Effects of Genetic Variants Previously Associated with Fasting Glucose and Insulin in the Diabetes Prevention Program

Common genetic variants have been recently associated with fasting glucose and insulin levels in white populations. Whether these associations replicate in pre-diabetes is not known. We extended these findings to the Diabetes Prevention Program, a clinical trial in which participants at high risk for diabetes were randomized to placebo, lifestyle modification or metformin for diabetes prevention. We genotyped previously reported polymorphisms (or their proxies) in/near G6PC2, MTNR1B, GCK, DGKB, GCKR, ADCY5, MADD, CRY2, ADRA2A, FADS1, PROX1, SLC2A2, GLIS3, C2CD4B, IGF1, and IRS1 in 3,548 Diabetes Prevention Program participants. We analyzed variants for association with baseline glycemic traits, incident diabetes and their interaction with response to metformin or lifestyle intervention. We replicated associations with fasting glucose at MTNR1B (P<0.001), G6PC2 (P = 0.002) and GCKR (P = 0.001). We noted impaired β-cell function in carriers of glucose-raising alleles at MTNR1B (P<0.001), and an increase in the insulinogenic index for the glucose-raising allele at G6PC2 (P<0.001). The association of MTNR1B with fasting glucose and impaired β-cell function persisted at 1 year despite adjustment for the baseline trait, indicating a sustained deleterious effect at this locus. We also replicated the association of MADD with fasting proinsulin levels (P<0.001). We detected no significant impact of these variants on diabetes incidence or interaction with preventive interventions. The association of several polymorphisms with quantitative glycemic traits is replicated in a cohort of high-risk persons. These variants do not have a detectable impact on diabetes incidence or response to metformin or lifestyle modification in the Diabetes Prevention Program

Genetic modulation of lipid profiles following lifestyle modification or metformin treatment: The Diabetes Prevention Program

Weight-loss interventions generally improve lipid profiles and reduce cardiovascular disease risk, but effects are variable and may depend on genetic factors. We performed a genetic association analysis of data from 2,993 participants in the Diabetes Prevention Program to test the hypotheses that a genetic risk score (GRS) based on deleterious alleles at 32 lipid-associated single-nucleotide polymorphisms modifies the effects of lifestyle and/or metformin interventions on lipid levels and nuclear magnetic resonance (NMR) lipoprotein subfraction size and number. Twenty-three loci previously associated with fasting LDL-C, HDL-C, or triglycerides replicated (P = 0.04–1×10−17). Except for total HDL particles (r = −0.03, P = 0.26), all components of the lipid profile correlated with the GRS (partial |r| = 0.07–0.17, P = 5×10−5–1×10−19). The GRS was associated with higher baseline-adjusted 1-year LDL cholesterol levels (β = +0.87, SEE±0.22 mg/dl/allele, P = 8×10−5, Pinteraction = 0.02) in the lifestyle intervention group, but not in the placebo (β = +0.20, SEE±0.22 mg/dl/allele, P = 0.35) or metformin (β = −0.03, SEE±0.22 mg/dl/allele, P = 0.90; Pinteraction = 0.64) groups. Similarly, a higher GRS predicted a greater number of baseline-adjusted small LDL particles at 1 year in the lifestyle intervention arm (β = +0.30, SEE±0.012 ln nmol/L/allele, P = 0.01, Pinteraction = 0.01) but not in the placebo (β = −0.002, SEE±0.008 ln nmol/L/allele, P = 0.74) or metformin (β = +0.013, SEE±0.008 nmol/L/allele, P = 0.12; Pinteraction = 0.24) groups. Our findings suggest that a high genetic burden confers an adverse lipid profile and predicts attenuated response in LDL-C levels and small LDL particle number to dietary and physical activity interventions aimed at weight loss

Comprehensive Analysis of Established Dyslipidemia-Associated Loci in the Diabetes Prevention Program

Background-We assessed whether 234 established dyslipidemia-associated loci modify the effects of metformin treatment and lifestyle intervention (versus placebo control) on lipid and lipid subfraction levels in the Diabetes Prevention Program randomized controlled trial. Methods and Results-We tested gene treatment interactions in relation to baseline-adjusted follow-up blood lipid concentrations (high-density lipoprotein [HDL] and low-density lipoprotein-cholesterol, total cholesterol, and triglycerides) and lipoprotein subfraction particle concentrations and size in 2993 participants with pre-diabetes. Of the previously reported single-nucleotide polymorphism associations, 32.5% replicated at PP>1.1×10-16) with their respective baseline traits for all but 2 traits. Lifestyle modified the effect of the genetic risk score for large HDL particle numbers, such that each risk allele of the genetic risk scores was associated with lower concentrations of large HDL particles at follow-up in the lifestyle arm (β=-0.11 μmol/L per genetic risk scores risk allele; 95% confidence interval,-0.188 to-0.033; P=5×10-3; Pinteraction=1×10-3 for lifestyle versus placebo), but not in the metformin or placebo arms (P>0.05). In the lifestyle arm, participants with high genetic risk had more favorable or similar trait levels at 1-year compared with participants at lower genetic risk at baseline for 17 of the 20 traits. Conclusions-Improvements in large HDL particle concentrations conferred by lifestyle may be diminished by genetic factors. Lifestyle intervention, however, was successful in offsetting unfavorable genetic loading for most lipid traits. Clinical Trial Registration-URL: https://www.clinicaltrials.gov. Unique Identifier: NCT00004992

The Impact of the Species–Area Relationship on Estimates of Paleodiversity

Estimates of paleodiversity patterns through time have relied on datasets that lump taxonomic occurrences from geographic areas of varying size per interval of time. In essence, such estimates assume that the species–area effect, whereby more species are recorded from larger geographic areas, is negligible for fossil data. We tested this assumption by using the newly developed Miocene Mammal Mapping Project database of western North American fossil mammals and its associated analysis tools to empirically determine the geographic area that contributed to species diversity counts in successive temporal bins. The results indicate that a species–area effect markedly influences counts of fossil species, just as variable spatial sampling influences diversity counts on the modern landscape. Removing this bias suggests some traditionally recognized peaks in paleodiversity are just artifacts of the species–area effect while others stand out as meriting further attention. This discovery means that there is great potential for refining existing time-series estimates of paleodiversity, and for using species–area relationships to more reliably understand the magnitude and timing of such biotically important events as extinction, lineage diversification, and long-term trends in ecological structure

Does transient increase in axial length during accommodation attenuate with age?

Background: The aim was to profile transient accommodative axial length (AXL) changes from early adulthood to advanced presbyopia and to determine whether any differences exist between the responses of myopic and emmetropic individuals. Methods: Ocular biometry was measured by the LenStar biometer (Haag-Streit, Switzerland) in response to 0.00, 3.00 and 4.50 D accommodative stimuli in 35 emmetropes and 37 myopes, aged 18 to 60 years. All results were corrected to reduce errors arising from the increase in crystalline lens thickness with accommodation. Accommodative responses were measured sequentially by the WAM 5500 Auto Ref/Keratometer (Grand Seiko, Japan). Results: AXL increased significantly with accommodation (p<0.001), with a mean corrected AXL elongation of 2 ± 18 µm and 8 ± 16 µm observed at 3.00 D and 4.50 D, respectively. The magnitude of accommodative AXL change was not dependent on refractive error classification (p=0.959), however a significant reduction in the magnitude and variance of AXL change was evident after 43-44 years of age (p<0.002). Conclusion: The negative association between transient AXL elongation and age, in combination with reduced variance of data after age 43-44 years, is consistent with a significant increase in posterior ocular rigidity, which may be influential in the development of presbyopia

Transcriptome Analysis and SNP Development Can Resolve Population Differentiation of Streblospio benedicti, a Developmentally Dimorphic Marine Annelid

Next-generation sequencing technology is now frequently being used to develop genomic tools for non-model organisms, which are generally important for advancing studies of evolutionary ecology. One such species, the marine annelid Streblospio benedicti, is an ideal system to study the evolutionary consequences of larval life history mode because the species displays a rare offspring dimorphism termed poecilogony, where females can produce either many small offspring or a few large ones. To further develop S. benedicti as a model system for studies of life history evolution, we apply 454 sequencing to characterize the transcriptome for embryos, larvae, and juveniles of this species, for which no genomic resources are currently available. Here we performed a de novo alignment of 336,715 reads generated by a quarter GS-FLX (Roche 454) run, which produced 7,222 contigs. We developed a novel approach for evaluating the site frequency spectrum across the transcriptome to identify potential signatures of selection. We also developed 84 novel single nucleotide polymorphism (SNP) markers for this species that are used to distinguish coastal populations of S. benedicti. We validated the SNPs by genotyping individuals of different developmental modes using the BeadXPress Golden Gate assay (Illumina). This allowed us to evaluate markers that may be associated with life-history mode

Plasma Dynamics

Contains table of contents for Section 2 and reports on four research projects.Lawrence Livermore National Laboratory Subcontract 6264005National Science Foundation Grant ECS 84-13173National Science Foundation Grant ECS 85-14517U.S. Air Force - Office of Scientific Research Contract AFOSR 89-0082-AU.S. Army - Harry Diamond Laboratories Contract DAAL02-86-C-0050U.S. Navy - Office of Naval Research Contract N00014-87-K-2001Lawrence Livermore National Laboratory Subcontract B108472National Science Foundation Grant ECS 88-22475U.S. Department of Energy Contract DE-FG02-91-ER-54109National Aeronautics and Space Administration Grant NAGW-2048U.S. Department of Energy Contract DE-AC02-ET-51013U.S. Department of Energy Contract DE-AC02-78-ET-5101

Plasma Dynamics

Contains table of contents for Section 2 and reports on four research projects.Lawrence Livermore National Laboratory Subcontract 6264005National Science Foundation Grant ECS 84-13173National Science Foundation Grant ECS 85-14517U.S. Air Force - Office of Scientific Research Contract AFOSR 84-0026U.S. Army - Harry Diamond Laboratories Contract DAAL02-86-C-0050U.S. Navy - Office of Naval Research Contract N00014-87-K-2001National Science Foundation Grant ECS 85-15032National Science Foundation Grant ECS 88-22475U.S. Department of Energy Contract DE-AC02-ET-5101

Plasma Dynamics

Contains table of contents for Section 2 and reports on four research projects.National Science Foundation Grant ECS 89-02990U.S. Air Force - Office of Scientific Research Grant AFOSR 89-0082-BU.S. Army - Harry Diamond Laboratories Contract DAAL02-89-K-0084U.S. Department of Energy Contract DE-AC02-90ER40591U.S. Navy - Office of Naval Research Grant N00014-90-J-4130Lawrence Livermore National Laboratory Subcontract B-160456National Science Foundation Grant ECS 88-22475U.S. Department of Energy Contract DE-FG02-91-ER-54109National Aeronautics and Space Administration Grant NAGW-2048U.S.-Israel Binational Science Foundation Grant 87-0057U.S Department of Energy Contract DE-AC02-78-ET-5101