Genome-wide meta-analysis identifies regions on 7p21 (AHR) and 15q24 (CYP1A2) as determinants of habitual caffeine consumption

We report the first genome-wide association study of habitual caffeine intake. We included 47,341 individuals of European descent based on five population-based studies within the United States. In a meta-analysis adjusted for age, sex, smoking, and eigenvectors of population variation, two loci achieved genome-wide significance: 7p21 (P = 2.4 × 10(-19)), near AHR, and 15q24 (P = 5.2 × 10(-14)), between CYP1A1 and CYP1A2. Both the AHR and CYP1A2 genes are biologically plausible candidates as CYP1A2 metabolizes caffeine and AHR regulates CYP1A2.     

Comprehensive evaluation of one-carbon metabolism pathway gene variants and renal cell cancer risk

Introduction

Folate and one-carbon metabolism are linked to cancer risk through their integral role in DNA synthesis and methylation. Variation in one-carbon metabolism genes, particularly MTHFR, has been associated with risk of a number of cancers in epidemiologic studies, but little is known regarding renal cancer.

Methods

Tag single nucleotide polymorphisms (SNPs) selected to produce high genomic coverage of 13 gene regions of one-carbon metabolism (ALDH1L1, BHMT, CBS, FOLR1, MTHFR, MTR, MTRR, SHMT1, SLC19A1, TYMS) and the closely associated glutathione synthesis pathway (CTH, GGH, GSS) were genotyped for 777 renal cell carcinoma (RCC) cases and 1,035 controls in the Central and Eastern European Renal Cancer case-control study. Associations of individual SNPs (n = 163) with RCC risk were calculated using unconditional logistic regression adjusted for age, sex and study center. Minimum p-value permutation (Min-P) tests were used to identify gene regions associated with risk, and haplotypes were evaluated within these genes.

Results

The strongest associations with RCC risk were observed for SLC19A1 (P_min-P = 0.03) and MTHFR (P_min-P = 0.13). A haplotype consisting of four SNPs in SLC19A1 (rs12483553, rs2838950, rs2838951, and rs17004785) was associated with a 37% increased risk (p = 0.02), and exploratory stratified analysis suggested the association was only significant among those in the lowest tertile of vegetable intake.

Conclusions

To our knowledge, this is the first study to comprehensively examine variation in one-carbon metabolism genes in relation to RCC risk. We identified a novel association with SLC19A1, which is important for transport of folate into cells. Replication in other populations is required to confirm these findings.     

Sources of Variability in Metabolite Measurements from Urinary Samples

Background

The application of metabolomics in epidemiological studies would potentially allow researchers to identify biomarkers associated with exposures and diseases. However, within-individual variability of metabolite levels caused by temporal variation of metabolites, together with technical variability introduced by laboratory procedures, may reduce the study power to detect such associations. We assessed the sources of variability of metabolites from urine samples and the implications for designing epidemiologic studies.

Methods

We measured 539 metabolites in urine samples from the Navy Colon Adenoma Study using liquid chromatography-mass spectrometry (LC-MS) and gas chromatography-mass spectroscopy (GC-MS). The study collected 2–3 samples per person from 17 male subjects (age 38–70) over 2–10 days. We estimated between-individual, within-individual, and technical variability and calculated expected study power with a specific focus on large case-control and nested case-control studies.

Results

Overall technical reliability was high (median intraclass correlation = 0.92), and for 72% of the metabolites, the majority of total variance can be attributed to between-individual variability. Age, gender and body mass index explained only a small proportion of the total metabolite variability. For a relative risk (comparing upper and lower quartiles of “usual” levels) of 1.5, we estimated that a study with 500, 1,000, and 5,000 individuals could detect 1.0%, 4.5% and 75% of the metabolite associations.

Conclusions

The use of metabolomics in urine samples from epidemiological studies would require large sample sizes to detect associations with moderate effect sizes.     

Human metabolic correlates of body mass index

A high body mass index (BMI) is a major risk factor for several chronic diseases, but the biology underlying these associations is not well-understood. Dyslipidemia, inflammation, and elevated levels of growth factors and sex steroid hormones explain some of the increased disease risk, but other metabolic factors not yet identified may also play a role. In order to discover novel metabolic biomarkers of BMI, we used non-targeted metabolomics to assay 317 metabolites in blood samples from 947 participants and examined the cross-sectional associations between metabolite levels and BMI. Participants were from three studies in the United States and China. Height, weight, and potential confounders were ascertained by questionnaire (US studies) or direct measurement (Chinese study). Metabolite levels were measured using liquid-phase chromatography and gas chromatography coupled with mass spectrometry. We evaluated study-specific associations using linear regression, adjusted for age, gender, and smoking, and we estimated combined associations using random effects meta-analysis. The meta-analysis revealed 37 metabolites significantly associated with BMI, including 19 lipids, 12 amino acids, and 6 others, at the Bonferroni significance threshold (P < 0.00016). Eighteen of these associations had not been previously reported, including histidine, an amino acid neurotransmitter, and butyrylcarnitine, a lipid marker of whole-body fatty acid oxidation. Heterogeneity by study was minimal (all P _{heterogeneity} > 0.05). In total, 110 metabolites were associated with BMI at the P < 0.05 level. These findings establish a baseline for the BMI metabolome, and suggest new targets for researchers attempting to clarify mechanistic links between BMI and disease risk.     

Serum pepsinogen level,atrophic gastritis and the risk of incident pancreatic cancer—A prospective cohort study

Background: Pancreatic cancer is a highly fatal disease without screening tests. Studies have suggested possible etiologic similarities between gastric and pancreatic cancers. Atrophic gastritis, a pre-malignant condition for gastric cancer, is characterized by low serum pepsinogen I (SPGI) level. We hypothesized that low SPGI level may be associated with an increased risk of pancreatic cancer and be a useful biomarker for the disease. Methods: Our analytic cohort included 20,962 participants in the Alpha-Tocopherol, Beta-Carotene Cancer Prevention Study (ATBC) who had SPGI level measured. Of these, 1663 (7.9%) subjects had low SPGI levels (<25 μg/l) and were invited for gastroscopy which was completed in 1059 (63.7%) participants. Atrophic gastritis was histologically confirmed in 1006 (95.0%) subjects. We used Cox proportional hazards regression to calculate the hazard ratios (HR) and 95% confidence intervals (CI) for pancreatic cancer. Results: During follow-up of up to 16.3 years (mean = 10.8 years; 226,325 person-years), 227 incident pancreatic cancers were diagnosed. The incidence rates were 9.9, 11.3, and 12.7 per 10,000 person-years of follow-up for participants with normal pepsinogen level (≥25 μg/l), low pepsinogen level and histologically confirmed atrophic gastritis, respectively. Compared to subjects with normal pepsinogen levels, there was no statistically significant increased risk of pancreatic cancer among subjects with low pepsinogen level (adjusted HR = 1.01; 95% CI: 0.63–1.62) or those with histologically confirmed atrophic gastritis (adjusted HR = 1.13; 95% CI: 0.66–1.95). Conclusions: Atrophic gastritis, serological or histological, is not associated with increased risk of pancreatic cancer. These findings do not provide any evidence for potential usefulness of SPGI for pancreatic cancer screening.     

Comparison of different delivery systems of DNA vaccination for the induction of protection against tuberculosis in mice and guinea pigs

The great challenges for researchers working in the field of vaccinology are optimizing DNA vaccines for use in humans or large animals and creating effective single-dose vaccines using appropriated controlled delivery systems. Plasmid DNA encoding the heat-shock protein 65 (hsp65) (DNAhsp65) has been shown to induce protective and therapeutic immune responses in a murine model of tuberculosis (TB). Despite the success of naked DNAhsp65-based vaccine to protect mice against TB, it requires multiple doses of high amounts of DNA for effective immunization. In order to optimize this DNA vaccine and simplify the vaccination schedule, we coencapsulated DNAhsp65 and the adjuvant trehalose dimycolate (TDM) into biodegradable poly (DL-lactide-co-glycolide) (PLGA) microspheres for a single dose administration. Moreover, a single-shot prime-boost vaccine formulation based on a mixture of two different PLGA microspheres, presenting faster and slower release of, respectively, DNAhsp65 and the recombinant hsp65 protein was also developed. These formulations were tested in mice as well as in guinea pigs by comparison with the efficacy and toxicity induced by the naked DNA preparation or BCG. The single-shot prime-boost formulation clearly presented good efficacy and diminished lung pathology in both mice and guinea pigs.