A Genome-Wide Association Study of a Biomarker of Nicotine Metabolism

Individuals with fast nicotine metabolism typically smoke more and thus have a greater risk for smoking-induced diseases. Further, the efficacy of smoking cessation pharmacotherapy is dependent on the rate of nicotine metabolism. Our objective was to use nicotine metabolite ratio (NMR), an established biomarker of nicotine metabolism rate, in a genome-wide association study (GWAS) to identify novel genetic variants influencing nicotine metabolism. A heritability estimate of 0.81 (95% CI 0.70–0.88) was obtained for NMR using monozygotic and dizygotic twins of the FinnTwin cohort. We performed a GWAS in cotinine-verified current smokers of three Finnish cohorts (FinnTwin, Young Finns Study, FINRISK2007), followed by a meta-analysis of 1518 subjects, and annotated the genome-wide significant SNPs with methylation quantitative loci (meQTL) analyses. We detected association on 19q13 with 719 SNPs exceeding genome-wide significance within a 4.2 Mb region. The strongest evidence for association emerged for CYP2A6 (min p = 5.77E-86, in intron 4), the main metabolic enzyme for nicotine. Other interesting genes with genome-wide significant signals included CYP2B6, CYP2A7, EGLN2, and NUMBL. Conditional analyses revealed three independent signals on 19q13, all located within or in the immediate vicinity of CYP2A6. A genetic risk score constructed using the independent signals showed association with smoking quantity (p = 0.0019) in two independent Finnish samples. Our meQTL results showed that methylation values of 16 CpG sites within the region are affected by genotypes of the genome-wide significant SNPs, and according to causal inference test, for some of the SNPs the effect on NMR is mediated through methylation. To our knowledge, this is the first GWAS on NMR. Our results enclose three independent novel signals on 19q13.2. The detected CYP2A6 variants explain a strikingly large fraction of variance (up to 31%) in NMR in these study samples. Further, we provide evidence for plausible epigenetic mechanisms influencing NMR.     

Multispectral canopy reflectance improves spatial distribution models of Amazonian understory species

Species distribution models are required for the research and management of biodiversity in the hyperdiverse tropical forests, but reliable and ecologically relevant digital environmental data layers are not always available. We here assess the usefulness of multispectral canopy reflectance (Landsat) relative to climate data in modelling understory plant species distributions in tropical rainforests. We used a large dataset of quantitative fern and lycophyte species inventories across lowland Amazonia as the basis for species distribution modelling (SDM). As predictors, we used CHELSA climatic variables and canopy reflectance values from a recent basin-wide composite of Landsat TM/ETM+ images both separately and in combination. We also investigated how species accumulate over sites when environmental distances were expressed in terms of climatic or surface reflectance variables. When species accumulation curves were constructed such that differences in Landsat reflectance among the selected plots were maximised, species accumulated faster than when climatic differences were maximised or plots were selected in a random order. Sixty-nine species were sufficiently frequent for species distribution modelling. For most of them, adequate SDMs were obtained whether the models were based on CHELSA data only, Landsat data only or both combined. Model performance was not influenced by species’ prevalence or abundance. Adding Landsat-based environmental data layers overall improved the discriminatory capacity of SDMs compared to climate-only models, especially for soil specialist species. Our results show that canopy surface reflectance obtained by multispectral sensors can provide studies of tropical ecology, as exemplified by SDMs, much higher thematic (taxonomic) detail than is generally assumed. Furthermore, multispectral datasets complement the traditionally used climatic layers in analyses requiring information on environmental site conditions. We demonstrate the utility of freely available, global remote sensing data for biogeographical studies that can aid conservation planning and biodiversity management.     

Genetic structure of the northwestern Russian wolf populations and gene flow between Russia and Finland

We examined the genetic diversity and structure of wolf populations in northwestern Russia. Populations in Republic of Karelia and Arkhangelsk Oblast were sampled during 1995–2000, and 43 individuals were genotyped with 10 microsatellite markers. Moreover, 118 previously genotyped wolves from the neighbouring Finnish population were used as a reference population. A relatively large amount of genetic variation was found in the Russian populations, and the Karelian wolf population tended to be slightly more polymorphic than the Arkhangelsk population. We found significant inbreeding (F = 0.094) in the Karelian, but not in the Arkhangelsk population. The effective size estimates of the Karelian wolf population based on the approximate Bayesian computation and linkage disequilibrium methods were 39.9 and 46.7 individuals, respectively. AMOVA-analysis and exact test of population differentiation suggested clear differentiation between the Karelian, Arkhangelsk and Finnish wolf populations. Indirect estimates of gene flow based on the level of population differentiation (ϕ _ST  = 0.152) and frequency of private alleles (0.029) both suggested a low level of gene flow between the populations (Nm = 1.4 and Nm = 3.7, respectively). Assignment analysis of Karelian and Finnish populations suggested an even lower number of recent migrants (less than 0.03) between populations, with a larger amount of migration from Finland to Karelia than vice versa. Our findings emphasise the role of physical obstacles and territorial behaviour in creating barriers to gene flow between populations in relatively limited geographical areas, even in large-bodied mammalian species with long-distance dispersal capabilities and an apparently continuous population structure.     

Bottom-up and cascading top-down control of macroalgae along a depth gradient

On marine rocky shores, macroalgal herbivory is often intense, such that the cascading effects of fish predation may contribute to the control of algal communities. To estimate the magnitudes of top-down and bottom-up control on a macroalgal community, we manipulated the access of carnivorous fish to macroalgal colonization substrates, as well as nutrient availability, at two sub-littoral depths. There were three levels of fish manipulation: natural fish community, no fish and the enclosure of one common species, the perch, Perca fluviatilis. We found a clear cascade effect of fish predation on both the total density and several individual species of macroalgae, which was more pronounced in deep than shallow water. The density of the dominant grazers, i.e. snails, increased in nutrient-enriched conditions; perch were inefficient in controlling herbivores, and had therefore no cascading effect on algal densities under such conditions. Although nutrients enhanced the growth of opportunistic algae, herbivores, in the absence of fish, inhibited this response. While algal diversity was higher in shallow than in deep water, the enrichment effect was opposite at the two depths with lowered diversity in the shallows and increased at depth. Our results indicate that fish predation is an efficient regulator of meso-herbivores and that its effect thereby cascades onto the producer trophic level such that both perennial and opportunistic algae benefit from the presence of fish. This cascade effect is probably stronger at depth where predation efficiency is less disturbed by wave motion.     

Biomarker Profiling by Nuclear Magnetic Resonance Spectroscopy for the Prediction of All-Cause Mortality: An Observational Study of 17,345 Persons

Background

Early identification of ambulatory persons at high short-term risk of death could benefit targeted prevention. To identify biomarkers for all-cause mortality and enhance risk prediction, we conducted high-throughput profiling of blood specimens in two large population-based cohorts.

Methods and Findings

106 candidate biomarkers were quantified by nuclear magnetic resonance spectroscopy of non-fasting plasma samples from a random subset of the Estonian Biobank (n = 9,842; age range 18–103 y; 508 deaths during a median of 5.4 y of follow-up). Biomarkers for all-cause mortality were examined using stepwise proportional hazards models. Significant biomarkers were validated and incremental predictive utility assessed in a population-based cohort from Finland (n = 7,503; 176 deaths during 5 y of follow-up). Four circulating biomarkers predicted the risk of all-cause mortality among participants from the Estonian Biobank after adjusting for conventional risk factors: alpha-1-acid glycoprotein (hazard ratio [HR] 1.67 per 1–standard deviation increment, 95% CI 1.53–1.82, p = 5×10⁻³¹), albumin (HR 0.70, 95% CI 0.65–0.76, p = 2×10⁻¹⁸), very-low-density lipoprotein particle size (HR 0.69, 95% CI 0.62–0.77, p = 3×10⁻¹²), and citrate (HR 1.33, 95% CI 1.21–1.45, p = 5×10⁻¹⁰). All four biomarkers were predictive of cardiovascular mortality, as well as death from cancer and other nonvascular diseases. One in five participants in the Estonian Biobank cohort with a biomarker summary score within the highest percentile died during the first year of follow-up, indicating prominent systemic reflections of frailty. The biomarker associations all replicated in the Finnish validation cohort. Including the four biomarkers in a risk prediction score improved risk assessment for 5-y mortality (increase in C-statistics 0.031, p = 0.01; continuous reclassification improvement 26.3%, p = 0.001).

Conclusions

Biomarker associations with cardiovascular, nonvascular, and cancer mortality suggest novel systemic connectivities across seemingly disparate morbidities. The biomarker profiling improved prediction of the short-term risk of death from all causes above established risk factors. Further investigations are needed to clarify the biological mechanisms and the utility of these biomarkers for guiding screening and prevention. Please see later in the article for the Editors'' Summary     

Role of sterol type on lateral pressure profiles of lipid membranes affecting membrane protein functionality: Comparison between cholesterol, desmosterol, 7-dehydrocholesterol and ketosterol

Lateral pressure profiles have been suggested to play a significant role in many cellular membrane processes by affecting, for example, the activation of membrane proteins through changes in their conformational state. This may be the case if the lateral pressure profile is altered due to changes in molecular composition surrounding the protein. In this work, we elucidate the effect of varying sterol type on the lateral pressure profile, an issue of topical interest due to lipid rafts and their putative role for membrane protein functionality. We find that the lateral pressure profile is altered when cholesterol is replaced by either desmosterol, 7-dehydrocholesterol, or ketosterol. The observed changes in the lateral pressure profile are notable and important since desmosterol and 7-dehydrocholesterol are the immediate precursors of cholesterol along its biosynthetic pathway. The results show that the lateral pressure profile and the resulting elastic behavior of lipid membranes are sensitive to the sterol type, and support a mechanism where changes in protein conformational state are facilitated by changes in the lateral pressure profile. From a structural point of view, the results provide compelling evidence that despite seemingly minor differences, sterols are characterized by structural specificity.     

Protein shape change has a major effect on the gating energy of a mechanosensitive channel

Increasing experimental evidence has shown that membrane protein functionality depends on molecular composition of cell membranes. However, the origin of this dependence is not fully understood. It is reasonable to assume that specific lipid-protein interactions are important, yet more generic effects due to mechanical properties of lipid bilayers likely play a significant role too. Previously it has been demonstrated using models for elastic properties of membranes and lateral pressure profiles of lipid bilayers that the mechanical properties of a lipid bilayer can contribute as much as ∼10 k_BT to the free energy difference associated with a change in protein conformational state. Here, we extend those previous approaches to a more realistic model for a large mechanosensitive channel (MscL). We use molecular dynamics together with the MARTINI model to simulate the open and closed states of MscL embedded in a DOPC bilayer. We introduce a procedure to calculate the mechanical energy change in the channel gating using a three-dimensional pressure distribution inside a membrane, computed from the molecular dynamics simulations. We decompose the mechanical energy to terms associated with area dilation and shape contribution. Our results highlight that the lateral pressure profile of a lipid bilayer together with the shape change in gating can induce a contribution of ∼30 k_BT on the gating energy of MscL. This contribution arises largely from the interfacial tension between hydrophobic and hydrophilic regions in a lipid bilayer.     

Further evidence for the role of ENPP1 in obesity: association with morbid obesity in Finns

The aim of this study was to investigate a series of single-nucleotide polymorphisms (SNPs) in the genes MC2R, MC3R, MC4R, MC5R, POMC, and ENPP1 for association with obesity. Twenty-five SNPs (2-7 SNPs/gene) were genotyped in 246 Finns with extreme obesity (BMI > or = 40 kg/m2) and in 481 lean subjects (BMI 20-25 kg/m2). Of the obese subjects, 23% had concomitant type 2 diabetes. SNPs and SNP haplotypes were tested for association with obesity and type 2 diabetes. Allele frequencies differed between obese and lean subjects for two SNPs in the ENPP1 gene, rs1800949 (P = 0.006) and rs943003 (P = 0.0009). These SNPs are part of a haplotype (rs1800949 C-rs943003 A), which was observed more frequently in lean subjects compared to obese subjects (P = 0.0007). Weaker associations were detected between the SNPs rs1541276 in the MC5R, rs1926065 in the MC3R genes and obesity (P = 0.04 and P = 0.03, respectively), and between SNPs rs2236700 in the MC5R, rs2118404 in the POMC, rs943003 in the ENPP1 genes and type 2 diabetes (P = 0.03, P = 0.02 and P = 0.02, respectively); these associations did not, however, remain significant after correction for multiple testing. In conclusion, a previously unexplored ENPP1 haplotype composed of SNPs rs1800949 and rs943003 showed suggestive evidence for association with adult-onset morbid obesity in Finns. In this study, we did not find association between the frequently studied ENPP1 K121Q variant, nor SNPs in the MCR or POMC genes and obesity or type 2 diabetes.