Metabolomics provides a comprehensive assessment of numerous small molecules in biological samples. As it integrates the effects of exogenous exposures, endogenous metabolism, and genetic variation, metabolomics is well-suited for studies examining metabolic profiles associated with a variety of chronic diseases. In this review, we summarize the studies that have characterized the effects of various pre-analytical factors on both targeted and untargeted metabolomic studies involving human plasma, serum, and urine and were published through 14 January 2019. A standardized protocol was used for extracting data from full-text articles identified by searching PubMed and EMBASE. For plasma and serum samples, metabolomic profiles were affected by fasting status, hemolysis, collection time, processing delays, particularly at room temperature, and repeated freeze/thaw cycles. For urine samples, collection time and fasting, centrifugation conditions, filtration and the use of additives, normalization procedures and multiple freeze/thaw cycles were found to alter metabolomic findings. Consideration of the effects of pre-analytical factors is a particularly important issue for epidemiological studies where samples are often collected in nonclinical settings and various locations and are subjected to time and temperature delays prior being to processed and frozen for storage.

Heavy smoking is a strong predictor of nicotine dependence, which is a major impediment to smoking cessation. Although both heavy smoking and nicotine dependence are highly heritable, previous attempts to identify genes influencing these phenotypes have been largely unsuccessful until very recently. We studied 1,452 heavy smokers (defined as smoking at least 30 cigarettes per day for at least 5 years) and 1,395 light smokers (defined as smoking 2-fold. Our findings identify two loci in the CHRNA5-CHRNA3-CHRNB4 gene cluster that predict smoking behavior and provide strong evidence for the involvement of the α5 nicotinic receptor in heavy smoking. (Cancer Epidemiol Biomarkers Prev 2008;17(12):3517–25)

Introduction: Vascular endothelial growth factor (VEGF) plays a central role in promoting angiogenesis and is over-expressed in breast cancer. At least four polymorphisms in the VEGF gene have been associated with changes in VEGF expression levels: -2578C/A, -1154G/A and -634G/C are all located in the promoter region; and +936C/T is located in the 3'-untranslated region. Method: We examined the association between these four VEGF polymorphisms and risk for breast cancer among postmenopausal women in CPS-II (Cancer Prevention Study II) Nutrition Cohort. This cohort was established in 1992 and participants were invited to provide a blood sample between 1998 and 2001. Included in this analysis were 501 postmenopausal women who provided a blood sample and were diagnosed with breast cancer between 1992 and 2001 (cases). Control individuals were 504 cancer-free postmenopausal women matched to the cases with respect to age, race/ethnicity, and date of blood collection (controls). Results: We found no association between any of the polymorphisms examined and overall breast cancer risk. However, associations were markedly different in separate analyses of invasive cancer (n = 380) and in situ cancer (n = 107). The -2578C and -1154G alleles, which are both hypothesized to increase expression of VEGF, were associated with increased risk for invasive breast cancer (odds ratio [OR] 1.46, 95% confidence interval [CI] 1.00–2.14 for -2578 CC versus AA; OR 1.64, 95% CI 1.02–2.64 for -1154 GG versus AA) but they were not associated with risk for in situ cancer. The +936C allele, which is also hypothesized to increase VEGF expression, was not clearly associated with invasive breast cancer (OR 1.21, 95% CI 0.88–1.67 for +936 CC versus TT/CT), but it was associated with reduced risk for in situ cancer (OR 0.59, 95% CI 0.37–0.93 for CC versus TT/CT). The -634 C/G polymorphism was not associated with either invasive or in situ cancer. Conclusion: Our findings provide limited support for the hypothesis that the -2578C and -1154G VEGF alleles are associated with increased risk for invasive but not in situ breast cancer in postmenopausal women.

Introduction: Vitamin D receptor (VDR) polymorphisms have been inconsistently associated with breast cancer risk. Whether risk is influenced by polymorphisms in other vitamin D metabolism genes and whether calcium or vitamin D intake modifies risk by genotype have not been evaluated. Methods: We conducted a nested case-control study within the Cancer Prevention Study II Nutrition Cohort of associations between breast cancer and four VDR single-nucleotide polymorphisms (SNPs), Bsm1,Apa1,Taq1, and Fok1, a poly(A) microsatellite, and associated haplotypes (baTL and BAtS). We also examined one SNP in the 24-hydroxylase gene (CYP24A1) and two in the vitamin D-binding protein (group-specific component [GC]) gene. Participants completed a questionnaire on diet and medical history at baseline in 1992. This study includes 500 postmenopausal breast cancer cases and 500 controls matched by age, race/ethnicity, and date of blood collection. Results: Incident breast cancer was not associated with any genotype examined. However, women with the Bsm1 bb SNP who consumed greater than the median intake of total calcium (≥902 mg/day) had lower odds of breast cancer compared to women with the Bb or BB genotype and less than the median calcium intake (odds ratio 0.61, 95% confidence interval 0.38 to 0.96; p_interaction = 0.01). Similar interactions were observed for Taq1 (T allele) and the poly(A) (LL) repeat. Conclusion: We found no overall association between selected vitamin D pathway genes and postmenopausal breast cancer risk. However, certain VDR gene polymorphisms were associated with lower risk in women consuming high levels of calcium, suggesting that dietary factors may modify associations by VDR genotype.

Genome-wide association studies (GWAS) have identified >300 loci associated with measures of adiposity including body mass index (BMI) and waist-to-hip ratio (adjusted for BMI, WHR_adjBMI), but few have been identified through screening of the African ancestry genomes. We performed large scale meta-analyses and replications in up to 52,895 individuals for BMI and up to 23,095 individuals for WHR_adjBMI from the African Ancestry Anthropometry Genetics Consortium (AAAGC) using 1000 Genomes phase 1 imputed GWAS to improve coverage of both common and low frequency variants in the low linkage disequilibrium African ancestry genomes. In the sex-combined analyses, we identified one novel locus (TCF7L2/HABP2) for WHR_adjBMI and eight previously established loci at P < 5×10⁻⁸: seven for BMI, and one for WHR_adjBMI in African ancestry individuals. An additional novel locus (SPRYD7/DLEU2) was identified for WHR_adjBMI when combined with European GWAS. In the sex-stratified analyses, we identified three novel loci for BMI (INTS10/LPL and MLC1 in men, IRX4/IRX2 in women) and four for WHR_adjBMI (SSX2IP, CASC8, PDE3B and ZDHHC1/HSD11B2 in women) in individuals of African ancestry or both African and European ancestry. For four of the novel variants, the minor allele frequency was low (<5%). In the trans-ethnic fine mapping of 47 BMI loci and 27 WHR_adjBMI loci that were locus-wide significant (P < 0.05 adjusted for effective number of variants per locus) from the African ancestry sex-combined and sex-stratified analyses, 26 BMI loci and 17 WHR_adjBMI loci contained ≤ 20 variants in the credible sets that jointly account for 99% posterior probability of driving the associations. The lead variants in 13 of these loci had a high probability of being causal. As compared to our previous HapMap imputed GWAS for BMI and WHR_adjBMI including up to 71,412 and 27,350 African ancestry individuals, respectively, our results suggest that 1000 Genomes imputation showed modest improvement in identifying GWAS loci including low frequency variants. Trans-ethnic meta-analyses further improved fine mapping of putative causal variants in loci shared between the African and European ancestry populations. Genome-wide association studies (GWAS) have identified >300 genetic regions that influence body size and shape as measured by body mass index (BMI) and waist-to-hip ratio (WHR), respectively, but few have been identified in populations of African ancestry. We conducted large scale high coverage GWAS and replication of these traits in 52,895 and 23,095 individuals of African ancestry, respectively, followed by additional replication in European populations. We identified 10 genome-wide significant loci in all individuals, and an additional seven loci by analyzing men and women separately. We combined African and European ancestry GWAS and were able to narrow down 43 out of 74 African ancestry associated genetic regions to contain small number of putative causal variants. Our results highlight the improvement of applying high density genome coverage and combining multiple ancestries in the identification and refinement of location of genetic regions associated with adiposity traits.