Polymorphisms in the Gene That Encodes the Iron Transport Protein Ferroportin 1 Influence Susceptibility to Tuberculosis

Background: We studied the association between iron intake and polymorphisms in the iron transporter gene, SLC40A1, and the risk of tuberculosis. Methods: We compared iron intake, the frequency of SLC40A1 mutations, and interactions between these variables among 98 TB patients and 125 controls in Kwazulu-Natal, South Africa. Results: Four SLC40A1 SNPs were associated with an increased risk of tuberculosis and one with reduced risk. We also found a gene-environment interaction for four non-exonic SNPs and iron intake. Conclusions: This pilot study demonstrated an association between polymorphisms in SLC40A1 and tuberculosis and provided evidence for an interaction between dietary iron and SLC40A1.Organismic and Evolutionary Biolog

The Transcriptional Regulator Rv0485 Modulates the Expression of a pe and ppe Gene Pair and Is Required for Mycobacterium tuberculosis Virulence▿ §

The pe and ppe genes are unique to mycobacteria and are widely speculated to play a role in tuberculosis pathogenesis. However, little is known about how expression of these genes is controlled. Elucidating the regulatory control of genes found exclusively in mycobacteria, such as the pe and ppe gene families, may be key to understanding the success of this pathogen. In this study, we used a transposon mutagenesis approach to elucidate pe and ppe regulation. This resulted in the identification of Rv0485, a previously uncharacterized transcriptional regulator. Microarray and quantitative real-time PCR analysis confirmed that disruption of Rv0485 reduced the expression of the pe13 and ppe18 gene pair (Rv1195 and Rv1196), defined the Rv0485 regulon, and emphasized the lack of global regulation of pe and ppe genes. The in vivo phenotype of the Rv0485 transposon mutant strain (Rv0485::Tn) was investigated in the mouse model, where it was demonstrated that the mutation has minimal effect on bacterial organ burden. Despite this, disruption of Rv0485 allowed mice to survive for significantly longer, with substantially reduced lung pathology in comparison with mice infected with wild-type Mycobacterium tuberculosis. Infection of immune-deficient SCID mice with the Rv0485::Tn strain also resulted in extended survival times, suggesting that Rv0485 plays a role in modulation of innate immune responses. This is further supported by the finding that disruption of Rv0485 resulted in reduced secretion of proinflammatory cytokines by infected murine macrophages. In summary, we have demonstrated that disruption of a previously uncharacterized transcriptional regulator, Rv0485, results in reduced expression of pe13 and ppe18 and attenuation of M. tuberculosis virulence

Biogeographic Ancestry Is Associated with Higher Total Body Adiposity among African-American Females: The Boston Area Community Health Survey

Objectives: The prevalence of obesity is disproportionately higher among African-Americans and Hispanics as compared to whites. We investigated the role of biogeographic ancestry (BGA) on adiposity and changes in adiposity in the Boston Area Community Health Survey. Methods: We evaluated associations between BGA, assessed via Ancestry Informative Markers, and adiposity (body mass index (BMI), percent body fat (PBF), and waist-to-hip ratio (WHR)) and changes in adiposity over 7 years for BMI and WHR and 2.5 years for PBF, per 10% greater proportion of BGA using multivariable linear regression. We also examined effect-modification by demographic and socio-behavioral variables. Results: We observed positive associations between West-African ancestry and cross-sectional BMI (percent difference=0.62%; 95% CI: 0.04%, 1.20%), and PBF (β=0.35; 95% CI: 0.11, 0.58). We also observed significant effect-modification of the association between West-African ancestry and BMI by gender (p-interaction: <0.002) with a substantially greater association in women. We observed no main associations between Native-American ancestry and adiposity but observed significant effect-modification of the association with BMI by diet (p-interaction: <0.003) with inverse associations among participants with higher Healthy Eating Scores. No associations were observed between BGA and changes in adiposity over time. Conclusion: Findings support that West-African ancestry may contribute to high prevalence of total body adiposity among African-Americans, particularly African-American women

Associations between West-African and Native-American genetic ancestry and adiposity, stratified by gender and Healthy Eating Score.

<p>^<i>a</i><i>Models additionally adjusted for age</i>, <i>income</i>, <i>education</i>, <i>healthy eating score (HE Score)</i>, <i>physical activity</i>, <i>caloric intake</i>, <i>and occupation;</i></p><p>^<i>b</i><i>models additionally adjusted for age</i>, <i>gender</i>, <i>income</i>, <i>education</i>, <i>physical activity</i>, <i>caloric intake</i>, <i>and occupation; CI = confidence interval; HE Score = Healthy Eating Score; int</i>. <i>= interaction; referent = European Ancestral Markers</i>: <i>percent change in BMI = 0</i>.<i>0000; WHR = 0</i>.<i>0000</i>, <i>PBF = 0</i>.<i>0000;</i></p><p>^<i>*</i><i>significant at p<0</i>.<i>005;</i></p><p>^<i>**</i><i>significant at p<0</i>.<i>0005</i>.</p><p>Associations between West-African and Native-American genetic ancestry and adiposity, stratified by gender and Healthy Eating Score.</p

Multivariable results for cross-sectional BMI (N = 1726).

<p><i>*Models adjusted for age</i>, <i>gender</i>, <i>income</i>, <i>education</i>, <i>healthy eating score</i>, <i>physical activity</i>, <i>caloric intake</i>, <i>occupation</i>, <i>and ancestry</i>.</p><p>Multivariable results for cross-sectional BMI (N = 1726).</p

Associations between genetic ancestry (per 10% greater proportion of BGA) and BMI, WHR and PBF (N = 1726).

<p>^<i>a</i><i>Univariate analysis;</i></p><p>^<i>b</i><i>Adjusted for age and gender only;</i></p><p>^<i>c</i><i>Adjusted for age</i>, <i>gender</i>, <i>income</i>, <i>education</i>, <i>healthy eating score</i>, <i>physical activity</i>, <i>caloric intake</i>, <i>and occupation; CI = confidence interval; β = effect estimate for log BMI</i>, <i>or WHR or PBF;</i></p><p>^<i>d</i><i>44% decrease in effect estimate was mostly due to adjustment for educational level and income;</i></p><p>^<i>e</i><i>30% decrease in effect estimate was mostly due to adjustment for educational level;</i></p><p><i>*significant at p<0</i>.<i>005;</i></p><p><i>**significant at p<0</i>.<i>0005</i>.</p><p>Associations between genetic ancestry (per 10% greater proportion of BGA) and BMI, WHR and PBF (N = 1726).</p

Characteristics of the overall population and by self-identified race/ethnicity.

<p>^<i>a</i><i>Mean sample size for 15 datasets; total counts may not always add up as numbers were not the same for all 15 data sets (the number deleted was based on imputed values for each data set); the percentages may not add up to 100% due to rounding;</i></p><p>^<i>b</i><i>means and percentages are weighted;</i></p><p>^<i>c</i><i>data not available for 533 participants;</i></p><p>^<i>d</i><i>between BACH I and III</i>,</p><p>^<i>e</i><i>between BACH II and III; CI = confidence interval; p25 = lower quartile; p75 = upper quartile</i>.</p><p>Characteristics of the overall population and by self-identified race/ethnicity.</p