65 research outputs found

    Particle export from the upper ocean over the continental shelf of the west Antarctic Peninsula: A long-term record, 1992–2007

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    Author Posting. © The Author(s), 2008. This is the author's version of the work. It is posted here by permission of Elsevier B.V. for personal use, not for redistribution. The definitive version was published in Deep Sea Research Part II: Topical Studies in Oceanography 55 (2008): 2118-2131, doi:10.1016/j.dsr2.2008.04.028.Includes supplemental materialsWe report on results of a long-term (1993-2007) time series sediment trap moored at 170 m to the west of the Antarctic Peninsula in the mid-continental shelf region (350 m depth; 64Âș30’ S, 66Âș00’ W). This is a region characterized by late spring-summer diatom blooms, moderately high seasonal primary productivity (50-150 mmol C m-2 d-1 in December-February) and high phytoplankton and krill biomass in the seasonal sea ice zone. The mass flux ranged from near 0 to over 1 g m-2 d-1 and was near 0 to >30% organic carbon (mean 8%). Sedimentation from the upper ocean as estimated by the trap collections at 170 m exhibited strong seasonality with high fluxes (1-10 mmol C m-2 d-1) in November-March following ice retreat and very low fluxes (<0.001 mmol C m-2 d-1) during the Austral winter and under sea ice cover. An average of 85% of the annual export of 212 mmol C m-2 occurred during the seasonal peak flux episodes. Over the trap record, the annual peak flux episode has tended to occur later in the Austral summer, advancing by about 40 days since 1993. The time-integrated sedimentation during the peak flux episode was <1 – 50% of the SeaWiFS-estimated primary production (mean 4%) at the trap site over the period 1998-2006. The elemental composition of material captured in the traps had an average C:N:P of 212:28:1, greater than the canonical Redfield values. High C:P ratios (400- 600) corresponded with the annual flux peak, indicating preferential loss of P from the sinking particles in the summer, ice-free period. The composition of the exported material more closely approximated the Redfield composition during the low-flux, winter period.This research was supported by NSF Grants OPP 9011927, 9632763 and 0217282 for the Palmer Long Term Ecological Research project

    Transethnic insight into the genetics of glycaemic traits: fine-mapping results from the Population Architecture using Genomics and Epidemiology (PAGE) consortium

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    AIMS/HYPOTHESIS: Elevated levels of fasting glucose and fasting insulin in non-diabetic individuals are markers of dysregulation of glucose metabolism and are strong risk factors for type 2 diabetes. Genome-wide association studies have discovered over 50 SNPs associated with these traits. Most of these loci were discovered in European populations and have not been tested in a well-powered multi-ethnic study. We hypothesised that a large, ancestrally diverse, fine-mapping genetic study of glycaemic traits would identify novel and population-specific associations that were previously undetectable by European-centric studies. METHODS: A multiethnic study of up to 26,760 unrelated individuals without diabetes, of predominantly Hispanic/Latino and African ancestries, were genotyped using the Metabochip. Transethnic meta-analysis of racial/ethnic-specific linear regression analyses were performed for fasting glucose and fasting insulin. We attempted to replicate 39 fasting glucose and 17 fasting insulin loci. Genetic fine-mapping was performed through sequential conditional analyses in 15 regions that included both the initially reported SNP association(s) and denser coverage of SNP markers. In addition, Metabochip-wide analyses were performed to discover novel fasting glucose and fasting insulin loci. The most significant SNP associations were further examined using bioinformatic functional annotation. RESULTS: Previously reported SNP associations were significantly replicated (p ≀ 0.05) in 31/39 fasting glucose loci and 14/17 fasting insulin loci. Eleven glycaemic trait loci were refined to a smaller list of potentially causal variants through transethnic meta-analysis. Stepwise conditional analysis identified two loci with independent secondary signals (G6PC2-rs477224 and GCK-rs2908290), which had not previously been reported. Population-specific conditional analyses identified an independent signal in G6PC2 tagged by the rare variant rs77719485 in African ancestry. Further Metabochip-wide analysis uncovered one novel fasting insulin locus at SLC17A2-rs75862513. CONCLUSIONS/INTERPRETATION: These findings suggest that while glycaemic trait loci often have generalisable effects across the studied populations, transethnic genetic studies help to prioritise likely functional SNPs, identify novel associations that may be population-specific and in turn have the potential to influence screening efforts or therapeutic discoveries. DATA AVAILABILITY: The summary statistics from each of the ancestry-specific and transethnic (combined ancestry) results can be found under the PAGE study on dbGaP here: https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000356.v1.p1

    Harmful algal blooms and eutrophication : examining linkages from selected coastal regions of the United States

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    Author Posting. © Elsevier B.V., 2008. This is the author's version of the work. It is posted here by permission of Elsevier B.V. for personal use, not for redistribution. The definitive version was published in Harmful Algae 8 (2008): 39-53, doi:10.1016/j.hal.2008.08.017.Coastal waters of the United States (U.S.) are subject to many of the major harmful algal bloom (HAB) poisoning syndromes and impacts. These include paralytic shellfish poisoning (PSP), neurotoxic shellfish poisoning (NSP), amnesic shellfish poisoning (ASP), ciguatera fish poisoning (CFP) and various other HAB phenomena such as fish kills, loss of submerged vegetation, shellfish mortalities, and widespread marine mammal mortalities. Here, the occurrences of selected HABs in a selected set of regions are described in terms of their relationship to eutrophication, illustrating a range of responses. Evidence suggestive of changes in the frequency, extent or magnitude of HABs in these areas is explored in the context of the nutrient sources underlying those blooms, both natural and anthropogenic. In some regions of the U.S., the linkages between HABs and eutrophication are clear and well documented, whereas in others, information is limited, thereby highlighting important areas for further research.Support was provided through the Woods Hole Center for Oceans and Human Health (to DMA), National Science Foundation (NSF) grants OCE-9808173 and OCE-0430724 (to DMA), OCE-0234587 (to WPC), OCE04-32479 (to MLP), OCE-0138544 (to RMK), OCE-9981617 (to PMG); National Institute of Environmental Health Sciences (NIEHS) grants P50ES012742-01 (to DMA) and P50ES012740 (to MLP); NOAA Grants NA96OP0099 (to DMA), NA16OP1450 (to VLT), NA96P00084 (to GAV and CAH), NA160C2936 and NA108H-C (to RMK), NA860P0493 and NA04NOS4780241 (to PMG), NA04NOS4780239-02 (to RMK), NA06NOS4780245 (to DWT). Support was also provided from the West Coast Center for Oceans and Human Health (to VLT and WPC), USEPA Grant CR826792-01-0 (to GAV and CAH), and the State of Florida Grant S7701617826 (to GAV and CAH)

    Effects of smoking on the genetic risk of obesity: the population architecture using genomics and epidemiology study

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    Abstract Background Although smoking behavior is known to affect body mass index (BMI), the potential for smoking to influence genetic associations with BMI is largely unexplored. Methods As part of the ‘Population Architecture using Genomics and Epidemiology (PAGE)’ Consortium, we investigated interaction between genetic risk factors associated with BMI and smoking for 10 single nucleotide polymorphisms (SNPs) previously identified in genome-wide association studies. We included 6 studies with a total of 56,466 subjects (16,750 African Americans (AA) and 39,716 European Americans (EA)). We assessed effect modification by testing an interaction term for each SNP and smoking (current vs. former/never) in the linear regression and by stratified analyses. Results We did not observe strong evidence for interactions and only observed two interactions with p-values <0.1: for rs6548238/TMEM18, the risk allele (C) was associated with BMI only among AA females who were former/never smokers (ÎČ = 0.018, p = 0.002), vs. current smokers (ÎČ = 0.001, p = 0.95, pinteraction = 0.10). For rs9939609/FTO, the A allele was more strongly associated with BMI among current smoker EA females (ÎČ = 0.017, p = 3.5x10-5), vs. former/never smokers (ÎČ = 0.006, p = 0.05, pinteraction = 0.08). Conclusions These analyses provide limited evidence that smoking status may modify genetic effects of previously identified genetic risk factors for BMI. Larger studies are needed to follow up our results. Clinical Trial Registration NCT0000061

    Genetic risk factors for BMI and obesity in an ethnically diverse population: Results from the population architecture using genomics and epidemiology (PAGE) study

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    Several genome-wide association studies (GWAS) have demonstrated that common genetic variants contribute to obesity. However, studies of this complex trait have focused on ancestrally European populations, despite the high prevalence of obesity in some minority groups. As part of the ‘Population Architecture using Genomics and Epidemiology (PAGE)’ Consortium, we investigated the association between thirteen GWAS-identified SNPs and BMI and obesity in 69,775 subjects, including 6,149 American Indians, 15,415 African-Americans, 2,438 East Asians, 7,346 Hispanics, 604 Pacific Islanders, and 37,823 European Americans. For the BMI-increasing allele of each SNP, we calculated beta coefficients using linear regression (for BMI) and risk estimates using logistic regression (for obesity defined as BMI ≄ 30) followed by fixed-effects meta-analysis to combine results across PAGE sites. Analyses stratified by racial/ethnic group assumed an additive genetic model and adjusted for age, sex, and current smoking. We defined “replicating SNPs” (in European Americans) and “generalizing SNPs” (in other racial/ethnic groups) as those associated with an allele frequency-specific increase in BMI. By this definition, we replicated 9/13 SNP associations (5 out of 8 loci) in European Americans. We also generalized 8/13 SNP associations (5/8 loci) in East Asians, 7/13 (5/8 loci) in African Americans, 6/13 (4/8 loci) in Hispanics, 5/8 in Pacific Islanders (5/8 loci), and 5/9 (4/8 loci) in American Indians. Linkage disequilibrium patterns suggest that tagSNPs selected for European Americans may not adequately tag causal variants in other ancestry groups. Accordingly, fine-mapping in large samples is needed to comprehensively explore these loci in diverse populations

    Rare coding variants in PLCG2, ABI3, and TREM2 implicate microglial-mediated innate immunity in Alzheimer's disease

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    We identified rare coding variants associated with Alzheimer’s disease (AD) in a 3-stage case-control study of 85,133 subjects. In stage 1, 34,174 samples were genotyped using a whole-exome microarray. In stage 2, we tested associated variants (P<1×10-4) in 35,962 independent samples using de novo genotyping and imputed genotypes. In stage 3, an additional 14,997 samples were used to test the most significant stage 2 associations (P<5×10-8) using imputed genotypes. We observed 3 novel genome-wide significant (GWS) AD associated non-synonymous variants; a protective variant in PLCG2 (rs72824905/p.P522R, P=5.38×10-10, OR=0.68, MAFcases=0.0059, MAFcontrols=0.0093), a risk variant in ABI3 (rs616338/p.S209F, P=4.56×10-10, OR=1.43, MAFcases=0.011, MAFcontrols=0.008), and a novel GWS variant in TREM2 (rs143332484/p.R62H, P=1.55×10-14, OR=1.67, MAFcases=0.0143, MAFcontrols=0.0089), a known AD susceptibility gene. These protein-coding changes are in genes highly expressed in microglia and highlight an immune-related protein-protein interaction network enriched for previously identified AD risk genes. These genetic findings provide additional evidence that the microglia-mediated innate immune response contributes directly to AD development
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