Elevated rates of horizontal gene transfer in the industrialized human microbiome.

Industrialization has impacted the human gut ecosystem, resulting in altered microbiome composition and diversity. Whether bacterial genomes may also adapt to the industrialization of their host populations remains largely unexplored. Here, we investigate the extent to which the rates and targets of horizontal gene transfer (HGT) vary across thousands of bacterial strains from 15 human populations spanning a range of industrialization. We show that HGTs have accumulated in the microbiome over recent host generations and that HGT occurs at high frequency within individuals. Comparison across human populations reveals that industrialized lifestyles are associated with higher HGT rates and that the functions of HGTs are related to the level of host industrialization. Our results suggest that gut bacteria continuously acquire new functionality based on host lifestyle and that high rates of HGT may be a recent development in human history linked to industrialization.

Decoding the Genomics of Abdominal Aortic Aneurysm.

A key aspect of genomic medicine is to make individualized clinical decisions from personal genomes. We developed a machine-learning framework to integrate personal genomes and electronic health record (EHR) data and used this framework to study abdominal aortic aneurysm (AAA), a prevalent irreversible cardiovascular disease with unclear etiology. Performing whole-genome sequencing on AAA patients and controls, we demonstrated its predictive precision solely from personal genomes. By modeling personal genomes with EHRs, this framework quantitatively assessed the effectiveness of adjusting personal lifestyles given personal genome baselines, demonstrating its utility as a personal health management tool. We showed that this new framework agnostically identified genetic components involved in AAA, which were subsequently validated in human aortic tissues and in murine models. Our study presents a new framework for disease genome analysis, which can be used for both health management and understanding the biological architecture of complex diseases. VIDEO ABSTRACT.

Phage display sequencing reveals that genetic, environmental, and intrinsic factors influence variation of human antibody epitope repertoire.

Phage-displayed immunoprecipitation sequencing (PhIP-seq) has enabled high-throughput profiling of human antibody repertoires. However, a comprehensive overview of environmental and genetic determinants shaping human adaptive immunity is lacking. In this study, we investigated the effects of genetic, environmental, and intrinsic factors on the variation in human antibody repertoires. We characterized serological antibody repertoires against 344,000 peptides using PhIP-seq libraries from a wide range of microbial and environmental antigens in 1,443 participants from a population cohort. We detected individual-specificity, temporal consistency, and co-housing similarities in antibody repertoires. Genetic analyses showed the involvement of the HLA, IGHV, and FUT2 gene regions in antibody-bound peptide reactivity. Furthermore, we uncovered associations between phenotypic factors (including age, cell counts, sex, smoking behavior, and allergies, among others) and particular antibody-bound peptides. Our results indicate that human antibody epitope repertoires are shaped by both genetics and environmental exposures and highlight specific signatures of distinct phenotypes and genotypes.

DeePhafier: a phage lifestyle classifier using a multilayer self-attention neural network combining protein information.

Bacteriophages are the viruses that infect bacterial cells. They are the most diverse biological entities on earth and play important roles in microbiome. According to the phage lifestyle, phages can be divided into the virulent phages and the temperate phages. Classifying virulent and temperate phages is crucial for further understanding of the phage-host interactions. Although there are several methods designed for phage lifestyle classification, they merely either consider sequence features or gene features, leading to low accuracy. A new computational method, DeePhafier, is proposed to improve classification performance on phage lifestyle. Built by several multilayer self-attention neural networks, a global self-attention neural network, and being combined by protein features of the Position Specific Scoring Matrix matrix, DeePhafier improves the classification accuracy and outperforms two benchmark methods. The accuracy of DeePhafier on five-fold cross-validation is as high as 87.54% for sequences with length >2000bp.

Chitin utilization by marine picocyanobacteria and the evolution of a planktonic lifestyle.

Marine picocyanobacteria Prochlorococcus and Synechococcus, the most abundant photosynthetic cells in the oceans, are generally thought to have a primarily single-celled and free-living lifestyle. However, while studying the ability of picocyanobacteria to supplement photosynthetic carbon fixation with the use of exogenous organic carbon, we found the widespread occurrence of genes for breaking down chitin, an abundant source of organic carbon that exists primarily as particles. We show that cells that encode a chitin degradation pathway display chitin degradation activity, attach to chitin particles, and show enhanced growth under low light conditions when exposed to chitosan, a partially deacetylated soluble form of chitin. Marine chitin is largely derived from arthropods, which underwent major diversifications 520 to 535 Mya, close to when marine picocyanobacteria are inferred to have appeared in the ocean. Phylogenetic analyses confirm that the chitin utilization trait was acquired at the root of marine picocyanobacteria. Together this leads us to postulate that attachment to chitin particles allowed benthic cyanobacteria to emulate their mat-based lifestyle in the water column, initiating their expansion into the open ocean, seeding the rise of modern marine ecosystems. Subsequently, transitioning to a constitutive planktonic life without chitin associations led to cellular and genomic streamlining along a major early branch within Prochlorococcus. Our work highlights how the emergence of associations between organisms from different trophic levels, and their coevolution, creates opportunities for colonizing new environments. In this view, the rise of ecological complexity and the expansion of the biosphere are deeply intertwined processes.

Molecular regulation of virulence in Legionella pneumophila.

Legionella pneumophila is a gram-negative bacteria found in natural and anthropogenic aquatic environments such as evaporative cooling towers, where it reproduces as an intracellular parasite of cohabiting protozoa. If L. pneumophila is aerosolized and inhaled by a susceptible person, bacteria may colonize their alveolar macrophages causing the opportunistic pneumonia Legionnaires' disease. L. pneumophila utilizes an elaborate regulatory network to control virulence processes such as the Dot/Icm Type IV secretion system and effector repertoire, responding to changing nutritional cues as their host becomes depleted. The bacteria subsequently differentiate to a transmissive state that can survive in the environment until a replacement host is encountered and colonized. In this review, we discuss the lifecycle of L. pneumophila and the molecular regulatory network that senses nutritional depletion via the stringent response, a link to stationary phase-like metabolic changes via alternative sigma factors, and two-component systems that are homologous to stress sensors in other pathogens, to regulate differentiation between the intracellular replicative phase and more transmissible states. Together, we highlight how this prototypic intracellular pathogen offers enormous potential in understanding how molecular mechanisms enable intracellular parasitism and pathogenicity.

PhaTYP: predicting the lifestyle for bacteriophages using BERT.

Bacteriophages (or phages), which infect bacteria, have two distinct lifestyles: virulent and temperate. Predicting the lifestyle of phages helps decipher their interactions with their bacterial hosts, aiding phages' applications in fields such as phage therapy. Because experimental methods for annotating the lifestyle of phages cannot keep pace with the fast accumulation of sequenced phages, computational method for predicting phages' lifestyles has become an attractive alternative. Despite some promising results, computational lifestyle prediction remains difficult because of the limited known annotations and the sheer amount of sequenced phage contigs assembled from metagenomic data. In particular, most of the existing tools cannot precisely predict phages' lifestyles for short contigs. In this work, we develop PhaTYP (Phage TYPe prediction tool) to improve the accuracy of lifestyle prediction on short contigs. We design two different training tasks, self-supervised and fine-tuning tasks, to overcome lifestyle prediction difficulties. We rigorously tested and compared PhaTYP with four state-of-the-art methods: DeePhage, PHACTS, PhagePred and BACPHLIP. The experimental results show that PhaTYP outperforms all these methods and achieves more stable performance on short contigs. In addition, we demonstrated the utility of PhaTYP for analyzing the phage lifestyle on human neonates' gut data. This application shows that PhaTYP is a useful means for studying phages in metagenomic data and helps extend our understanding of microbial communities.

Effects of repeated weight cycling on non-alcoholic steatohepatitis in diet-induced obese mice.

Lifestyle interventions remain the treatment of choice for patients with obesity and metabolic complications, yet are difficult to maintain and often lead to cycles of weight loss and regain (weight cycling). Literature on weight cycling remains controversial and we therefore investigated the association between weight cycling and metabolic complications using preexistent obese mice. Ldlr-/-.Leiden mice received a high-fat diet (HFD) for 20 weeks to induce obesity. Subsequently, weight-cycled mice were switched between the healthy chow diet and HFD for four 2-week periods and compared to mice that received HFD for the total study period. Repeated weight cycling tended to decrease body weight and significantly reduced fat mass, whereas adipose tissue inflammation was similar relative to HFD controls. Weight cycling did not significantly affect blood glucose or plasma insulin levels yet significantly reduced plasma free fatty acid and alanine transaminase/aspartate transaminase levels. Hepatic macrovesicular steatosis was similar and microvesicular steatosis tended to be increased upon weight cycling. Weight cycling resulted in a robust decrease in hepatic inflammation compared to HFD controls while hepatic fibrosis and atherosclerosis development were not affected. These results argue against the postulate that repeated weight cycling leads to unfavorable metabolic effects, when compared to a continuous unhealthy lifestyle, and in fact revealed beneficial effects on hepatic inflammation, an important hallmark of non-alcoholic steatohepatitis.

Epigenetics of Early Cardiometabolic Disease: Mechanisms and Precision Medicine.

Epigenetics has transformed our understanding of the molecular basis of complex diseases, including cardiovascular and metabolic disorders. This review offers a comprehensive overview of the current state of knowledge on epigenetic processes implicated in cardiovascular and metabolic diseases, highlighting the potential of DNA methylation as a precision medicine biomarker and examining the impact of social determinants of health, gut bacterial epigenomics, noncoding RNA, and epitranscriptomics on disease development and progression. We discuss challenges and barriers to advancing cardiometabolic epigenetics research, along with the opportunities for novel preventive strategies, targeted therapies, and personalized medicine approaches that may arise from a better understanding of epigenetic processes. Emerging technologies, such as single-cell sequencing and epigenetic editing, hold the potential to further enhance our ability to dissect the complex interplay between genetic, environmental, and lifestyle factors. To translate research findings into clinical practice, interdisciplinary collaborations, technical and ethical considerations, and accessibility of resources and knowledge are crucial. Ultimately, the field of epigenetics has the potential to revolutionize the way we approach cardiovascular and metabolic diseases, paving the way for precision medicine and personalized health care, and improving the lives of millions of individuals worldwide affected by these conditions.

Wearable Devices in Cardiovascular Medicine.

Wearable devices, such as smartwatches and activity trackers, are commonly used by patients in their everyday lives to manage their health and well-being. These devices collect and analyze long-term continuous data on measures of behavioral or physiologic function, which may provide clinicians with a more comprehensive view of a patients' health compared with the traditional sporadic measures captured by office visits and hospitalizations. Wearable devices have a wide range of potential clinical applications ranging from arrhythmia screening of high-risk individuals to remote management of chronic conditions such as heart failure or peripheral artery disease. As the use of wearable devices continues to grow, we must adopt a multifaceted approach with collaboration among all key stakeholders to effectively and safely integrate these technologies into routine clinical practice. In this Review, we summarize the features of wearable devices and associated machine learning techniques. We describe key research studies that illustrate the role of wearable devices in the screening and management of cardiovascular conditions and identify directions for future research. Last, we highlight the challenges that are currently hindering the widespread use of wearable devices in cardiovascular medicine and provide short- and long-term solutions to promote increased use of wearable devices in clinical care.

The interaction effects of age, APOE and common environmental risk factors on human brain structure.

Mounting evidence suggests considerable diversity in brain aging trajectories, primarily arising from the complex interplay between age, genetic, and environmental risk factors, leading to distinct patterns of micro- and macro-cerebral aging. The underlying mechanisms of such effects still remain unclear. We conducted a comprehensive association analysis between cerebral structural measures and prevalent risk factors, using data from 36,969 UK Biobank subjects aged 44-81. Participants were assessed for brain volume, white matter diffusivity, Apolipoprotein E (APOE) genotypes, polygenic risk scores, lifestyles, and socioeconomic status. We examined genetic and environmental effects and their interactions with age and sex, and identified 726 signals, with education, alcohol, and smoking affecting most brain regions. Our analysis revealed negative age-APOE-ε4 and positive age-APOE-ε2 interaction effects, respectively, especially in females on the volume of amygdala, positive age-sex-APOE-ε4 interaction on the cerebellar volume, positive age-excessive-alcohol interaction effect on the mean diffusivity of the splenium of the corpus callosum, positive age-healthy-diet interaction effect on the paracentral volume, and negative APOE-ε4-moderate-alcohol interaction effects on the axial diffusivity of the superior fronto-occipital fasciculus. These findings highlight the need of considering age, sex, genetic, and environmental joint effects in elucidating normal or abnormal brain aging.

Metabolites, Healthy Lifestyle, and Polygenic Risk Score Associated with Upper Gastrointestinal Cancer: Findings from the UK Biobank Study.

Previous metabolomics studies have highlighted the predictive value of metabolites on upper gastrointestinal (UGI) cancer, while most of them ignored the potential effects of lifestyle and genetic risk on plasma metabolites. This study aimed to evaluate the role of lifestyle and genetic risk in the metabolic mechanism of UGI cancer. Differential metabolites of UGI cancer were identified using partial least-squares discriminant analysis and the Wilcoxon test. Then, we calculated the healthy lifestyle index (HLI) score and polygenic risk score (PRS) and divided them into three groups, respectively. A total of 15 metabolites were identified as UGI-cancer-related differential metabolites. The metabolite model (AUC = 0.699) exhibited superior discrimination ability compared to those of the HLI model (AUC = 0.615) and the PRS model (AUC = 0.593). Moreover, subgroup analysis revealed that the metabolite model showed higher discrimination ability for individuals with unhealthy lifestyles compared to that with healthy individuals (AUC = 0.783 vs 0.684). Furthermore, in the genetic risk subgroup analysis, individuals with a genetic predisposition to UGI cancer exhibited the best discriminative performance in the metabolite model (AUC = 0.770). These findings demonstrated the clinical significance of metabolic biomarkers in UGI cancer discrimination, especially in individuals with unhealthy lifestyles and a high genetic risk.

Impact of remission from type 2 diabetes on long-term health outcomes: findings from the Look AHEAD study.

AIMS/HYPOTHESIS: We examined the association of attainment of diabetes remission in the context of a 12 year intensive lifestyle intervention with subsequent incidence of chronic kidney disease (CKD) and CVD. METHODS: The Look AHEAD study was a multi-centre RCT comparing the effect of a 12 year intensive lifestyle intervention with that of diabetes support and education on CVD and other long-term health conditions. We compared the incidence of CVD and CKD among 4402 and 4132 participants, respectively, based on achievement and duration of diabetes remission. Participants were 58% female, and had a mean age of 59 years, a duration of diabetes of 6 year and BMI of 35.8 kg/m2. We applied an epidemiological definition of remission: taking no diabetes medications and having HbA1c <48 mmol/mol (6.5%) at a single point in time. We defined high-risk or very high-risk CKD based on the Kidney Disease Improving Global Outcomes (KDIGO) criteria, and CVD incidence as any occurrence of non-fatal acute myocardial infarction, stroke, admission for angina or CVD death. RESULTS: Participants with evidence of any remission during follow-up had a 33% lower rate of CKD (HR 0.67; 95% CI 0.52, 0.87) and a 40% lower rate of the composite CVD measure (HR 0.60; 95% CI 0.47, 0.79) in multivariate analyses adjusting for HbA1c, BP, lipid levels, CVD history, diabetes duration and intervention arm, compared with participants without remission. The magnitude of risk reduction was greatest for participants with evidence of longer-term remission. CONCLUSIONS/INTERPRETATION: Participants with type 2 diabetes with evidence of remission had a substantially lower incidence of CKD and CVD, respectively, compared with participants who did not achieve remission. This association may be affected by post-baseline improvements in weight, fitness, HbA1c and LDL-cholesterol. TRIAL REGISTRATION: ClinicalTrials.gov NCT00017953 DATA AVAILABILITY: https://repository.niddk.nih.gov/studies/look-ahead/.

Epidemiology of heart failure in diabetes: a disease in disguise.

Left ventricular diastolic dysfunction (LVDD) without symptoms, and heart failure (HF) with preserved ejection fraction (HFpEF) represent the most common phenotypes of HF in individuals with type 2 diabetes mellitus, and are more common than HF with reduced ejection fraction (HFrEF), HF with mildly reduced ejection fraction (HFmrEF) and left ventricular systolic dysfunction (LVSD) in these individuals. However, diagnostic criteria for HF have changed over the years, resulting in heterogeneity in the prevalence/incidence rates reported in different studies. We aimed to give an overview of the diagnosis and epidemiology of HF in type 2 diabetes, using both a narrative and systematic review approach; we focus narratively on diagnosing (using the 2021 European Society of Cardiology [ESC] guidelines) and screening for HF in type 2 diabetes. We performed an updated (2016-October 2022) systematic review and meta-analysis of studies reporting the prevalence and incidence of HF subtypes in adults ≥18 years with type 2 diabetes, using echocardiographic data. Embase and MEDLINE databases were searched and data were assessed using random-effects meta-analyses, with findings presented as forest plots. From the 5015 studies found, 209 were screened using the full-text article. In total, 57 studies were included, together with 29 studies that were identified in a prior meta-analysis; these studies reported on the prevalence of LVSD (n=25 studies, 24,460 individuals), LVDD (n=65 studies, 25,729 individuals), HFrEF (n=4 studies, 4090 individuals), HFmrEF (n=2 studies, 2442 individuals) and/or HFpEF (n=8 studies, 5292 individuals), and on HF incidence (n=7 studies, 17,935 individuals). Using Hoy et al's risk-of-bias tool, we found that the studies included generally had a high risk of bias. They showed a prevalence of 43% (95% CI 37%, 50%) for LVDD, 17% (95% CI 7%, 35%) for HFpEF, 6% (95% CI 3%, 10%) for LVSD, 7% (95% CI 3%, 15%) for HFrEF, and 12% (95% CI 7%, 22%) for HFmrEF. For LVDD, grade I was found to be most prevalent. Additionally, we reported a higher incidence rate of HFpEF (7% [95% CI 4%, 11%]) than HFrEF 4% [95% CI 3%, 7%]). The evidence is limited by the heterogeneity of the diagnostic criteria over the years. The systematic section of this review provides new insights on the prevalence/incidence of HF in type 2 diabetes, unveiling a large pre-clinical target group with LVDD/HFpEF in which disease progression could be halted by early recognition and treatment.Registration PROSPERO ID CRD42022368035.

Integration of a fasting-mimicking diet programme in primary care for type 2 diabetes reduces the need for medication and improves glycaemic control: a 12-month randomised controlled trial.

AIMS/HYPOTHESIS: The aim of this study was to evaluate the impact on metabolic control of periodic use of a 5-day fasting-mimicking diet (FMD) programme as an adjunct to usual care in people with type 2 diabetes under regular primary care surveillance. METHODS: In this randomised, controlled, assessor-blinded trial, people with type 2 diabetes using metformin as the only glucose-lowering drug and/or diet for glycaemic control were randomised to receive 5-day cycles of an FMD monthly as an adjunct to regular care by their general practitioner or to receive regular care only. The primary outcomes were changes in glucose-lowering medication (as reflected by the medication effect score) and HbA1c levels after 12 months. Moreover, changes in use of glucose-lowering medication and/or HbA1c levels in individual participants were combined to yield a clinically relevant outcome measure ('glycaemic management'), which was categorised as improved, stable or deteriorated after 1 year of follow-up. Several secondary outcome measures were also examined, including changes in body weight. RESULTS: One hundred individuals with type 2 diabetes, age 18-75 years, BMI ≥27 kg/m2, were randomised to the FMD group (n=51) or the control group (n=49). Eight FMD participants and ten control participants were lost to follow-up. Intention-to-treat analyses, using linear mixed models, revealed adjusted estimated treatment effects for the medication effect score (-0.3; 95% CI -0.4, -0.2; p<0.001), HbA1c (-3.2 mmol/mol; 95% CI -6.2, -0.2 and -0.3%; 95% CI -0.6, -0.0; p=0.04) and body weight (-3.6 kg; 95% CI -5.2, -2.1; p<0.001) at 12 months. Glycaemic management improved in 53% of participants using FMD vs 8% of control participants, remained stable in 23% vs 33%, and deteriorated in 23% vs 59% (p<0.001). CONCLUSIONS/INTERPRETATION: Integration of a monthly FMD programme in regular primary care for people with type 2 diabetes who use metformin as the only glucose-lowering drug and/or diet for glycaemic control reduces the need for glucose-lowering medication, improves HbA1c despite the reduction in medication use, and appears to be safe in routine clinical practice. TRIAL REGISTRATION: ClinicalTrials.gov NCT03811587 FUNDING: The project was co-funded by Health~Holland, Top Sector Life Sciences & Health, the Dutch Diabetes Foundation and L-Nutra.

Morning exercise and pre-breakfast metformin interact to reduce glycaemia in people with type 2 diabetes: a randomized crossover trial.

Exercise is recommended in the treatment of type 2 diabetes and can improve insulin sensitivity. However, previous evidence suggests that exercise at different times of the day in people with type 2 diabetes may have opposing outcomes on glycaemia. Metformin is the most commonly prescribed initial pharmacological intervention in type 2 diabetes, and may alter adaptions to exercise. It is unknown if there is an interaction between metformin and diurnal exercise outcomes. We aimed to investigate glycaemic outcomes of moderate intensity morning vs. evening exercise in people with type 2 diabetes being prescribed metformin monotherapy. In this study, nine males and nine females with type 2 diabetes undergoing metformin monotherapy (age 61 ± 8.2 years, mean ± SD) completed a 16-week crossover trial including 2-week baseline recording, 6 weeks randomly assigned to a morning exercise (07.00-10.00 h) or evening exercise (16.00-19.00 h) and a 2-week wash-out period. Exercise arms consisted of 30 min of walking at 70% of estimated max heart rate every other day. Glucose levels were measured with continuous glucose monitors and activity measured by wrist-worn monitors. Food-intake was recorded by 4-day food diaries during baseline, first and last 2 weeks of each exercise arm. There was no difference in exercise intensity, total caloric intake or total physical activity between morning and evening arms. As primary outcomes, acute (24 h) glucose area under the curve (AUC), was lower (P = 0.02) after acute morning exercise (180.6 ± 68.4 mmol/l) compared to baseline (210.3 ± 76.7 mmol/l); and there were no differences identified for glucose (mmol/l) between baseline, morning and evening exercise at any specific time point when data were analysed with two-way ANOVA. As secondary outcomes, acute glucose AUC was significantly lower (P = 0.01) in participants taking metformin before breakfast (152.5 ± 29.95 mmol/l) compared with participants taking metformin after breakfast (227.2 ± 61.51 mmol/l) only during the morning exercise arm; and during weeks 5-6 of the exercise protocol, glucose AUC was significantly lower (P = 0.04) for participants taking metformin before breakfast (168.8 ± 15.8 mmol/l), rather than after breakfast (224.5 ± 52.0 mmol/l), only during morning exercise. Our data reveal morning moderate exercise acutely lowers glucose levels in people with type 2 diabetes being prescribed metformin. This difference appears to be driven by individuals that consumed metformin prior to breakfast rather than after breakfast. This beneficial effect upon glucose levels of combined morning exercise and pre-breakfast metformin persisted through the final 2 weeks of the trial. Our findings suggest that morning moderate intensity exercise combined with pre-breakfast metformin intake may benefit the management of glycaemia in people with type 2 diabetes. KEY POINTS: Morning moderate exercise acutely lowers glucose levels in people with type 2 diabetes being prescribed metformin. This difference appears to be driven by individuals that consumed metformin prior to breakfast rather than after breakfast. Morning exercise combined with pre-breakfast metformin persistently reduced glucose compared to morning exercise combined with post-breakfast metformin through the final week (week 6) of the intervention. Our study suggests it may be possible to make simple changes to the time that people with type 2 diabetes take metformin and perform exercise to improve their blood glucose.

Increasing Equity of Physical Activity Promotion for Optimal Cardiovascular Health in Adults: A Scientific Statement From the American Heart Association.

Fewer than 1 in 4 adults achieves the recommended amount of physical activity, with lower activity levels reported among some groups. Addressing low levels of physical activity among underresourced groups provides a modifiable target with the potential to improve equity in cardiovascular health. This article (1) examines physical activity levels across strata of cardiovascular disease risk factors, individual level characteristics, and environmental factors; (2) reviews strategies for increasing physical activity in groups who are underresourced or at risk for poor cardiovascular health; and (3) provides practical suggestions for physical activity promotion to increase equity of risk reduction and to improve cardiovascular health. Physical activity levels are lower among those with elevated cardiovascular disease risk factors, among certain groups (eg, older age, female, Black race, lower socioeconomic status), and in some environments (eg, rural). There are strategies for physical activity promotion that can specifically support underresourced groups such as engaging the target community in designing and implementing interventions, developing culturally appropriate study materials, identifying culturally tailored physical activity options and leaders, building social support, and developing materials for those with low literacy. Although addressing low physical activity levels will not address the underlying structural inequities that deserve attention, promoting physical activity among adults, especially those with both low physical activity levels and poor cardiovascular health, is a promising and underused strategy to reduce cardiovascular health inequalities.

Quorum sensing in bacteria: in silico protein analysis, ecophysiology, and reconstruction of their evolutionary history.

BACKGROUND: Quorum sensing (QS) is a sophisticated cell-to-cell signalling mechanism that allows the coordination of important processes in microbial populations. The AI-1 and AI-2 autoinducer systems are among the best characterized bacterial QS systems at the genetic level. RESULTS: In this study, we present data derived from in silico screening of QS proteins from bacterial genomes available in public databases. Sequence analyses allowed identifying candidate sequences of known QS systems that were used to build phylogenetic trees. Eight categories were established according to the number of genes from the two major QS systems present in each genome, revealing a correlation with specific taxa, lifestyles or metabolic traits. Many species had incomplete QS systems, encoding the receptor protein but not the biosynthesis of the quorum sensing molecule (QSMs). Reconstruction of the evolutionary history of the LuxR family and prediction of the 3D structure of the ancestral protein suggested their monomeric configuration in the absence of the signal molecule and the presence of a cavity for its binding. CONCLUSIONS: Here we correlate the taxonomic affiliation and lifestyle of bacteria from different genera with the QS systems encoded in their genomes. Moreover, we present the first ancestral reconstruction of the LuxR QS receptors, providing further insight in their evolutionary history.

Polygenic risk score model for renal cell carcinoma in the Korean population and relationship with lifestyle-associated factors.

BACKGROUND: The polygenic risk score (PRS) is used to predict the risk of developing common complex diseases or cancers using genetic markers. Although PRS is used in clinical practice to predict breast cancer risk, it is more accurate for Europeans than for non-Europeans because of the sample size of training genome-wide association studies (GWAS). To address this disparity, we constructed a PRS model for predicting the risk of renal cell carcinoma (RCC) in the Korean population. RESULTS: Using GWAS analysis, we identified 43 Korean-specific variants and calculated the PRS. Subsequent to plotting receiver operating characteristic (ROC) curves, we selected the 31 best-performing variants to construct an optimal PRS model. The resultant PRS model with 31 variants demonstrated a prediction rate of 77.4%. The pathway analysis indicated that the identified non-coding variants are involved in regulating the expression of genes related to cancer initiation and progression. Notably, favorable lifestyle habits, such as avoiding tobacco and alcohol, mitigated the risk of RCC across PRS strata expressing genetic risk. CONCLUSION: A Korean-specific PRS model was established to predict the risk of RCC in the underrepresented Korean population. Our findings suggest that lifestyle-associated factors influencing RCC risk are associated with acquired risk factors indirectly through epigenetic modification, even among individuals in the higher PRS category.

Differential patterns of reproductive and lifestyle risk factors for breast cancer according to birth cohorts among women in China, Japan and Korea.

BACKGROUND: The birth cohort effect has been suggested to influence the rate of breast cancer incidence and the trends of associated reproductive and lifestyle factors. We conducted a cohort study to determine whether a differential pattern of associations exists between certain factors and breast cancer risk based on birth cohorts. METHODS: This was a cohort study using pooled data from 12 cohort studies. We analysed associations between reproductive (menarche age, menopause age, parity and age at first delivery) and lifestyle (smoking and alcohol consumption) factors and breast cancer risk. We obtained hazard ratios (HRs) with 95% confidence intervals (CIs) using the Cox proportional hazard regression analysis on the 1920s, 1930s, 1940s and 1950s birth cohorts. RESULTS: Parity was found to lower the risk of breast cancer in the older but not in the younger birth cohort, whereas lifestyle factors showed associations with breast cancer risk only among the participants born in the 1950s. In the younger birth cohort group, the effect size was lower for parous women compared to the other cohort groups (HR [95% CI] 0.86 [0.66-1.13] compared to 0.60 [0.49-0.73], 0.46 [0.38-0.56] and 0.62 [0.51-0.77]). Meanwhile, a higher effect size was found for smoking (1.45 [1.14-1.84] compared to 1.25 [0.99-1.58], 1.06 [0.85-1.32] and 0.86 [0.69-1.08]) and alcohol consumption (1.22 [1.01-1.48] compared to 1.10 [0.90-1.33], 1.15 [0.96-1.38], and 1.07 [0.91-1.26]). CONCLUSION: We observed different associations of parity, smoking and alcohol consumption with breast cancer risk across various birth cohorts.