Explore the vast range of titles available.

Improved understanding of the lung microbiome in HIV-infected individuals could lead to better strategies for diagnosis, therapy, and prophylaxis of HIV-associated pneumonias. Differences in the oral and lung microbiomes in HIV-infected and HIV-uninfected individuals are not well defined. Whether highly active antiretroviral therapy influences these microbiomes is unclear. We determined whether oral and lung microbiomes differed in clinically healthy groups of HIV-infected and HIV-uninfected subjects. Participating sites in the Lung HIV Microbiome Project contributed bacterial 16S rRNA sequencing data from oral washes and bronchoalveolar lavages (BALs) obtained from HIV-uninfected individuals (n = 86), HIV-infected individuals who were treatment naive (n = 18), and HIV-infected individuals receiving antiretroviral therapy (n = 38). Microbial populations differed in the oral washes among the subject groups (Streptococcus, Actinomyces, Rothia, and Atopobium), but there were no individual taxa that differed among the BALs. Comparison of oral washes and BALs demonstrated similar patterns from HIV-uninfected individuals and HIV-infected individuals receiving antiretroviral therapy, with multiple taxa differing in abundance. The pattern observed from HIV-infected individuals who were treatment naive differed from the other two groups, with differences limited to Veillonella, Rothia, and Granulicatella. CD4 cell counts did not influence the oral or BAL microbiome in these relatively healthy, HIV-infected subjects. The overall similarity of the microbiomes in participants with and without HIV infection was unexpected, because HIV-infected individuals with relatively preserved CD4 cell counts are at higher risk for lower respiratory tract infections, indicating impaired local immune function.

Genome-wide association studies have begun to elucidate the genetic architecture of type 2 diabetes. We examined whether single nucleotide polymorphisms (SNPs) identified through targeted complementary approaches affect diabetes incidence in the at-risk population of the Diabetes Prevention Program (DPP) and whether they influence a response to preventive interventions. We selected SNPs identified by prior genome-wide association studies for type 2 diabetes and related traits, or capturing common variation in 40 candidate genes previously associated with type 2 diabetes, implicated in monogenic diabetes, encoding type 2 diabetes drug targets or drug-metabolizing/transporting enzymes, or involved in relevant physiological processes. We analyzed 1,590 SNPs for association with incident diabetes and their interaction with response to metformin or lifestyle interventions in 2,994 DPP participants. We controlled for multiple hypothesis testing by assessing false discovery rates. We replicated the association of variants in the metformin transporter gene SLC47A1 with metformin response and detected nominal interactions in the AMP kinase (AMPK) gene STK11, the AMPK subunit genes PRKAA1 and PRKAA2, and a missense SNP in SLC22A1, which encodes another metformin transporter. The most significant association with diabetes incidence occurred in the AMPK subunit gene PRKAG2 (hazard ratio 1.24, 95% CI 1.09-1.40, P = 7 × 10(-4)). Overall, there were nominal associations with diabetes incidence at 85 SNPs and nominal interactions with the metformin and lifestyle interventions at 91 and 69 mostly nonoverlapping SNPs, respectively. The lowest P values were consistent with experiment-wide 33% false discovery rates. We have identified potential genetic determinants of metformin response. These results merit confirmation in independent samples.

The complex genetic architecture of type-2-diabetes (T2D) includes gene-by-environment (G×E) and gene-by-gene (G×G) interactions. To identify G×E and G×G, we screened markers for patterns indicative of interactions (relationship loci [rQTL] and variance heterogeneity loci [vQTL]). rQTL exist when the correlation between multiple traits varies by genotype and vQTL occur when the variance of a trait differs by genotype (potentially flagging G×G and G×E). In the metformin and placebo arms of the DPP (n = 1762) we screened 280,965 exomic and intergenic SNPs, for rQTL and vQTL patterns in association with year one changes from baseline in glycemia and related traits (insulinogenic index [IGI], insulin sensitivity index [ISI], fasting glucose and fasting insulin). Significant (p < 1.8 × 10−7) rQTL and vQTL generated a priori hypotheses of individual G×E tests for a SNP × metformin treatment interaction and secondarily for G×G screens. Several rQTL and vQTL identified led to 6 nominally significant (p < 0.05) metformin treatment × SNP interactions (4 for IGI, one insulin, and one glucose) and 12G×G interactions (all IGI) that exceeded experiment-wide significance (p < 4.1 × 10−9). Some loci are directly associated with incident diabetes, and others are rQTL and modify a trait’s relationship with diabetes (2 diabetes/glucose, 2 diabetes/insulin, 1 diabetes/IGI). rs3197999, an ISI/insulin rQTL, is a possible gene damaging missense mutation in MST1, is associated with ulcerative colitis, sclerosing cholangitis, Crohn’s disease, BMI and coronary artery disease. This study demonstrates evidence for context-dependent effects (G×G & G×E) and the complexity of these T2D-related traits.

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.

Type 2 Diabetes–Associated Missense Polymorphisms KCNJ11 E23K and ABCC8 A1369S Influence Progression to Diabetes and Response to Interventions in the Diabetes Prevention Program Jose C. Florez 1 2 3 4 , Kathleen A. Jablonski 5 , Steven E. Kahn 6 , Paul W. Franks 7 8 , Dana Dabelea 9 , Richard F. Hamman 9 , William C. Knowler 8 , David M. Nathan 2 3 , David Altshuler 1 2 3 4 10 and for the Diabetes Prevention Program Research Groupy * 1 Center for Human Genetic Research, Massachusetts General Hospital, Boston, Massachusetts 2 Department of Medicine, Massachusetts General Hospital, Boston, Massachusetts 3 Department of Medicine, Harvard Medical School, Boston, Massachusetts 4 Program in Medical and Population Genetics, Broad Institute of Harvard and Massachusetts Institute of Technology, Cambridge, Massachusetts 5 Biostatistics Center, George Washington University, Rockville, Maryland 6 Division of Metabolism, Endocrinology and Nutrition, Department of Medicine, VA Puget Sound Health Care System and University of Washington, Seattle, Washington 7 Genetic Epidemiology and Clinical Research Group, Institute of Public Health and Clinical Medicine, Umeå University Hospital, Umeå, Sweden 8 Diabetes Epidemiology and Clinical Research Section, National Institute of Diabetes and Digestive and Kidney Diseases, Phoenix, Arizona 9 Department of Preventive Medicine and Biometrics, University of Colorado at Denver and Health Sciences Center, Denver, Colorado 10 Department of Genetics, Harvard Medical School, Boston, Massachusetts Address correspondence and reprint requests to Jose C. Florez, Diabetes Prevention Program Coordinating Center, Biostatistics Center, George Washington University, 6110 Executive Blvd., Suite 750, Rockville, MD 20852. E-mail: dppmail{at}biostat.bsc.gwu.edu Abstract The common polymorphisms KCNJ11 E23K and ABCC8 A1369S have been consistently associated with type 2 diabetes. We examined whether these variants are also associated with progression from impaired glucose tolerance (IGT) to diabetes and responses to preventive interventions in the Diabetes Prevention Program. We genotyped both variants in 3,534 participants and performed Cox regression analysis using genotype, intervention, and their interactions as predictors of diabetes incidence over ∼3 years. We also assessed the effect of genotype on insulin secretion and insulin sensitivity at 1 year. As previously shown in other studies, lysine carriers at KCNJ11 E23K had reduced insulin secretion at baseline; however, they were less likely to develop diabetes than E/E homozygotes. Lysine carriers were less protected by 1-year metformin treatment than E/E homozygotes ( P < 0.02). Results for ABCC8 A1369S were essentially identical to those for KCNJ11 E23K. We conclude that the lysine variant in KCNJ11 E23K leads to diminished insulin secretion in individuals with IGT. Given our contrasting results compared with case-control analyses, we hypothesize that its effect on diabetes risk may occur before the IGT-to-diabetes transition. We further hypothesize that the diabetes-preventive effect of metformin may interact with the impact of these variants on insulin regulation. DPP, Diabetes Prevention Program IGT, impaired glucose tolerance OGTT, oral glucose tolerance test SNP, single nucleotide polymorphism Footnotes * * A list of the members of the Diabetes Prevention Program Research Group can be found in ref. 16 . The costs of publication of this article were defrayed in part by the payment of page charges. This article must therefore be hereby marked “advertisement” in accordance with 18 U.S.C. Section 1734 solely to indicate this fact. Accepted November 12, 2006. Received July 12, 2006. DIABETES

Extension of Type 2 Diabetes Genome-Wide Association Scan Results in the Diabetes Prevention Program Allan F. Moore 1 2 3 4 † , Kathleen A. Jablonski 5 , Jarred B. McAteer 1 4 , Richa Saxena 1 4 , Toni I. Pollin 6 , Paul W. Franks 7 , Robert L. Hanson 8 , Alan R. Shuldiner 6 , William C. Knowler 8 , David Altshuler 1 2 3 4 9 , Jose C. Florez 1 2 3 4 and for the Diabetes Prevention Program Research Group 1 Center for Human Genetic Research, Department of Medicine, Massachusetts General Hospital, Boston, Massachusetts 2 Diabetes Center, Department of Medicine, Massachusetts General Hospital, Boston, Massachusetts 3 Department of Medicine, Harvard Medical School, Boston, Massachusetts 4 Program in Medical and Population Genetics, Broad Institute of Harvard and Massachusetts Institute of Technology, Cambridge, Massachusetts 5 The Biostatistics Center, George Washington University, Rockville, Maryland 6 Department of Medicine, Division of Endocrinology, Diabetes, and Nutrition, University of Maryland School of Medicine, Baltimore, Maryland 7 Genetic Epidemiology and Clinical Research Group, Department of Public Health and Clinical Medicine, Division of Medicine, Umeå University Hospital, Umeå, Sweden 8 Diabetes Epidemiology and Clinical Research Section, National Institute of Diabetes and Digestive and Kidney Diseases, Phoenix, Arizona 9 Department of Genetics, Harvard Medical School, Boston, Massachusetts Corresponding author: Jose C. Florez, dppmail{at}biostat.bsc.gwu.edu Abstract OBJECTIVE— Genome-wide association scans (GWASs) have identified novel diabetes-associated genes. We evaluated how these variants impact diabetes incidence, quantitative glycemic traits, and response to preventive interventions in 3,548 subjects at high risk of type 2 diabetes enrolled in the Diabetes Prevention Program (DPP), which examined the effects of lifestyle intervention, metformin, and troglitazone versus placebo. RESEARCH DESIGN AND METHODS— We genotyped selected single nucleotide polymorphisms (SNPs) in or near diabetes-associated loci, including EXT2 , CDKAL1 , CDKN2A/B , IGF2BP2 , HHEX , LOC387761, and SLC30A8 in DPP participants and performed Cox regression analyses using genotype, intervention, and their interactions as predictors of diabetes incidence. We evaluated their effect on insulin resistance and secretion at 1 year. RESULTS— None of the selected SNPs were associated with increased diabetes incidence in this population. After adjustments for ethnicity, baseline insulin secretion was lower in subjects with the risk genotype at HHEX rs1111875 ( P = 0.01); there were no significant differences in baseline insulin sensitivity. Both at baseline and at 1 year, subjects with the risk genotype at LOC387761 had paradoxically increased insulin secretion; adjustment for self-reported ethnicity abolished these differences. In ethnicity-adjusted analyses, we noted a nominal differential improvement in β-cell function for carriers of the protective genotype at CDKN2A/B after 1 year of troglitazone treatment ( P = 0.01) and possibly lifestyle modification ( P = 0.05). CONCLUSIONS— We were unable to replicate the GWAS findings regarding diabetes risk in the DPP. We did observe genotype associations with differences in baseline insulin secretion at the HHEX locus and a possible pharmacogenetic interaction at CDKNA2/B . Footnotes Published ahead of print at http://diabetes.diabetesjournals.org on 10 June 2008. Clinical trial reg. no. NCT00004992, clinicaltrials.gov. A complete list of Diabetes Prevention Program Research Group investigators is provided in the online appendix available at http://dx.doi.org/10.2337/db08-0284 . † † Dr. Allan F. Moore passed away on 24 July 2008. This article, to which he contributed his privileged intellect and unwavering enthusiasm, is dedicated to his memory. His colleagues and peers will miss him. Readers may use this article as long as the work is properly cited, the use is educational and not for profit, and the work is not altered. See http://creativecommons.org/licenses/by-nc-nd/3.0/ for details. The costs of publication of this article were defrayed in part by the payment of page charges. This article must therefore be hereby marked “advertisement” in accordance with 18 U.S.C. Section 1734 solely to indicate this fact. Accepted June 1, 2008. Received February 28, 2008. DIABETES

Body Size and Shape Changes and the Risk of Diabetes in the Diabetes Prevention Program Wilfred Y. Fujimoto 1 , Kathleen A. Jablonski 2 , George A. Bray 3 , Andrea Kriska 4 , Elizabeth Barrett-Connor 5 , Steven Haffner 6 , Robert Hanson 7 , James O. Hill 8 , Van Hubbard 9 , E. Stamm 10 , F. Xavier Pi-Sunyer 11 and for the Diabetes Prevention Program Research Group 1 Department of Medicine, University of Washington, Seattle, Washington 2 Biostatistics Center, George Washington University, Rockville, Maryland 3 Pennington Biomedical Research Center, Baton Rouge, Louisiana 4 Department of Epidemiology, University of Pittsburgh Graduate School of Public Health, Pittsburgh, Pennsylvania 5 Department of Family and Preventive Medicine, School of Medicine, University of California San Diego, La Jolla, California 6 Department of Medicine, University of Texas Health Science Center at San Antonio, San Antonio, Texas 7 Phoenix Epidemiology and Clinical Research Branch, National Institute of Diabetes and Digestive and Kidney Diseases, Phoenix, Arizona 8 Center for Human Nutrition, University of Colorado School of Medicine, Denver, Colorado 9 Division of Nutrition Research, National Institute of Diabetes and Digestive and Kidney Diseases, Bethesda, Maryland 10 Department of Radiology, University of Colorado Health Sciences Center, Denver, Colorado 11 Department of Medicine, Roosevelt-St. Luke's Hospital, New York, New York Address correspondence and reprint requests to Wilfred Y. Fujimoto, MD, GWU Biostatistics Center DPPOS, 6110 Executive Blvd., Suite 750, Rockville, MD 20852. E-mail: dppmail{at}biostat.bsc.gwu.edu or wilfuji{at}u.washington.edu Abstract The researchers conducted this study to test the hypothesis that risk of type 2 diabetes is less following reductions in body size and central adiposity. The Diabetes Prevention Program (DPP) recruited and randomized individuals with impaired glucose tolerance to treatment with placebo, metformin, or lifestyle modification. Height, weight, waist circumference, and subcutaneous and visceral fat at L2-L3 and L4-L5 by computed tomography were measured at baseline and at 1 year. Cox proportional hazards models assessed by sex the effect of change in these variables over the 1st year of intervention upon development of diabetes over subsequent follow-up in a subset of 758 participants. Lifestyle reduced visceral fat at L2-L3 (men −24.3%, women −18.2%) and at L4-L5 (men −22.4%, women −17.8%), subcutaneous fat at L2-L3 (men −15.7%, women −11.4%) and at L4-L5 (men −16.7%, women −11.9%), weight (men −8.2%, women −7.8%), BMI (men −8.2%, women −7.8%), and waist circumference (men −7.5%, women −6.1%). Metformin reduced weight (−2.9%) and BMI (−2.9%) in men and subcutaneous fat (−3.6% at L2-L3 and −4.7% at L4-L5), weight (−3.3%), BMI (−3.3%), and waist circumference (−2.8%) in women. Decreased diabetes risk by lifestyle intervention was associated with reductions of body weight, BMI, and central body fat distribution after adjustment for age and self-reported ethnicity. Reduced diabetes risk with lifestyle intervention may have been through effects upon both overall body fat and central body fat but with metformin appeared to be independent of body fat. CT, computed tomography DPP, Diabetes Prevention Program WHR, waist-to-hip ratio Footnotes Published ahead of print at http://diabetes.diabetesjournals.org on 30 March 2007. DOI: 10.2337/db07-0009. The costs of publication of this article were defrayed in part by the payment of page charges. This article must therefore be hereby marked “advertisement” in accordance with 18 U.S.C. Section 1734 solely to indicate this fact. Accepted March 7, 2007. Received January 3, 2007. DIABETES

Diagnosis of pneumonia remains challenging. Digitally recorded and remote human classified lung sounds may offer benefits beyond conventional auscultation, but it is unclear whether classifications differ between the two approaches. We evaluated concordance between digital and conventional auscultation. We collected digitally recorded lung sounds, conventional auscultation classifications and clinical measures and samples from children with pneumonia (cases) in low-income and middle-income countries. Physicians remotely classified recordings as crackles, wheeze or uninterpretable. Conventional and digital auscultation concordance was evaluated among 383 pneumonia cases with concurrently (within 2 hours) collected conventional and digital auscultation classifications using prevalence-adjusted bias-adjusted kappa (PABAK). Using an expanded set of 737 cases that also incorporated the non-concurrently collected assessments, we evaluated whether associations between auscultation classifications and clinical or aetiological findings differed between conventional or digital auscultation using χ tests and logistic regression adjusted for age, sex and site. Conventional and digital auscultation concordance was moderate for classifying crackles and/or wheeze versus neither crackles nor wheeze (PABAK=0.50), and fair for crackles-only versus not crackles-only (PABAK=0.30) and any wheeze versus no wheeze (PABAK=0.27). Crackles were more common on conventional auscultation, whereas wheeze was more frequent on digital auscultation. Compared with neither crackles nor wheeze, crackles-only on both conventional and digital auscultation was associated with abnormal chest radiographs (adjusted OR (aOR)=1.53, 95% CI 0.99 to 2.36; aOR=2.09, 95% CI 1.19 to 3.68, respectively); any wheeze was inversely associated with C-reactive protein >40 mg/L using conventional auscultation (aOR=0.50, 95% CI 0.27 to 0.92) and with very severe pneumonia using digital auscultation (aOR=0.67, 95% CI 0.46 to 0.97). Crackles-only on digital auscultation was associated with mortality compared with any wheeze (aOR=2.70, 95% CI 1.12 to 6.25). Conventional auscultation and remotely-classified digital auscultation displayed moderate concordance for presence/absence of wheeze and crackles among cases. Conventional and digital auscultation may provide different classification patterns, but wheeze was associated with decreased clinical severity on both.

In a retrospective analysis from a randomized trial, stored serum samples from patients with stable coronary artery disease were analyzed with the use of a new, highly sensitive assay for cardiac troponin T. At levels well below the limit of detection of the conventional assay, troponin T concentrations correlated significantly with the subsequent risk of cardiovascular death and heart failure but not with the risk of myocardial infarction. This retrospective analysis used a new, highly sensitive assay for cardiac troponin T. At levels well below the limit of detection of the conventional assay, troponin T concentrations correlated significantly with the subsequent risk of cardiovascular death and heart failure but not with the risk of myocardial infarction. Cardiac troponins T and I are components of the contractile apparatus of cardiomyocytes and are the preferred biochemical markers of myocardial necrosis in patients with suspected acute coronary syndromes. 1 Among such patients, a strong association between elevated troponin levels and recurrent coronary ischemic events has been firmly established. 2 – 4 It has been shown that even very small elevations in troponins are associated with an increased risk of an adverse outcome in patients with acute coronary syndromes. 5 Moreover, among men clinically free of cardiovascular disease, as well as in patients with recent acute coronary syndromes, levels of cardiac troponin greater than . . .

TCF7L2 variants have been associated with type 2 diabetes, body mass index (BMI), and deficits in proinsulin processing and insulin secretion. Here we sought to test whether these effects were apparent in high-risk individuals and modify treatment responses. We examined the potential role of the TCF7L2 rs7903146 variant in predicting resistance to weight loss or a lack of improvement of proinsulin processing during 2.5-years of follow-up participants (N = 2,994) from the Diabetes Prevention Program (DPP), a randomized controlled trial designed to prevent or delay diabetes in high-risk adults. We observed no difference in the degree of weight loss by rs7903146 genotypes. However, the T allele (conferring higher risk of diabetes) at rs7903146 was associated with higher fasting proinsulin at baseline (P<0.001), higher baseline proinsulin:insulin ratio (p<0.0001) and increased proinsulin:insulin ratio over a median of 2.5 years of follow-up (P = 0.003). Effects were comparable across treatment arms. The combination of a lack of impact of the TCF7L2 genotypes on the ability to lose weight, but the presence of a consistent effect on the proinsulin:insulin ratio over the course of DPP, suggests that high-risk genotype carriers at this locus can successfully lose weight to counter diabetes risk despite persistent deficits in insulin production.