Association of two apolipoprotein A-I gene MspI polymorphisms with high density lipoprotein (HDL)-cholesterol levels and indices of obesity in selected healthy Chinese subjects and in patients with early-onset type 2 diabetes

OBJECTIVE: Previous studies have reported associations between two apolipoprotein A-I (apoA-I) gene MspI polymorphisms (G-75A and C83T) and high density lipoprotein (HDL)-cholesterol and/or apoA-I levels, but have not investigated the relationship with obesity. METHODS: We determined the distribution of these polymorphisms in 482 early-onset (< or = 40 years) Type 2 Chinese diabetics and 167 Chinese selected healthy controls. RESULTS: The -75A and 83T allele frequencies were similar in the diabetic and healthy subjects. In the healthy control subjects, HDL-cholesterol levels were significantly higher in the AA homozygotes than in the GG/GA carriers (1.74 +/- 0.58 vs. 1.45 +/- 0.58 mmol/l, P<0.001). Furthermore, analyses showed a significant relationship between increasing HDL-cholesterol tertiles and the AA genotype frequency in the selected healthy subjects (3.6, 8.9 and 16.1%, P=0.026). For the C83T polymorphism, healthy male CT carriers had higher HDL-cholesterol levels than CC homozygotes (1.71 +/- 0.57 vs. 1.25 +/- 0.30 mmol/l, P=0.001), but this was not found in females. No relationship between these polymorphisms and lipid levels was found in the diabetics, who had a more adverse lipid profile than the selected controls. In the diabetics, but not the controls, in CT carriers compared to CC homozygotes there were lower levels of body mass index (BMI; 23.8 +/- 3.9 vs. 25.4 +/- 4.7 kg/m2, P=0.048) and waist-to-height ratio (0.49 +/- 0.06 vs. 0.52 +/- 0.07, P=0.023), and this relationship was supported by tertile analysis. CONCLUSIONS: The -75AA genotype was associated with higher HDL-cholesterol levels in the selected healthy, but not diabetic, subjects. The 83T allele was associated with greater indices of obesity in the diabetic patients, and with higher HDL-cholesterol in heterozygous healthy male subjects.postprin

Transmission of methicillin-resistant staphylococcus aureus in the long term care facilities in Hong Kong

Background The relative contribution of long term care facilities (LTCFs) and hospitals in the transmission of methicillin-resistant Staphylococcus aureus (MRSA) is unknown. Methods Concurrent MRSA screening and spa type analysis was performed in LTCFs and their network hospitals to estimate the rate of MRSA acquisition among residents during their stay in LTCFs and hospitals, by colonization pressure and MRSA transmission calculations. Results In 40 LTCFs, 436 (21.6%) of 2020 residents were identified as ‘MRSA-positive’. The incidence of MRSA transmission per 1000-colonization-days among the residents during their stay in LTCFs and hospitals were 309 and 113 respectively, while the colonization pressure in LTCFs and hospitals were 210 and 185 per 1000-patient-days respectively. MRSA spa type t1081 was the most commonly isolated linage in both LTCF residents (76/121, 62.8%) and hospitalized patients (51/87, 58.6%), while type t4677 was significantly associated with LTCF residents (24/121, 19.8%) compared with hospitalized patients (3/87, 3.4%) (p < 0.001). This suggested continuous transmission of MRSA t4677 among LTCF residents. Also, an inverse linear relationship between MRSA prevalence in LTCFs and the average living area per LTCF resident was observed (Pearson correlation −0.443, p = 0.004), with the odds of patients acquiring MRSA reduced by a factor of 0.90 for each 10 square feet increase in living area. Conclusions Our data suggest that MRSA transmission was more serious in LTCFs than in hospitals. Infection control should be focused on LTCFs in order to reduce the burden of MRSA carriers in healthcare settings.published_or_final_versio

Tunable bipolar optical interactions between guided lightwaves

The optical binding forces between guided lightwaves in dielectric waveguides can be either repulsive or attractive. So far only attractive force has been observed. Here we experimentally demonstrate a bipolar optical force between coupled nanomechanical waveguides. Both attractive and repulsive optical forces are obtained. The sign of the force can be switched reversibly by tuning the relative phase of the interacting lightwaves. This tunable, bipolar interaction forms the foundation for the operation of a new class of light force devices and circuits.Comment: 4 figure

Imaging Chromophores With Undetectable Fluorescence by Stimulated Emission Microscopy

Fluorescence, that is, spontaneous emission, is generally more sensitive than absorption measurement, and is widely used in optical imaging. However, many chromophores, such as haemoglobin and cytochromes, absorb but have undetectable fluorescence because the spontaneous emission is dominated by their fast non-radiative decay. Yet the detection of their absorption is difficult under a microscope. Here we use stimulated emission, which competes effectively with the nonradiative decay, to make the chromophores detectable, and report a new contrast mechanism for optical microscopy. In a pump-probe experiment, on photoexcitation by a pump pulse, the sample is stimulated down to the ground state by a time-delayed probe pulse, the intensity of which is concurrently increased. We extract the miniscule intensity increase with shot-noise-limited sensitivity by using a lock-in amplifier and intensity modulation of the pump beam at a high megahertz frequency. The signal is generated only at the laser foci owing to the nonlinear dependence on the input intensities, providing intrinsic three-dimensional optical sectioning capability. In contrast, conventional one-beam absorption measurement exhibits low sensitivity, lack of three-dimensional sectioning capability, and complication by linear scattering of heterogeneous samples. We demonstrate a variety of applications of stimulated emission microscopy, such as visualizing chromoproteins, non-fluorescent variants of the green fluorescent protein, monitoring lacZ gene expression with a chromogenic reporter, mapping transdermal drug distributions without histological sectioning, and label-free microvascular imaging based on endogenous contrast of haemoglobin. For all these applications, sensitivity is orders of magnitude higher than for spontaneous emission or absorption contrast, permitting nonfluorescent reporters for molecular imaging.Chemistry and Chemical Biolog

Identification of genetic effects underlying Type 2 Diabetes in South Asian and European populations

South Asians are at high risk of developing type 2 diabetes (T2D). We carried out a genome-wide association meta-analysis with South Asian T2D cases (n=16,677) and controls (n=33,856), followed by combined analyses with Europeans (neff=231,420). We identify 21 novel genetic loci for significant association with T2D (P=4.7x10-8 to 5.2x10-12), to the best of our knowledge at the point of analysis. The loci are enriched for regulatory features, including DNA methylation and gene expression in relevant tissues, and highlight CHMP4B, PDHB, LRIG1 and other genes linked to adiposity and glucose metabolism. A polygenic risk score based on South Asian-derived summary statistics shows ~4-fold higher risk for T2D between the top and bottom quartile. Our results provide further insights into the genetic mechanisms underlying T2D, and highlight the opportunities for discovery from joint analysis of data from across ancestral populations

Ontology-guided data preparation for discovering genotype-phenotype relationships

International audienceComplexity of post-genomic data and multiplicity of mining strategies are two limits to Knowledge Discovery in Databases (KDD) in life sciences. Because they provide a semantic frame to data and because they benefit from the progress of semantic web technologies, bio-ontologies should be considered for playing a key role in the KDD process. In the frame of a case study relative to the search of genotype-phenotype relationships, we demonstrate the capability of bio-ontologies to guide data selection during the preparation step of the KDD process. We propose three scenarios to illustrate how domain knowledge can be taken into account in order to select or aggregate data to mine, and consequently how it can facilitate result interpretation at the end of the process

Genetic drivers of heterogeneity in type 2 diabetes pathophysiology.

Type 2 diabetes (T2D) is a heterogeneous disease that develops through diverse pathophysiological processes1,2 and molecular mechanisms that are often specific to cell type3,4. Here, to characterize the genetic contribution to these processes across ancestry groups, we aggregate genome-wide association study data from 2,535,601 individuals (39.7% not of European ancestry), including 428,452 cases of T2D. We identify 1,289 independent association signals at genome-wide significance (P < 5 × 10-8) that map to 611 loci, of which 145 loci are, to our knowledge, previously unreported. We define eight non-overlapping clusters of T2D signals that are characterized by distinct profiles of cardiometabolic trait associations. These clusters are differentially enriched for cell-type-specific regions of open chromatin, including pancreatic islets, adipocytes, endothelial cells and enteroendocrine cells. We build cluster-specific partitioned polygenic scores5 in a further 279,552 individuals of diverse ancestry, including 30,288 cases of T2D, and test their association with T2D-related vascular outcomes. Cluster-specific partitioned polygenic scores are associated with coronary artery disease, peripheral artery disease and end-stage diabetic nephropathy across ancestry groups, highlighting the importance of obesity-related processes in the development of vascular outcomes. Our findings show the value of integrating multi-ancestry genome-wide association study data with single-cell epigenomics to disentangle the aetiological heterogeneity that drives the development and progression of T2D. This might offer a route to optimize global access to genetically informed diabetes care

A Low-Frequency Inactivating Akt2 Variant Enriched in the Finnish Population is Associated With Fasting Insulin Levels and Type 2 Diabetes Risk

To identify novel coding association signals and facilitate characterization of mechanisms influencing glycemic traits and type 2 diabetes risk, we analyzed 109,215 variants derived from exome array genotyping together with an additional 390,225 variants from exome sequence in up to 39,339 normoglycemic individuals from five ancestry groups. We identified a novel association between the coding variant (p.Pro50Thr) in AKT2 and fasting insulin, a gene in which rare fully penetrant mutations are causal for monogenic glycemic disorders. The low-frequency allele is associated with a 12% increase in fasting plasma insulin (FI) levels. This variant is present at 1.1% frequency in Finns but virtually absent in individuals from other ancestries. Carriers of the FI-increasing allele had increased 2-hour insulin values, decreased insulin sensitivity, and increased risk of type 2 diabetes (odds ratio=1.05). In cellular studies, the AKT2-Thr50 protein exhibited a partial loss of function. We extend the allelic spectrum for coding variants in AKT2 associated with disorders of glucose homeostasis and demonstrate bidirectional effects of variants within the pleckstrin homology domain of AKT2.Academy of Finland (129293, 128315, 129330, 131593, 139635, 139635, 121584, 126925, 124282, 129378, 258753); Action on Hearing Loss (G51); Ahokas Foundation; American Diabetes Association (#7-12-MN-02); Atlantic Canada Opportunities Agency; Augustinus foundation; Becket foundation; Benzon Foundation; Biomedical Research Council; British Heart Foundation (SP/04/002); Canada Foundation for Innovation; Commission of the European Communities, Directorate C-Public Health (2004310); Copenhagen County; Danish Centre for Evaluation and Health Technology Assessment; Danish Council for Independent Research; Danish Heart Foundation (07-10-R61-A1754-B838-22392F); Danish Medical Research Council; Danish Pharmaceutical Association; Emil Aaltonen Foundation; European Research Council Advanced Research Grant; European Union FP7 (EpiMigrant, 279143; FP7/2007-2013; 259749); Finland's Slottery Machine Association; Finnish Cultural Foundation; Finnish Diabetes Research Foundation; Finnish Foundation for Cardiovascular Research; Finnish Foundation of Cardiovascular Research; Finnish Medical Society; Finnish National Public Health Institute; Finska Läkaresällskapet; Folkhälsan Research Foundation; Foundation for Life and Health in Finland; German Center for Diabetes Research (DZD) ; German Federal Ministry of Education and Research; Health Care Centers in Vasa, Närpes and Korsholm; Health Insurance Foundation (2012B233) ; Helsinki University Central Hospital Research Foundation; Hospital districts of Pirkanmaa, Southern Ostrobothnia, North Ostrobothnia, Central Finland, and Northern Savo; Ib Henriksen foundation; Juho Vainio Foundation; Korea Centers for Disease Control and Prevention (4845–301); Korea National Institute of Health (2012-N73002-00); Li Ka Shing Foundation; Liv och Hälsa; Lundbeck Foundation; Marie-Curie Fellowship (PIEF-GA-2012-329156); Medical Research Council (G0601261, G0900747-91070, G0601966, G0700931); Ministry of Education in Finland; Ministry of Social Affairs and Health in Finland; MRC-PHE Centre for Environment and Health;Municipal Heath Care Center and Hospital in Jakobstad; Närpes Health Care Foundation; National Institute for Health Research (RP-PG-0407-10371); National Institutes of Health (U01 DK085526, U01 DK085501, U01 DK085524, U01 DK085545, U01 DK085584, U01 DK088389, RC2-DK088389, DK085545, DK098032, HHSN268201300046C, HHSN268201300047C, HHSN268201300048C, HHSN268201300049C, HHSN, R01MH107666 and K12CA139160268201300050C, U01 DK062370, R01 DK066358, U01DK085501, R01HL102830, R01DK073541, PO1AG027734, R01AG046949, 1R01AG042188, P30AG038072, R01 MH101820, R01MH090937, P30DK020595, R01 DK078616, NIDDK K24 DK080140, 1RC2DK088389, T32GM007753); National Medical Research Council; National Research Foundation of Korea (NRF-2012R1A2A1A03006155); Nordic Center of Excellence in Disease Genetics; Novo Nordisk; Ollqvist Foundation; OrionFarmos Research Foundation; Paavo Nurmi Foundation; Perklén Foundation; Samfundet Folkhälsan; Signe and Ane Gyllenberg Foundation; Sigrid Juselius Foundation; Social Insurance Institution of Finland; South East Norway Health Authority (2011060); Swedish Cultural Foundation in Finland; Swedish Heart-Lung Foundation; Swedish Research Council; Swedish Research Council (Linné and Strategic Research Grant); The American Federation for Aging Research; The Einstein Glenn Center; The European Commission (HEALTH-F4-2007-201413); The Finnish Diabetes Association; The Folkhälsan Research Foundation; The Påhlssons Foundation; The provinces of Newfoundland and Labrador, Nova Scotia, and New Brunswick; The Sigrid Juselius Foundation; The Skåne Regional Health Authority; The Swedish Heart-Lung Foundation; Timber Merchant Vilhelm Bang’s Foundation; Turku University Foundation; Uppsala University; Wellcome Trust (064890, 083948, 085475, 086596, 090367, 090532, 092447, 095101/Z/10/Z, 200837/Z/16/Z, 095552, 098017, 098381, 098051, 084723, 072960/2/ 03/2, 086113/Z/08/Z, WT098017, WT064890, WT090532, WT098017, 098051, WT086596/Z/08/A and 086596/Z/08/Z). Detailed acknowledgment of funding sources is provided in the Additional Acknowledgements section of the Supplementary Materials