Mexican Biobank advances population and medical genomics of diverse ancestries.

Latin America continues to be severely underrepresented in genomics research, and fine-scale genetic histories and complex trait architectures remain hidden owing to insufficient data1. To fill this gap, the Mexican Biobank project genotyped 6,057 individuals from 898 rural and urban localities across all 32 states in Mexico at a resolution of 1.8 million genome-wide markers with linked complex trait and disease information creating a valuable nationwide genotype-phenotype database. Here, using ancestry deconvolution and inference of identity-by-descent segments, we inferred ancestral population sizes across Mesoamerican regions over time, unravelling Indigenous, colonial and postcolonial demographic dynamics2-6. We observed variation in runs of homozygosity among genomic regions with different ancestries reflecting distinct demographic histories and, in turn, different distributions of rare deleterious variants. We conducted genome-wide association studies (GWAS) for 22 complex traits and found that several traits are better predicted using the Mexican Biobank GWAS compared to the UK Biobank GWAS7,8. We identified genetic and environmental factors associating with trait variation, such as the length of the genome in runs of homozygosity as a predictor for body mass index, triglycerides, glucose and height. This study provides insights into the genetic histories of individuals in Mexico and dissects their complex trait architectures, both crucial for making precision and preventive medicine initiatives accessible worldwide.

Rare coding variants in 35 genes associate with circulating lipid levels-A multi-ancestry analysis of 170,000 exomes.

Large-scale gene sequencing studies for complex traits have the potential to identify causal genes with therapeutic implications. We performed gene-based association testing of blood lipid levels with rare (minor allele frequency < 1%) predicted damaging coding variation by using sequence data from >170,000 individuals from multiple ancestries: 97,493 European, 30,025 South Asian, 16,507 African, 16,440 Hispanic/Latino, 10,420 East Asian, and 1,182 Samoan. We identified 35 genes associated with circulating lipid levels; some of these genes have not been previously associated with lipid levels when using rare coding variation from population-based samples. We prioritize 32 genes in array-based genome-wide association study (GWAS) loci based on aggregations of rare coding variants; three (EVI5, SH2B3, and PLIN1) had no prior association of rare coding variants with lipid levels. Most of our associated genes showed evidence of association among multiple ancestries. Finally, we observed an enrichment of gene-based associations for low-density lipoprotein cholesterol drug target genes and for genes closest to GWAS index single-nucleotide polymorphisms (SNPs). Our results demonstrate that gene-based associations can be beneficial for drug target development and provide evidence that the gene closest to the array-based GWAS index SNP is often the functional gene for blood lipid levels.

Improving diagnosis and treatment of hypomagnesemia.

Magnesium is one of the most abundant cations in the body and acts as a cofactor in more than 600 biochemical reactions. Hypomagnesemia is a highly prevalent condition, especially in subjects with comorbid conditions, but has received less attention than other electrolyte disturbances. This review will discuss magnesium physiology, absorption, storage, distribution across the body, and kidney excretion. After reviewing the regulation of magnesium homeostasis, we will focus on the etiology and clinical presentation of hypomagnesemia. The role of laboratory medicine in hypomagnesemia will be the main purpose of this review, and we will discuss the laboratory tests and different samples and methods for its measurement. Although free magnesium is physiologically active, total serum magnesium is the most commonly used measurement in laboratory medicine and is apt for clinical purposes; however, it is not appropriately used, and many patients with hypomagnesemia remain undiagnosed and not treated. Using information technologies, laboratory medicine can largely improve the diagnosis and treatment of hypomagnesemia through the design and establishment of automatic demand management and result management interventions by acting in the first and last steps of the laboratory cycle, test requests, and actions taken after test results, to unmask patients with hypomagnesemia and improve the number of patients undergoing treatment.

Elongated particulate burden in an individual who died of mesothelioma and had an occupational history as a talc "mucker".

INTRODUCTION: Tissue from a 77-year-old man diagnosed with mesothelioma was referred with a request for identification of the presence of fibrous structures in tissue samples. The individual's work history including working as a "mucker" at a specific "industrial" talc mine. METHODS: Ferruginous bodies in the tissue digests as well as asbestos fibers were found. A bulk sample of a talc containing product from that mine was also analyzed. DISCUSSIONS/CONCLUSIONS: The correlation between the unique asbestos mineral/fibrous content of the talc to which he was exposed and findings of the same type of asbestos found in his lung is discussed. The type of asbestos found (tremolite) is a "non-commercial" type of asbestos that has been identified in some talc deposits. Tremolite, like all forms of asbestos is a causative agent for mesothelioma-the disease from which this individual suffered.

Early Brain Amyloid Accumulation at PET in Military Instructors Exposed to Subconcussive Blast Injuries.

Background Traumatic brain injury (TBI) is the leading cause of disability in young adults. Recurrent TBI is associated with a range of neurologic sequelae, but the contributing factors behind the development of such chronic encephalopathy are poorly understood. Purpose To quantify early amyloid ß deposition in the brain of otherwise healthy adult men exposed to repeated subconcussive blast injury using amyloid PET. Materials and Methods In this prospective study from January 2020 to December 2021, military instructors who were routinely exposed to repeated blast events were evaluated at two different points: baseline (before blast exposure from breacher or grenade) and approximately 5 months after baseline (after blast exposure). Age-matched healthy control participants not exposed to blasts and without a history of brain injury were evaluated at similar two points. Neurocognitive evaluation was performed with standard neuropsychologic testing in both groups. Analysis of PET data consisted of standardized uptake value measurements in six relevant brain regions and a whole-brain voxel-based statistical approach. Results Participants were men (nine control participants [median age, 33 years; IQR, 32-36 years] and nine blast-exposed participants [median age, 33 years; IQR, 30-34 years]; P = .82). In the blast-exposed participants, four brain regions showed significantly increased amyloid deposition after blast exposure: inferomedial frontal lobe (P = .004), precuneus (P = .02), anterior cingulum (P = .002), and superior parietal lobule (P = .003). No amyloid deposition was observed in the control participants. Discriminant analysis on the basis of regional changes of amyloid accumulation correctly classified the nine healthy control participants as healthy control participants (100%), and seven of the nine blast-exposed participants (78%) were correctly classified as blast exposed. Based on the voxel-based analysis, whole-brain parametric maps of early abnormal early amyloid uptake were obtained. Conclusion Early brain amyloid accumulation was identified and quantified at PET in otherwise healthy adult men exposed to repetitive subconcussive traumatic events. © RSNA, 2023 Supplemental material is available for this article. See also the editorial by Haller in this issue.

The role of SLC16A11 variations in diabetes mellitus.

PURPOSE OF REVIEW: The aim of this study was to summarize the existing evidence that proves the association between an ethnic-specific SLC16A11 risk haplotype and type 2 diabetes found in the Latin American population. RECENT FINDINGS: The association has been replicated in consortia studies, especially in early-onset type 2 diabetes. No association has been found with gestational diabetes. Mild obesity-related diabetes is the most common T2D subphenotype found in patients with the risk haplotype. The SLC16A11 risk haplotype is associated with decreased insulin action, higher acute insulin secretory response to an intravenous glucose bolus and higher serum alanine aminotransferase levels. SUMMARY: The study of underrepresented populations in large genomic databases is a valuable resource to gain new knowledge about the pathophysiology of complex traits, especially if these groups have suffered repeated selection process caused by famine, migrations and war. This is the case of diabetes, obesity and lipid disorders in Latin American countries. Here, we summarize the existing evidence of a proof-of concept finding: the association between the SLC16A11 ethnic-specific risk haplotype and T2D.

Stratification in Heterozygous Familial Hypercholesterolemia: Imaging, Biomarkers, and Genetic Testing.

PURPOSE OF REVIEW: Heterozygous familial hypercholesterolemia (HeFH) is the most common monogenic autosomal dominant disorder. However, the condition is often underdiagnosed and undertreated. The objective of this review is to provide an update on the risk stratification in patients with HeFH, incorporating new cardiovascular imaging techniques, various biomarkers, and genetic studies. RECENT FINDINGS: The diagnosis of HeFH places patients in a high cardiovascular risk category due to the increased incidence of premature atherosclerotic cardiovascular disease. However, the level of risk varies significantly among different individuals with HeFH. Achieving an optimal stratification of cardiovascular risk is crucial for establishing appropriate and accurate treatment and management strategies. Different new tools such as risk scores have emerged in recent years, aiding physicians in assessing the risk stratification for HeFH using imaging, biomarkers, and genetics. This review emphasizes that not all patients with HeFH face the same cardiovascular risk. By utilizing different assessment tools, we can identify those who require more intensive monitoring, follow-up, and treatment.

A metagenomic study identifies a Prevotella copri enriched microbial profile associated with non-alcoholic steatohepatitis in subjects with obesity.

BACKGROUND AND AIM: Non-alcoholic fatty liver disease (NAFLD) is the most common cause of liver disease. Increasing evidence indicates that the gut microbiota can play an important role in the pathophysiology of NAFLD. Recently, several studies have tested the predictive value of gut microbiome profiles in NAFLD progression; however, comparisons of microbial signatures in NAFLD or non-alcoholic steatohepatitis (NASH) have produced discrepant results, possibly due to ethnic and environmental factors. Thus, we aimed to characterize the gut metagenome composition of patients with fatty liver disease. METHODS: Gut microbiome of 45 well-characterized patients with obesity and biopsy-proven NAFLD was evaluated using shot-gun sequencing: 11 non-alcoholic fatty liver controls (non-NAFL), 11 with fatty liver, and 23 with NASH. RESULTS: Our study showed that Parabacteroides distasonis and Alistipes putredenis were enriched in fatty liver but not in NASH patients. Notably, in a hierarchical clustering analysis, microbial profiles were differentially distributed among groups, and membership to a Prevotella copri dominant cluster was associated with a greater risk of developing NASH. Functional analyses showed that although no differences in LPS biosynthesis pathways were observed, Prevotella-dominant subjects had higher circulating levels of LPS and a lower abundance of pathways encoding butyrate production. CONCLUSIONS: Our findings suggest that a Prevotella copri dominant bacterial community is associated with a greater risk for NAFLD disease progression, probably linked to higher intestinal permeability and lower capacity for butyrate production.

Artificial intelligence and real-world data for drug and food safety - A regulatory science perspective.

In 2013, the Global Coalition for Regulatory Science Research (GCRSR) was established with members from over ten countries (www.gcrsr.net). One of the main objectives of GCRSR is to facilitate communication among global regulators on the rise of new technologies with regulatory applications through the annual conference Global Summit on Regulatory Science (GSRS). The 11th annual GSRS conference (GSRS21) focused on "Regulatory Sciences for Food/Drug Safety with Real-World Data (RWD) and Artificial Intelligence (AI)." The conference discussed current advancements in both AI and RWD approaches with a specific emphasis on how they impact regulatory sciences and how regulatory agencies across the globe are pursuing the adaptation and oversight of these technologies. There were presentations from Brazil, Canada, India, Italy, Japan, Germany, Switzerland, Singapore, the United Kingdom, and the United States. These presentations highlighted how various agencies are moving forward with these technologies by either improving the agencies' operation and/or preparing regulatory mechanisms to approve the products containing these innovations. To increase the content and discussion, the GSRS21 hosted two debate sessions on the question of "Is Regulatory Science Ready for AI?" and a workshop to showcase the analytical data tools that global regulatory agencies have been using and/or plan to apply to regulatory science. Several key topics were highlighted and discussed during the conference, such as the capabilities of AI and RWD to assist regulatory science policies for drug and food safety, the readiness of AI and data science to provide solutions for regulatory science. Discussions highlighted the need for a constant effort to evaluate emerging technologies for fit-for-purpose regulatory applications. The annual GSRS conferences offer a unique platform to facilitate discussion and collaboration across regulatory agencies, modernizing regulatory approaches, and harmonizing efforts.

The causal effect of obesity on prediabetes and insulin resistance reveals the important role of adipose tissue in insulin resistance.

Reverse causality has made it difficult to establish the causal directions between obesity and prediabetes and obesity and insulin resistance. To disentangle whether obesity causally drives prediabetes and insulin resistance already in non-diabetic individuals, we utilized the UK Biobank and METSIM cohort to perform a Mendelian randomization (MR) analyses in the non-diabetic individuals. Our results suggest that both prediabetes and systemic insulin resistance are caused by obesity (p = 1.2×10-3 and p = 3.1×10-24). As obesity reflects the amount of body fat, we next studied how adipose tissue affects insulin resistance. We performed both bulk RNA-sequencing and single nucleus RNA sequencing on frozen human subcutaneous adipose biopsies to assess adipose cell-type heterogeneity and mitochondrial (MT) gene expression in insulin resistance. We discovered that the adipose MT gene expression and body fat percent are both independently associated with insulin resistance (p≤0.05 for each) when adjusting for the decomposed adipose cell-type proportions. Next, we showed that these 3 factors, adipose MT gene expression, body fat percent, and adipose cell types, explain a substantial amount (44.39%) of variance in insulin resistance and can be used to predict it (p≤2.64×10-5 in 3 independent human cohorts). In summary, we demonstrated that obesity is a strong determinant of both prediabetes and insulin resistance, and discovered that individuals' adipose cell-type composition, adipose MT gene expression, and body fat percent predict their insulin resistance, emphasizing the critical role of adipose tissue in systemic insulin resistance.

Associated factors to the consumption of non-nutritive sweeteners in the Mexican adult population.

OBJECTIVE: To identify the associated factors to the consumption of non-nutritive sweeteners (NNS) in the Mexican adult population since its consumption has increased exponentially worldwide. MATERIALS AND METHODS: An online survey was applied to 5 038 Mexican adults to evaluate the frequency of NNS consumption and classify the population in tertiles. The sociodemographic, lifestyle and health status characteristics of the participants were compared by gradient of NNS consumption, and a multiple linear regression analysis was performed to determine the associated factors to the NNS consumption. RESULTS: The variables that showed a positive association (p≤0.01) with the consumption of NNS were economic income, BMI, smoking, physical activity, diet quality, the presence of chronic diseases (diabetes, hypertension, or dyslipidemias), and the consumption of fruit. The age and the consumption of confectionery and sugar-sweetened beverages were negatively associated (p<0.01) with the consumption of NNS. CONCLUSION: The results of this study help to characterize the target population that is a consumer of NNS since it is recommended not encourage the preference for sweet taste and to promote a decrease in the consumption of both caloric and NNS, preferring the natural flavor of food.

Tamizaje, prevalencia, diagnóstico previo, tratamiento y control de hipertensión, hipercolesterolemia y diabetes en adultos mexicanos. Ensanut 2022.

OBJETIVO: Describir las estimaciones de tamizaje, prevalencia, diagnóstico previo, tratamiento y control de hipertensión, hipercolesterolemia y diabetes, así como sus factores asociados en los adultos mexicanos. Material y métodos. Se utilizó información de los adultos de 20 años o más participantes de la Encuesta Nacional de Salud y Nutrición 2022 (Ensanut 2022). Se presentan estimaciones de prevalencias con sus intervalos de confianza al 95%, y modelos de regresión logística múltiple para cada padecimiento, con factores asociados al tamizaje, diagnóstico previo, tratamiento y control. RESULTADOS: El tamizaje de estas tres enfermedades es bajo, menor a 15%. La prevalencia de hipercolesterolemia y de diabetes es de 18% y la de hipertensión es 27.8%; cerca de la mitad conoce su diagnóstico. La proporción de pacientes con tratamiento farmacológico ha incrementado, pero menos de la mitad está en control. Conclusión. Es recomendable que la detección de estas enfermedades se haga de manera integrada con otros factores de riesgo cardiovascular. Se necesita aumentar los porcentajes de tamizaje, incrementar la proporción de enfermos con diagnóstico previo, mejorar el porcentaje de tratamiento médico de estas enfermedades y, sobre todo, aumentar la proporción de enfermos con tratamiento en control metabólico.

Prevalencia de prediabetes y diabetes en México: Ensanut 2022.

OBJETIVO: Estimar la prevalencia de prediabetes y diabetes en la población adulta mexicana. Material y métodos. Se utilizó información de la submuestra de adultos de la Encuesta Nacional de Salud y Nutrición 2022 con una muestra de sangre de 10 ml. Se excluyeron 150 individuos con ayuno menor a 8 horas y cuatro personas con diabetes gestacional. La muestra final fue de 1 945 adultos que expande a 78.3 millones de adultos. RESULTADOS: La prevalencia de prediabetes fue de 22.1%, y de diabetes diagnosticada y no diagnosticada de 12.6 y 5.8%, respectivamente, lo que resulta en una prevalencia de diabetes total de 18.3%. Conclusión. La diabetes en México es muy prevalente e implica un reto importante para el sistema de salud. Se requieren acciones contundentes para prevenir la enfermedad, mejorar el tamizaje, el diagnóstico oportuno y el control de la enfermedad.

Driver Identification Using Statistical Features of Motor Activity and Genetic Algorithms.

Driver identification refers to the process whose primary purpose is identifying the person behind the steering wheel using collected information about the driver him/herself. The constant monitoring of drivers through sensors generates great benefits in advanced driver assistance systems (ADAS), to learn more about the behavior of road users. Currently, there are many research works that address the subject in search of creating intelligent models that help to identify vehicle users in an efficient and objective way. However, the different methodologies proposed to create these models are based on data generated from sensors that include different vehicle brands on routes established in real environments, which, although they provide very important information for different purposes, in the case of driver identification, there may be a certain degree of bias due to the different situations in which the route environment may change. The proposed method seeks to intelligently and objectively select the most outstanding statistical features from motor activity generated in the main elements of the vehicle with genetic algorithms for driver identification, this process being newer than those established by the state-of-the-art. The results obtained from the proposal were an accuracy of 90.74% to identify two drivers and 62% for four, using a Random Forest Classifier (RFC). With this, it can be concluded that a comprehensive selection of features can greatly optimize the identification of drivers.

Crystal Engineering of Two Light and Pressure Responsive Physisorbents.

An emerging strategy in the design of efficient gas storage technologies is the development of stimuli-responsive physisorbents which undergo transformations in response to a particular stimulus, such as pressure, heat or light. Herein, we report two isostructural light modulated adsorbents (LMAs) containing bis-3-thienylcyclopentene (BTCP), LMA-1 [Cd(BTCP)(DPT)2 ] (DPT=2,5-diphenylbenzene-1,4-dicarboxylate) and LMA-2 [Cd(BTCP)(FDPT)2 ] (FDPT=5-fluoro-2,diphenylbenzene-1,4-dicarboxylate). Both LMAs undergo pressure induced switching transformations from non-porous to porous via adsorption of N2 , CO2 and C2 H2 . LMA-1 exhibited multi-step adsorption while LMA-2 showed a single-step adsorption isotherm. The light responsive nature of the BTPC ligand in both frameworks was exploited with irradiation of LMA-1 resulting in a 55 % maximum reduction of CO2 uptake at 298 K. This study reports the first example of a switching sorbent (closed to open) that can be further modulated by light.

Zinc associated nanomaterials and their intervention in emerging respiratory viruses: Journey to the field of biomedicine and biomaterials.

Respiratory viruses represent a severe public health risk worldwide, and the research contribution to tackle the current pandemic caused by the SARS-CoV-2 is one of the main targets among the scientific community. In this regard, experts from different fields have gathered to confront this catastrophic pandemic. This review illustrates how nanotechnology intervention could be valuable in solving this difficult situation, and the state of the art of Zn-based nanostructures are discussed in detail. For virus detection, learning from the experience of other respiratory viruses such as influenza, the potential use of Zn nanomaterials as suitable sensing platforms to recognize the S1 spike protein in SARS-CoV-2 are shown. Furthermore, a discussion about the antiviral mechanisms reported for ZnO nanostructures is included, which can help develop surface disinfectants and protective coatings. At the same time, the properties of Zn-based materials as supplements for reducing viral activity and the recovery of infected patients are illustrated. Within the scope of noble adjuvants to improve the immune response, the ZnO NPs properties as immunomodulators are explained, and potential prototypes of nanoengineered particles with metallic cations (like Zn2+) are suggested. Therefore, using Zn-associated nanomaterials from detection to disinfection, supplementation, and immunomodulation opens a wide area of opportunities to combat these emerging respiratory viruses. Finally, the attractive properties of these nanomaterials can be extrapolated to new clinical challenges.

Characterization of data-driven clusters in diabetes-free adults and their utility for risk stratification of type 2 diabetes.

BACKGROUND: The prevention of type 2 diabetes is challenging due to the variable effects of risk factors at an individual level. Data-driven methods could be useful to detect more homogeneous groups based on risk factor variability. The aim of this study was to derive characteristic phenotypes using cluster analysis of common risk factors and to assess their utility to stratify the risk of type 2 diabetes. METHODS: Data on 7317 diabetes-free adults from Sweden were used in the main analysis and on 2332 diabetes-free adults from Mexico for external validation. Clusters were based on sex, family history of diabetes, educational attainment, fasting blood glucose and insulin levels, estimated insulin resistance and ß-cell function, systolic and diastolic blood pressure, and BMI. The risk of type 2 diabetes was assessed using Cox proportional hazards models. The predictive accuracy and long-term stability of the clusters were then compared to different definitions of prediabetes. RESULTS: Six risk phenotypes were identified independently in both cohorts: very low-risk (VLR), low-risk low ß-cell function (LRLB), low-risk high ß-cell function (LRHB), high-risk high blood pressure (HRHBP), high-risk ß-cell failure (HRBF), and high-risk insulin-resistant (HRIR). Compared to the LRHB cluster, the VLR and LRLB clusters showed a lower risk, while the HRHBP, HRBF, and HRIR clusters showed a higher risk of developing type 2 diabetes. The high-risk clusters, as a group, had a better predictive accuracy than prediabetes and adequate stability after 20 years. CONCLUSIONS: Phenotypes derived using cluster analysis were useful in stratifying the risk of type 2 diabetes among diabetes-free adults in two independent cohorts. These results could be used to develop more precise public health interventions.

Epicardial adipose tissue thickness is associated with increased COVID-19 severity and mortality.

BACKGROUND: Increased adiposity and visceral obesity have been linked to adverse COVID-19 outcomes. The amount of epicardial adipose tissue (EAT) may have relevant implications given its proximity to the heart and lungs. Here, we explored the role of EAT in increasing the risk for COVID-19 adverse outcomes. METHODS: We included 748 patients with COVID-19 attending a reference center in Mexico City. EAT thickness, sub-thoracic and extra-pericardial fat were measured using thoracic CT scans. We explored the association of each thoracic adipose tissue compartment with COVID-19 mortality and severe COVID-19 (defined as mortality and need for invasive mechanical ventilation), according to the presence or absence of obesity. Mediation analyses evaluated the role of EAT in facilitating the effect of age, body mass index and cardiac troponin levels with COVID-19 outcomes. RESULTS: EAT thickness was associated with increased risk of COVID-19 mortality (HR 1.18, 95% CI 1.01-1.39) independent of age, gender, comorbid conditions and BMI. Increased EAT was associated with lower SpO2 and PaFi index and higher levels of cardiac troponins, D-dimer, fibrinogen, C-reactive protein, and 4 C severity score, independent of obesity. EAT mediated 13.1% (95% CI 3.67-28.0%) and 5.1% (95% CI 0.19-14.0%) of the effect of age and 19.4% (95% CI 4.67-63.0%) and 12.8% (95% CI 0.03-46.0%) of the effect of BMI on requirement for intubation and mortality, respectively. EAT also mediated the effect of increased cardiac troponins on myocardial infarction during COVID-19. CONCLUSION: EAT is an independent risk factor for severe COVID-19 and mortality independent of obesity. EAT partly mediates the effect of age and BMI and increased cardiac troponins on adverse COVID-19 outcomes.

Elevated serum uric acid is a facilitating mechanism for insulin resistance mediated accumulation of visceral adipose tissue.

OBJECTIVE: Serum uric acid (SUA) has been associated with cardiometabolic conditions such as insulin resistance (IR) and visceral adipose tissue (VAT) accumulation. Here, we aimed to clarify a unifying mechanism linking elevated SUA to IR and VAT. METHODS: We conducted analyses in 226 subjects from the UIEM cohort with both euglycemic hyperinsulinemic clamp (EHC) and dual X-ray absorptiometry (DXA) measurements for IR and VAT accumulation and explored the role of SUA and adiponectin by developing a network of causal mediation analyses to assess their impact on IR and VAT. These models were then translated to two population-based cohorts comprising 6337 subjects from NHANES 2003-2004 and 2011-2012 cycles in the US and ENSANUT Medio Camino 2016 in Mexico, using HOMA2IR and adipoIR as indicators of peripheral and adipose tissue IR, and METS-VF as a surrogate for VAT accumulation. RESULTS: SUA has a mediating role inside a bidirectional relationship between IR and visceral obesity, which was similar using either gold standard measurements or surrogate measures for IR and VAT. Furthermore, adiponectin acts as a linking mediator between elevated SUA and both peripheral IR and VAT accumulation. The proportion of the mechanism for IR-mediated (in either peripheral or adipose tissue) VAT accumulation was greater, compared to VAT-mediated IR accumulation (10.53% [9.23%-12.00%] to 5.44% [3.78%-7.00%]). Normal-range SUA levels can be used to rule-out underlying cardio-metabolic abnormalities in both men and women. CONCLUSIONS: Elevated SUA acts as a mediator inside the bidirectional relationship between IR and VAT accumulation and these observations could be applicable at a phenotype scale.

Galectin-3 is overexpressed in advanced cirrhosis and predicts post-liver transplant infectious complications.

BACKGROUND & AIMS: Patients with advanced cirrhosis often have immune dysfunction and are more susceptible to infections. Galectin-3 is a ß-galactoside-binding lectin implicated in inflammation, immune regulation and liver fibrosis. We aim to investigate galectin-3 expression in advanced cirrhosis and its ability to predict post-transplant infectious complications. METHODS: We collected sera and liver samples from 129 cirrhotic patients at the time of liver transplantation and from an external cohort of 37 patients with alcoholic liver disease including alcoholic hepatitis (AH) at the time of diagnosis. Galectin-3 was assessed by ELISA, real-time PCR, immunohistochemistry and RNA-seq. Receiver operating characteristic curves and Cox proportional-hazards regression analysis were performed to assess the predictive power of galectin-3 for disease severity and post-transplant infections. RESULTS: Increased galectin-3 levels were found in advanced cirrhosis. Galectin-3 significantly correlated with disease severity parameters and inflammatory markers. Galectin-3 had significant discriminating power for compensated and advanced cirrhosis (AUC = 0.78/0.84, circulating/liver galectin-3; p < .01), and was even higher to discriminate severe AH (AUC = 0.95, p < .0001). Cox Proportional-hazard model showed that galectin-3, MELD-Na and the presence of SIRS predict the development of post-transplant infectious complications. Patients with circulating galectin-3 (>16.58 ng/ml) were at 2.19-fold 95% CI (1.12-4.29) increased risk, but when combined with MELD-Na > 20.0 and SIRS, the risk to develop post-transplant infectious complications, increased to 4.60, 95% CI (2.38-8.90). CONCLUSION: Galectin-3 is a novel biological marker of active inflammation and disease severity that could be clinically useful alone or in combination with other scores to discriminate advanced cirrhosis and predict post-transplant infectious complications.