Adaptive genetic variation and population differences

Population structure and genetic diversity of Trichomonas vaginalis clinical isolates in Australia and Ghana

Population genetic studies of Trichomonas vaginalis have detected high genetic diversity associated with phenotypic differences in clinical presentations. In this study, microscopy and next generation-multi-locus sequence typing (NG-MLST) were used to identify and genetically characterise T. vaginalis isolates from patients in Australia and Ghana. Seventy-one polymorphic nucleotide sites, 36 different alleles, 48 sequence types, 24 of which were novel, were identified among 178 isolates, revealing a geneticallly diverse T. vaginalis population. Polymorphism was found at most loci, clustering genotypes into eight groups among both Australian and Ghanaian isolates, although there was some variation between countries. The number of alleles for each locus ranged from two to nine. Study results confirmed geographic expansion and diversity of the T. vaginalis population. Two-type populations in almost equal frequencies and a third unassigned group were identified in this study. Linkage disequilibrium was observed, suggesting T. vaginalis population is highly clonal. Multillocus disequilibrium was observed even when analysing clades separately, as well as widespread clonal genotypes, suggesting that there is no evidence of recent recombination. A more comprehensive study to assess the extent of genetic diversity and population structure of T. vaginalis and their potential impact on varied pathology observed among infected individuals is recommended.

Associations of the MCM6-rs3754686 proxy for milk intake in Mediterranean and American populations with cardiovascular biomarkers, disease and mortality: Mendelian randomization

Controversy persists on the association between dairy products, especially milk, and cardiovascular diseases (CVD). Genetic proxies may improve dairy intake estimations, and clarify diet-disease relationships through Mendelian randomization. We meta-analytically (n ≤ 20,089) evaluated associations between a lactase persistence (LP) SNP, the minichromosome maintenance complex component 6 (MCM6)-rs3754686C>T (nonpersistence>persistence), dairy intake, and CVD biomarkers in American (Hispanics, African-American and Whites) and Mediterranean populations. Moreover, we analyzed longitudinal associations with milk, CVD and mortality in PREDIMED), a randomized Mediterranean diet (MedDiet) intervention trial (n = 7185). The MCM6-rs3754686/MCM6-rs309180 (as proxy), LP-allele (T) was strongly associated with higher milk intake, but inconsistently associated with glucose and lipids, and not associated with CVD or total mortality in the whole population. Heterogeneity analyses suggested some sex-specific associations. The T-allele was associated with higher CVD and mortality risk in women but not in men (P-sex interaction:0.005 and 0.032, respectively), mainly in the MedDiet group. However, milk intake was not associated with CVD biomarkers, CVD or mortality either generally or in sub-groups. Although MCM6-rs3754686 is a good milk intake proxy in these populations, attributing its associations with CVD and mortality in Mediterranean women to milk is unwarranted, as other factors limiting the assumption of causality in Mendelian randomization may exist.

CardioGxE, a catalog of gene-environment interactions for cardiometabolic traits

Background

Genetic understanding of complex traits has developed immensely over the past decade but remains hampered by incomplete descriptions of contribution to phenotypic variance. Gene-environment (GxE) interactions are one of these contributors and in the guise of diet and physical activity are important modulators of cardiometabolic phenotypes and ensuing diseases.

Results

We mined the scientific literature to collect GxE interactions from 386 publications for blood lipids, glycemic traits, obesity anthropometrics, vascular measures, inflammation and metabolic syndrome, and introduce CardioGxE, a gene-environment interaction resource. We then analyzed the genes and SNPs supporting cardiometabolic GxEs in order to demonstrate utility of GxE SNPs and to discern characteristics of these important genetic variants. We were able to draw many observations from our extensive analysis of GxEs. 1) The CardioGxE SNPs showed little overlap with variants identified by main effect GWAS, indicating the importance of environmental interactions with genetic factors on cardiometabolic traits. 2) These GxE SNPs were enriched in adaptation to climatic and geographical features, with implications on energy homeostasis and response to physical activity. 3) Comparison to gene networks responding to plasma cholesterol-lowering or regression of atherosclerotic plaques showed that GxE genes have a greater role in those responses, particularly through high-energy diets and fat intake, than do GWAS-identified genes for the same traits. Other aspects of the CardioGxE dataset were explored.

Conclusions

Overall, we demonstrate that SNPs supporting cardiometabolic GxE interactions often exhibit transcriptional effects or are under positive selection. Still, not all such SNPs can be assigned potential functional or regulatory roles often because data are lacking in specific cell types or from treatments that approximate the environmental factor of the GxE. With research on metabolic related complex disease risk embarking on genome-wide GxE interaction tests, CardioGxE will be a useful resource.

Genome-wide contribution of genotype by environment interaction to variation of diabetes-related traits

While genome-wide association studies (GWAS) and candidate gene approaches have identified many genetic variants that contribute to disease risk as main effects, the impact of genotype by environment (GxE) interactions remains rather under-surveyed. To explore the importance of GxE interactions for diabetes-related traits, a tool for Genome-wide Complex Trait Analysis (GCTA) was used to examine GxE variance contribution of 15 macronutrients and lifestyle to the total phenotypic variance of diabetes-related traits at the genome-wide level in a European American population. GCTA identified two key environmental factors making significant contributions to the GxE variance for diabetes-related traits: carbohydrate for fasting insulin (25.1% of total variance, P-nominal = 0.032) and homeostasis model assessment of insulin resistance (HOMA-IR) (24.2% of total variance, P-nominal = 0.035), n-6 polyunsaturated fatty acid (PUFA) for HOMA-β-cell-function (39.0% of total variance, P-nominal = 0.005). To demonstrate and support the results from GCTA, a GxE GWAS was conducted with each of the significant dietary factors and a control E factor (dietary protein), which contributed a non-significant GxE variance. We observed that GxE GWAS for the environmental factor contributing a significant GxE variance yielded more significant SNPs than the control factor. For each trait, we selected all significant SNPs produced from GxE GWAS, and conducted anew the GCTA to estimate the variance they contributed. We noted the variance contributed by these SNPs is higher than that of the control. In conclusion, we utilized a novel method that demonstrates the importance of genome-wide GxE interactions in explaining the variance of diabetes-related traits.

Quantifying diet for nutrigenomic studies

The field of nutrigenomics shows tremendous promise for improved understanding of the effects of dietary intake on health. The knowledge that metabolic pathways may be altered in individuals with genetic variants in the presence of certain dietary exposures offers great potential for personalized nutrition advice. However, although considerable resources have gone into improving technology for measurement of the genome and biological systems, dietary intake assessment remains inadequate. Each of the methods currently used has limitations that may be exaggerated in the context of gene × nutrient interaction in large multiethnic studies. Because of the specificity of most gene × nutrient interactions, valid data are needed for nutrient intakes at the individual level. Most statistical adjustment efforts are designed to improve estimates of nutrient intake distributions in populations and are unlikely to solve this problem. An improved method of direct measurement of individual usual dietary intake that is unbiased across populations is urgently needed.

Marine N-3 polyunsaturated fatty acids are inversely associated with risk of type 2 diabetes in Asians: a systematic review and meta-analysis

BACKGROUND

Prospective cohort studies in relation to the associations between n-3 polyunsaturated fatty acids (PUFA) and risk of type 2 diabetes (T2D) were inconsistent. Differences in tissue n-3 PUFA compositions in subjects with and without T2D were also inconsistent in both cohort and case-control studies. We conducted a systematic review and meta-analysis of prospective cohort studies to examine the associations of fish and n-3 PUFA intake with T2D risk. The differences in tissue n-3 PUFA compositions in subjects with and without T2D were investigated based on cohort and case-control studies.

METHODS AND FINDINGS

PubMed, Embase, Cochrane library, China National Knowledge Infrastructure (CNKI) and Chinese VIP database up to January 2012 was used to identify relevant studies, and reference lists from retrieved studies were reviewed. Two authors independently extracted the data. Random-effects models were used to pool the summary relative risk (RR). Twenty-four studies including 24,509 T2D patients and 545,275 participants were identified. For cohort studies, the summary RR of T2D for the highest vs lowest categories of total fish, marine n-3 PUFA and alpha-linolenic acid intake was 1.07 (95% CI: 0.91, 1.25), 1.07 (95% CI: 0.95, 1.20) and 0.93 (95% CI: 0.81, 1.07), respectively. Subgroup analyses indicated that summary RR (highest vs lowest category) of T2D for fish and marine n-3 PUFA intake was 0.89 (95% CI: 0.81, 0.98) and 0.87 (95% CI: 0.79, 0.96) for Asian populations, and 1.20 (95% CI: 1.01, 1.44) and 1.16 (95% CI: 1.04, 1.28) for Western populations. Asian subjects with T2D had significantly lower tissue compositions of C22:6n-3 (SMD: -1.43; 95% CI: -1.75, -1.12) and total n-3 PUFA (SMD: -1.41; 95% CI: -2.23, -0.59) compared with those without T2D.

CONCLUSION

This systematic review and meta-analysis provides evidence that marine n-3 PUFA have beneficial effects on the prevention of T2D in Asian populations.