Protection against fibrosis by a bacterial consortium in metabolic dysfunction-associated steatohepatitis and the role of amino acid metabolism.

The gut microbiota drives progression to liver fibrosis, the main determinant of mortality in metabolic dysfunction-associated steatohepatitis (MASH). In this study, we aimed to identify bacterial species associated with protection against liver fibrosis in a high-risk population, and test their potential to protect against liver fibrosis in vivo. Based on stool shotgun metagenomic sequencing of 340 subjects from a population cohort disproportionally affected by MASH, we identified bacterial species from the Bacteroidales and Clostridiales orders associated with reduced risk of liver fibrosis. A bacterial consortium was subsequently tested in a mouse model of MASH, which demonstrated protective effects against liver fibrosis. Six of the eight inoculated bacteria were detected in mouse stool and liver. Intrahepatic presence of bacteria was further confirmed by bacterial culture of mouse liver tissue. Changes in liver histological parameters, gut functional profiles, and amino acid profiles were additionally assessed. Comparison between fibrosis-associated human metagenome and bacteria-induced metagenome changes in mice identified microbial functions likely to mediate the protective effect against liver fibrosis. Amino acid profiling confirmed an increase in cysteine synthase activity, associated with reduced fibrosis. Other microbiota-induced changes in amino acids associated with reduced fibrosis included increased gut asparaginase activity and decreased hepatic tryptophan-to-kynurenine conversion. This human-to-mouse study identified bacterial species and their effects on amino acid metabolism as innovative strategies to protect against liver fibrosis in MASH.

Gut phageome in Mexican Americans: a population at high risk for metabolic dysfunction-associated steatotic liver disease and diabetes.

Mexican Americans are disproportionally affected by metabolic dysfunction-associated steatotic liver disease (MASLD), which often co-occurs with diabetes. Despite extensive evidence on the causative role of the gut microbiome in MASLD, studies determining the involvement of the gut phageome are scarce. In this cross-sectional study, we characterized the gut phageome in Mexican Americans of South Texas by stool shotgun metagenomic sequencing of 340 subjects, concurrently screened for liver steatosis by transient elastography. Inter-individual variations in the phageome were associated with gender, country of birth, diabetes, and liver steatosis. The phage signatures for diabetes and liver steatosis were subsequently determined. Enrichment of Inoviridae was associated with both diabetes and liver steatosis. Diabetes was further associated with the enrichment of predominantly temperate Escherichia phages, some of which possessed virulence factors. Liver steatosis was associated with the depletion of Lactococcus phages r1t and BK5-T, and enrichment of the globally prevalent Crassvirales phages, including members of genus cluster IX (Burzaovirus coli, Burzaovirus faecalis) and VI (Kahnovirus oralis). The Lactococcus phages showed strong correlations and co-occurrence with Lactococcus lactis, while the Crassvirales phages, B. coli, B. faecalis, and UAG-readthrough crAss clade correlated and co-occurred with Prevotella copri. In conclusion, we identified the gut phageome signatures for two closely linked metabolic diseases with significant global burden. These phage signatures may have utility in risk modeling and disease prevention in this high-risk population, and identification of potential bacterial targets for phage therapy.IMPORTANCEPhages influence human health and disease by shaping the gut bacterial community. Using stool samples from a high-risk Mexican American population, we provide insights into the gut phageome changes associated with diabetes and liver steatosis, two closely linked metabolic diseases with significant global burden. Common to both diseases was an enrichment of Inoviridae, a group of phages that infect bacterial hosts chronically without lysis, allowing them to significantly influence bacterial growth, virulence, motility, biofilm formation, and horizontal gene transfer. Diabetes was additionally associated with the enrichment of Escherichia coli-infecting phages, some of which contained virulence factors. Liver steatosis was additionally associated with the depletion of Lactococcus lactis-infecting phages, and enrichment of Crassvirales phages, a group of virulent phages with high global prevalence and persistence across generations. These phageome signatures may have utility in risk modeling, as well as identify potential bacterial targets for phage therapy.

Integrating Genetic and Transcriptomic Data to Identify Genes Underlying Obesity Risk Loci.

Genome-wide association studies (GWAS) have identified numerous body mass index (BMI) loci. However, most underlying mechanisms from risk locus to BMI remain unknown. Leveraging omics data through integrative analyses could provide more comprehensive views of biological pathways on BMI. We analyzed genotype and blood gene expression data in up to 5,619 samples from the Framingham Heart Study (FHS). Using 3,992 single nucleotide polymorphisms (SNPs) at 97 BMI loci and 20,692 transcripts within 1 Mb, we performed separate association analyses of transcript with BMI and SNP with transcript (PBMI and PSNP, respectively) and then a correlated meta-analysis between the full summary data sets (PMETA). We identified transcripts that met Bonferroni-corrected significance for each omic, were more significant in the correlated meta-analysis than each omic, and were at least nominally associated with BMI in FHS data. Among 308 significant SNP-transcript-BMI associations, we identified seven genes (NT5C2, GSTM3, SNAPC3, SPNS1, TMEM245, YPEL3, and ZNF646) in five association regions. Using an independent sample of blood gene expression data, we validated results for SNAPC3 and YPEL3. We tested for generalization of these associations in hypothalamus, nucleus accumbens, and liver and observed significant (PMETA<0.05 & PMETA

The association of cancer-preventive lifestyle with colonoscopy screening use in border Hispanic adults along the Texas-Mexico border.

PURPOSE: The relationship between engaging in two domains of cancer-preventive behaviors, lifestyle behaviors and colonoscopy screening, is unknown in Hispanic adults. Accordingly, the study examined the association between lifestyle and colonoscopy screening in Hispanic adults along the Texas-Mexico border, where there is suboptimal colorectal cancer prevention. METHODS: Lifestyle behavior adherence and compliance with colonoscopy screening schedules were assessed using 2013-2023 data from the Cameron County Hispanic Cohorta population-based sample of Hispanic adults living along the Texas-Mexico border. The 2018 World Cancer Research Fund scoring system characterized healthy lifestyle engagement. Multivariable logistic regression quantified the association between lifestyle behaviors and colonoscopy screening. RESULTS: Among 914 Hispanic adults, there was a mean adherence score of 2.5 out of 7 for recommended behaviors. Only 33.0% (95% CI 25.64-41.39%) were up-to-date with colonoscopy. Complete adherence to fruit and vegetable (AOR [adjusted odds ratio] 5.2, 95% CI 1.68-16.30; p = 0.004), fiber (AOR 2.2, 95% CI 1.06-4.37; p = 0.04), and ultra-processed foods (AOR 2.8, 95% CI 1.30-6.21; p = 0.01) consumption recommendations were associated with up-to-date colonoscopy screening. Having insurance versus being uninsured (AOR 10.8, 95% CI 3.83-30.62; p < 0.001) and having local medical care versus in Mexico (AOR 7.0, 95% CI 2.26-21.43; p < 0.001) were associated with up-to-date colonoscopy. CONCLUSIONS: Adherence to dietary lifestyle recommendations was associated with being up-to-date with colonoscopy screenings. Those with poor dietary behavior are at risk for low-colonoscopy use. Improving lifestyle behaviors may complement colonoscopy promotion interventions. Healthcare accessibility influences up-to-date colonoscopy prevalence. Our findings can inform cancer prevention strategies for the Hispanic population.

An expanded chronic care management approach to multiple chronic conditions in Hispanics using community health workers as community extenders in the Rio Grande Valley of Texas.

INTRODUCTION: The synergistic negative effects of type 2 diabetes (T2DM) and hypertension increases all-cause mortality and the medical complexity of management, which disproportionately impact Hispanics who face barriers to healthcare access. The Salud y Vida intervention was delivered to Hispanic adults living along the Texas-Mexico Border with comorbid poorly controlled T2DM and hypertension. The Salud y Vida multicomponent intervention incorporated community health workers (CHWs) into an expanded chronic care management model to deliver home-based follow-up visits and provided community-based diabetes self-management education. METHODS: We conducted multivariable longitudinal analysis to examine the longitudinal intervention effect on reducing systolic and diastolic blood pressure among 3806 participants enrolled between 2013 and 2019. Participants were compared according to their program participation as either higher (≥ 10 combined educational classes and CHW visits) or lower engagement (<10 encounters). Data was collected between 2013 and 2020. RESULTS: Baseline mean systolic and diastolic blood pressure were 138 and 81 mmHg respectively. There were overall improvements in systolic (-6.49; 95% CI = [-7.13, -5.85]; p < 0.001) and diastolic blood pressure (-3.97; 95% CI = [-4.37, -3.56]; p < 0.001). The higher engagement group had greater systolic blood pressure reduction at 3 months (adjusted mean difference = -1.8 mmHg; 95% CI = [-3.2, -0.3]; p = 0.016) and at 15 month follow-up (adjusted mean difference = -2.3 mmHg; 95% CI = [-4.2, -0.39]; p = 0.0225) compared to the lower engagement group. CONCLUSION: This intervention, tested and delivered in a real-world setting, provides an example of how CHW integration into an expanded chronic care model can improve blood pressure outcomes for individuals with co-morbidities.

Genome-wide association study identifies human genetic variants associated with fatal outcome from Lassa fever.

Infection with Lassa virus (LASV) can cause Lassa fever, a haemorrhagic illness with an estimated fatality rate of 29.7%, but causes no or mild symptoms in many individuals. Here, to investigate whether human genetic variation underlies the heterogeneity of LASV infection, we carried out genome-wide association studies (GWAS) as well as seroprevalence surveys, human leukocyte antigen typing and high-throughput variant functional characterization assays. We analysed Lassa fever susceptibility and fatal outcomes in 533 cases of Lassa fever and 1,986 population controls recruited over a 7 year period in Nigeria and Sierra Leone. We detected genome-wide significant variant associations with Lassa fever fatal outcomes near GRM7 and LIF in the Nigerian cohort. We also show that a haplotype bearing signatures of positive selection and overlapping LARGE1, a required LASV entry factor, is associated with decreased risk of Lassa fever in the Nigerian cohort but not in the Sierra Leone cohort. Overall, we identified variants and genes that may impact the risk of severe Lassa fever, demonstrating how GWAS can provide insight into viral pathogenesis.

A Laplacian regularized graph neural network for predictive modeling of multiple chronic conditions.

BACKGROUND AND GOALS: One of the biggest difficulties facing healthcare systems today is the prevalence of multiple chronic diseases (MCC). Mortality and the development of new chronic illnesses are more likely in those with MCC. Pre-existing diseases and risk factors specific to the patient have an impact on the complex stochastic process that guides the evolution of MCC. This study's goal is to use a brand-new Graph Neural Network (GNN) model to examine the connections between specific chronic illnesses, patient-level risk factors, and pre-existing conditions. METHODS: We propose a graph neural network model to analyze the relationship between five chronic conditions (diabetes, obesity, cognitive impairment, hyperlipidemia, and hypertension). The proposed model adds a graph Laplacian regularization term to the loss function, which aims to improve the parameter learning process and accuracy of the GNN based on the graph structure. For validation, we used historical data from the Cameron County Hispanic Cohort (CCHC). RESULTS: Evaluating the Laplacian regularized GNN on data from 600 patients, we expanded our analysis from two chronic conditions to five chronic conditions. The proposed model consistently surpassed a baseline GNN model, achieving an average accuracy of ≥89% across all combinations. In contrast, the performance of the standard model declined more markedly with the addition of more chronic conditions. The Laplacian regularization provided consistent predictions for adjacent nodes, beneficial in cases with shared attributes among nodes. CONCLUSIONS: The incorporation of Laplacian regularization in our GNN model is essential, resulting in enhanced node categorization and better predictive performance by harnessing the graph structure. This study underscores the significance of considering graph structure when designing neural networks for graph data. Future research might further explore and refine this regularization method for various tasks using graph-structured data.

A high burden of diabetes and ankle brachial index abnormalities exists in Mexican Americans in South Texas.

Ethnic differences exist in the United States in the interrelated problems of diabetes (DM), peripheral arterial disease (PAD), and leg amputations. The purpose of this study was to determine the prevalence and risk factor associations for subclinical PAD in a population sample of Mexican Americans using the ankle brachial (ABI) index. The ABI-High (higher of the two ankle pressures/highest brachial pressure) and ABI-Low (lower of the two ankle pressures/highest brachial pressure) were calculated to define PAD. Toe brachial index (TBI) was also calculated. 746 participants were included with an age of 53.4 ± 0.9 years, 28.3 % had diabetes mellitus (DM), 12.6 % were smokers, and 51.2 % had hypertension (HTN). Using ABI-High ≤ 0.9, the prevalence of PAD was 2.7 %. This rose to 12.7 % when an ABI-Low ≤ 0.9 was used; 4.0 % of the population had an ABI-High > 1.4. The prevalence of TBI < 0.7 was 3.9 %. DM was a significant risk factor for ABI-High ≤ 0.9 and ABI-High > 1.4, and TBI < 0.7. Increased age, HTN, smoking was associated with ABI-High ≤ 0.9, while being male was associated with ABI-High > 1.4. Increased age, smoking, and lower education were all associated with abnormal TBI. Despite relatively younger mean age than other studied Hispanic cohorts, the present population has a high burden of ABI abnormalities. DM was a consistent risk factor for PAD. These abnormalities indicate an important underlying substrate of vascular and metabolic disease that may predispose this population to the development of symptomatic PAD and incident amputations.

Evaluation of a Targeted COVID-19 Community Outreach Intervention: Case Report for Precision Public Health.

BACKGROUND: Cameron County, a low-income south Texas-Mexico border county marked by severe health disparities, was consistently among the top counties with the highest COVID-19 mortality in Texas at the onset of the pandemic. The disparity in COVID-19 burden within Texas counties revealed the need for effective interventions to address the specific needs of local health departments and their communities. Publicly available COVID-19 surveillance data were not sufficiently timely or granular to deliver such targeted interventions. An agency-academic collaboration in Cameron used novel geographic information science methods to produce granular COVID-19 surveillance data. These data were used to strategically target an educational outreach intervention named "Boots on the Ground" (BOG) in the City of Brownsville (COB). OBJECTIVE: This study aimed to evaluate the impact of a spatially targeted community intervention on daily COVID-19 test counts. METHODS: The agency-academic collaboration between the COB and UTHealth Houston led to the creation of weekly COVID-19 epidemiological reports at the census tract level. These reports guided the selection of census tracts to deliver targeted BOG between April 21 and June 8, 2020. Recordkeeping of the targeted BOG tracts and the intervention dates, along with COVID-19 daily testing counts per census tract, provided data for intervention evaluation. An interrupted time series design was used to evaluate the impact on COVID-19 test counts 2 weeks before and after targeted BOG. A piecewise Poisson regression analysis was used to quantify the slope (sustained) and intercept (immediate) change between pre- and post-BOG COVID-19 daily test count trends. Additional analysis of COB tracts that did not receive targeted BOG was conducted for comparison purposes. RESULTS: During the intervention period, 18 of the 48 COB census tracts received targeted BOG. Among these, a significant change in the slope between pre- and post-BOG daily test counts was observed in 5 tracts, 80% (n=4) of which had a positive slope change. A positive slope change implied a significant increase in daily COVID-19 test counts 2 weeks after targeted BOG compared to the testing trend observed 2 weeks before intervention. In an additional analysis of the 30 census tracts that did not receive targeted BOG, significant slope changes were observed in 10 tracts, of which positive slope changes were only observed in 20% (n=2). In summary, we found that BOG-targeted tracts had mostly positive daily COVID-19 test count slope changes, whereas untargeted tracts had mostly negative daily COVID-19 test count slope changes. CONCLUSIONS: Evaluation of spatially targeted community interventions is necessary to strengthen the evidence base of this important approach for local emergency preparedness. This report highlights how an academic-agency collaboration established and evaluated the impact of a real-time, targeted intervention delivering precision public health to a small community.

Sex-specific associations between adipokine profiles and carotid-intima media thickness in the Cameron County Hispanic Cohort (CCHC).

BACKGROUND: Adipokines are hormones secreted from adipose tissue and are associated with cardiometabolic diseases (CMD). Functional differences between adipokines (leptin, adiponectin, and resistin) are known, but inconsistently reported associations with CMD and lack of studies in Hispanic populations are research gaps. We investigated the relationship between subclinical atherosclerosis and multiple adipokine measures. METHODS: Cross-sectional data from the Cameron County Hispanic Cohort (N = 624; mean age = 50; Female = 70.8%) were utilized to assess associations between adipokines [continuous measures of adiponectin, leptin, resistin, leptin-to-adiponectin ratio (LAR), and adiponectin-resistin index (ARI)] and early atherosclerosis [carotid-intima media thickness (cIMT)]. We adjusted for sex, age, body mass index (BMI), smoking status, cytokines, fasting blood glucose levels, blood pressure, lipid levels, and medication usage in the fully adjusted linear regression model. We conducted sexes-combined and sex-stratified analyses to account for sex-specificity and additionally tested whether stratification of participants by their metabolic status (metabolically elevated risk for CMD as defined by having two or more of the following conditions: hypertension, dyslipidemia, insulin resistance, and inflammation vs. not) influenced the relationship between adipokines and cIMT. RESULTS: In the fully adjusted analyses, adiponectin, leptin, and LAR displayed significant interaction by sex (p < 0.1). Male-specific associations were between cIMT and LAR [ß(SE) = 0.060 (0.016), p = 2.52 × 10-4], and female-specific associations were between cIMT and adiponectin [ß(SE) = 0.010 (0.005), p = 0.043] and ARI [ß(SE) = - 0.011 (0.005), p = 0.036]. When stratified by metabolic health status, the male-specific positive association between LAR and cIMT was more evident among the metabolically healthy group [ß(SE) = 0.127 (0.015), p = 4.70 × 10-10] (p for interaction by metabolic health < 0.1). However, the female-specific associations between adiponectin and cIMT and ARI and cIMT were observed only among the metabolically elevated risk group [ß(SE) = 0.014 (0.005), p = 0.012 for adiponectin; ß(SE) = - 0.015 (0.006), p = 0.013 for ARI; p for interaction by metabolic health < 0.1]. CONCLUSION: Associations between adipokines and cIMT were sex-specific, and metabolic health status influenced the relationships between adipokines and cIMT. These heterogeneities by sex and metabolic health affirm the complex relationships between adipokines and atherosclerosis.

The Effect of Volitional Preemptive Abdominal Contraction on Biomechanical Measures During A Front Versus Back Loaded Barbell Squat.

Background: Weightlifting is growing in popularity among recreational and competitive athletes. The barbell back squat (BackS) is commonly included in these training programs, while the barbell front squat (FrontS) is commonly performed as a component of other lifts such as the power clean or clean and jerk, it is less commonly practiced in isolation. Hypothesis/Purpose: The purpose of this study was to examine the effects of VPAC performance on trunk muscle and LE biomechanical responses during loaded BackS versus FrontS in healthy subjects. Study Design: Controlled Laboratory Study. Methods: Healthy male subjects with the ability to perform a sub-maximal loaded barbell squat lift were recruited. Subjects completed informed consent, demographic/medical history questionnaires and an instructional video. Subjects practiced VPAC and received feedback. Surface electromyography (sEMG) electrodes and kinematic markers were applied. Muscles included were the internal oblique (IO), external oblique (EO), rectus abdominis, iliocostalis lumborum (ICL), superficial multifidi, rectus femoris, vastus lateralis, biceps femoris, and gluteus maximus. Maximal voluntary isometric contractions established reference sEMG values. A squat one-rep-max (1RM) was predicted by researchers using a three to five repetition maximum (3RM, 5RM) load protocol. Subjects performed BackS trials at 75% 1RM while FrontS trials were performed at 75% BackS weight, both with and without VPAC. Subjects performed three repetitions of each condition with feet positioned on two adjacent force plates. Significant interactions and main effects were tested using a 2(VPAC strategy) x 2(squat variation) and 2(VPAC strategy) x 2(direction) within-subject repeated measures ANOVAs. Tukey's Post-Hoc tests identified the location of significant differences. Results: Trunk muscle activity was significantly higher during FrontS versus BackS regardless of VPAC condition. (IO: p=0.018, EO: p<0.001, ICL: p<0.001) VPAC increased performance time for both squat variations (p=.0011), which may be associated with decreased detrimental force potential on the lumbar spine and knees. VPAC led to improved ability to maintain a neutral lumbar spine during both squat variations. This finding is associated with decreased detrimental force potential on the lumbar spine. Conclusions: Findings could help guide practitioners and coaches to choose squat variations and incorporate VPAC strategies during their treatments and/or training programs. Level of Evidence: Level 3©The Author(s).

Endothelial Dysfunction and Cardiometabolic Risk Factors in Mexican American Adults: The Cameron County Hispanic Cohort.

Endothelial dysfunction assessed by impaired brachial flow-mediated dilation (FMD) predicts incident cardiovascular disease (CVD). We have previously shown that clustering of diabetes mellitus, obesity, and metabolic syndrome in young Hispanic patients was associated with subclinical atherosclerosis. This study aimed to assess determinants of impaired FMD response (%FMD), an earlier marker of atherosclerosis, in a population-based sample of asymptomatic Mexican Americans. Cardiometabolic biomarkers and FMD were obtained from 960 Cameron County Hispanic Cohort participants. Gender-specific median values of %FMD were used to categorize participants into those with %FMD below or above the median. The sample was further stratified into those younger and older than 55 years. Survey-weighted logistic regression analyses were conducted to evaluate the effects of cardiometabolic biomarkers on the %FMD groups. The low %FMD group was significantly older, had higher visceral adipose tissue, systolic blood pressure, or plasma glucose, and had metabolic syndrome compared with those in the high %FMD group. Multivariable-adjusted age-stratified logistic regression analyses showed that in older participants, male gender (odds ratio [OR] = 2.4 [1.4 to 4.2]) and having hypertension (OR = 2.3 [1.3 to 4.3]) or prediabetes mellitus (OR = 3.4 [1.5 to 7.5]) remained significantly associated with odds of low %FMD. In younger participants, high low-density lipoprotein (OR = 2.8 [1.6 to 4.9]) or having the metabolic syndrome (OR = 1.9 [1.1 to 3.6]) were significantly associated with odds of low %FMD. In conclusion, we found age-dependent associations between cardiometabolic biomarkers and an FMD response below the gender-specific median in a sample composed of Mexican Americans without previous CVD. Targeting specific risk factors by age may mitigate progression to incident CVD in this high-risk racial disparity group.

Challenges and strategies for recruitment of minorities to clinical research and trials.

Minority populations are largely absent from clinical research trials. The neglect of these populations has become increasingly apparent, with escalating cancer burdens and chronic disease. The challenges to recruitment of minorities in the United States are multiple including trust or lack thereof. Keys to successful recruitment are responding to community issues, its history, beliefs, and its social and economic pressures. The strategy we have used in many low-income, sometimes remote, communities is to recruit staff from the same community and train them in the required basic research methods. They are the first line of communication. After our arrival in the Texas Rio Grande Valley in 2001, we applied these principles learned over years of global research, to studies of chronic diseases. Beginning in 2004, we recruited and trained a team of local women who enrolled in a cohort of over five thousand Mexican Americans from randomly selected households. This cohort is being followed, and the team has remained, acquiring not only advanced skills (ultrasound, FibroScan, retinal photos, measures of cognition, etc.) but capacity to derive key health information. Currently, we are participating in multiple funded studies, including an NIH clinical trial, liver disease, obesity, and diabetes using multiomics aimed at developing precision medicine approaches to chronic disease prevention and treatment.

The power of TOPMed imputation for the discovery of Latino-enriched rare variants associated with type 2 diabetes.

AIMS/HYPOTHESIS: The Latino population has been systematically underrepresented in large-scale genetic analyses, and previous studies have relied on the imputation of ungenotyped variants based on the 1000 Genomes (1000G) imputation panel, which results in suboptimal capture of low-frequency or Latino-enriched variants. The National Heart, Lung, and Blood Institute (NHLBI) Trans-Omics for Precision Medicine (TOPMed) released the largest multi-ancestry genotype reference panel representing a unique opportunity to analyse rare genetic variations in the Latino population. We hypothesise that a more comprehensive analysis of low/rare variation using the TOPMed panel would improve our knowledge of the genetics of type 2 diabetes in the Latino population. METHODS: We evaluated the TOPMed imputation performance using genotyping array and whole-exome sequence data in six Latino cohorts. To evaluate the ability of TOPMed imputation to increase the number of identified loci, we performed a Latino type 2 diabetes genome-wide association study (GWAS) meta-analysis in 8150 individuals with type 2 diabetes and 10,735 control individuals and replicated the results in six additional cohorts including whole-genome sequence data from the All of Us cohort. RESULTS: Compared with imputation with 1000G, the TOPMed panel improved the identification of rare and low-frequency variants. We identified 26 genome-wide significant signals including a novel variant (minor allele frequency 1.7%; OR 1.37, p=3.4 × 10-9). A Latino-tailored polygenic score constructed from our data and GWAS data from East Asian and European populations improved the prediction accuracy in a Latino target dataset, explaining up to 7.6% of the type 2 diabetes risk variance. CONCLUSIONS/INTERPRETATION: Our results demonstrate the utility of TOPMed imputation for identifying low-frequency variants in understudied populations, leading to the discovery of novel disease associations and the improvement of polygenic scores. DATA AVAILABILITY: Full summary statistics are available through the Common Metabolic Diseases Knowledge Portal ( https://t2d.hugeamp.org/downloads.html ) and through the GWAS catalog ( https://www.ebi.ac.uk/gwas/ , accession ID: GCST90255648). Polygenic score (PS) weights for each ancestry are available via the PGS catalog ( https://www.pgscatalog.org , publication ID: PGP000445, scores IDs: PGS003443, PGS003444 and PGS003445).

Population-Based Mini-Mental State Examination Norms in Adults of Mexican Heritage in the Cameron County Hispanic Cohort.

BACKGROUND: Accurately identifying cognitive changes in Mexican American (MA) adults using the Mini-Mental State Examination (MMSE) requires knowledge of population-based norms for the MMSE, a scale which has widespread use in research settings. OBJECTIVE: To describe the distribution of MMSE scores in a large cohort of MA adults, assess the impact of MMSE requirements on their clinical trial eligibility, and explore which factors are most strongly associated with their MMSE scores. METHODS: Visits between 2004-2021 in the Cameron County Hispanic Cohort were analyzed. Eligible participants were ≥18 years old and of Mexican descent. MMSE distributions before and after stratification by age and years of education (YOE) were assessed, as was the proportion of trial-aged (50-85- year-old) participants with MMSE <24, a minimum MMSE cutoff most frequently used in Alzheimer's disease (AD) clinical trials. As a secondary analysis, random forest models were constructed to estimate the relative association of the MMSE with potentially relevant variables. RESULTS: The mean age of the sample set (n = 3,404) was 44.4 (SD, 16.0) years old and 64.5% female. Median MMSE was 28 (IQR, 28-29). The percentage of trial-aged participants (n = 1,267) with MMSE <24 was 18.6% overall and 54.3% among the subset with 0-4 YOE (n = 230). The five variables most associated with the MMSE in the study sample were education, age, exercise, C-reactive protein, and anxiety. CONCLUSION: The minimum MMSE cutoffs in most phase III prodromal-to-mild AD trials would exclude a significant proportion of trial-aged participants in this MA cohort, including over half of those with 0-4 YOE.

Prevalence and factors associated with liver fibrosis among first-degree relatives of Mexican Americans with hepatocellular carcinoma.

BACKGROUND AND AIMS: Whether hepatocellular carcinoma (HCC) increases the familial risk for hepatic fibrosis has not been thoroughly explored, particularly in Mexican Americans who are disproportionately affected by obesity and metabolic syndrome. We evaluated the risk of significant hepatic fibrosis in first-degree relatives of Mexican American adults with HCC. METHODS: We performed a cross-sectional analysis of a prospective cohort of Mexican American probands with HCC and first-degree relatives enrolled in the Hispanic Liver Cancer Cohort study. We evaluated the prevalence of hepatic fibrosis in first-degree relatives, defined by liver stiffness measurement (LSM) >= 7.0 kPa with transient elastography (TE). Secondary outcomes included the prevalence of definite hepatic steatosis, defined by controlled attenuation parameter >=288 dB/m. RESULTS: We identified 70 probands diagnosed with HCC; 47% were female and the mean age was 62 years (±13 years). Among 112 first-degree relatives with a mean age of 43 years (±14 years), 19 (17%) had significant fibrosis and 47 (42%) had definite hepatic steatosis, respectively. The prevalence of significant fibrosis was 20% in first-degree relatives 40 years of age or older. Regression analysis revealed that diabetes (OR 3.2, 95% CI: 1.1-9.2, p = 0.03) and aspartate aminotransferase >=30 units/L (OR 4.0, 95% CI: 1.4-11.7, p = 0.01) were predictors of significant fibrosis in first-degree relatives. CONCLUSIONS: Using a well-phenotyped familial cohort, we found that the prevalence of significant fibrosis and definite hepatic steatosis are high in first-degree relatives of Mexican Americans with HCC, particularly those with diabetes, suggesting that this population may benefit from screening for liver disease.

Data Mining Framework for Discovering and Clustering Phenotypes of Atypical Diabetes.

CONTEXT: Some individuals present with forms of diabetes that are "atypical" (AD), which do not conform to typical features of either type 1 diabetes (T1D) or type 2 diabetes (T2D). These forms of AD display a range of phenotypic characteristics that likely reflect different endotypes based on unique etiologies or pathogenic processes. OBJECTIVE: To develop an analytical approach to identify and cluster phenotypes of AD. METHODS: We developed Discover Atypical Diabetes (DiscoverAD), a data mining framework, to identify and cluster phenotypes of AD. DiscoverAD was trained against characteristics of manually classified patients with AD among 278 adults with diabetes within the Cameron County Hispanic Cohort (CCHC) (Study A). We then tested DiscoverAD in a separate population of 758 multiethnic children with T1D within the Texas Children's Hospital Registry for New-Onset Type 1 Diabetes (TCHRNO-1) (Study B). RESULTS: We identified an AD frequency of 11.5% in the CCHC (Study A) and 5.3% in the pediatric TCHRNO-1 (Study B). Cluster analysis identified 4 distinct groups of AD in Study A: cluster 1, positive for the 65 kDa glutamate decarboxylase autoantibody (GAD65Ab), adult-onset, long disease duration, preserved beta-cell function, no insulin treatment; cluster 2, GAD65Ab negative, diagnosed at age ≤21 years; cluster 3, GAD65Ab negative, adult-onset, poor beta-cell function, lacking central obesity; cluster 4, diabetic ketoacidosis (DKA)-prone participants lacking a typical T1D phenotype. Applying DiscoverAD to the pediatric patients with T1D in Study B revealed 2 distinct groups of AD: cluster 1, autoantibody negative, poor beta-cell function, lower body mass index (BMI); cluster 2, autoantibody positive, higher BMI, higher incidence of DKA. CONCLUSION: DiscoverAD can be adapted to different datasets to identify and define phenotypes of participants with AD based on available clinical variables.

Genetic variants associated with circulating liver injury markers in Mexican Americans, a population at risk for non-alcoholic fatty liver disease.

Objective: Mexican Americans are disproportionally affected by non-alcoholic fatty liver disease (NAFLD), liver fibrosis and hepatocellular carcinoma. Noninvasive means to identify those in this population at high risk for these diseases are urgently needed. Approach: The Cameron County Hispanic Cohort (CCHC) is a population-based cohort with high rates of obesity (51%), type 2 diabetes (28%) and NAFLD (49%). In a subgroup of 564 CCHC subjects, we evaluated 339 genetic variants previously reported to be associated with liver injury markers aspartate aminotransferase (AST) and alanine aminotransferase (ALT) in United Kingdom and Japanese cohorts. Results: Association was confirmed for 86 variants. Among them, 27 had higher effect allele frequency in the CCHC than in the United Kingdom and Japanese cohorts, and 16 had stronger associations with AST and ALT than rs738409 (PNPLA3). These included rs17710008 (MYCT1), rs2519093 (ABO), rs1801690 (APOH), rs10409243 (S1PR2), rs1800759 (LOC100507053) and rs2491441 (RGL1), which were also associated with steatosis and/or liver fibrosis measured by vibration-controlled transient elastography. Main contributors to advanced fibrosis risk were rs11240351 (CNTN2), rs1800759 (LOC100507053), rs738409 (PNPLA3) and rs1801690 (APOH), with advanced fibrosis detected in 37.5% of subjects with 3 of these 4 variants [AOR = 11.6 (95% CI) = 3.8-35.3]. AST- and ALT-associated variants implicated distinct pathways (ethanol and galactose degradation versus antigen presentation and B cell development). Finally, 8 variants, including rs62292950 (DNAJC13), were associated with gut microbiome changes. Conclusion: These genotype-phenotype findings may have utility in risk modeling and disease prevention in this high-risk population.

Participant engagement in a community health worker-delivered intervention and type 2 diabetes clinical outcomes: a quasiexperimental study in MexicanAmericans.

OBJECTIVES: This study helps to fill the existing research gap related to participant engagement in behavioural interventions and diabetes management. We examined type 2 diabetes control over time among Mexican Americans by level of engagement in a chronic care management (CCM) program that included community health worker (CHW)-delivered multilevel interventions. The programme complemented clinical care and promoted behaviour changes to improve diabetes self-management. DESIGN: Quasiexperimental study. SETTING: The study was implemented in the Rio Grande Valley region in the USA. Recruitment was conducted in clinics and community events. All other visits were provided in participant homes and community locations. PARTICIPANTS: 5649 adults (aged ≥18 years) with poorly controlled type 2 diabetes who enrolled in a community-delivered CCM programme between September 2013 and 2018. INTERVENTIONS: The intervention comprised two components: CHW home visits conducted every 3 months and diabetes self-management education (DSME) classes provided in community locations. PRIMARY OUTCOME MEASURES: The primary outcome was haemoglobin A1c (HbA1c) measured at baseline every 3 months for up to 24 months. We first examined changes in HbA1c levels over time. The number of completed CHW and DSME encounters was used to classify participants into engagement groups-high engagement defined as ≥10 encounters (n=2952); low engagement defined as 1-9 encounters (n=2697). We used univariable and multivariable longitudinal linear regression models with a generalised estimating equation method. We tested interactions between engagement groups and time. RESULTS: Participants' mean HbA1c decreased from 10.20% at baseline to 8.93% (p<0.0001) at 3 months, remaining stable thereafter. Changes in HbA1c were statistically different between the engagement groups. High engagement participants had lower HbA1c levels over the first 15 months of the follow-up period compared with low engagement participants, as compared at 3 months (-0.44%, 95% CI -0.57% to -0.31%; p<0.0001), 6 months (-0.31%, 95% CI -0.43% to -0.14%; p<0.0001), 9 months (-0.27%, 95% CI -0.42% to -0.13%; p=0.0001), 12 months (-0.23%, 95% CI -0.37% to -0.08%; p=0.0025) and 15 months (-0.32%, 95% CI -0.54% to -0.10%; p=0.0040). At months 18, 21 and 24, the HbA1c differences were not statistically significant (18 months: -0.34%, 95% CI -0.77% to 0.08%; p=0.1086; 21 months: -0.22%, 95% CI -1.00% to 0.56%; p=0.5721; 24 months: -0.42%, 95% CI -1.38% to 0.55%; p=0.3966). CONCLUSIONS: Higher engagement in the CCM programme delivered by CHWs and coordinated with clinical care was associated with beneficial improvements in type 2 diabetes control, but both engagement groups showed strong improvements.

Genetic pleiotropy underpinning adiposity and inflammation in self-identified Hispanic/Latino populations.

BACKGROUND: Concurrent variation in adiposity and inflammation suggests potential shared functional pathways and pleiotropic disease underpinning. Yet, exploration of pleiotropy in the context of adiposity-inflammation has been scarce, and none has included self-identified Hispanic/Latino populations. Given the high level of ancestral diversity in Hispanic American population, genetic studies may reveal variants that are infrequent/monomorphic in more homogeneous populations. METHODS: Using multi-trait Adaptive Sum of Powered Score (aSPU) method, we examined individual and shared genetic effects underlying inflammatory (CRP) and adiposity-related traits (Body Mass Index [BMI]), and central adiposity (Waist to Hip Ratio [WHR]) in HLA participating in the Population Architecture Using Genomics and Epidemiology (PAGE) cohort (N = 35,871) with replication of effects in the Cameron County Hispanic Cohort (CCHC) which consists of Mexican American individuals. RESULTS: Of the > 16 million SNPs tested, variants representing 7 independent loci were found to illustrate significant association with multiple traits. Two out of 7 variants were replicated at statistically significant level in multi-trait analyses in CCHC. The lead variant on APOE (rs439401) and rs11208712 were found to harbor multi-trait associations with adiposity and inflammation. CONCLUSIONS: Results from this study demonstrate the importance of considering pleiotropy for improving our understanding of the etiology of the various metabolic pathways that regulate cardiovascular disease development.