Individual variations in cardiovascular-disease-related protein levels are driven by genetics and gut microbiome

Antibody signatures against viruses and microbiome reflect past and chronic exposures and associate with aging and inflammation

Encounters with pathogens and other molecules can imprint long-lasting effects on our immune system, influencing future physiological outcomes. Given the wide range of microbes to which humans are exposed, their collective impact on health is not fully understood. To explore relations between exposures and biological aging and inflammation, we profiled an antibody-binding repertoire against 2,815 microbial, viral, and environmental peptides in a population cohort of 1,443 participants. Utilizing antibody-binding as a proxy for past exposures, we investigated their impact on biological aging, cell composition, and inflammation. Immune response against cytomegalovirus (CMV), rhinovirus, and gut bacteria relates with telomere length. Single-cell expression measurements identified an effect of CMV infection on the transcriptional landscape of subpopulations of CD8 and CD4 T-cells. This examination of the relationship between microbial exposures and biological aging and inflammation highlights a role for chronic infections (CMV and Epstein-Barr virus) and common pathogens (rhinoviruses and adenovirus C).

Single-Cell Dissection of the Immune Response After Acute Myocardial Infarction

BACKGROUND

The immune system's role in ST-segment-elevated myocardial infarction (STEMI) remains poorly characterized but is an important driver of recurrent cardiovascular events. While anti-inflammatory drugs show promise in reducing recurrence risk, their broad immune system impairment may induce severe side effects. To overcome these challenges, a nuanced understanding of the immune response to STEMI is needed.

METHODS

For this, we compared peripheral blood mononuclear single-cell RNA-sequencing (scRNA-seq) and plasma protein expression over time (hospital admission, 24 hours, and 6-8 weeks post-STEMI) in 38 patients and 38 controls (95 995 diseased and 33 878 control peripheral blood mononuclear cells).

RESULTS

Compared with controls, classical monocytes were increased and CD56dim natural killer cells were decreased in patients with STEMI at admission and persisted until 24 hours post-STEMI. The largest gene expression changes were observed in monocytes, associating with changes in toll-like receptor, interferon, and interleukin signaling activity. Finally, a targeted cardiovascular biomarker panel revealed expression changes in 33/92 plasma proteins post-STEMI. Interestingly, interleukin-6R, MMP9 (matrix metalloproteinase-9), and LDLR (low-density lipoprotein receptor) were affected by coronary artery disease-associated genetic risk variation, disease status, and time post-STEMI, indicating the importance of considering these aspects when defining potential future therapies.

CONCLUSIONS

Our analyses revealed the immunologic pathways disturbed by STEMI, specifying affected cell types and disease stages. Additionally, we provide insights into patients expected to benefit most from anti-inflammatory treatments by identifying the genetic variants and disease stage at which these variants affect the outcome of these (drug-targeted) pathways. These findings advance our knowledge of the immune response post-STEMI and provide guidance for future therapeutic studies.

Probiotics, gut microbiome, and cardiovascular diseases: An update

Cardiovascular diseases (CVD) are one of the most challenging diseases and many factors have been demonstrated to affect their pathogenesis. One of the major factors that affect CVDs, especially atherosclerosis, is the gut microbiota (GM). Genetics play a key role in linking CVDs with GM, in addition to some environmental factors which can be either beneficial or harmful. The interplay between GM and CVDs is complex due to the numerous mechanisms through which microbial components and their metabolites can influence CVDs. Within this interplay, the immune system plays a major role, mainly based on the immunomodulatory effects of microbial dysbiosis and its resulting metabolites. The resulting modulation of chronic inflammatory processes was found to reduce the severity of CVDs and to maintain cardiovascular health. To better understand the specific roles of GM-related metabolites in this interplay, this review presents an updated perspective on gut metabolites related effects on the cardiovascular system, highlighting the possible benefits of probiotics in therapeutic strategies.

Host genetic regulation of human gut microbial structural variation

Although the impact of host genetics on gut microbial diversity and the abundance of specific taxa is well established1-6, little is known about how host genetics regulates the genetic diversity of gut microorganisms. Here we conducted a meta-analysis of associations between human genetic variation and gut microbial structural variation in 9,015 individuals from four Dutch cohorts. Strikingly, the presence rate of a structural variation segment in Faecalibacterium prausnitzii that harbours an N-acetylgalactosamine (GalNAc) utilization gene cluster is higher in individuals who secrete the type A oligosaccharide antigen terminating in GalNAc, a feature that is jointly determined by human ABO and FUT2 genotypes, and we could replicate this association in a Tanzanian cohort. In vitro experiments demonstrated that GalNAc can be used as the sole carbohydrate source for F. prausnitzii strains that carry the GalNAc-metabolizing pathway. Further in silico and in vitro studies demonstrated that other ABO-associated species can also utilize GalNAc, particularly Collinsella aerofaciens. The GalNAc utilization genes are also associated with the host's cardiometabolic health, particularly in individuals with mucosal A-antigen. Together, the findings of our study demonstrate that genetic associations across the human genome and bacterial metagenome can provide functional insights into the reciprocal host-microbiome relationship.

Evaluation of circulating plasma proteins in breast cancer using Mendelian randomisation

Biomarkers for early detection of breast cancer may complement population screening approaches to enable earlier and more precise treatment. The blood proteome is an important source for biomarker discovery but so far, few proteins have been identified with breast cancer risk. Here, we measure 2929 unique proteins in plasma from 598 women selected from the Karolinska Mammography Project to explore the association between protein levels, clinical characteristics, and gene variants, and to identify proteins with a causal role in breast cancer. We present 812 cis-acting protein quantitative trait loci for 737 proteins which are used as instruments in Mendelian randomisation analyses of breast cancer risk. Of those, we present five proteins (CD160, DNPH1, LAYN, LRRC37A2 and TLR1) that show a potential causal role in breast cancer risk with confirmatory results in independent cohorts. Our study suggests that these proteins should be further explored as biomarkers and potential drug targets in breast cancer.

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.

Gut Microbiota and Microbial Metabolism in Early Risk of Cardiometabolic Disease

Cardiometabolic disease comprises cardiovascular and metabolic dysfunction and underlies the leading causes of morbidity and mortality, both within the United States and worldwide. Commensal microbiota are implicated in the development of cardiometabolic disease. Evidence suggests that the microbiome is relatively variable during infancy and early childhood, becoming more fixed in later childhood and adulthood. Effects of microbiota, both during early development, and in later life, may induce changes in host metabolism that modulate risk mechanisms and predispose toward the development of cardiometabolic disease. In this review, we summarize the factors that influence gut microbiome composition and function during early life and explore how changes in microbiota and microbial metabolism influence host metabolism and cardiometabolic risk throughout life. We highlight limitations in current methodology and approaches and outline state-of-the-art advances, which are improving research and building toward refined diagnosis and treatment options in microbiome-targeted therapies.

Genetic mapping of microbial and host traits reveals production of immunomodulatory lipids by Akkermansia muciniphila in the murine gut

The molecular bases of how host genetic variation impacts the gut microbiome remain largely unknown. Here we used a genetically diverse mouse population and applied systems genetics strategies to identify interactions between host and microbe phenotypes including microbial functions, using faecal metagenomics, small intestinal transcripts and caecal lipids that influence microbe-host dynamics. Quantitative trait locus (QTL) mapping identified murine genomic regions associated with variations in bacterial taxa; bacterial functions including motility, sporulation and lipopolysaccharide production and levels of bacterial- and host-derived lipids. We found overlapping QTL for the abundance of Akkermansia muciniphila and caecal levels of ornithine lipids. Follow-up in vitro and in vivo studies revealed that A. muciniphila is a major source of these lipids in the gut, provided evidence that ornithine lipids have immunomodulatory effects and identified intestinal transcripts co-regulated with these traits including Atf3, which encodes for a transcription factor that plays vital roles in modulating metabolism and immunity. Collectively, these results suggest that ornithine lipids are potentially important for A. muciniphila-host interactions and support the role of host genetics as a determinant of responses to gut microbes.

Microbial vitamin production mediates dietary effects on diabetic risk

Adequate levels of essential vitamins are important for the prevention of diabetes. While the main efforts to address this are currently focused on the intake of vitamin supplements, improving and maintaining intrinsic vitamin production capacity, which is determined by gut microbes, has received insufficient attention. In this study, we systematically investigated the relationship between gut microbial vitamin production and factors related to diabetes and cardiometabolic health in a deeply phenotyped cohort, Lifelines-DEEP (N = 1,135). We found that blood glucose-related factors, lipids, circulating inflammation, and fecal short-chain fatty acids are associated with gut microbial vitamin production. Use of laxatives and metformin are associated with increased levels of vitamin B1/B6 biosynthesis pathways. We further reveal a mediatory role for microbial vitamin B1/B2 production on the influence of fruit intake on diabetes risk. This study provides preliminary evidence for microbiome-targeted vitamin metabolism interventions to promote health.

Biobanking as a Tool for Genomic Research: From Allele Frequencies to Cross-Ancestry Association Studies

In recent years, great advances have been made in the field of collection, storage, and analysis of biological samples. Large collections of samples, biobanks, have been established in many countries. Biobanks typically collect large amounts of biological samples and associated clinical information; the largest collections include over a million samples. In this review, we summarize the main directions in which biobanks aid medical genetics and genomic research, from providing reference allele frequency information to allowing large-scale cross-ancestry meta-analyses. The largest biobanks greatly vary in the size of the collection, and the amount of available phenotype and genotype data. Nevertheless, all of them are extensively used in genomics, providing a rich resource for genome-wide association analysis, genetic epidemiology, and statistical research into the structure, function, and evolution of the human genome. Recently, multiple research efforts were based on trans-biobank data integration, which increases sample size and allows for the identification of robust genetic associations. We provide prominent examples of such data integration and discuss important caveats which have to be taken into account in trans-biobank research.

Metabolomics profiles of premenopausal women are different based on O-desmethylangolensin metabotype

Urinary O-desmethylangolensin (ODMA) concentrations provide a functional gut microbiome marker of dietary isoflavone daidzein metabolism to ODMA. Individuals who do not have gut microbial environments that produce ODMA have less favourable cardiometabolic and cancer risk profiles. Urinary metabolomics profiles were evaluated in relation to ODMA metabotypes within and between individuals over time. Secondary analysis of data was conducted from the BEAN2 trial, which was a cross-over study of premenopausal women consuming 6 months on a high and a low soya diet, each separated by a 1-month washout period. In all of the 672 samples in the study, sixty-six of the eighty-four women had the same ODMA metabotype at seven or all eight time points. Two or four urine samples per woman were selected based on temporal metabotypes in order to compare within and across individuals. Metabolomics assays for primary metabolism and biogenic amines were conducted in sixty urine samples from twenty women. Partial least-squares discriminant analysis was used to compare metabolomics profiles. For the same ODMA metabotype across different time points, no profile differences were detected. For changes in metabotype within individuals and across individuals with different metabotypes, distinct metabolomes emerged. Influential metabolites (variables importance in projection score > 2) included several phenolic compounds, carnitine and derivatives, fatty acid and amino acid metabolites and some medications. Based on the distinct metabolomes of producers v. non-producers, the ODMA metabotype may be a marker of gut microbiome functionality broadly involved in nutrient and bioactive metabolism and should be evaluated for relevance to precision nutrition initiatives.

Emerging computational paradigms to address the complex role of gut microbial metabolism in cardiovascular diseases

The human gut microbiota and its associated perturbations are implicated in a variety of cardiovascular diseases (CVDs). There is evidence that the structure and metabolic composition of the gut microbiome and some of its metabolites have mechanistic associations with several CVDs. Nevertheless, there is a need to unravel metabolic behavior and underlying mechanisms of microbiome-host interactions. This need is even more highlighted when considering that microbiome-secreted metabolites contributing to CVDs are the subject of intensive research to develop new prevention and therapeutic techniques. In addition to the application of high-throughput data used in microbiome-related studies, advanced computational tools enable us to integrate omics into different mathematical models, including constraint-based models, dynamic models, agent-based models, and machine learning tools, to build a holistic picture of metabolic pathological mechanisms. In this article, we aim to review and introduce state-of-the-art mathematical models and computational approaches addressing the link between the microbiome and CVDs.

Genetic, parental and lifestyle factors influence telomere length

The average length of telomere repeats (TL) declines with age and is considered to be a marker of biological ageing. Here, we measured TL in six blood cell types from 1046 individuals using the clinically validated Flow-FISH method. We identified remarkable cell-type-specific variations in TL. Host genetics, environmental, parental and intrinsic factors such as sex, parental age, and smoking are associated to variations in TL. By analysing the genome-wide methylation patterns, we identified that the association of maternal, but not paternal, age to TL is mediated by epigenetics. Single-cell RNA-sequencing data for 62 participants revealed differential gene expression in T-cells. Genes negatively associated with TL were enriched for pathways related to translation and nonsense-mediated decay. Altogether, this study addresses cell-type-specific differences in telomere biology and its relation to cell-type-specific gene expression and highlights how perinatal factors play a role in determining TL, on top of genetics and lifestyle.

Gut microbiota induces high platelet response in patients with ST segment elevation myocardial infarction after ticagrelor treatment

Background:

Ticagrelor is a first-line drug for the treatment of acute ST elevation myocardial infarction (STEMI). However, approximately 20% STEMI patients taking ticagrelor exhibited a delayed response and the mechanism was still unclear.

Methods:

To explore the mechanism of the poor response of ticagrelor in post-percutaneous coronary intervention (PCI) patients, we enrolled 65 high platelet reactivity (HPR) patients and 90 controls (normal platelet reactivity [NPR]). Pharmacokinetic assessment result showed that the plasma concentrations of ticagrelor and its metabolism production, AR-C124910XX, were lower in HPR patients than controls. Further single nucloetide polymorphism (SNP) analysis identified that there is no difference in ATP binding cassette subfamily B member 1 (ABCB1) gene expression between the NPR group and the HPR group. Metagenomic and metabolomic analyses of fecal samples showed that HPR patients had higher microbial richness and diversity. Transplantation of the gut microbiota from HPR donors to microbiota-depleted mice obviously decreased plasma concentration of ticagrelor.

Results:

Our findings highlight that gut microbiota dysbiosis may be an important mechanism for the ticagrelor of HPR in patients with STEMI and support that modify gut microbiota is a potential therapeutic option for STEMI.

Conclusions:

Our findings highlight that gut microbiota dysbiosis may be an important mechanism for the ticagrelor of HPR in patients with ST elevation myocardial infarction (STEMI) and support that modify gut microbiota is a potential therapeutic option for STEMI

Funding:

NSFC 82170297 and 82070300 from the National Natural Science Foundation of China.

Dysbiosis of Cervical and Vaginal Microbiota Associated With Cervical Intraepithelial Neoplasia

Cervical intraepithelial neoplasia (CIN) is a precancerous condition inducing local lesions on the surface of the squamocolumnar junction of the cervix. Despite the role of vaginal microbiota having been under-discussed, the role of the cervical microbiome and the microbial migration across the reproductive tract involved in CIN was limitedly studied. We aimed to synchronously characterize the dysbiosis associated with CIN in both the cervix and vagina in a Chinese population. Profiling of cervical and vaginal microbiota from 60 CIN women and 60 healthy women was conducted. 16S rRNA sequencing was adopted. By comparing the microbial profiles between different parts of the reproductive tract, our results demonstrated an increased shift of microbial diversity in the cervix compared with that in the vagina for the CIN patients, specifically in CIN 1. Less dysbiosis was found between the CIN patients and controls, in either the vagina or cervix. The microbial community may be modulated by the onset of sexual activity, a known clinical risk factor for cervical neoplasia. Distinct patterns of perturbated bacteria were found in the vaginal and cervical microbiota, in which reduced Actinobacteria-related operational taxonomic units (OTUs) and increased Proteobacteria-related OTUs were found in the vagina and cervix, respectively. A good agreement between the direction of the top-significant perturbated OTUs was observed between the vaginal and cervical microbiome, suggesting a potential microbial migration in the reproductive tract. Enriched genera such as Sphingomonas and Stenotrophomonas were found in cervical microbiota-associated CIN. Multivariate analysis revealed Comamonas, Rhizobium, and Pseudomonas as independent genera contributing to CIN in the cervix. In summary, this study revealed the perturbation of microbiota in the presence of CIN and demonstrated a distinct pattern of characteristic bacteria community between the vagina and cervix involved in the development of CIN.

Advances in integrative African genomics

There has been a rapid increase in human genome sequencing in the past two decades, resulting in the identification of millions of previously unknown genetic variants. However, African populations are under-represented in sequencing efforts. Additional sequencing from diverse African populations and the construction of African-specific reference genomes is needed to better characterize the full spectrum of variation in humans. However, sequencing alone is insufficient to address the molecular and cellular mechanisms underlying variable phenotypes and disease risks. Determining functional consequences of genetic variation using multi-omics approaches is a fundamental post-genomic challenge. We discuss approaches to close the knowledge gaps about African genomic diversity and review advances in African integrative genomic studies and their implications for precision medicine.

Role of Biological Sex in the Cardiovascular-Gut Microbiome Axis

There has been a recent, unprecedented interest in the role of gut microbiota in host health and disease. Technological advances have dramatically expanded our knowledge of the gut microbiome. Increasing evidence has indicated a strong link between gut microbiota and the development of cardiovascular diseases (CVD). In the present article, we discuss the contribution of gut microbiota in the development and progression of CVD. We further discuss how the gut microbiome may differ between the sexes and how it may be influenced by sex hormones. We put forward that regulation of microbial composition and function by sex might lead to sex-biased disease susceptibility, thereby offering a mechanistic insight into sex differences in CVD. A better understanding of this could identify novel targets, ultimately contributing to the development of innovative preventive, diagnostic and therapeutic strategies for men and women.

Posttranscriptional Regulation of the Human LDL Receptor by the U2-Spliceosome

BACKGROUND

The LDLR (low-density lipoprotein receptor) in the liver is the major determinant of LDL-cholesterol levels in human plasma. The discovery of genes that regulate the activity of LDLR helps to identify pathomechanisms of hypercholesterolemia and novel therapeutic targets against atherosclerotic cardiovascular disease.

METHODS

We performed a genome-wide RNA interference screen for genes limiting the uptake of fluorescent LDL into Huh-7 hepatocarcinoma cells. Top hit genes were validated by in vitro experiments as well as analyses of data sets on gene expression and variants in human populations.

RESULTS

The knockdown of 54 genes significantly inhibited LDL uptake. Fifteen of them encode for components or interactors of the U2-spliceosome. Knocking down any one of 11 out of 15 genes resulted in the selective retention of intron 3 of LDLR. The translated LDLR fragment lacks 88% of the full length LDLR and is detectable neither in nontransfected cells nor in human plasma. The hepatic expression of the intron 3 retention transcript is increased in nonalcoholic fatty liver disease as well as after bariatric surgery. Its expression in blood cells correlates with LDL-cholesterol and age. Single nucleotide polymorphisms and 3 rare variants of one spliceosome gene, RBM25, are associated with LDL-cholesterol in the population and familial hypercholesterolemia, respectively. Compared with overexpression of wild-type RBM25, overexpression of the 3 rare RBM25 mutants in Huh-7 cells led to lower LDL uptake.

CONCLUSIONS

We identified a novel mechanism of posttranscriptional regulation of LDLR activity in humans and associations of genetic variants of RBM25 with LDL-cholesterol levels.

An Integrative Genomic Strategy Identifies sRAGE as a Causal and Protective Biomarker of Lung Function

BACKGROUND

There are few clinically useful circulating biomarkers of lung function and lung disease. We hypothesized that genome-wide association studies (GWAS) of circulating proteins in conjunction with GWAS of pulmonary traits represents a clinically relevant approach to identifying causal proteins and therapeutically useful insights into mechanisms related to lung function and disease.

STUDY QUESTION

Can an integrative genomic strategy using GWAS of plasma soluble receptor for advanced glycation end-products (sRAGE) levels in conjunction with GWAS of lung function traits identify putatively causal relations of sRAGE to lung function?

STUDY DESIGN AND METHODS

Plasma sRAGE levels were measured in 6,861 Framingham Heart Study participants and GWAS of sRAGE was conducted to identify protein quantitative trait loci (pQTL), including cis-pQTL variants at the sRAGE protein-coding gene locus (AGER). We integrated sRAGE pQTL variants with variants from GWAS of lung traits. Colocalization of sRAGE pQTL variants with lung trait GWAS variants was conducted, and Mendelian randomization was performed using sRAGE cis-pQTL variants to infer causality of sRAGE for pulmonary traits. Cross-sectional and longitudinal protein-trait association analyses were conducted for sRAGE in relation to lung traits.

RESULTS

Colocalization identified shared genetic signals for sRAGE with lung traits. Mendelian randomization analyses suggested protective causal relations of sRAGE to several pulmonary traits. Protein-trait association analyses demonstrated higher sRAGE levels to be cross-sectionally and longitudinally associated with preserved lung function.

INTERPRETATION

sRAGE is produced by type I alveolar cells, and it acts as a decoy receptor to block the inflammatory cascade. Our integrative genomics approach provides evidence for sRAGE as a causal and protective biomarker of lung function, and the pattern of associations is suggestive of a protective role of sRAGE against restrictive lung physiology. We speculate that targeting the AGER/sRAGE axis may be therapeutically beneficial for the treatment and prevention of inflammation-related lung disease.

Influence of the microbiome, diet and genetics on inter-individual variation in the human plasma metabolome

The levels of the thousands of metabolites in the human plasma metabolome are strongly influenced by an individual's genetics and the composition of their diet and gut microbiome. Here, by assessing 1,183 plasma metabolites in 1,368 extensively phenotyped individuals from the Lifelines DEEP and Genome of the Netherlands cohorts, we quantified the proportion of inter-individual variation in the plasma metabolome explained by different factors, characterizing 610, 85 and 38 metabolites as dominantly associated with diet, the gut microbiome and genetics, respectively. Moreover, a diet quality score derived from metabolite levels was significantly associated with diet quality, as assessed by a detailed food frequency questionnaire. Through Mendelian randomization and mediation analyses, we revealed putative causal relationships between diet, the gut microbiome and metabolites. For example, Mendelian randomization analyses support a potential causal effect of Eubacterium rectale in decreasing plasma levels of hydrogen sulfite-a toxin that affects cardiovascular function. Lastly, based on analysis of the plasma metabolome of 311 individuals at two time points separated by 4 years, we observed a positive correlation between the stability of metabolite levels and the amount of variance in the levels of that metabolite that could be explained in our analysis. Altogether, characterization of factors that explain inter-individual variation in the plasma metabolome can help design approaches for modulating diet or the gut microbiome to shape a healthy metabolome.

The promise of graphene-based transistors for democratizing multiomics studies

As biological research has synthesized genomics, proteomics, metabolomics, and transcriptomics into systems biology, a new multiomics approach to biological research has emerged. Today, multiomics studies are challenging and expensive. An experimental platform that could unify the multiple omics approaches to measurement could increase access to multiomics data by enabling more individual labs to successfully attempt multiomics studies. Field effect biosensing based on graphene transistors have gained significant attention as a potential unifying technology for such multiomics studies. This review article highlights the outstanding performance characteristics that makes graphene field effect transistor an attractive sensing platform for a wide variety of analytes important to system biology. In addition to many studies demonstrating the biosensing capabilities of graphene field effect transistors, they are uniquely suited to address the challenges of multiomics studies by providing an integrative multiplex platform for large scale manufacturing using the well-established processes of semiconductor industry. Furthermore, the resulting digital data is readily analyzable by machine learning to derive actionable biological insight to address the challenge of data compatibility for multiomics studies. A critical stage of systems biology will be democratizing multiomics study, and the graphene field effect transistor is uniquely positioned to serve as an accessible multiomics platform.

Interplay Between Gut Microbiota and Amino Acid Metabolism in Heart Failure

Heart failure (HF) is a complex clinical syndrome of which the incidence is on the rise worldwide. Cardiometabolic disorders are associated with the deterioration of cardiac function and progression of HF. Recently, there has been renewed interest in gut microbiota (GM) and its metabolites in the cardiovascular disease. HF-caused hypoperfusion could increase intestinal permeability, and a “leaky” bowel leads to bacterial translocation and make its metabolites more easily enter the circulation. Considerable evidence shows that the composition of microbiota and amino acids (AAs) has been altered in HF patients, and AAs could serve as a diagnostic and prognostic biomarker in HF. The findings indicate that the gut–amino acid–HF axis may play a key role in the progression of HF. In this paper, we focus on the interrelationship between the AA metabolism and GM alterations during the development of heart failure. We also discuss the potential prognostic and therapeutic value of the gut–amino acid–HF axis in the cortex of HF.

Disentangling the Progression of Non-alcoholic Fatty Liver Disease in the Human Gut Microbiota

Gut microbiome dysbiosis has been known to be associated with all stages of non-alcoholic fatty liver disease (NAFLD), but questions remain about microbial profiles in progression and homogeneity across NAFLD stages. We performed a meta-analysis of three publicly shotgun datasets and built predictive models to determine diagnostic capacity. Here, we found consistently microbiome shifts across NAFLD stages, of which co-occurrence patterns and core sets of new biomarkers significantly correlated with NAFLD progression were identified. Machine learning models that are able to distinguish patients with any NAFLD stage from healthy controls remained predictive when applied to patients with other NAFLD stages, suggesting the homogeneity across stages once again. Focusing on species and metabolic pathways specifically associated with progressive stages, we found that increased toxic metabolites and decreased protection of butyrate and choline contributed to advanced NAFLD. We further built models discriminating one stage from the others with an average of 0.86 of area under the curve. In conclusion, this meta-analysis firmly establishes generalizable microbiome dysbiosis and predictive taxonomic and functional signatures as a basis for future diagnostics across NAFLD stages.

Towards Building a Quantitative Proteomics Toolbox in Precision Medicine: A Mini-Review

Precision medicine as a framework for disease diagnosis, treatment, and prevention at the molecular level has entered clinical practice. From the start, genetics has been an indispensable tool to understand and stratify the biology of chronic and complex diseases in precision medicine. However, with the advances in biomedical and omics technologies, quantitative proteomics is emerging as a powerful technology complementing genetics. Quantitative proteomics provide insight about the dynamic behaviour of proteins as they represent intermediate phenotypes. They provide direct biological insights into physiological patterns, while genetics accounting for baseline characteristics. Additionally, it opens a wide range of applications in clinical diagnostics, treatment stratification, and drug discovery. In this mini-review, we discuss the current status of quantitative proteomics in precision medicine including the available technologies and common methods to analyze quantitative proteomics data. Furthermore, we highlight the current challenges to put quantitative proteomics into clinical settings and provide a perspective to integrate proteomics data with genomics data for future applications in precision medicine.

The Effect of Phenotype and Genotype on the Plasma Proteome in Patients with Inflammatory Bowel Disease

BACKGROUND AND AIMS

Protein profiling in patients with inflammatory bowel diseases [IBD] for diagnostic and therapeutic purposes is underexplored. This study analysed the association between phenotype, genotype, and the plasma proteome in IBD.

METHODS

A total of 92 inflammation-related proteins were quantified in plasma of 1028 patients with IBD (567 Crohn's disease [CD]; 461 ulcerative colitis [UC]) and 148 healthy individuals to assess protein-phenotype associations. Corresponding whole-exome sequencing and global screening array data of 919 patients with IBD were included to analyse the effect of genetics on protein levels (protein quantitative trait loci [pQTL] analysis). Intestinal mucosal RNA sequencing and faecal metagenomic data were used for complementary analyses.

RESULTS

Thirty-two proteins were differentially abundant between IBD and healthy individuals, of which 22 proteins were independent of active inflammation; 69 proteins were associated with 15 demographic and clinical factors. Fibroblast growth factor-19 levels were decreased in CD patients with ileal disease or a history of ileocecal resection. Thirteen novel cis-pQTLs were identified and 10 replicated from previous studies. One trans-pQTL of the fucosyltransferase 2 [FUT2] gene [rs602662] and two independent cis-pQTLs of C-C motif chemokine 25 [CCL25] affected plasma CCL25 levels. Intestinal gene expression data revealed an overlapping cis-expression [e]QTL-variant [rs3745387] of the CCL25 gene. The FUT2 rs602662 trans-pQTL was associated with reduced abundances of faecal butyrate-producing bacteria.

CONCLUSIONS

This study shows that genotype and multiple disease phenotypes strongly associate with the plasma inflammatory proteome in IBD, and identifies disease-associated pathways that may help to improve disease management in the future.

Consideration of Gut Microbiome in Murine Models of Diseases

The gut microbiome (GM), a complex community of bacteria, viruses, protozoa, and fungi located in the gut of humans and animals, plays significant roles in host health and disease. Animal models are widely used to investigate human diseases in biomedical research and the GM within animal models can change due to the impact of many factors, such as the vendor, husbandry, and environment. Notably, variations in GM can contribute to differences in disease model phenotypes, which can result in poor reproducibility in biomedical research. Variation in the gut microbiome can also impact the translatability of animal models. For example, standard lab mice have different pathogen exposure experiences when compared to wild or pet store mice. As humans have antigen experiences that are more similar to the latter, the use of lab mice with more simplified microbiomes may not yield optimally translatable data. Additionally, the literature describes many methods to manipulate the GM and differences between these methods can also result in differing interpretations of outcomes measures. In this review, we focus on the GM as a potential contributor to the poor reproducibility and translatability of mouse models of disease. First, we summarize the important role of GM in host disease and health through different gut–organ axes and the close association between GM and disease susceptibility through colonization resistance, immune response, and metabolic pathways. Then, we focus on the variation in the microbiome in mouse models of disease and address how this variation can potentially impact disease phenotypes and subsequently influence research reproducibility and translatability. We also discuss the variations between genetic substrains as potential factors that cause poor reproducibility via their effects on the microbiome. In addition, we discuss the utility of complex microbiomes in prospective studies and how manipulation of the GM through differing transfer methods can impact model phenotypes. Lastly, we emphasize the need to explore appropriate methods of GM characterization and manipulation.

Use of omic technologies in early life gastrointestinal health and disease: from bench to bedside

Introduction: At birth, the gastrointestinal (GI) tract is colonized by a complex community of microorganisms, forming the basis of the gut microbiome. The gut microbiome plays a fundamental role in host health, disorders of which can lead to an array of GI diseases, both short and long term. Pediatric GI diseases are responsible for significant morbidity and mortality, but many remain poorly understood. Recent advancements in high-throughput technologies have enabled deeper profiling of GI morbidities. Technologies, such as metagenomics, transcriptomics, proteomics and metabolomics, have already been used to identify associations with specific pathologies, and highlight an exciting area of research. However, since these diseases are often complex and multifactorial by nature, reliance on a single experimental approach may not capture the true biological complexity. Therefore, multi-omics aims to integrate singular omic data to further enhance our understanding of disease.Areas covered: This review will discuss and provide an overview of the main omic technologies that are used to study complex GI pathologies in early life.Expert opinion: Multi-omic technologies can help to unravel the complexities of several diseases during early life, aiding in biomarker discovery and enabling the development of novel therapeutics and augment predictive models.

Co-exposure to inorganic arsenic and fluoride prominently disrupts gut microbiota equilibrium and induces adverse cardiovascular effects in offspring rats

Co-exposure to inorganic arsenic (iAs) and fluoride (F^-) and their collective actions on cardiovascular systems have been recognized as a global public health concern. Emerging studies suggest an association between the perturbation of gut bacterial microbiota and adverse cardiovascular effects (CVEs), both of which are the consequence of iAs and F^- exposure in human and experimental animals. The aim of this study was to fill the gap of understanding the relationship among co-exposure to iAs and F^-, gut microbiota perturbation, and adverse CVEs. We systematically assessed cardiac morphology and functions (blood pressure, echocardiogram, and electrocardiogram), and generated gut microbiota profiles using 16S rRNA gene sequencing on rats exposed to iAs (50 mg/L NaAsO₂), F^- (100 mg/L NaF) or combined iAs and F^- (50 mg/L NaAsO₂ + 100 mg/L NaF), in utero and during early postnatal periods (postnatal day 90). Correlation analysis was then performed to examine relationship between significantly altered microbiota and cardiac performance indices. Our results showed that co-exposure to iAs and F^- resulted in more prominent effects in CVEs and perturbation of gut microbiota profiles, compared to iAs or F^- treatment alone. Furthermore, nine bacterial genera (Adlercreutzia, Clostridium sensu stricto 1, Coprococcus 3, Romboutsia, [Bacteroides] Pectinophilus group, Lachnospiraceae NC2004 group, Desulfovibrio, and two unidentified genera in Muribaculaceae and Ruminococcaceae family), which differed significantly in relative abundance between control and iAs and F^- co-exposure group, were strongly correlated with the higher risk of CVEs (correlation coefficient = 0.70-0.88, p < 0.05). Collectively, these results suggest that co-exposure to iAs and F^- poses a higher risk of CVEs, and the part of the mode of action is potentially through inducing gut microbiota disruption, and the strong correlations between them indicate a high potential for the development of novel microbiome-based biomarkers of iAs and/or F^- associated CVEs.

Molecular Mechanisms of Obesity-Linked Cardiac Dysfunction: An Up-Date on Current Knowledge

Obesity is defined as excessive body fat accumulation, and worldwide obesity has nearly tripled since 1975. Excess of free fatty acids (FFAs) and triglycerides in obese individuals promote ectopic lipid accumulation in the liver, skeletal muscle tissue, and heart, among others, inducing insulin resistance, hypertension, metabolic syndrome, type 2 diabetes (T2D), atherosclerosis, and cardiovascular disease (CVD). These diseases are promoted by visceral white adipocyte tissue (WAT) dysfunction through an increase in pro-inflammatory adipokines, oxidative stress, activation of the renin-angiotensin-aldosterone system (RAAS), and adverse changes in the gut microbiome. In the heart, obesity and T2D induce changes in substrate utilization, tissue metabolism, oxidative stress, and inflammation, leading to myocardial fibrosis and ultimately cardiac dysfunction. Peroxisome proliferator-activated receptors (PPARs) are involved in the regulation of carbohydrate and lipid metabolism, also improve insulin sensitivity, triglyceride levels, inflammation, and oxidative stress. The purpose of this review is to provide an update on the molecular mechanisms involved in obesity-linked CVD pathophysiology, considering pro-inflammatory cytokines, adipokines, and hormones, as well as the role of oxidative stress, inflammation, and PPARs. In addition, cell lines and animal models, biomarkers, gut microbiota dysbiosis, epigenetic modifications, and current therapeutic treatments in CVD associated with obesity are outlined in this paper.

An overview of cancer health disparities: new approaches and insights and why they matter

Cancer health disparities remain stubbornly entrenched in the US health care system. The Affordable Care Act was legislation to target these disparities in health outcomes. Expanded access to health care, reduction in tobacco use, uptake of other preventive measures and cancer screening, and improved cancer therapies greatly reduced cancer mortality among women and men and underserved communities in this country. Yet, disparities in cancer outcomes remain. Underserved populations continue to experience an excessive cancer burden. This burden is largely explained by health care disparities, lifestyle factors, cultural barriers, and disparate exposures to carcinogens and pathogens, as exemplified by the COVID-19 epidemic. However, research also shows that comorbidities, social stress, ancestral and immunobiological factors, and the microbiome, may contribute to health disparities in cancer risk and survival. Recent studies revealed that comorbid conditions can induce an adverse tumor biology, leading to a more aggressive disease and decreased patient survival. In this review, we will discuss unanswered questions and new opportunities in cancer health disparity research related to comorbid chronic diseases, stress signaling, the immune response, and the microbiome, and what contribution these factors may have as causes of cancer health disparities.

Large-scale association analyses identify host factors influencing human gut microbiome composition

To study the effect of host genetics on gut microbiome composition, the MiBioGen consortium curated and analyzed genome-wide genotypes and 16S fecal microbiome data from 18,340 individuals (24 cohorts). Microbial composition showed high variability across cohorts: only 9 of 410 genera were detected in more than 95% of samples. A genome-wide association study of host genetic variation regarding microbial taxa identified 31 loci affecting the microbiome at a genome-wide significant (P < 5 × 10-8) threshold. One locus, the lactase (LCT) gene locus, reached study-wide significance (genome-wide association study signal: P = 1.28 × 10-20), and it showed an age-dependent association with Bifidobacterium abundance. Other associations were suggestive (1.95 × 10-10 < P < 5 × 10-8) but enriched for taxa showing high heritability and for genes expressed in the intestine and brain. A phenome-wide association study and Mendelian randomization identified enrichment of microbiome trait loci in the metabolic, nutrition and environment domains and suggested the microbiome might have causal effects in ulcerative colitis and rheumatoid arthritis.

jMorp updates in 2020: large enhancement of multi-omics data resources on the general Japanese population

In the Tohoku Medical Megabank project, genome and omics analyses of participants in two cohort studies were performed. A part of the data is available at the Japanese Multi Omics Reference Panel (jMorp; https://jmorp.megabank.tohoku.ac.jp) as a web-based database, as reported in our previous manuscript published in Nucleic Acid Research in 2018. At that time, jMorp mainly consisted of metabolome data; however, now genome, methylome, and transcriptome data have been integrated in addition to the enhancement of the number of samples for the metabolome data. For genomic data, jMorp provides a Japanese reference sequence obtained using de novo assembly of sequences from three Japanese individuals and allele frequencies obtained using whole-genome sequencing of 8,380 Japanese individuals. In addition, the omics data include methylome and transcriptome data from ∼300 samples and distribution of concentrations of more than 755 metabolites obtained using high-throughput nuclear magnetic resonance and high-sensitivity mass spectrometry. In summary, jMorp now provides four different kinds of omics data (genome, methylome, transcriptome, and metabolome), with a user-friendly web interface. This will be a useful scientific data resource on the general population for the discovery of disease biomarkers and personalized disease prevention and early diagnosis.

Proteome-wide Systems Genetics to Identify Functional Regulators of Complex Traits

Proteomic technologies now enable the rapid quantification of thousands of proteins across genetically diverse samples. Integration of these data with systems-genetics analyses is a powerful approach to identify new regulators of economically important or disease-relevant phenotypes in various populations. In this review, we summarize the latest proteomic technologies and discuss technical challenges for their use in population studies. We demonstrate how the analysis of correlation structure and loci mapping can be used to identify genetic factors regulating functional protein networks and complex traits. Finally, we provide an extensive summary of the use of proteome-wide systems genetics throughout fungi, plant, and animal kingdoms and discuss the power of this approach to identify candidate regulators and drug targets in large human consortium studies.

Genomic and drug target evaluation of 90 cardiovascular proteins in 30,931 individuals

Circulating proteins are vital in human health and disease and are frequently used as biomarkers for clinical decision-making or as targets for pharmacological intervention. Here, we map and replicate protein quantitative trait loci (pQTL) for 90 cardiovascular proteins in over 30,000 individuals, resulting in 451 pQTLs for 85 proteins. For each protein, we further perform pathway mapping to obtain trans-pQTL gene and regulatory designations. We substantiate these regulatory findings with orthogonal evidence for trans-pQTLs using mouse knockdown experiments (ABCA1 and TRIB1) and clinical trial results (chemokine receptors CCR2 and CCR5), with consistent regulation. Finally, we evaluate known drug targets, and suggest new target candidates or repositioning opportunities using Mendelian randomization. This identifies 11 proteins with causal evidence of involvement in human disease that have not previously been targeted, including EGF, IL-16, PAPPA, SPON1, F3, ADM, CASP-8, CHI3L1, CXCL16, GDF15 and MMP-12. Taken together, these findings demonstrate the utility of large-scale mapping of the genetics of the proteome and provide a resource for future precision studies of circulating proteins in human health.

Urbanization in China is associated with pronounced perturbation of plasma metabolites

INTRODUCTION

Urbanization is associated with major changes in environmental and lifestyle exposures that may influence metabolic signatures.

OBJECTIVES

We investigated cross-sectional urban and rural differences in plasma metabolome analyzed by liquid chromatography/mass spectrometry platform in 500 Chinese adults aged 25-68 years from two neighboring southern Chinese provinces.

METHODS

We first examined the overall metabolome differences by urban and rural residential location, using Orthogonal Partial Least Squares Discriminant Analysis (OPLS-DA) and random forest classification. We then tested the association between urbanization status and individual metabolites using a linear regression adjusting for age, sex, and province and conducted pathway analysis (Fisher's exact test) to identify metabolic pathways differed by urbanization status.

RESULTS

We observed distinct overall metabolome by urbanization status in OPLS-DA and random forest classification. Using linear regression, out of a total of 1108 unique metabolite features identified in this sample, we found that 266 metabolites were differed by urbanization status (positive false discovery rate-adjusted p-value, q-value < 0.05). For example, the following metabolites were positively associated with urbanization status: caffeine metabolites from xanthine metabolism, hazardous pollutants like 4-hydroxychlorothalonil and perfluorooctanesulfonate, and metabolites implicated in cardiometabolic diseases, such as branched-chain amino acids. In pathway analysis, we found that xanthine metabolism pathways differed by urbanization status (q-value = 1.64E-04).

CONCLUSION

We detected profound differences in host metabolites by urbanization status. Urban residents were characterized by metabolites signaling caffeine metabolism and toxic pollutants and metabolites on known pathways to cardiometabolic disease risks, compared to their rural counterparts. Our findings highlight the importance of considering urbanization in metabolomics analysis.

Genetics meets proteomics: perspectives for large population-based studies

Proteomic analysis of cells, tissues and body fluids has generated valuable insights into the complex processes influencing human biology. Proteins represent intermediate phenotypes for disease and provide insight into how genetic and non-genetic risk factors are mechanistically linked to clinical outcomes. Associations between protein levels and DNA sequence variants that colocalize with risk alleles for common diseases can expose disease-associated pathways, revealing novel drug targets and translational biomarkers. However, genome-wide, population-scale analyses of proteomic data are only now emerging. Here, we review current findings from studies of the plasma proteome and discuss their potential for advancing biomedical translation through the interpretation of genome-wide association analyses. We highlight the challenges faced by currently available technologies and provide perspectives relevant to their future application in large-scale biobank studies.

Gut microbial co-abundance networks show specificity in inflammatory bowel disease and obesity

The gut microbiome is an ecosystem that involves complex interactions. Currently, our knowledge about the role of the gut microbiome in health and disease relies mainly on differential microbial abundance, and little is known about the role of microbial interactions in the context of human disease. Here, we construct and compare microbial co-abundance networks using 2,379 metagenomes from four human cohorts: an inflammatory bowel disease (IBD) cohort, an obese cohort and two population-based cohorts. We find that the strengths of 38.6% of species co-abundances and 64.3% of pathway co-abundances vary significantly between cohorts, with 113 species and 1,050 pathway co-abundances showing IBD-specific effects and 281 pathway co-abundances showing obesity-specific effects. We can also replicate these IBD microbial co-abundances in longitudinal data from the IBD cohort of the integrative human microbiome (iHMP-IBD) project. Our study identifies several key species and pathways in IBD and obesity and provides evidence that altered microbial abundances in disease can influence their co-abundance relationship, which expands our current knowledge regarding microbial dysbiosis in disease.

Gut microbiome alterations have been linked to inflammatory bowel disease (IBD) and obesity. Here, the authors characterize the metagenomes of four large human cohorts and perform co-abundance network analysis showing that dysbiosis in disease is marked by the altered co-abundance relationships, suggesting that pathway coabundance networks are more heterogeneous than species network.

Implications of gut microbiome on coronary artery disease

Despite the enormous progress achieved in diagnosis and medical therapy of coronary artery disease (CAD) in the last decades, CAD continues to represent the leading cause of morbidity and mortality worldwide, leading to a massive health-care cost and social burden. Due to the dynamic and complex nature of CAD, the mechanisms underlying the progression of atherosclerotic plaque were largely unknown. With the development of metagenomics and bioinformatics, humans are gradually understanding the important role of the gut microbiome on their hosts. Trillions of microbes colonize in the human gut, they digest and absorb nutrients, as well as participate in a series of human functions and regulate the pathogenesis of diseases, including the cardiovascular disease (CVD) that has received much attention. Meanwhile, metabolomics studies have revealed associations between gut microbiota-derived metabolic bioactive signaling modules, including trimethylamine-N-oxide (TMAO), short-chain fatty acids (SCFAs), and bile acids (BAs), with the progression of CAD. Disturbance of the gut microbiome and microbial metabolites are important factors leading to CAD, which has become a novel target for CAD prevention and treatment. This review provides a brief overview of gut microbiome composition in CAD patients according to the recently reported studies, summarizes the underlying mechanisms, and highlights the prognostic value of the gut microbiome in CAD.

From obesity through gut microbiota to cardiovascular diseases: a dangerous journey

The co-existence of humans and gut microbiota started millions of years ago. Until now, a balance gradually developed between gut bacteria and their hosts. It is now recognized that gut microbiota are key to form adequate immune and metabolic functions and, more in general, for the maintenance of good health. Gut microbiota are established before birth under the influence of maternal nutrition and metabolic status, which can impact the future metabolic risk of the offspring in terms of obesity, diabetes, and cardiometabolic disorders during the lifespan. Obesity and diabetes are prone to disrupt the gut microbiota and alter the gut barrier permeability, leading to metabolic endotoxaemia with its detrimental consequences on health. Specific bacterial sequences are now viewed as peculiar signatures of the metabolic syndrome across life stages in each individual, and are linked to pathogenesis of cardiovascular diseases (CVDs) via metabolic products (metabolites) and immune modulation. These mechanisms have been linked, in association with abnormalities in microbial richness and diversity, to an increased risk of developing arterial hypertension, systemic inflammation, nonalcoholic fatty liver disease, coronary artery disease, chronic kidney disease, and heart failure. Emerging strategies for the manipulation of intestinal microbiota represent a promising therapeutic option for the prevention and treatment of CVD especially in individuals prone to CV events.

Lack of Association Between Genetic Variants at ACE2 and TMPRSS2 Genes Involved in SARS-CoV-2 Infection and Human Quantitative Phenotypes

Coronavirus disease 2019 (COVID-19) shows a wide variation in expression and severity of symptoms, from very mild or no symptoms, to flu-like symptoms, and in more severe cases, to pneumonia, acute respiratory distress syndrome, and even death. Large differences in outcome have also been observed between males and females. The causes for this variability are likely to be multifactorial, and to include genetics. The SARS-CoV-2 virus responsible for the infection depends on two human genes: the human receptor angiotensin converting enzyme 2 (ACE2) for cell invasion, and the serine protease TMPRSS2 for S protein priming. Genetic variation in these two genes may thus modulate an individual's genetic predisposition to infection and virus clearance. While genetic data on COVID-19 patients is being gathered, we carried out a phenome-wide association scan (PheWAS) to investigate the role of these genes in other human phenotypes in the general population. We examined 178 quantitative phenotypes including cytokines and cardio-metabolic biomarkers, as well as usage of 58 medications in 36,339 volunteers from the Lifelines population cohort, in relation to 1,273 genetic variants located in or near ACE2 and TMPRSS2. While none reached our threshold for significance, we observed several interesting suggestive associations. For example, single nucleotide polymorphisms (SNPs) near the TMPRSS2 genes were associated with thrombocytes count (p = 1.8 × 10-5). SNPs within the ACE2 gene were associated with (1) the use of angiotensin II receptor blockers (ARBs) combination therapies (p = 5.7 × 10-4), an association that is significantly stronger in females (p dif f = 0.01), and (2) with the use of non-steroid anti-inflammatory and antirheumatic products (p = 5.5 × 10-4). While these associations need to be confirmed in larger sample sizes, they suggest that these variants could play a role in diseases such as thrombocytopenia, hypertension, and chronic inflammation that are often observed in the more severe COVID-19 cases. Further investigation of these genetic variants in the context of COVID-19 is thus promising for better understanding of disease variability. Full results are available at https://covid19research.nl.

Unraveling Host-Gut Microbiota Dialogue and Its Impact on Cholesterol Levels

Disruption in cholesterol metabolism, particularly hypercholesterolemia, is a significant cause of atherosclerotic cardiovascular disease. Large interindividual variations in plasma cholesterol levels are traditionally related to genetic factors, and the remaining portion of their variance is accredited to environmental factors. In recent years, the essential role played by intestinal microbiota in human health and diseases has emerged. The gut microbiota is currently viewed as a fundamental regulator of host metabolism and of innate and adaptive immunity. Its bacterial composition but also the synthesis of multiple molecules resulting from bacterial metabolism vary according to diet, antibiotics, drugs used, and exposure to pollutants and infectious agents. Microbiota modifications induced by recent changes in the human environment thus seem to be a major factor in the current epidemic of metabolic/inflammatory diseases (diabetes mellitus, liver diseases, inflammatory bowel disease, obesity, and dyslipidemia). Epidemiological and preclinical studies report associations between bacterial communities and cholesterolemia. However, such an association remains poorly investigated and characterized. The objectives of this review are to present the current knowledge on and potential mechanisms underlying the host-microbiota dialogue for a better understanding of the contribution of microbial communities to the regulation of cholesterol homeostasis.

Using Mendelian randomization to understand and develop treatments for neurodegenerative disease

Common neurodegenerative diseases are thought to arise from a combination of environmental and genetic exposures. Mendelian randomization is a powerful way to leverage existing genetic data to investigate causal relationships between risk factors and disease. In recent years, Mendelian randomization has gathered considerable traction in neurodegenerative disease research, providing valuable insights into the aetiology of these conditions. This review aims to evaluate the impact of Mendelian randomization studies on translational medicine for neurodegenerative diseases, highlighting the advances made and challenges faced. We will first describe the fundamental principles and limitations of Mendelian randomization and then discuss the lessons from Mendelian randomization studies of environmental risk factors for neurodegeneration. We will illustrate how Mendelian randomization projects have used novel resources to study molecular pathways of neurodegenerative disease and discuss the emerging role of Mendelian randomization in drug development. Finally, we will conclude with our view of the future of Mendelian randomization in these conditions, underscoring unanswered questions in this field.

Immunochip meta-analysis in European and Argentinian populations identifies two novel genetic loci associated with celiac disease

Celiac disease (CeD) is a common immune-mediated disease of the small intestine that is triggered by exposure to dietary gluten. While the HLA locus plays a major role in disease susceptibility, 39 non-HLA loci were also identified in a study of 24,269 individuals. We now build on this earlier study by adding 4125 additional Caucasian samples including an Argentinian cohort. In doing so, we not only confirm the previous associations, we also identify two novel independent genome-wide significant associations at loci: 12p13.31 and 22q13.1. By applying a genomics approach and differential expression analysis in CeD intestinal biopsies, we prioritize potential causal genes at these novel loci, including LTBR, CYTH4, and RAC2. Nineteen prioritized causal genes are overlapping known drug targets. Pathway enrichment analysis and expression of these genes in CeD biopsies suggest that they have roles in regulating multiple pathways such as the tumor necrosis factor (TNF) mediated signaling pathway and positive regulation of I-κB kinase/NF-κB signaling.

Abnormal metabolism of gut microbiota reveals the possible molecular mechanism of nephropathy induced by hyperuricemia

The progression of hyperuricemia disease is often accompanied by damage to renal function. However, there are few studies on hyperuricemia nephropathy, especially its association with intestinal flora. This study combines metabolomics and gut microbiota diversity analysis to explore metabolic changes using a rat model as well as the changes in intestinal flora composition. The results showed that amino acid metabolism was disturbed with serine, glutamate and glutamine being downregulated whilst glycine, hydroxyproline and alanine being upregulated. The combined glycine, serine and glutamate could predict hyperuricemia nephropathy with an area under the curve of 1.00. Imbalanced intestinal flora was also observed. Flavobacterium, Myroides, Corynebacterium, Alcaligenaceae, Oligella and other conditional pathogens increased significantly in the model group, while Blautia and Roseburia, the short-chain fatty acid producing bacteria, declined greatly. At phylum, family and genus levels, disordered nitrogen circulation in gut microbiota was detected. In the model group, the uric acid decomposition pathway was enhanced with reinforced urea liver-intestine circulation. The results implied that the intestinal flora play a vital role in the pathogenesis of hyperuricemia nephropathy. Hence, modulation of gut microbiota or targeting at metabolic enzymes, i.e., urease, could assist the treatment and prevention of this disease.