Linkage Analysis of Plasma ApoE in Three Ethnic Groups: Multiple Genes with Context-Dependent Effects

We performed variance component-based linkage analysis in four samples (two of non-Hispanic European-Americans from Rochester, MN; African-Americans from Jackson, MS; and Mexican-Americans from Starr County, TX) to identify chromosomal regions containing genes influencing plasma apolipoprotein E (apoE) levels. The APOE gene region on chromosome (chr) 19 was identified with a LOD ≥ 2.00 in both samples from Rochester and the sample from Jackson. Adjustment of apoE levels for differences among means of genotypes defined by the APOE ε2/3/4 alleles reduced evidence of linkage, indicating that the APOE gene was responsible for the majority of the linkage signal. In stratified linkage analyses, there was a LOD of 1.70 in the Starr County sibships with average total cholesterol (TC) above the median level for all sibships in that population. Adjustment for APOE genotype did not remove this LOD score, suggesting a second gene in this region may influence apoE variation. Evidence of linkage ( LOD = 3.32) on chr 17 was observed in the Starr County sibships with average TC below the median. Inter-individual variation in plasma apoE level may be influenced by variations in the structural gene, and at least one other gene whose effects differ among populations and are dependent on the influence of unmeasured genetic and environmental factors indexed by correlated measures of lipid metabolism.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/66071/1/j.1469-1809.2004.00148.x.pd

The Impact of the Th17:Treg axis On the Iga-Biome across the Glycemic Spectrum

Secretory IgA (SIgA) is released into mucosal surfaces where its function extends beyond that of host defense to include the shaping of resident microbial communities by mediating exclusion/inclusion of respective microbes and regulating bacterial gene expression. In this capacity, SIgA acts as the fulcrum on which host immunity and the health of the microbiota are balanced. We recently completed an analysis of the gut and salivary IgA-Biomes (16S rDNA sequencing of SIgA-coated/uncoated bacteria) in Mexican-American adults that identified IgA-Biome differences across the glycemic spectrum. As Th17:Treg ratio imbalances are associated with gut microbiome dysbiosis and chronic inflammatory conditions such as type 2 diabetes, the present study extends our prior work by examining the impact of Th17:Treg ratios (pro-inflammatory:anti-inflammatory T-cell ratios) and the SIgA response (Th17:Treg-SIgA axis) in shaping microbial communities. Examining the impact of Th17:Treg ratios (determined by epigenetic qPCR lymphocyte subset quantification) on the IgA-Biome across diabetes phenotypes identified a proportional relationship between Th17:Treg ratios and alpha diversity in the stool IgA-Biome of those with dysglycemia, significant changes in community composition of the stool and salivary microbiomes across glycemic profiles, and genera preferentially abundant by T-cell inflammatory phenotype. This is the first study to associate epigenetically quantified Th17:Treg ratios with both the larger and SIgA-fractionated microbiome, assess these associations in the context of a chronic inflammatory disease, and offers a novel frame through which to evaluate mucosal microbiomes in the context of host responses and inflammation

Worsening Glycemia increases the Odds of intermittent But Not Persistent Staphylococcus aureus Nasal Carriage in Two Cohorts of Mexican american adults

Numerous host and environmental factors contribute to persistent and intermittent nasal Staphylococcus aureus carriage in humans. The effects of worsening glycemia on the odds of S. aureus intermittent and persistent nasal carriage was established in two cohorts from an adult Mexican American population living in Starr County, Texas. The anterior nares were sampled at two time points and the presence of S. aureus determined by laboratory culture an

Epidemiology of antibiotic Use and Drivers of Cross-Border Procurement in a Mexican american Border Community

BACKGROUND: The U.S.-Mexico Border is an area of opportunity for improved health care access; however, gaps remain as to how and where U.S. border residents, particularly those who are underinsured, obtain care. Antibiotics are one of the most common reported drivers of cross-border healthcare access and a medication of particular concern since indiscriminate or inappropriate use is associated with antimicrobial resistance. In addition, many studies assessing preferences for Mexican pharmaceuticals and healthcare in U.S. border residents were done prior to 2010 when many prescription medications, including antibiotics, were available over the counter in Mexico. METHODS: Data used in this study were collected during the baseline examination of an ongoing longitudinal cohort study in Starr Country, Texas, one of 14 counties on the Texas-Mexico border. Participants self-reported the name, date of use, and the source country of each antibiotic used in the past 12 months. Logistic regression was used to determine social, cultural, and clinical features associated with cross-border procurement of antibiotics. RESULTS: Over 10% of the study cohort reported using antibiotics in the past 30 days with over 60% of all rounds used in the past 12 months sourced from Mexico. A lack of health insurance and generation score, a measure of acculturation, were the strongest predictors of cross-border procurement of antibiotics. CONCLUSIONS: Factors previously associated with cross-border acquisition of antibiotics are still present despite changes in 2010 to prescription drug regulations in Mexico. These results may be used to inform future public health initiatives to provide culturally sensitive education about responsible antibiotic stewardship and to address barriers to U.S. healthcare and pharmaceutical access in medically underserved, impoverished U.S.-Mexico border communities

Iga-Biome Profiles Correlate With Clinical Parkinson\u27s Disease Subtypes

BACKGROUND: Parkinson\u27s disease is a heterogeneous neurodegenerative disorder with distinctive gut microbiome patterns suggesting that interventions targeting the gut microbiota may prevent, slow, or reverse disease progression and severity. OBJECTIVE: Because secretory IgA (SIgA) plays a key role in shaping the gut microbiota, characterization of the IgA-Biome of individuals classified into either the akinetic rigid (AR) or tremor dominant (TD) Parkinson\u27s disease clinical subtypes was used to further define taxa unique to these distinct clinical phenotypes. METHODS: Flow cytometry was used to separate IgA-coated and -uncoated bacteria from stool samples obtained from AR and TD patients followed by amplification and sequencing of the V4 region of the 16 S rDNA gene on the MiSeq platform (Illumina). RESULTS: IgA-Biome analyses identified significant alpha and beta diversity differences between the Parkinson\u27s disease phenotypes and the Firmicutes/Bacteroides ratio was significantly higher in those with TD compared to those with AR. In addition, discriminant taxa analyses identified a more pro-inflammatory bacterial profile in the IgA+ fraction of those with the AR clinical subclass compared to IgA-Biome analyses of those with the TD subclass and with the taxa identified in the unsorted control samples. CONCLUSION: IgA-Biome analyses underscores the importance of the host immune response in shaping the gut microbiome potentially affecting disease progression and presentation. In the present study, IgA-Biome analyses identified a unique proinflammatory microbial signature in the IgA+ fraction of those with AR that would have otherwise been undetected using conventional microbiome analysis approaches

Iga-Biome Profiles Correlate With Clinical Parkinson\u27s Disease Subtypes

BACKGROUND: Parkinson\u27s disease is a heterogeneous neurodegenerative disorder with distinctive gut microbiome patterns suggesting that interventions targeting the gut microbiota may prevent, slow, or reverse disease progression and severity. OBJECTIVE: Because secretory IgA (SIgA) plays a key role in shaping the gut microbiota, characterization of the IgA-Biome of individuals classified into either the akinetic rigid (AR) or tremor dominant (TD) Parkinson\u27s disease clinical subtypes was used to further define taxa unique to these distinct clinical phenotypes. METHODS: Flow cytometry was used to separate IgA-coated and -uncoated bacteria from stool samples obtained from AR and TD patients followed by amplification and sequencing of the V4 region of the 16 S rDNA gene on the MiSeq platform (Illumina). RESULTS: IgA-Biome analyses identified significant alpha and beta diversity differences between the Parkinson\u27s disease phenotypes and the Firmicutes/Bacteroides ratio was significantly higher in those with TD compared to those with AR. In addition, discriminant taxa analyses identified a more pro-inflammatory bacterial profile in the IgA+ fraction of those with the AR clinical subclass compared to IgA-Biome analyses of those with the TD subclass and with the taxa identified in the unsorted control samples. CONCLUSION: IgA-Biome analyses underscores the importance of the host immune response in shaping the gut microbiome potentially affecting disease progression and presentation. In the present study, IgA-Biome analyses identified a unique proinflammatory microbial signature in the IgA+ fraction of those with AR that would have otherwise been undetected using conventional microbiome analysis approaches

Missed opportunities for diagnosis and treatment of diabetes, hypertension, and hypercholesterolemia in a Mexican American population, Cameron County Hispanic Cohort, 2003-2008

Introduction Diabetes, hypertension, and hypercholesterolemia are common chronic diseases among Hispanics, a group projected to comprise 30% of the US population by 2050. Mexican Americans are the largest ethnically distinct subgroup among Hispanics. We assessed the prevalence of and risk factors for undiagnosed and untreated diabetes, hypertension, and hypercholesterolemia among Mexican Americans in Cameron County, Texas. Methods We analyzed cross-sectional baseline data collected from 2003 to 2008 in the Cameron County Hispanic Cohort, a randomly selected, community-recruited cohort of 2,000 Mexican American adults aged 18 or older, to assess prevalence of diabetes, hypertension, and hypercholesterolemia; to assess the extent to which these diseases had been previously diagnosed based on self-report; and to determine whether participants who self-reported having these diseases were receiving treatment. We also assessed social and economic factors associated with prevalence, diagnosis, and treatment. Results Approximately 70% of participants had 1 or more of the 3 chronic diseases studied. Of these, at least half had had 1 of these 3 diagnosed, and at least half of those who had had a disease diagnosed were not being treated. Having insurance coverage was positively associated with having the 3 diseases diagnosed and treated, as were higher income and education level. Conclusions Although having insurance coverage is associated with receiving treatment, important social and cultural barriers remain. Failure to provide widespread preventive medicine at the primary care level will have costly consequences

Disorder- and magnetic field-tuned fermionic superconductor-insulator transition in MoN thin films. Transport and STM studies

Superconductor-insulator transition (SIT) driven by disorder and transverse magnetic field has been investigated in ultrathin MoN films by means of transport measurements and scanning tunneling microscopy and spectroscopy. Upon decreasing thickness, the homogeneously disordered films show increasing sheet resistance Rs, shift of the superconducting transition Tc to lower temperatures with the 3 nm MoN being the last superconducting film and thinner films already insulating. Fermionic scenario of SIT is evidenced by applicability of the Finkelsteins model, by the fact that Tc and the superconducting gap are coupled with a constant ratio, and by the spatial homogeneity of the superconducting and electronic characteristics. The logarithmic anomaly found in the tunneling spectra of the non-superconducting films is further enhanced in increased magnetic field due to the Zeeman spin effects driving the system deeper into the insulating state and pointing also to fermionic SIT.Comment: Manuscript (6 Figures) including Supplemental Materials (7 Figures

Electrocardiographic abnormalities among Mexican Americans: Correlations with diabetes, obesity, and the metabolic syndrome

Background: Resting ischemic electrocardiographic abnormalities have been associated with cardiovascular mortality. Simple markers of abnormal autonomic tone have also been associated with diabetes, obesity, and the metabolic syndrome in some populations. Data on these electrocardiographic abnormalities and correlations with coronary risk factors are lacking among Mexican Americans wherein these conditions are prevalent. Objective: This study aimed to evaluate the prevalent resting electrocardiographic abnormalities among community-dwelling Mexican Americans, and correlate these findings with coronary risk factors, particularly diabetes, obesity, and the metabolic syndrome. Methods: Study subjects (n=1280) were drawn from the Cameron County Hispanic Cohort comprised of community-dwelling Mexican Americans living in Brownsville, Texas at the United States-Mexico border. Ischemic electrocardiographic abnormalities were defined as presence of ST/T wave abnormalities suggestive of ischemia, abnormal Q waves, and left bundle branch block. Parameters that reflect autonomic tone, such as heart rate-corrected QT interval and resting heart rate, were also measured. Results: Ischemic electrocardiographic abnormalities were more prevalent among older persons and those with hypertension, diabetes, obesity, and the metabolic syndrome. Subjects in the highest quartiles of QTc interval and resting heart rate were also more likely to be diabetic, hypertensive, obese, or have the metabolic syndrome. Conclusions: Among Mexican Americans, persons with diabetes, obesity, and the metabolic syndrome were more likely to have ischemic electrocardiographic abnormalities, longer QTc intervals, and higher resting heart rates. A resting electrocardiogram can play a complementary role in the comprehensive evaluation of cardiovascular risk in this minority population

A comparison of methods to quantify greenhouse gas emissions of cropping systems in LCA

Carbon dioxide and nitrous oxide are two important greenhouse gases (GHG) released from cropping systems. Their emissions can vary substantially with climate, soil, and crop management. While different methods are available to account for GHG emissions in life cycle assessments (LCA) of crop production, there are no standard procedures. In this study, the objectives were: (i) to compare several methods of estimating CO2 and N2O emissions for a LCA of cropping systems and (ii) to estimate the relative contribution of soil GHG emissions to the overall global warming potential (GWP) using results from a field experiment located in Manitoba, Canada. The methods were: (A) measurements; (B) Tier I and (C) Tier II IPCC (Intergovernmental panel on Climate Change) methodology, (D) a simple carbon model combined with Intergovernmental Panel for Climate Change (IPCC) Tier II methodology for soil N2O emissions, and (E) the DNDC (DeNitrification DeComposition) agroecosystem model. The estimated GWPs (−7.2–17 Mg CO2eq ha−1 y−1; −80 to 600 kg CO2eq GJ−1 y−1) were similar to previous results in North America and no statistical difference was found between GWP based on methods D and E and GWP based on observations. The five methods gave estimates of soil CO2 emissions that were not statistically different from each other, whereas for N2O emissions only DNDC estimates were similar to observations. Across crop types, all methods gave comparable CO2 and N2O emission estimates for perennial and legume crops, but only DNDC gave similar results with respect to observations for both annual and cereal crops. Whilst the results should be confirmed for other locations, the agroecosystem model and method D can be used, at certainly one selected site, in place of observations for estimating GHGs in agricultural LCA