Genome-wide physical activity interactions in adiposity. A meta-analysis of 200,452 adults

Physical activity (PA) may modify the genetic effects that give rise to increased risk of obesity. To identify adiposity loci whose effects are modified by PA, we performed genome-wide interaction meta-analyses of BMI and BMI-adjusted waist circumference and waist-hip ratio from up to 200,452 adults of European (n = 180,423) or other ancestry (n = 20,029). We standardized PA by categorizing it into a dichotomous variable where, on average, 23% of participants were categorized as inactive and 77% as physically active. While we replicate the interaction with PA for the strongest known obesity-risk locus in the FTO gene, of which the effect is attenuated by similar to 30% in physically active individuals compared to inactive individuals, we do not identify additional loci that are sensitive to PA. In additional genome-wide meta-analyses adjusting for PA and interaction with PA, we identify 11 novel adiposity loci, suggesting that accounting for PA or other environmental factors that contribute to variation in adiposity may facilitate gene discovery.Peer reviewe

A "Candidate-Interactome" Aggregate Analysis of Genome-Wide Association Data in Multiple Sclerosis

Though difficult, the study of gene-environment interactions in multifactorial diseases is crucial for interpreting the relevance of non-heritable factors and prevents from overlooking genetic associations with small but measurable effects. We propose a “candidate interactome” (i.e. a group of genes whose products are known to physically interact with environmental factors that may be relevant for disease pathogenesis) analysis of genome-wide association data in multiple sclerosis. We looked for statistical enrichment of associations among interactomes that, at the current state of knowledge, may be representative of gene-environment interactions of potential, uncertain or unlikely relevance for multiple sclerosis pathogenesis: Epstein-Barr virus, human immunodeficiency virus, hepatitis B virus, hepatitis C virus, cytomegalovirus, HHV8-Kaposi sarcoma, H1N1-influenza, JC virus, human innate immunity interactome for type I interferon, autoimmune regulator, vitamin D receptor, aryl hydrocarbon receptor and a panel of proteins targeted by 70 innate immune-modulating viral open reading frames from 30 viral species. Interactomes were either obtained from the literature or were manually curated. The P values of all single nucleotide polymorphism mapping to a given interactome were obtained from the last genome-wide association study of the International Multiple Sclerosis Genetics Consortium & the Wellcome Trust Case Control Consortium, 2. The interaction between genotype and Epstein Barr virus emerges as relevant for multiple sclerosis etiology. However, in line with recent data on the coexistence of common and unique strategies used by viruses to perturb the human molecular system, also other viruses have a similar potential, though probably less relevant in epidemiological terms

Greenhouse gas emissions resulting from conversion of peat swamp forest to oil palm plantation.

Conversion of tropical peat swamp forest to drainage-based agriculture alters greenhouse gas (GHG) production, but the magnitude of these changes remains highly uncertain. Current emissions factors for oil palm grown on drained peat do not account for temporal variation over the plantation cycle and only consider CO2 emissions. Here, we present direct measurements of GHGs emitted during the conversion from peat swamp forest to oil palm plantation, accounting for CH4 and N2O as well as CO2. Our results demonstrate that emissions factors for converted peat swamp forest is in the range 70-117 t CO2 eq ha-1 yr-1 (95% confidence interval, CI), with CO2 and N2O responsible for ca. 60 and ca. 40% of this value, respectively. These GHG emissions suggest that conversion of Southeast Asian peat swamp forest is contributing between 16.6 and 27.9% (95% CI) of combined total national GHG emissions from Malaysia and Indonesia or 0.44 and 0.74% (95% CI) of annual global emissions

Morphological predictors of BRCA1 germline mutations in young women with breast cancer

BACKGROUND: Knowing a young woman with newly diagnosed breast cancer has a germline BRCA1 mutation informs her clinical management and that of her relatives. We sought an optimal strategy for identifying carriers using family history, breast cancer morphology and hormone receptor status data.METHODS: We studied a population-based sample of 452 Australian women with invasive breast cancer diagnosed before age 40 years for whom we conducted extensive germline mutation testing (29 carried a BRCA1 mutation) and a systematic pathology review, and collected three-generational family history and tumour ER and PR status. Predictors of mutation status were identified using multiple logistic regression. Areas under receiver operator characteristic (ROC) curves were estimated using five-fold stratified cross-validation.RESULTS: The probability of being a BRCA1 mutation carrier increased with number of selected histology features even after adjusting for family history and ER and PR status (Po0.0001). From the most parsimonious multivariate model, the odds ratio for being a carrier were: 9.7 (95% confidence interval: 2.6-47.0) for trabecular growth pattern (P=0.001); 7.8 (2.7-25.7) for mitotic index over 50 mitoses per 10 high-powered field (P 0.0003); and 2.7 (1.3-5.9) for each first-degree relative with breast cancer diagnosed before age 60 years (P 0.01). The area under the ROC curve was 0.87 (0.83-0.90).CONCLUSION: Pathology review, with attention to a few specific morphological features of invasive breast cancers, can identify almost all BRCA1 germline mutation carriers among women with early-onset breast cancer without taking into account family history. British Journal of Cancer (2011) 104, 903-909. doi: 10.1038/ bjc. 2011.41 www. bjcancer. co

Nationwide Molecular Surveillance of Pandemic H1N1 Influenza A Virus Genomes: Canada, 2009

BACKGROUND: In April 2009, a novel triple-reassortant swine influenza A H1N1 virus ("A/H1N1pdm"; also known as SOIV) was detected and spread globally as the first influenza pandemic of the 21(st) century. Sequencing has since been conducted at an unprecedented rate globally in order to monitor the diversification of this emergent virus and to track mutations that may affect virus behavior. METHODOLOGY/PRINCIPAL FINDINGS: By Sanger sequencing, we determined consensus whole-genome sequences for A/H1N1pdm viruses sampled nationwide in Canada over 33 weeks during the 2009 first and second pandemic waves. A total of 235 virus genomes sampled from unique subjects were analyzed, providing insight into the temporal and spatial trajectory of A/H1N1pdm lineages within Canada. Three clades (2, 3, and 7) were identifiable within the first two weeks of A/H1N1pdm appearance, with clades 5 and 6 appearing thereafter; further diversification was not apparent. Only two viral sites displayed evidence of adaptive evolution, located in hemagglutinin (HA) corresponding to D222 in the HA receptor-binding site, and to E374 at HA2-subunit position 47. Among the Canadian sampled viruses, we observed notable genetic diversity (1.47 x 10⁻³ amino acid substitutions per site) in the gene encoding PB1, particularly within the viral genomic RNA (vRNA)-binding domain (residues 493-757). This genome data set supports the conclusion that A/H1N1pdm is evolving but not excessively relative to other H1N1 influenza A viruses. Entropy analysis was used to investigate whether any mutated A/H1N1pdm protein residues were associated with infection severity; however no virus genotypes were observed to trend with infection severity. One virus that harboured heterozygote coding mutations, including PB2 D567D/G, was attributed to a severe and potentially mixed infection; yet the functional significance of this PB2 mutation remains unknown. CONCLUSIONS/SIGNIFICANCE: These findings contribute to enhanced understanding of Influenza A/H1N1pdm viral dynamics

A "candidate-interactome" aggregate analysis of genome-wide association data in multiple sclerosis

Though difficult, the study of gene-environment interactions in multifactorial diseases is crucial for interpreting the relevance of non-heritable factors and prevents from overlooking genetic associations with small but measurable effects. We propose a "candidate interactome" (i.e. a group of genes whose products are known to physically interact with environmental factors that may be relevant for disease pathogenesis) analysis of genome-wide association data in multiple sclerosis. We looked for statistical enrichment of associations among interactomes that, at the current state of knowledge, may be representative of gene-environment interactions of potential, uncertain or unlikely relevance for multiple sclerosis pathogenesis: Epstein-Barr virus, human immunodeficiency virus, hepatitis B virus, hepatitis C virus, cytomegalovirus, HHV8-Kaposi sarcoma, H1N1-influenza, JC virus, human innate immunity interactome for type I interferon, autoimmune regulator, vitamin D receptor, aryl hydrocarbon receptor and a panel of proteins targeted by 70 innate immune-modulating viral open reading frames from 30 viral species. Interactomes were either obtained from the literature or were manually curated. The P values of all single nucleotide polymorphism mapping to a given interactome were obtained from the last genome-wide association study of the International Multiple Sclerosis Genetics Consortium & the Wellcome Trust Case Control Consortium, 2. The interaction between genotype and Epstein Barr virus emerges as relevant for multiple sclerosis etiology. However, in line with recent data on the coexistence of common and unique strategies used by viruses to perturb the human molecular system, also other viruses have a similar potential, though probably less relevant in epidemiological terms