Addition of Inflammatory Biomarkers Did Not Improve Diabetes Prediction in the Community: The Framingham Heart Study

Background: Prior studies have reported conflicting findings with regard to the association of biomarkers in the prediction of incident type 2 diabetes. We evaluated 12 biomarkers as possible diabetes predictors in the Framingham Heart Study. Methods and results: Biomarkers representing inflammation (C-reactive protein, interleukin-6, monocyte chemoattractant protein-1, tumor necrosis factor receptor 2, osteoprotegerin, and fibrinogen), endothelial dysfunction (intercellular adhesion molecule-1), vascular damage (CD40-ligand, P-selectin, and lipoprotein-associated phospholipase A2 mass and activity), and oxidative stress (urinary isoprostanes) were measured in participants without diabetes attending the Offspring seventh (n=2499) or multiethnic Omni second (n=189) examination (1998–2001). Biomarkers were loge transformed and standardized. Multivariable logistic regression tested each biomarker in association with incident diabetes at a follow-up examination (the Offspring eighth and Omni third examination; mean 6.6 years later), with adjustment for age, sex, cohort, body mass index, fasting glucose, systolic blood pressure, high-density lipoprotein cholesterol, triglycerides, and smoking. C statistics were evaluated with and without inflammatory markers. In 2638 participants (56% women, mean age 59 years), 162 (6.1%) developed type 2 diabetes. All biomarkers, excluding osteoprotegerin, were associated with the outcome with adjustment for age, sex, and cohort; however, none remained significant after multivariable adjustment (all P>0.05). The c statistic from the model including only clinical covariates (0.89) did not statistically significantly improve after addition of biomarkers (all P>0.10). Conclusions: Biomarkers representing different inflammatory pathways are associated with incident diabetes but do not remain statistically significant after adjustment for established clinical covariates. Inflammatory biomarkers might not be an effective resource to predict type 2 diabetes in community-based samples

Spatially distinct, temporally stable microbial populations mediate biogeochemical cycling at and below the seafloor in hydrothermal vent fluids

© The Author(s), 2017. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Environmental Microbiology 20 (2018): 769–784, doi:10.1111/1462-2920.14011.At deep-sea hydrothermal vents, microbial communities thrive across geochemical gradients above, at, and below the seafloor. In this study, we determined the gene content and transcription patterns of microbial communities and specific populations to understand the taxonomy and metabolism both spatially and temporally across geochemically different diffuse fluid hydrothermal vents. Vent fluids were examined via metagenomic, metatranscriptomic, genomic binning, and geochemical analyses from Axial Seamount, an active submarine volcano on the Juan de Fuca Ridge in the NE Pacific Ocean, from 2013 to 2015 at three different vents: Anemone, Marker 33, and Marker 113. Results showed that individual vent sites maintained microbial communities and specific populations over time, but with spatially distinct taxonomic, metabolic potential, and gene transcription profiles. The geochemistry and physical structure of each vent both played important roles in shaping the dominant organisms and metabolisms present at each site. Genomic binning identified key populations of SUP05, Aquificales and methanogenic archaea carrying out important transformations of carbon, sulfur, hydrogen, and nitrogen, with groups that appear unique to individual sites. This work highlights the connection between microbial metabolic processes, fluid chemistry, and microbial population dynamics at and below the seafloor and increases understanding of the role of hydrothermal vent microbial communities in deep ocean biogeochemical cycles.Gordon and Betty Moore Foundation Grant Number: GBMF3297; NSF Center for Dark Energy Biosphere Investigations Grant Number: OCE—0939564; Schmidt Ocean Institut

Adiposity, Cardiometabolic Risk, and Vitamin D Status: The Framingham Heart Study

OBJECTIVE: Because vitamin D deficiency is associated with a variety of chronic diseases, understanding the characteristics that promote vitamin D deficiency in otherwise healthy adults could have important clinical implications. Few studies relating vitamin D deficiency to obesity have included direct measures of adiposity. Furthermore, the degree to which vitamin D is associated with metabolic traits after adjusting for adiposity measures is unclear. RESEARCH DESIGN AND METHODS: We investigated the relations of serum 25-hydroxyvitamin D (25[OH]D) concentrations with indexes of cardiometabolic risk in 3,890 nondiabetic individuals; 1,882 had subcutaneous adipose tissue (SAT) and visceral adipose tissue (VAT) volumes measured by multidetector computed tomography (CT). RESULTS: In multivariable-adjusted regression models, 25(OH)D was inversely associated with winter season, waist circumference, and serum insulin (P < 0.005 for all). In models further adjusted for CT measures, 25(OH)D was inversely related to SAT (−1.1 ng/ml per SD increment in SAT, P = 0.016) and VAT (−2.3 ng/ml per SD, P < 0.0001). The association of 25(OH)D with insulin resistance measures became nonsignificant after adjustment for VAT. Higher adiposity volumes were correlated with lower 25(OH)D across different categories of BMI, including in lean individuals (BMI <25 kg/m2). The prevalence of vitamin D deficiency (25[OH]D <20 ng/ml) was threefold higher in those with high SAT and high VAT than in those with low SAT and low VAT (P < 0.0001). CONCLUSIONS: Vitamin D status is strongly associated with variation in subcutaneous and especially visceral adiposity. The mechanisms by which adiposity promotes vitamin D deficiency warrant further study.National Institutes of Health's National Heart, Lung, and Blood Institute (N01-HC-25195, R01-DK-80739): American Heart Associatio

Using Family-Based Imputation in Genome-Wide Association Studies with Large Complex Pedigrees: The Framingham Heart Study

Imputation has been widely used in genome-wide association studies (GWAS) to infer genotypes of un-genotyped variants based on the linkage disequilibrium in external reference panels such as the HapMap and 1000 Genomes. However, imputation has only rarely been performed based on family relationships to infer genotypes of un-genotyped individuals. Using 8998 Framingham Heart Study (FHS) participants genotyped with Affymetrix 550K SNPs, we imputed genotypes of same set of SNPs for additional 3121 participants, most of whom were never genotyped due to lack of DNA sample. Prior to imputation, 122 pedigrees were too large to be handled by the imputation software Merlin. Therefore, we developed a novel pedigree splitting algorithm that can maximize the number of genotyped relatives for imputing each un-genotyped individual, while keeping new sub-pedigrees under a pre-specified size. In GWAS of four phenotypes available in FHS (Alzheimer disease, circulating levels of fibrinogen, high-density lipoprotein cholesterol, and uric acid), we compared results using genotyped individuals only with results using both genotyped and imputed individuals. We studied the impact of applying different imputation quality filtering thresholds on the association results and did not found a universal threshold that always resulted in a more significant p-value for previously identified loci. However most of these loci had a lower p-value when we only included imputed genotypes with with ≥60% SNP- and ≥50% person-specific imputation certainty. In summary, we developed a novel algorithm for splitting large pedigrees for imputation and found a plausible imputation quality filtering threshold based on FHS. Further examination may be required to generalize this threshold to other studies

Increasing Written Language Skills Utilizing Writing Software and Traditional Methods

A grid based computer program, Clicker5, appeared to have many features that logically may assist struggling writers. It utilizes pictures, sound, speech synthesis, word banks and a spelling checker. Karemaker et al. (2008) examined the use of Clicker5 and observed increased attention and focus during reading, and greater gains in word recognition and rhyme awareness. Scattered research exists on some of the multimedia features that Clicker5 utilizes (e.g. auditory and visual instruction, specific feedback, student specific examples, Wissick & Gardner, 2000; composition processes and revision facilitation, MacArthur 2000; spell checkers with strategy instruction, and speech synthesis to increase error detection and correction, Borgh & Dickson, 1992). However, no research exists on writing outcomes utilizing Clicker5. The purpose of this study was to evaluate the effectiveness of individual Clicker instruction on classroom hand-written products and individually generated computer-assisted written products for children with speech-language deficits who were identified as weak writers by their teachers. A single subject multiple baseline across subjects design was utilized to investigate the research question. The participants included 2 matched pairs of second grade students from two second grade classrooms demonstrating speech-language deficits and difficulty with writing. They were identified by teachers and the speech-language pathologist (SLP) at the Shelbyville elementary school as being at risk for reading difficulty. In the regular classroom, the Daily 6-Trait Writing program was utilized for writing instruction, and consisted of five days of instruction over a 25 week period. The students in the regular classroom filled in a graphic organizer to a writing prompt on the fourth day, and responded to the prompt on the fifth day. The intervention was conducted with one student from each matched pair in two phases, one in the fall and one in the spring, and included three 20 minute sessions each week for four weeks. Each Friday, the subjects responded to the writing prompt in the regular classroom, and then responded to it utilizing Clicker5 independently. These responses were scored on measures of form and content including total number of words, number of different words (NDW), mean length of utterance (MLU), spelling and grammatical accuracy, and local and global coherence. Results indicated good growth in a relatively short treatment period. The phase 1 intervention subject demonstrated an increase from the initial to final writing samples in the classroom and using Clicker5 on measures of total number of words, NDW and MLU. The phase 2 intervention subject demonstrated gains on the same measures when using Clicker5 to respond to the writing prompt. Overall, spelling accuracy was higher when the subjects used Clicker5 to respond to the writing prompts. The intervention subjects also scored highest on total number of words and NDW when using Clicker5 across subjects and samples. Clinical implications include that the subjects demonstrated motivation and enjoyment when using the software program. Some limitations may be that the independent response was conducted in the presence of the primary investigator, and there was inconsistency in the classroom instruction from week to week. Future directions include a multiple baseline across subjects design and a longer treatment period with more participants

Metallicity Gradients at Large Galactocentric Radii Using the Near-infrared Calcium Triplet

We describe a new spectroscopic technique for measuring radial metallicity gradients out to large galactocentric radii. We use the DEIMOS multi-object spectrograph on the Keck telescope and the galaxy spectrum extraction technique of Proctor et al. (2009). We also make use of the metallicity sensitive near-infrared (NIR) Calcium triplet (CaT) features together with single stellar population models to obtain metallicities. Our technique is applied as a pilot study to a sample of three relatively nearby (<30 Mpc) intermediate-mass to massive early-type galaxies. Results are compared with previous literature inner region values and generally show good agreement. We also include a comparison with profiles from dissipational disk-disk major merger simulations. Based on our new extended metallicity gradients combined with other observational evidence and theoretical predictions, we discuss possible formation scenarios for the galaxies in our sample. The limitations of our new technique are also discussed.Comment: 13 Pages, 9 Figures, 7 Tables, Accepted for publication in MNRA

Thoracic Periaortic and Visceral Adipose Tissue and Their Cross-sectional Associations with Measures of Vascular Function

Objective: Perivascular fat may have a local adverse effect on the vasculature. We evaluated whether thoracic periaortic adipose tissue (TAT), a type of perivascular fat, and visceral adipose tissue (VAT) are associated with vascular function. Design and Methods TAT and VAT were quantified in Framingham Heart Study participants using multidetector computed tomography; vascular function was assessed using brachial artery vasodilator function, peripheral arterial tone and arterial tonometry (n= 2735, 48% women, mean age 50 years, mean BMI 27.7 kg/m2). Using multiple linear regression, we examined relations between TAT, VAT, and vascular measures while adjusting for cardiovascular risk factors. Results: Mean TAT and VAT volumes were 13.2 and 1763 cm3. TAT and VAT were associated with multiple vascular function measures after multivariable adjustment. After BMI adjustment, TAT and VAT remained negatively associated with peripheral arterial tone and inverse carotid femoral pulse wave velocity (p0.06). Conclusion: Thoracic periaortic and visceral fat are associated with microvascular function and large artery stiffness after BMI adjustment. These findings support the growing recognition of associations between ectopic fat and vascular function

CLASS: The Cosmology Large Angular Scale Surveyor

The Cosmology Large Angular Scale Surveyor (CLASS) is an experiment to measure the signature of a gravita-tional-wave background from inflation in the polarization of the cosmic microwave background (CMB). CLASS is a multi-frequency array of four telescopes operating from a high-altitude site in the Atacama Desert in Chile. CLASS will survey 70\% of the sky in four frequency bands centered at 38, 93, 148, and 217 GHz, which are chosen to straddle the Galactic-foreground minimum while avoiding strong atmospheric emission lines. This broad frequency coverage ensures that CLASS can distinguish Galactic emission from the CMB. The sky fraction of the CLASS survey will allow the full shape of the primordial B-mode power spectrum to be characterized, including the signal from reionization at low $\ell$. Its unique combination of large sky coverage, control of systematic errors, and high sensitivity will allow CLASS to measure or place upper limits on the tensor-to-scalar ratio at a level of $r=0.01$ and make a cosmic-variance-limited measurement of the optical depth to the surface of last scattering, $\tau$.Comment: 23 pages, 10 figures, Presented at SPIE Astronomical Telescopes and Instrumentation 2014: Millimeter, Submillimeter, and Far-Infrared Detectors and Instrumentation for Astronomy VII. To be published in Proceedings of SPIE Volume 915

Validated SNPs for eGFR and their associations with albuminuria

Albuminuria and reduced glomerular filtration rate are manifestations of chronic kidney disease (CKD) that predict end-stage renal disease, acute kidney injury, cardiovascular disease and death. We hypothesized that SNPs identified in association with the estimated glomerular filtration rate (eGFR) would also be associated with albuminuria. Within the CKDGen Consortium cohort (n= 31 580, European ancestry), we tested 16 eGFR-associated SNPs for association with the urinary albumin-to-creatinine ratio (UACR) and albuminuria [UACR >25 mg/g (women); 17 mg/g (men)]. In parallel, within the CARe Renal Consortium (n= 5569, African ancestry), we tested seven eGFR-associated SNPs for association with the UACR. We used a Bonferroni-corrected P-value of 0.003 (0.05/16) in CKDGen and 0.007 (0.05/7) in CARe. We also assessed whether the 16 eGFR SNPs were associated with the UACR in aggregate using a beta-weighted genotype score. In the CKDGen Consortium, the minor A allele of rs17319721 in the SHROOM3 gene, known to be associated with a lower eGFR, was associated with lower ln(UACR) levels (beta = −0.034, P-value = 0.0002). No additional eGFR-associated SNPs met the Bonferroni-corrected P-value threshold of 0.003 for either UACR or albuminuria. In the CARe Renal Consortium, there were no associations between SNPs and UACR with a P< 0.007. Although we found the genotype score to be associated with albuminuria (P= 0.0006), this result was driven almost entirely by the known SHROOM3 variant, rs17319721. Removal of rs17319721 resulted in a P-value 0.03, indicating a weak residual aggregate signal. No alleles, previously demonstrated to be associated with a lower eGFR, were associated with the UACR or albuminuria, suggesting that there may be distinct genetic components for these trait

Quantitative analysis of bone scans in prostate cancer patients

Prostate cancer (PCa) is one of the most common diseases in the world. PCa can primarily disseminate to the bone, causing bone metastases, which in turn can lead to death. It is important to diagnose bone metastases as soon as possible in order to treat the disease. Bone metastases are diagnosed commonly by bone scan imaging. However, interpretation of bone scan images is not always an easy task for physicians. One way of minimising the risk of misinterpretation is quantitative analysis of bone scan images in order to ascertain whether they show any metastatic lesions, and if so, to what extent. Quantification of the bone scan, i.e. the bone scan index (BSI) method, could be used for prognostication of survival, or to follow up the effect of treatment. The aim of the thesis was to develop and validate a fully automated method for the quantification of skeletal images in patients with prostate cancer based on the BSI method. This thesis is based on four papers. In paper 1, "A Novel Automated Platform for Quantifying the Extent of Skeletal Tumour Involvement in Prostate Cancer Patients Using the Bone Scan Index", we developed an automated BSI-quantification method, used it in a training group of 795 patients, compared it to a manual method and assessed the prognostic value of BSI in an evaluating group of 384 patients. The automated method showed a good correlation (r=80%) with the manual method, and BSI was strongly associated with prostate cancer death. In paper 2, "Bone Scan Index: a prognostic imaging biomarker for high-risk prostate cancer patients receiving primary hormonal therapy”, we found that BSI included prognostic information in addition to other clinical parameters such as “prostate-specific antigens”. Patients with BSI5. In paper 3, “Progression of Bone Metastases in Patients with Prostate Cancer - Automated Detection of New Lesions and Calculation of Bone Scan Index”, we further develop the automatic method to find new metastases using a training group of 266 patients. The method evaluated 31 patients who received chemotherapy. Patients with an increase in BSI during treatment had a lower two-year survival rate (18%) than those with a decrease in BSI (57%). In the final paper, “Assessment of baseline and longitudinal bone scan index measures in the context of a randomised placebo-controlled trial of tasquinimod in men with metastatic castration-resistant prostate cancer (mCRPC)”, we retrospectively calculated BSI at baseline and upon treatment in 85 patients from a clinical trial. We found that BSI and BSI change on-treatment were associated with survival. BSI correlated with known biomarkers of survival, but adds independent prognostic information. In conclusion, BSI calculated using an automated method contains prognostic information and can be used to evaluate treatment effects