechanisms

Depression and Type 2 Diabetes (T2D) are two prevalent and debilitating chronic conditions that often coexist and exhibit a bidirectional relationship. This review paper aims to dissect the causal mechanisms underlying the association between depression and T2D, shedding light on the complex interplay between these two disorders. Epidemiological evidence suggests a robust association between depression and an increased risk of developing T2D, as well as a reciprocal relationship where T2D serves as a risk factor for depression onset. Various biological, psychological, and behavioral mechanisms have been proposed to underlie this bidirectional relationship. Depression is thought to contribute to the development of T2D through dysregulation of neuroendocrine pathways, increased inflammation, alterations in lifestyle behaviors, and poor treatment adherence. Conversely, T2D may exacerbate or precipitate depression through mechanisms involving insulin resistance, hyperglycemia-induced neuronal damage, inflammation, and the impact of chronic illness on psychological well-being. Shared pathophysiological mechanisms between depression and T2D, including dysregulation of the hypothalamic-pituitary-adrenal axis, insulin signaling pathways, and inflammatory processes, further contribute to their co-occurrence. Psychosocial factors such as socioeconomic status, social support, and access to healthcare also play significant roles in shaping the depression-T2D relationship. Integrated care models that address both physical and mental health needs, along with targeted interventions addressing lifestyle modifications and psychosocial support, are essential for managing these comorbid conditions effectively. Future research directions include longitudinal studies to elucidate temporal associations, intervention trials targeting shared mechanisms, and precision medicine approaches to identify subgroups at heightened risk. Understanding the causal mechanisms underlying the depression-T2D relationship is crucial for informing clinical practice, public health strategies, and the development of personalized interventions aimed at mitigating the burden of these interconnected disorders.

Genetic mapping across autoimmune diseases reveals shared associations and mechanisms.

Autoimmune and inflammatory diseases are polygenic disorders of the immune system. Many genomic loci harbor risk alleles for several diseases, but the limited resolution of genetic mapping prevents determining whether the same allele is responsible, indicating a shared underlying mechanism. Here, using a collection of 129,058 cases and controls across 6 diseases, we show that ~40% of overlapping associations are due to the same allele. We improve fine-mapping resolution for shared alleles twofold by combining cases and controls across diseases, allowing us to identify more expression quantitative trait loci driven by the shared alleles. The patterns indicate widespread sharing of pathogenic mechanisms but not a single global autoimmune mechanism. Our approach can be applied to any set of traits and is particularly valuable as sample collections become depleted.

Abstract 3102: NELISA High-throughput Proteomics Captures Disease Phenotypes And Cytokine Interactions By Quantifying Immune, Metabolic, And Cardiovascular Markers

The variety of cell types and interactions involved in vascular diseases pose a significant challenge to quantifying the breadth of inflammatory, metabolic, and cardiovascular proteins that could provide mechanistic information or serve as clinical biomarkers, particularly at the scale needed for population studies or drug discovery screens. Unfortunately, proteomics tools able to quantify these proteins compromise either content or throughput/cost, limiting their use. To overcome this issue, we developed the nELISA: a high-throughput miniaturized ELISA capable of quantifying 272 cytokines, adipokines, proteases, soluble receptors, and growth factors, at 10x-reduced cost compared to previous tools. We applied the nELISA to model systems as a proof-of-concept for use in high-throughput screens. We ran the largest PBMC secretome screen to date, in which ~10,000 PBMC samples were profiled at a throughput of 1536 samples/day. Cells were treated with a selection of myeloid and T cell stimuli to model different disease states, and were further perturbed with a selected library of 80 recombinant cytokine perturbagens; secreted proteins were profiled in all samples, resulting in ~2M datapoints. In addition to distinguishing the various disease states, the nELISA captured 449 cytokine interactions, where addition of a specific perturbagen resulted in a change in the expression levels of a secreted protein. Of note, we found 3.2-fold more of these interactions than reported at the transcriptomic level from the CytoSig database. By clustering these cytokine interactions, we identified perturbagens with shared mechanisms of action, including results supporting the use of IL-1 Receptor antagonist to replace IFN beta in certain indications. We will expand on these findings and discuss how the nELISA is being applied to HUVEC cultures, whole blood assays, and patient plasma/serum.

Exploring casual effects and shared molecular mechanism between psoriasis and liver cancer through Mendelian randomization and comprehensive bioinformatic analyses

Psoriasis (Ps), a chronic inflammatory disease affecting approximately 2 % of the global population, has been associated with an increased risk of liver cancer in observational studies. However, their causal relationships as well as underlying shared molecular mechanisms between Ps and liver cancer remain unclear. Using bidirectional Mendelian randomization analysis, we revealed that a genetic predisposition to liver cancer increased the risk of Ps in European and East Asian populations but not the other way around. Moreover, we analyzed three transcriptomic datasets of patients with Ps and liver cancer from open-source databases. Differentially expressed genes (DEGs) and disease-specific gene co-expression module analyses revealed that cell-cycle dysregulation was the shared mechanism of Ps and liver cancer. Moreover, we identified a rank-conservative gene signature shared between these two diseases, which demonstrated significance in diagnostic and prognostic predictions. These findings provided valuable insights into the interconnections between Ps and liver cancer, which may be helpful to guide therapeutic management.

Shared molecular mechanisms and transdiagnostic potential of neurodevelopmental disorders and immune disorders

The co-occurrence and familial clustering of neurodevelopmental disorders and immune disorders suggest shared genetic risk factors. Based on genome-wide association summary statistics from five neurodevelopmental disorders and four immune disorders, we conducted genome-wide, local genetic correlation and polygenic overlap analysis. We further performed a cross-trait GWAS meta-analysis. Pleotropic loci shared between the two categories of diseases were mapped to candidate genes using multiple algorithms and approaches. Significant genetic correlations were observed between neurodevelopmental disorders and immune disorders, including both positive and negative correlations. Neurodevelopmental disorders exhibited higher polygenicity compared to immune disorders. Around 50%-90% of genetic variants of the immune disorders were shared with neurodevelopmental disorders. The cross-trait meta-analysis revealed 154 genome-wide significant loci, including 8 novel pleiotropic loci. Significant associations were observed for 30 loci with both types of diseases. Pathway analysis on the candidate genes at these loci revealed common pathways shared by the two types of diseases, including neural signaling, inflammatory response, and PI3K-Akt signaling pathway. In addition, 26 of the 30 lead SNPs were associated with blood cell traits. Neurodevelopmental disorders exhibit complex polygenic architecture, with a subset of individuals being at a heightened genetic risk for both neurodevelopmental and immune disorders. The identification of pleiotropic loci has important implications for exploring opportunities for drug repurposing, enabling more accurate patient stratification, and advancing genomics-informed precision in the medical field of neurodevelopmental disorders.

OA01 Cluster medicine: the role of genetics for identifying shared biological pathways between rheumatoid arthritis and common comorbidities for targeting treatments

Abstract Background/Aims Rheumatoid arthritis (RA) is a chronic inflammatory disorder associated with significant pain and disability, as well as increased risk of comorbidities. These comorbidities, such as coronary artery disease, stroke, heart failure and type 2 diabetes, often form predictable clusters highlighting the importance of common disease mechanisms. Identifying these clusters, and the underlying shared mechanisms, is key to the concept of cluster medicine which aims to take a more systemic approach to treating comorbidity. It is hypothesised that inflammatory processes in RA promote the pathogenesis of these comorbid diseases, which typically occur at an earlier stage of life than in the general population. However, few studies have investigated the degree of shared genetic susceptibility implicated across these traits. The present study aimed to identify and characterise pleiotropic loci and shared biological pathways involved in the pathogenesis of RA and cardiometabolic disorders. Methods European-only GWAS summary statistics were collected for RA (seropositive, seronegative, and overall) and seven cardiometabolic traits, including ischemic stroke, any stroke, heart failure, coronary artery disease, hypertension, atrial fibrillation, and type 2 diabetes. Cross-trait linkage disequilibrium score regression was employed to estimate the degree of genetic correlation (rg) between all pairs of traits. Subset-based meta-analysis was performed using the R package ASSET to identify pleiotropic single nucleotide polymorphisms (SNPs). Pleiotropic SNPs were assigned to genes based on positional and eQTL mapping. Prioritised genes were tested for over-representation in functional categories and biological pathways in gene sets obtained from MsigDB and WikiPathways using the hypergeometric test loci. Gene mapping and enrichment analyses were conducted in FUMA. Results RA showed significant positive genetic correlation with all cardiometabolic traits, with the seronegative subtype showing greater correlation than the seropositive subtype. Correlations between RA and cardiometabolic phenotypes ranged from 0.11 - 0.38, the strongest of which was between seronegative RA and heart failure (rg = 0.38, P = 2.6e-07). A total of 67 lead SNPs were identified as potentially pleiotropic. Pleiotropic SNPs were mapped to genes including IL6R, PTPN11, ATXN2, PLCL1 and SOX6. Pathway enrichment analyses revealed that mapped genes were primarily involved in inflammatory signalling pathways, involving interleukins, TNF-α and interferon (gamma and alpha) response. Conclusion This study provides evidence for pleiotropy across RA and cardiometabolic traits, whereby inherited genetic variants predispose to aberrant cytokine signalling, thus conferring risk to multiple diseases where inflammation is a key driver of pathogenesis. Disclosure M. Stoves: None. M. Soomro: None. S. Zhao: None. D. Plant: None. A. Barton: None. J. Bowes: None.

0031 Shared Genetic Mechanisms Underlying Association Between Sleep Disturbances and Depressive Symptoms

0031 Shared Genetic Mechanisms Underlying Association Between Sleep Disturbances and Depressive Symptoms

The association between depressive symptoms and high-sensitivity C-reactive protein: Is body mass index a moderator?

ObjectiveDepression and obesity are highly comorbid conditions with shared biological mechanisms. It remains unclear how depressive symptoms and body mass index (BMI) interact in relation to inflammation. This cross-sectional study investigated the independent associations of depressive symptoms and BMI with high sensitivity C-reactive protein (hs-CRP), as well as the moderating role of BMI on the depressive symptoms-hs-CRP association. MethodsParticipants (n = 8827) from the 2015–2018 National Health and Nutrition Examination Surveys were aged ≥20 with a BMI ≥18.5 kg/m2, completed the Depression Screener, and had hs-CRP data. Multivariable linear regression was used to analyze hs-CRP in relation to depressive symptoms and BMI. An interaction term was included to examine whether the depressive symptoms-hs-CRP relationship differs depending on BMI. ResultsThere was a slight, albeit non-significant, increase in hs-CRP levels with each one-point increase in depressive symptoms (aCoef.Estm. = 0.01, 95% CI = −0.05, 0.06, p = 0.754). Participants with overweight (aCoef.Estm. = 1.07, 95% CI = 0.61, 1.53, p < 0.001) or obese (aCoef.Estm. = 3.51, 95% CI = 3.04, 3.98, p < 0.001) BMIs had higher mean hs-CRP levels than those with a healthy BMI. There were no significant interactions between depressive symptoms and overweight (aCoef.Estm. = 0.04, 95% CI = −0.04, 0.13, p = 0.278) or obese (aCoef.Estm. = 0.11, 95% CI = −0.01, 0.22, p = 0.066) BMI indicating a lack of difference in the depressive symptoms-hs-CRP association across participants in the healthy versus overweight and obese ranges. ConclusionsThis study suggests that BMI might not act as a moderator in the association between depressive symptoms and hs-CRP. Results should be replicated in larger samples. Further research is warranted to understand underlying mechanisms.

The Genomic Intersection of Oligodendrocyte Dynamics in Schizophrenia and Aging Unravels Novel Pathological Mechanisms and Therapeutic Potentials.

Schizophrenia is a significant worldwide health concern, affecting over 20 million individuals and contributing to a potential reduction in life expectancy by up to 14.5 years. Despite its profound impact, the precise pathological mechanisms underlying schizophrenia continue to remain enigmatic, with previous research yielding diverse and occasionally conflicting findings. Nonetheless, one consistently observed phenomenon in brain imaging studies of schizophrenia patients is the disruption of white matter, the bundles of myelinated axons that provide connectivity and rapid signalling between brain regions. Myelin is produced by specialised glial cells known as oligodendrocytes, which have been shown to be disrupted in post-mortem analyses of schizophrenia patients. Oligodendrocytes are generated throughout life by a major population of oligodendrocyte progenitor cells (OPC), which are essential for white matter health and plasticity. Notably, a decline in a specific subpopulation of OPC has been identified as a principal factor in oligodendrocyte disruption and white matter loss in the aging brain, suggesting this may also be a factor in schizophrenia. In this review, we analysed genomic databases to pinpoint intersections between aging and schizophrenia and identify shared mechanisms of white matter disruption and cognitive dysfunction.

Novel immune cross-talk between inflammatory bowel disease and IgA nephropathy

The mechanisms underlying the complex correlation between immunoglobulin A nephropathy (IgAN) and inflammatory bowel disease (IBD) remain unclear. This study aimed to identify the optimal cross-talk genes, potential pathways, and mutual immune-infiltrating microenvironments between IBD and IgAN to elucidate the linkage between patients with IBD and IgAN. The IgAN and IBD datasets were obtained from the Gene Expression Omnibus (GEO). Three algorithms, CIBERSORTx, ssGSEA, and xCell, were used to evaluate the similarities in the infiltrating microenvironment between the two diseases. Weighted gene co-expression network analysis (WGCNA) was implemented in the IBD dataset to identify the major immune infiltration modules, and the Boruta algorithm, RFE algorithm, and LASSO regression were applied to filter the cross-talk genes. Next, multiple machine learning models were applied to confirm the optimal cross-talk genes. Finally, the relevant findings were validated using histology and immunohistochemistry analysis of IBD mice. Immune infiltration analysis showed no significant differences between IBD and IgAN samples in most immune cells. The three algorithms identified 10 diagnostic genes, MAPK3, NFKB1, FDX1, EPHX2, SYNPO, KDF1, METTL7A, RIDA, HSDL2, and RIPK2; FDX1 and NFKB1 were enhanced in the kidney of IBD mice. Kyoto Encyclopedia of Genes and Genomes analysis showed 15 mutual pathways between the two diseases, with lipid metabolism playing a vital role in the cross-talk. Our findings offer insights into the shared immune mechanisms of IgAN and IBD. These common pathways, diagnostic cross-talk genes, and cell-mediated abnormal immunity may inform further experimental studies.

Shared genetic architecture between autoimmune disorders and B-cell acute lymphoblastic leukemia: insights from large-scale genome-wide cross-trait analysis.

To study the shared genetic structure between autoimmune diseases and B-cell acute lymphoblastic leukemia (B-ALL) and identify the shared risk loci and genes and genetic mechanisms involved. Based on large-scale genome-wide association study (GWAS) summary-level data sets, we observed genetic overlaps between autoimmune diseases and B-ALL, and cross-trait pleiotropic analysis was performed to detect shared pleiotropic loci and genes. A series of functional annotation and tissue-specific analysis were performed to determine the influence of pleiotropic genes. The heritability enrichment analysis was used to detect crucial immune cells and tissues. Finally, bidirectional Mendelian randomization (MR) methods were utilized to investigate the casual associations. Our research highlighted shared genetic mechanisms between seven autoimmune disorders and B-ALL. A total of 73 pleiotropic loci were identified at the genome-wide significance level (P < 5 × 10-8), 16 of which had strong evidence of colocalization. We demonstrated that several loci have been previously reported (e.g., 17q21) and discovered some novel loci (e.g., 10p12, 5p13). Further gene-level identified 194 unique pleiotropic genes, for example IKZF1, GATA3, IKZF3, GSDMB, and ORMDL3. Pathway analysis determined the key role of cellular response to cytokine stimulus, B cell activation, and JAK-STAT signaling pathways. SNP-level and gene-level tissue enrichment suggested that crucial role pleiotropic mechanisms involved in the spleen, whole blood, and EBV-transformed lymphocytes. Also, hyprcoloc and stratified LD score regression analyses revealed that B cells at different developmental stages may be involved in mechanisms shared between two different diseases. Finally, two-sample MR analysis determined causal effects of asthma and rheumatoid arthritis on B-ALL. Our research proved shared genetic architecture between autoimmune disorders and B-ALL and shed light on the potential mechanism that might involve in.

Assessment of TGx-DDI genes for genotoxicity in a comprehensive panel of chemicals

Background The TGx-DDI biomarker identifies transcripts specifically induced by primary DNA damage. Profiling similarity of TGx-DDI signatures can allow clustering compounds by genotoxic mechanism. This transcriptomics-based approach complements conventional toxicology testing by enhancing mechanistic resolution. Methods Unsupervised hierarchical clustering and t-distributed stochastic neighbor embedding (tSNE) were utilized to assess similarity of publicly-available per- and polyfluoroalkyl substances (PFAS) and ToxCast chemicals based on TGx-DDI modulation. TempO-seq transcriptomic data after highest chemical concentrations were analyzed. Results Clustering discriminated between genotoxic and non-genotoxic compounds while drawing similarity among chemicals with shared mechanisms. PFAS largely clustered distinctly from classical mutagens. However, dynamic range across PFAS types and durations indicated variable potential for DNA damage. tSNE visualization reinforced phenotypic groupings, with genotoxins clustering separately from non-DNA damaging agents. Discussion Unsupervised learning approaches applied to TGx-DDI profiles effectively categorizes chemical genotoxicity potential, aiding elucidation of biological response pathways. This transcriptomics-based strategy gives further insight into the role and effect of individual TGx-DDI biomarker genes and complements existing assays by enhancing mechanistic resolution. Overall, TGx-DDI biomarker profiling holds promise for predictive safety screening.

Atherosclerosis and the Bidirectional Relationship between Cancer and Cardiovascular Disease: From Bench to Bedside-Part 1.

Atherosclerosis, a complex metabolic-immune disease characterized by chronic inflammation driven by the buildup of lipid-rich plaques within arterial walls, has emerged as a pivotal factor in the intricate interplay between cancer and cardiovascular disease. This bidirectional relationship, marked by shared risk factors and pathophysiological mechanisms, underscores the need for a comprehensive understanding of how these two formidable health challenges intersect and influence each other. Cancer and its treatments can contribute to the progression of atherosclerosis, while atherosclerosis, with its inflammatory microenvironment, can exert profound effects on cancer development and outcomes. Both cancer and cardiovascular disease involve intricate interactions between general and personal exposomes. In this review, we aim to summarize the state of the art of translational data and try to show how oncologic studies on cardiotoxicity can broaden our knowledge of crucial pathways in cardiovascular biology and exert a positive impact on precision cardiology and cardio-oncology.

A review of air pollution as a driver of cardiovascular disease risk across the diabetes spectrum.

The prevalence of diabetes is estimated to reach almost 630 million cases worldwide by the year 2045; of current and projected cases, over 90% are type 2 diabetes. Air pollution exposure has been implicated in the onset and progression of diabetes. Increased exposure to fine particulate matter air pollution (PM2.5) is associated with increases in blood glucose and glycated hemoglobin (HbA1c) across the glycemic spectrum, including normoglycemia, prediabetes, and all forms of diabetes. Air pollution exposure is a driver of cardiovascular disease onset and exacerbation and can increase cardiovascular risk among those with diabetes. In this review, we summarize the literature describing the relationships between air pollution exposure, diabetes and cardiovascular disease, highlighting how airborne pollutants can disrupt glucose homeostasis. We discuss how air pollution and diabetes, via shared mechanisms leading to endothelial dysfunction, drive increased cardiovascular disease risk. We identify portable air cleaners as potentially useful tools to prevent adverse cardiovascular outcomes due to air pollution exposure across the diabetes spectrum, while emphasizing the need for further study in this particular population. Given the enormity of the health and financial impacts of air pollution exposure on patients with diabetes, a greater understanding of the interventions to reduce cardiovascular risk in this population is needed.