Variation in the fat mass and obesity associated (FTO) gene has been reproducibly associated with body mass index (BMI) and obesity in populations of White European origin. Data from Asians and African-Americans is less conclusive. We assessed the effect of 16 FTO polymorphisms on body mass in a large population of predominantly lean Gambians (N_max 2208) participating in a long-term surveillance program providing contemporary and early-life anthropometric measurements. Sixteen FTO tagSNPs screened here, including several associated with BMI in Europeans, were not associated with birth weight (BWT), early weight gain in 1–2 year olds, BMI in adults (≥ 18 y), or weight-for-height (WFH) z-score across all ages. No association was seen between genotype and WFH z-score or other measures of body mass. The confidence limits indicate that the effect size for WFH z-score never exceeded 0.17 units per allele copy for any SNP (excluding the three SNPs with allele < 15%). with much the lowest allele frequency. The confidence interval of the effect size for rs9939609 did not overlap that reported previously in Europeans. To our knowledge this is the first study of FTO gene variation in a well-characterised African population. Our results suggest that FTO gene variation does not influence measures of body mass in Gambians living a traditional lifestyle, or has a smaller effect than that detected in Europeans. These findings are not directly comparable to results from previous studies in African-Americans due to differences in study design and analysis. It is also possible that any effect of FTO genotype on body mass is of limited relevance in a lean population where little excess food is available, compared to similar ethnic populations where food supply is plentiful.

Aminoglycosides are a critical component of multidrug-resistant tuberculosis (MDR-TB) treatment but data on their efficacy and adverse effects in Botswana is scarce. We determined the effect of amikacin on treatment outcomes and development of hearing loss in MDR-TB patients. Patients started on MDR-TB treatment between 2006 and 2012 were included. Multivariate analysis was used to determine the effect of amikacin on treatment outcomes and development of hearing loss. 437 MDR-TB patients were included, 288 (66%) of whom were HIV co-infected. 270 (62%) developed hearing loss, of whom 147 (54%) had audiometry. Of the 313 (72%) patients who completed treatment, 228 (73%) had a good outcome (cure or treatment completion). Good outcome was associated with longer amikacin treatment (adjusted OR [aOR] 1.13, 95% CI 1.06 - 1.21) and higher dosage (aOR 1.90, 95% CI 1.12 – 2.99). Longer amikacin duration (aOR 1.98, 95% CI 1.86 – 2.12) and higher dosage per weight per month (aOR 1.15, 95% CI 1.04 – 1.28) were associated with development of hearing loss. Amikacin treatment duration modified the effect of the dosage on the risk of hearing loss, increasing this risk as the duration increased. Amikacin was effective for MDR-TB treatment, but was associated with a high incidence of hearing loss especially in our study population. Total treatment duration and average monthly amikacin dose were associated with improved outcomes; however these were also associated with development of hearing loss.

The two major class A scavenger receptors are scavenger receptor A (SRA), which is constitutively expressed on most macrophage populations, and macrophage receptor with collagenous structure (MARCO), which is constitutively expressed on a more restricted subset of macrophages, (e.g. alveolar macrophages) but whose expression increases on most macrophages during the course of infection. Although the primary role of SRA appears to be clearance of modified host proteins and lipids, mice defective in expression of either MARCO or SRA are immunocompromised in multiple models of infection and in vitro assays, the scavenger receptors have been demonstrated to bind bacteria and to enhance pro-inflammatory signalling to many bacterial lung pathogens; however their importance in Mycobacterium tuberculosis infection, is less clear. To determine whether polymorphisms in either SRA or MARCO were associated with tuberculosis, a case–control study of was performed. DNA samples from newly-detected, smear-positive, pulmonary tuberculosis cases were collected from The Gambia. Controls for this study consisted of DNA from cord bloods obtained from routine births at local Gambian health clinics. Informed written consent was obtained from patients or their parents or guardians. Ethical approval was provided by the joint The Gambian Government/MRC Joint Ethics Committee. We studied the frequencies of 25 polymorphisms of MSR1 (SRA) and 22 in MARCO in individuals with tuberculosis (n=1284) and matched controls (n=1349). No SNPs within the gene encoding or within 1 kb of the promoter sequence of MSR1 were associated with either susceptibility or resistance to tuberculosis. Three SNPs in MARCO (rs4491733, Mantel-Haenszel 2x2 χ2 = 6.5, p = 0.001, rs12998782, Mantel-Haenszel 2x2 χ2 = 6.59, p = 0.001, rs13389814 Mantel-Haenszel 2x2 χ2 = 6.9, p = 0.0009) were associated with susceptibility to tuberculosis and one (rs7559955, Mantel-Haenszel 2x2 χ2 = 6.9, p = 0.0009) was associated with resistance to tuberculosis. These findings identify MARCO as a potentially important receptor in the host response to tuberculosis.

Background: Identifying high-order genetics associations with non-additive (i.e. epistatic) effects in population-based studies of common human diseases is a computational challenge. Multifactor dimensionality reduction (MDR) is a machine learning method that was designed specifically for this problem. The goal of the present study was to apply MDR to mining high-order epistatic interactions in a population-based genetic study of tuberculosis (TB). Results: The study used a previously published data set consisting of 19 candidate single-nucleotide polymorphisms (SNPs) in 321 pulmonary TB cases and 347 healthy controls from Guniea-Bissau in Africa. The ReliefF algorithm was applied first to generate a smaller set of the five most informative SNPs. MDR with 10-fold cross-validation was then applied to look at all possible combinations of two, three, four and five SNPs. The MDR model with the best testing accuracy (TA) consisted of SNPs rs2305619, rs187084, and rs11465421 (TA = 0.588) in PTX3, TLR9 and DC-Sign, respectively. A general 1000-fold permutation test of the null hypothesis of no association confirmed the statistical significance of the model (p = 0.008). An additional 1000-fold permutation test designed specifically to test the linear null hypothesis that the association effects are only additive confirmed the presence of non-additive (i.e. nonlinear) or epistatic effects (p = 0.013). An independent information-gain measure corroborated these results with a third-order epistatic interaction that was stronger than any lower-order associations. Conclusions: We have identified statistically significant evidence for a three-way epistatic interaction that is associated with susceptibility to TB. This interaction is stronger than any previously described one-way or two-way associations. This study highlights the importance of using machine learning methods that are designed to embrace, rather than ignore, the complexity of common diseases such as TB. We recommend future studies of the genetics of TB take into account the possibility that high-order epistatic interactions might play an important role in disease susceptibility.

The association between volatile compounds (VCs) and microorganisms, as demonstrated by several studies, may offer the ground for a rapid identification of pathogens. To this regard, chemical sensors are a key enabling technology for the exploitation of this opportunity. In this study, we investigated the performance of an array of porphyrin-coated quartz microbalance gas sensors in the identification of a panel of 12 bacteria and fungi. The porphyrins were metal complexes and the free base of a functionalized tetraphenylporphyrin. Our results show that the sensor array distinguishes the VC patterns produced by microorganisms in vitro. Besides being individually identified, bacteria are also sorted into Gram-positive and Gram-negative.