TY  - JOUR
AB  - IMPORTANCE: Metabolic dysfunction-associated steatotic liver disease (MASLD) includes a range of liver conditions, progressing from isolated steatosis (characterized by fat accumulation in the liver without inflammation) to metabolic dysfunction-associated steatohepatitis (MASH), which involves fat accumulation and inflammation in the liver. The presence of MASLD is associated with increased morbidity and mortality due to liver-related complications, hepatocellular carcinoma, cardiovascular disease, and certain extrahepatic cancers. OBSERVATIONS: The most common chronic liver disease worldwide, MASLD affects approximately 30% to 40% of the general adult population globally (with varying prevalence across continents), including approximately 60% to 70% of individuals with type 2 diabetes and approximately 70% to 80% of those with obesity. It is typically diagnosed based on an ultrasonographic finding of hepatic steatosis, along with at least 1 of 5 features of the metabolic syndrome (abdominal overweight or obesity, prediabetes or type 2 diabetes, hypertension, elevated level of plasma triglycerides, and low level of high-density lipoprotein cholesterol) for women who consume less than 140 g/wk of alcohol (<2 standard drinks/d) and for men who consume less than 210 g/wk (<3 standard drinks/d) and have no other known causes of steatosis such as use of a particular medication (eg, corticosteroids, tamoxifen, or methotrexate), hepatitis C, or iron overload. Other risk factors for MASLD include older age (≥50 years) and male sex (male:female ratio approximately 2). The Fibrosis-4 index (a scoring system incorporating age, serum levels of aspartate aminotransferase and alanine aminotransferase, and platelet count) and vibration-controlled transient elastography (a noninvasive imaging technique) are commonly used to stage hepatic fibrosis in patients with MASLD. Cardiovascular disease is the leading cause of death, followed by certain extrahepatic cancers (primarily gastrointestinal, breast, and gynecologic cancer) and liver-related complications, including cirrhosis, hepatic decompensation (ascites, hepatic encephalopathy, or variceal bleeding), and hepatocellular carcinoma. First-line treatment of MASLD involves behavioral modifications (including hypocaloric low-carbohydrate and low-fat diets, physical exercise, and avoidance of alcohol) and management of type 2 diabetes, obesity, hypertension, and hyperlipidemia. Bariatric surgery should be considered for patients with MASLD and a body mass index greater than 35. Resmetirom (a liver-directed, thyroid hormone receptor β-selective agonist) and subcutaneous semaglutide (a glucagon-like peptide-1 receptor agonist) are conditionally approved by the US Food and Drug Administration (FDA) for the treatment of adults with MASH who have moderate to advanced fibrosis. CONCLUSIONS: A highly prevalent condition among adults worldwide, MASLD is associated with liver-related complications, hepatocellular carcinoma, cardiovascular disease, and certain extrahepatic cancers. First-line treatment includes behavioral modifications, including a weight-reducing diet, physical exercise, and avoidance of alcohol. Resmetirom and semaglutide are conditionally FDA-approved medications for the treatment of adults with MASH and moderate to advanced fibrosis.
AU  - Tilg, H.*
AU  - Petta, S.*
AU  - Stefan, N.
AU  - Targher, G.*
C1  - 75983
C2  - 58306
CY  - 330 N Wabash Ave, Ste 39300, Chicago, Il 60611-5885 Usa
TI  - Metabolic dysfunction-associated steatotic liver disease in adults: A review.
JO  - JAMA
PB  - Amer Medical Assoc
PY  - 2025
SN  - 0098-7484
ER  - 

TY  - JOUR
AB  - This study examines whether an association exists between COVID-19 infection and progression to clinical diabetes among youth with presymptomatic type 1 diabetes.
AU  - Friedl, N.
AU  - Sporreiter, M.S.
AU  - Winkler, C.
AU  - Heublein, A.
AU  - Haupt, F.
AU  - Ziegler, A.-G.
AU  - Bonifacio, E.*
C1  - 71140
C2  - 55908
CY  - 330 N Wabash Ave, Ste 39300, Chicago, Il 60611-5885 Usa
SP  - 501-502
TI  - Progression from presymptomatic to clinical type 1 diabetes after COVID-19 infection.
JO  - JAMA
VL  - 332
IS  - 6
PB  - Amer Medical Assoc
PY  - 2024
SN  - 0098-7484
ER  - 

TY  - JOUR
AB  - IMPORTANCE: Identification of individuals at high risk for atherosclerotic cardiovascular disease within the population is important to inform primary prevention strategies. OBJECTIVE: To evaluate the prognostic value of routinely available cardiovascular biomarkers when added to established risk factors. DESIGN, SETTING, AND PARTICIPANTS: Individual-level analysis including data on cardiovascular biomarkers from 28 general population-based cohorts from 12 countries and 4 continents with assessments by participant age. The median follow-up was 11.8 years. EXPOSURE: Measurement of high-sensitivity cardiac troponin I, high-sensitivity cardiac troponin T, N-terminal pro-B-type natriuretic peptide, B-type natriuretic peptide, or high-sensitivity C-reactive protein. MAIN OUTCOMES AND MEASURES: The primary outcome was incident atherosclerotic cardiovascular disease, which included all fatal and nonfatal events. The secondary outcomes were all-cause mortality, heart failure, ischemic stroke, and myocardial infarction. Subdistribution hazard ratios (HRs) for the association of biomarkers and outcomes were calculated after adjustment for established risk factors. The additional predictive value of the biomarkers was assessed using the C statistic and reclassification analyses. RESULTS: The analyses included 164 054 individuals (median age, 53.1 years [IQR, 42.7-62.9 years] and 52.4% were women). There were 17 211 incident atherosclerotic cardiovascular disease events. All biomarkers were significantly associated with incident atherosclerotic cardiovascular disease (subdistribution HR per 1-SD change, 1.13 [95% CI, 1.11-1.16] for high-sensitivity cardiac troponin I; 1.18 [95% CI, 1.12-1.23] for high-sensitivity cardiac troponin T; 1.21 [95% CI, 1.18-1.24] for N-terminal pro-B-type natriuretic peptide; 1.14 [95% CI, 1.08-1.22] for B-type natriuretic peptide; and 1.14 [95% CI, 1.12-1.16] for high-sensitivity C-reactive protein) and all secondary outcomes. The addition of each single biomarker to a model that included established risk factors improved the C statistic. For 10-year incident atherosclerotic cardiovascular disease in younger people (aged <65 years), the combination of high-sensitivity cardiac troponin I, N-terminal pro-B-type natriuretic peptide, and high-sensitivity C-reactive protein resulted in a C statistic improvement from 0.812 (95% CI, 0.8021-0.8208) to 0.8194 (95% CI, 0.8089-0.8277). The combination of these biomarkers also improved reclassification compared with the conventional model. Improvements in risk prediction were most pronounced for the secondary outcomes of heart failure and all-cause mortality. The incremental value of biomarkers was greater in people aged 65 years or older vs younger people. CONCLUSIONS AND RELEVANCE: Cardiovascular biomarkers were strongly associated with fatal and nonfatal cardiovascular events and mortality. The addition of biomarkers to established risk factors led to only a small improvement in risk prediction metrics for atherosclerotic cardiovascular disease, but was more favorable for heart failure and mortality.
AU  - Neumann, J.T.*
AU  - Twerenbold, R.*
AU  - Weimann, J.*
AU  - Ballantyne, C.M.*
AU  - Benjamin, E.J.*
AU  - Costanzo, S.*
AU  - de Lemos, J.A.*
AU  - deFilippi, C.R.*
AU  - Di Castelnuovo, A.*
AU  - Donfrancesco, C.*
AU  - Dörr, M.*
AU  - Eggers, K.M.*
AU  - Engström, G.*
AU  - Felix, S.B.*
AU  - Ferrario, M.M.*
AU  - Gansevoort, R.T.*
AU  - Giampaoli, S.*
AU  - Giedraitis, V.*
AU  - Hedberg, P.*
AU  - Iacoviello, L.*
AU  - Jørgensen, T.*
AU  - Kee, F.*
AU  - Koenig, W.*
AU  - Kuulasmaa, K.*
AU  - Lewis, J.R.*
AU  - Lorenz, T.*
AU  - Lyngbakken, M.N.*
AU  - Magnussen, C.*
AU  - Melander, O.*
AU  - Nauck, M.*
AU  - Niiranen, T.J.*
AU  - Nilsson, P.M.*
AU  - Olsen, M.H.*
AU  - Omland, T.*
AU  - Oskarsson, V.*
AU  - Palmieri, L.*
AU  - Peters, A.
AU  - Prince, R.L.*
AU  - Qaderi, V.*
AU  - Vasan, R.S.*
AU  - Salomaa, V.*
AU  - Sans, S.*
AU  - Smith, J.G.*
AU  - Söderberg, S.*
AU  - Thorand, B.
AU  - Tonkin, A.M.*
AU  - Tunstall-Pedoe, H.*
AU  - Veronesi, G.*
AU  - Watanabe, T.*
AU  - Watanabe, M.*
AU  - Zeiher, A.M.*
AU  - Zeller, T.*
AU  - Blankenberg, S.*
AU  - Ojeda, F.*
C1  - 70667
C2  - 55717
CY  - 330 N Wabash Ave, Ste 39300, Chicago, Il 60611-5885 Usa
TI  - Prognostic value of cardiovascular biomarkers in the population.
JO  - JAMA
PB  - Amer Medical Assoc
PY  - 2024
SN  - 0098-7484
ER  - 

TY  - JOUR
AB  - Importance: The incidence of diabetes in childhood has increased during the COVID-19 pandemic. Elucidating whether SARS-CoV-2 infection is associated with islet autoimmunity, which precedes type 1 diabetes onset, is relevant to disease etiology and future childhood diabetes trends. Objective: To determine whether there is a temporal relationship between SARS-CoV-2 infection and the development of islet autoimmunity in early childhood. Design, Setting, and Participants: Between February 2018 and March 2021, the Primary Oral Insulin Trial, a European multicenter study, enrolled 1050 infants (517 girls) aged 4 to 7 months with a more than 10% genetically defined risk of type 1 diabetes. Children were followed up through September 2022. Exposure: SARS-CoV-2 infection identified by SARS-CoV-2 antibody development in follow-up visits conducted at 2- to 6-month intervals until age 2 years from April 2018 through June 2022. Main Outcomes and Measures: The development of multiple (≥2) islet autoantibodies in follow-up in consecutive samples or single islet antibodies and type 1 diabetes. Antibody incidence rates and risk of developing islet autoantibodies were analyzed. Results: Consent was obtained for 885 (441 girls) children who were included in follow-up antibody measurements from age 6 months. SARS-CoV-2 antibodies developed in 170 children at a median age of 18 months (range, 6-25 months). Islet autoantibodies developed in 60 children. Six of these children tested positive for islet autoantibodies at the same time as they tested positive for SARS-CoV-2 antibodies and 6 at the visit after having tested positive for SARS-CoV-2 antibodies. The sex-, age-, and country-adjusted hazard ratio for developing islet autoantibodies when the children tested positive for SARS-CoV-2 antibodies was 3.5 (95% CI, 1.6-7.7; P =.002). The incidence rate of islet autoantibodies was 3.5 (95% CI, 2.2-5.1) per 100 person-years in children without SARS-CoV-2 antibodies and 7.8 (95% CI, 5.3-19.0) per 100 person-years in children with SARS-CoV-2 antibodies (P =.02). Islet autoantibody risk in children with SARS-CoV-2 antibodies was associated with younger age (<18 months) of SARS-CoV-2 antibody development (HR, 5.3; 95% CI, 1.5-18.3; P =.009). Conclusion and relevance: In young children with high genetic risk of type 1 diabetes, SARS-CoV-2 infection was temporally associated with the development of islet autoantibodies..
AU  - Lugar, M.*
AU  - Eugster, A.*
AU  - Achenbach, P.
AU  - von dem Berge, T.*
AU  - Berner, R.*
AU  - Besser, R.E.J.*
AU  - Casteels, K.*
AU  - Elding Larsson, H.*
AU  - Gemulla, G.*
AU  - Kordonouri, O.*
AU  - Lindner, A.*
AU  - Lundgren, M.*
AU  - Müller, D.*
AU  - Oltarzewski, M.*
AU  - Rochtus, A.*
AU  - Scholz, M.
AU  - Szypowska, A.*
AU  - Todd, J.A.*
AU  - Ziegler, A.-G.
AU  - Bonifacio, E.
C1  - 68237
C2  - 54724
CY  - 330 N Wabash Ave, Ste 39300, Chicago, Il 60611-5885 Usa
SP  - 1151-1160
TI  - SARS-CoV-2 infection and development of islet autoimmunity in early childhood.
JO  - JAMA
VL  - 330
IS  - 12
PB  - Amer Medical Assoc
PY  - 2023
SN  - 0098-7484
ER  - 

TY  - JOUR
AU  - Rewers, M.*
AU  - Ziegler, A.-G.
C1  - 67476
C2  - 54130
SP  - 512-513
TI  - SARS-CoV-2 infections and presymptomatic type 1 diabetes autoimmunity in children and adolescents-reply.
JO  - JAMA
VL  - 329
IS  - 6
PY  - 2023
SN  - 0098-7484
ER  - 

TY  - JOUR
AU  - Weiss, A.
AU  - Donnachie, E.*
AU  - Beyerlein, A.*
AU  - Ziegler, A.-G.
AU  - Bonifacio, E.*
C1  - 67913
C2  - 54391
SP  - 2089-2091
TI  - Type 1 diabetes incidence and risk in children with a diagnosis of COVID-19.
JO  - JAMA
VL  - 329
IS  - 23
PY  - 2023
SN  - 0098-7484
ER  - 

TY  - JOUR
AU  - Rewers, M.*
AU  - Bonifacio, E.*
AU  - Ewald, D.*
AU  - Geno Rasmussen, C.*
AU  - Jia, X.*
AU  - Pyle, L.*
AU  - Ziegler, A.-G.
C1  - 65901
C2  - 52969
SP  - 1252-1255
TI  - SARS-CoV-2 infections and presymptomatic type 1 diabetes autoimmunity in children and adolescents from Colorado, USA, and Bavaria, Germany.
JO  - JAMA
VL  - 328
IS  - 12
PY  - 2022
SN  - 0098-7484
ER  - 

TY  - JOUR
AB  - Importance Mental health comorbidities are increasing worldwide and worsen outcomes for people with diabetes, especially when care is fragmented. Objective To assess whether collaborative care vs usual care lowers depressive symptoms and improves cardiometabolic indices among adults with diabetes and depression. Design, Setting, and Participants Parallel, open-label, pragmatic randomized clinical trial conducted at 4 socioeconomically diverse clinics in India that recruited patients with type 2 diabetes; a Patient Health Questionnaire-9 score of at least 10 (range, 0-27); and hemoglobin A(1c)(HbA(1c)) of at least 8%, systolic blood pressure (SBP) of at least 140 mm Hg, or low-density lipoprotein (LDL) cholesterol of at least 130 mg/dL. The first patient was enrolled on March 9, 2015, and the last was enrolled on May 31, 2016; the final follow-up visit was July 14, 2018. Interventions Patients randomized to the intervention group (n = 196) received 12 months of self-management support from nonphysician care coordinators, decision support electronic health records facilitating physician treatment adjustments, and specialist case reviews; they were followed up for an additional 12 months without intervention. Patients in the control group (n = 208) received usual care over 24 months. Main Outcomes and Measures The primary outcome was the between-group difference in the percentage of patients at 24 months who had at least a 50% reduction in Symptom Checklist Depression Scale (SCL-20) scores (range, 0-4; higher scores indicate worse symptoms) and a reduction of at least 0.5 percentage points in HbA(1c), 5 mm Hg in SBP, or 10 mg/dL in LDL cholesterol. Prespecified secondary outcomes were percentage of patients at 12 and 24 months who met treatment targets (HbA(1c)<7.0%, SBP <130 mm Hg, LDL cholesterol <100 mg/dL [<70 mg/dL if prior cardiovascular disease]) or had improvements in individual outcomes (>= 50% reduction in SCL-20 score, >= 0.5-percentage point reduction in HbA(1c), >= 5-mm Hg reduction in SBP, >= 10-mg/dL reduction in LDL cholesterol); percentage of patients who met all HbA(1c), SBP, and LDL cholesterol targets; and mean reductions in SCL-20 score, Patient Health Questionnaire-9 score, HbA(1c), SBP, and LDL cholesterol. Results Among 404 patients randomized (mean [SD] age, 53 [8.6] years; 165 [40.8%] men), 378 (93.5%) completed the trial. A significantly greater percentage of patients in the intervention group vs the usual care group met the primary outcome (71.6% vs 57.4%; risk difference, 16.9% [95% CI, 8.5%-25.2%]). Of 16 prespecified secondary outcomes, there were no statistically significant between-group differences in improvements in 10 outcomes at 12 months and in 13 outcomes at 24 months. Serious adverse events in the intervention and usual care groups included cardiovascular events or hospitalizations (4 [2.0%] vs 7 [3.4%]), stroke (0 vs 3 [1.4%]), death (2 [1.0%] vs 7 [3.4%]), and severe hypoglycemia (8 [4.1%] vs 0). Conclusions and Relevance Among patients with diabetes and depression in India, a 12-month collaborative care intervention, compared with usual care, resulted in statistically significant improvements in a composite measure of depressive symptoms and cardiometabolic indices at 24 months. Further research is needed to understand the generalizability of the findings to other low- and middle-income health care settings.This randomized clinical trial compares the effect of a collaborative care model that integrates management of depression and enhanced diabetes care on depressive symptoms and HbA(1c), SBP, and LDL cholesterol measures among individuals with depression and diabetes in India.Question Among patients with diabetes and depression in India, does a 12-month collaborative care intervention that includes nonphysician care coordinators, decision support functions in electronic health records, and specialist case reviews improve depressive symptoms and measures of cardiometabolic health more than usual care at 24 months? Findings In this randomized clinical trial that included 404 patients at urban clinics in India with poorly controlled diabetes and depression, patients in the collaborative care intervention group, compared with the usual care group, were significantly more likely to achieve the composite outcome of at least a 50% reduction in the 20-item Symptom Checklist Depression Scale score and at least 1 of the following: reduction of at least 0.5 percentage points in hemoglobin A(1c), reduction of at least 5 mm Hg in systolic blood pressure, or reduction of at least 10 mg/dL in low-density lipoprotein cholesterol at 24 months (71.6% vs 54.7%). Meaning Among patients with diabetes and depressive symptoms in urban India, a multicomponent collaborative care intervention resulted in statistically significantly greater improvements in a composite measure of depressive symptoms and cardiometabolic indices compared with usual care.
AU  - Ali, M.K.*
AU  - Chwastiak, L.*
AU  - Poongothai, S.*
AU  - Emmert-Fees, K.
AU  - Patel, S.A.*
AU  - Anjana, R.M.*
AU  - Sagar, R.*
AU  - Shankar, R.*
AU  - Sridhar, G.R.*
AU  - Kosuri, M.*
AU  - Sosale, A.R.*
AU  - Sosale, B.*
AU  - Rao, D.*
AU  - Tandon, N.*
AU  - Narayan, K.M.V.*
AU  - Mohan, V.*
C1  - 59921
C2  - 49120
CY  - 330 N Wabash Ave, Ste 39300, Chicago, Il 60611-5885 Usa
SP  - 651-662
TI  - Effect of a collaborative care model on depressive symptoms and glycated hemoglobin, blood pressure, and serum cholesterol among patients with depression and diabetes in India. The INDEPENDENT randomized clinical trial.
JO  - JAMA
VL  - 324
IS  - 7
PB  - Amer Medical Assoc
PY  - 2020
SN  - 0098-7484
ER  - 

TY  - JOUR
AB  - Importance: Public health screening for type 1 diabetes in its presymptomatic stages may reduce disease severity and burden on a population level. Objective: To determine the prevalence of presymptomatic type 1 diabetes in children participating in a public health screening program for islet autoantibodies and the risk for progression to clinical diabetes. Design, Setting, and Participants: Screening for islet autoantibodies was offered to children aged 1.75 to 5.99 years in Bavaria, Germany, between 2015 and 2019 by primary care pediatricians during well-baby visits. Families of children with multiple islet autoantibodies (presymptomatic type 1 diabetes) were invited to participate in a program of diabetes education, metabolic staging, assessment of psychological stress associated with diagnosis, and prospective follow-up for progression to clinical diabetes until July 31, 2019. Exposures: Measurement of islet autoantibodies. Main Outcomes and Measures: The primary outcome was presymptomatic type 1 diabetes, defined by 2 or more islet autoantibodies, with categorization into stages 1 (normoglycemia), 2 (dysglycemia), or 3 (clinical) type 1 diabetes. Secondary outcomes were the frequency of diabetic ketoacidosis and parental psychological stress, assessed by the Patient Health Questionnaire-9 (range, 0-27; higher scores indicate worse depression; ≤4 indicates no to minimal depression; >20 indicates severe depression). Results: Of 90 632 children screened (median [interquartile range {IQR}] age, 3.1 [2.1-4.2] years; 48.5% girls), 280 (0.31%; 95% CI, 0.27-0.35) had presymptomatic type 1 diabetes, including 196 (0.22%) with stage 1, 17 (0.02%) with stage 2, 26 (0.03%) with stage 3, and 41 who were not staged. After a median (IQR) follow-up of 2.4 (1.0-3.2) years, another 36 children developed stage 3 type 1 diabetes. The 3-year cumulative risk for stage 3 type 1 diabetes in the 280 children with presymptomatic type 1 diabetes was 24.9% ([95% CI, 18.5%-30.7%]; 54 cases; annualized rate, 9.0%). Two children had diabetic ketoacidosis. Median (IQR) psychological stress scores were significantly increased at the time of metabolic staging in mothers of children with presymptomatic type 1 diabetes (3 [1-7]) compared with mothers of children without islet autoantibodies (2 [1-4]) (P = .002), but declined after 12 months of follow-up (2 [0-4]) (P < .001). Conclusions and Relevance: Among children aged 2 to 5 years in Bavaria, Germany, a program of primary care-based screening showed an islet autoantibody prevalence of 0.31%. These findings may inform considerations of population-based screening of children for islet autoantibodies.
AU  - Ziegler, A.-G.
AU  - Kick, K.
AU  - Bonifacio, E.
AU  - Haupt, F.
AU  - Hippich, M.
AU  - Dunstheimer, D.*
AU  - Lang, M.*
AU  - Laub, O.*
AU  - Warncke, K.*
AU  - Lange, K.*
AU  - Assfalg, R.
AU  - Jolink, M.
AU  - Winkler, C.
AU  - Achenbach, P.
C1  - 58672
C2  - 48237
SP  - 339-351
TI  - Yield of a public health screening of children for islet autoantibodies in Bavaria, Germany.
JO  - JAMA
VL  - 323
IS  - 4
PY  - 2020
SN  - 0098-7484
ER  - 

TY  - JOUR
AB  - IMPORTANCE High gluten intake during childhood may confer risk of celiac disease.OBJECTIVES To investigate if the amount of gluten intake is associated with celiac disease autoimmunity and celiac disease in genetically at-risk children.DESIGN, SETTING, AND PARTICIPANTS The participants in The Environmental Determinants of Diabetes in the Young (TEDDY), a prospective observational birth cohort study designed to identify environmental triggers of type 1 diabetes and celiac disease, were followed up at 6 clinical centers in Finland, Germany, Sweden, and the United States. Between 2004 and 2010, 8676 newborns carrying HLA antigen genotypes associated with type 1 diabetes and celiac disease were enrolled. Screening for celiac disease with tissue transglutaminase autoantibodies was performed annually in 6757 children from the age of 2 years. Data on gluten intake were available in 6605 children (98%) by September 30, 2017.EXPOSURES Gluten intake was estimated from 3-day food records collected at ages 6, 9, and 12 months and biannually thereafter until the age of 5 years.MAIN OUTCOMES AND MEASURES The primary outcome was celiac disease autoimmunity, defined as positive tissue transglutaminase autoantibodies found in 2 consecutive serum samples. The secondary outcome was celiac disease confirmed by intestinal biopsy or persistently high tissue transglutaminase autoantibody levels.RESULTS Of the 6605 children (49% females; median follow-up: 9.0 years [interquartile range, 8.0-10.0 years]), 1216 (18%) developed celiac disease autoimmunity and 447 (7%) developed celiac disease. The incidence for both outcomes peaked at the age of 2 to 3 years. Daily gluten intake was associated with higher risk of celiac disease autoimmunity for every 1-g/d increase in gluten consumption (hazard ratio [HR], 1.30 [95% CI, 1.22-1.38]; absolute risk by the age of 3 years if the reference amount of gluten was consumed, 28.1%; absolute risk if gluten intake was 1-g/d higher than the reference amount, 34.2%; absolute risk difference, 6.1% [95% CI, 4.5%-7.7%]). Daily gluten intake was associated with higher risk of celiac disease for every 1-g/d increase in gluten consumption (HR, 1.50 [95% CI, 1.35-1.66]; absolute risk by age of 3 years if the reference amount of gluten was consumed, 20.7%; absolute risk if gluten intake was 1-g/d higher than the reference amount, 27.9%; absolute risk difference, 7.2% [95% CI, 6.1%-8.3%]).CONCLUSIONS AND RELEVANCE Higher gluten intake during the first 5 years of life was associated with increased risk of celiac disease autoimmunity and celiac disease among genetically predisposed children.
AU  - Andrén Aronsson, C.*
AU  - Lee, H.S.*
AU  - Hård Af Segerstad, E.M.*
AU  - Uusitalo, U.*
AU  - Yang, J.*
AU  - Koletzko, S.*
AU  - Liu, E.*
AU  - Kurppa, K.*
AU  - Bingley, P.J.*
AU  - Toppari, J.*
AU  - Ziegler, A.-G.
AU  - She, J.X.*
AU  - Hagopian, W.A.*
AU  - Rewers, M.*
AU  - Akolkar, B.*
AU  - Krischer, J.P.*
AU  - Virtanen, S.M.*
AU  - Norris, J.M.*
AU  - Agardh, D.*
C1  - 56762
C2  - 47289
CY  - 330 N Wabash Ave, Ste 39300, Chicago, Il 60611-5885 Usa
SP  - 514-523
TI  - Association of gluten intake during the first 5 years of Llfe with incidence of celiac disease autoimmunity and celiac disease among children at increased risk.
JO  - JAMA
VL  - 322
IS  - 6
PB  - Amer Medical Assoc
PY  - 2019
SN  - 0098-7484
ER  - 

TY  - JOUR
AB  - Importance: Both low and high gestational weight gain have been associated with adverse maternal and infant outcomes, but optimal gestational weight gain remains uncertain and not well defined for all prepregnancy weight ranges. Objectives: To examine the association of ranges of gestational weight gain with risk of adverse maternal and infant outcomes and estimate optimal gestational weight gain ranges across prepregnancy body mass index categories. Design, Setting, and Participants: Individual participant-level meta-analysis using data from 196 670 participants within 25 cohort studies from Europe and North America (main study sample). Optimal gestational weight gain ranges were estimated for each prepregnancy body mass index (BMI) category by selecting the range of gestational weight gain that was associated with lower risk for any adverse outcome. Individual participant-level data from 3505 participants within 4 separate hospital-based cohorts were used as a validation sample. Data were collected between 1989 and 2015. The final date of follow-up was December 2015. Exposures: Gestational weight gain. Main Outcomes and Measures: The main outcome termed any adverse outcome was defined as the presence of 1 or more of the following outcomes: preeclampsia, gestational hypertension, gestational diabetes, cesarean delivery, preterm birth, and small or large size for gestational age at birth. Results: Of the 196 670 women (median age, 30.0 years [quartile 1 and 3, 27.0 and 33.0 years] and 40 937 were white) included in the main sample, 7809 (4.0%) were categorized at baseline as underweight (BMI <18.5); 133 788 (68.0%), normal weight (BMI, 18.5-24.9); 38 828 (19.7%), overweight (BMI, 25.0-29.9); 11 992 (6.1%), obesity grade 1 (BMI, 30.0-34.9); 3284 (1.7%), obesity grade 2 (BMI, 35.0-39.9); and 969 (0.5%), obesity grade 3 (BMI, ≥40.0). Overall, any adverse outcome occurred in 37.2% (n = 73 161) of women, ranging from 34.7% (2706 of 7809) among women categorized as underweight to 61.1% (592 of 969) among women categorized as obesity grade 3. Optimal gestational weight gain ranges were 14.0 kg to less than 16.0 kg for women categorized as underweight; 10.0 kg to less than 18.0 kg for normal weight; 2.0 kg to less than 16.0 kg for overweight; 2.0 kg to less than 6.0 kg for obesity grade 1; weight loss or gain of 0 kg to less than 4.0 kg for obesity grade 2; and weight gain of 0 kg to less than 6.0 kg for obesity grade 3. These gestational weight gain ranges were associated with low to moderate discrimination between those with and those without adverse outcomes (range for area under the receiver operating characteristic curve, 0.55-0.76). Results for discriminative performance in the validation sample were similar to the corresponding results in the main study sample (range for area under the receiver operating characteristic curve, 0.51-0.79). Conclusions and Relevance: In this meta-analysis of pooled individual participant data from 25 cohort studies, the risk for adverse maternal and infant outcomes varied by gestational weight gain and across the range of prepregnancy weights. The estimates of optimal gestational weight gain may inform prenatal counseling; however, the optimal gestational weight gain ranges had limited predictive value for the outcomes assessed.
AU  - LifeCycle Project-Maternal Obesity and Childhood Outcomes Study Group*
AU  - Voerman, E.*
AU  - Santos, S.*
AU  - Inskip, H.*
AU  - Amiano, P.*
AU  - Barros, H.*
AU  - Charles, M.A.*
AU  - Chatzi, L.*
AU  - Chrousos, G.P.*
AU  - Corpeleijn, E.*
AU  - Crozier, S.*
AU  - Doyon, M.*
AU  - Eggesbø, M.*
AU  - Fantini, M.P.*
AU  - Farchi, S.*
AU  - Forastiere, F.*
AU  - Georgiu, V.*
AU  - Gori, D.*
AU  - Hanke, W.*
AU  - Hertz-Picciotto, I.*
AU  - Heude, B.*
AU  - Hivert, M.F.*
AU  - Hryhorczuk, D.*
AU  - Iñiguez, C.*
AU  - Karvonen, A.M.*
AU  - Küpers, L.K.*
AU  - Lagström, H.*
AU  - Lawlor, D.A.*
AU  - Lehmann, I.*
AU  - Magnus, P.*
AU  - Majewska, R.*
AU  - Mäkelä, J.*
AU  - Manios, Y.*
AU  - Mommers, M.*
AU  - Morgen, C.S.*
AU  - Moschonis, G.*
AU  - Nohr, E.A.*
AU  - Nybo Andersen, A.M.*
AU  - Oken, E.*
AU  - Pac, A.*
AU  - Papadopoulou, E.*
AU  - Pekkanen, J.*
AU  - Pizzi, C.*
AU  - Polanska, K.*
AU  - Porta, D.*
AU  - Richiardi, L.*
AU  - Rifas-Shiman, S.L.*
AU  - Roeleveld, N.*
AU  - Ronfani, L.*
AU  - Santos, A.C.*
AU  - Standl, M.
AU  - Stigum, H.*
AU  - Stoltenberg, C.*
AU  - Thiering, E.
AU  - Thijs, C.*
AU  - Torrent, M.*
AU  - Trnovec, T.*
AU  - van Gelder, M.M.H.J.*
AU  - van Rossem, L.*
AU  - von Berg, A.*
AU  - Vrijheid, M.*
AU  - Wijga, A.*
AU  - Zvinchuk, O.*
AU  - Sørensen, T.I.A.*
AU  - Godfrey, K.M.*
AU  - Jaddoe, V.W.V.*
AU  - Gaillard, R.*
C1  - 56001
C2  - 46747
CY  - 330 N Wabash Ave, Ste 39300, Chicago, Il 60611-5885 Usa
SP  - 1702-1715
TI  - Association of gestational weight gain with adverse maternal and infant outcomes.
JO  - JAMA
VL  - 321
IS  - 17
PB  - Amer Medical Assoc
PY  - 2019
SN  - 0098-7484
ER  - 

TY  - JOUR
AB  - IMPORTANCE Phase 3 trials have not compared oral semaglutide, a glucagon-like peptide 1 receptor agonist, with other classes of glucose-lowering therapy.OBJECTIVE To compare efficacy and assess long-term adverse event profiles of once-daily oral semaglutide vs sitagliptin, 100 mg added on to metformin with or without sulfonylurea, in patients with type 2 diabetes.DESIGN, SETTING, AND PARTICIPANTS Randomized, double-blind, double-dummy, parallel-group, phase 3a trial conducted at 206 sites in 14 countries over 78 weeks from February 2016 to March 2018. Of 2463 patients screened, 1864 adults with type 2 diabetes uncontrolled with metformin with or without sulfonylurea were randomized.INTERVENTIONS Patients were randomized to receive once-daily oral semaglutide, 3 mg (n=466), 7 mg (n=466), or 14 mg (n=465), or sitagliptin, 100 mg (n=467). Semaglutide was initiated at 3 mg/d and escalated every 4 weeks, first to 7 mg/d then to 14 mg/d, until the randomized dosage was achieved.MAIN OUTCOMES AND MEASURES The primary end point was change in glycated hemoglobin (HbA(1c)), and the key secondary end point was change in body weight, both from baseline to week 26. Both were assessed at weeks 52 and 78 as additional secondary end points. End points were tested for noninferiority with respect to HbA(1c) (noninferiority margin, 0.3%) prior to testing for superiority of HbA(1c) and body weight.RESULTS Among 1864 patients randomized (mean age, 58 [SD, 10] years; mean baseline HbA(1c), 8.3%[SD, 0.9%]; mean body mass index, 32.5 [SD, 6.4]; n=879 [47.2%] women), 1758 (94.3%) completed the trial and 298 prematurely discontinued treatment (16.7% for semaglutide, 3 mg/d; 15.0% for semaglutide, 7 mg/d; 19.1% for semaglutide, 14 mg/d; and 13.1% for sitagliptin). Semaglutide, 7 and 14 mg/d, compared with sitagliptin, significantly reduced HbA(1c) (differences, -0.3%[95% CI, -0.4% to -0.1%] and -0.5%[95% CI, -0.6% to -0.4%], respectively; P<.001 for both) and body weight (differences, -1.6 kg [95% CI, -2.0 to -1.1 kg] and -2.5 kg [95% CI, -3.0 to -2.0 kg], respectively; P<.001 for both) from baseline to week 26. Noninferiority of semaglutide, 3mg/d, with respect to HbA(1c) was not demonstrated. Week 78 reductions in both end points were statistically significantly greater with semaglutide, 14 mg/d, vs sitagliptin.CONCLUSIONS AND RELEVANCE Among adults with type 2 diabetes uncontrolled with metformin with or without sulfonylurea, oral semaglutide, 7 mg/d and 14 mg/d, compared with sitagliptin, resulted in significantly greater reductions in HbA(1c) over 26 weeks, but there was no significant benefit with the 3-mg/d dosage. Further research is needed to assess effectiveness in a clinical setting.
AU  - Rosenstock, J.*
AU  - Allison, D.*
AU  - Birkenfeld, A.L.
AU  - Blicher, T.M.*
AU  - Deenadayalan, S.*
AU  - Jacobsen, J.B.*
AU  - Serusclat, P.*
AU  - Violante, R.*
AU  - Watada, H.*
AU  - Davies, M.*
C1  - 55780
C2  - 46563
CY  - 330 N Wabash Ave, Ste 39300, Chicago, Il 60611-5885 Usa
SP  - 1466-1480
TI  - Effect of additional oral semaglutide vs sitagliptin on glycated hemoglobin in adults with type 2 diabetes uncontrolled with metformin alone or with sulfonylurea the PIONEER 3 randomized clinical trial.
JO  - JAMA
VL  - 321
IS  - 15
PB  - Amer Medical Assoc
PY  - 2019
SN  - 0098-7484
ER  - 

TY  - JOUR
AU  - Beyerlein, A.
AU  - Donnachie, E.*
AU  - Jergens, S.
AU  - Ziegler, A.-G.
C1  - 48525
C2  - 41128
SP  - 1899-1901
TI  - Infections in early life and development of type 1 diabetes.
JO  - JAMA
VL  - 315
IS  - 17
PY  - 2016
SN  - 0098-7484
ER  - 

TY  - JOUR
AU  - Beyerlein, A.
AU  - Donnachie, E.*
AU  - Ziegler, A.-G.
C1  - 49314
C2  - 41739
CY  - Chicago
SP  - 883-883
TI  - Association of infection in early life and risk of developing type 1 diabetes - reply.
JO  - JAMA
VL  - 316
IS  - 8
PB  - Amer Medical Assoc
PY  - 2016
SN  - 0098-7484
ER  - 

TY  - JOUR
AB  - IMPORTANCE: Interstitial lung abnormalities have been associated with lower 6-minute walk distance, diffusion capacity for carbon monoxide, and total lung capacity. However, to our knowledge, an association with mortality has not been previously investigated. OBJECTIVE: To investigate whether interstitial lung abnormalities are associated with increased mortality. DESIGN, SETTING, AND POPULATION: Prospective cohort studies of 2633 participants from the FHS (Framingham Heart Study; computed tomographic [CT] scans obtained September 2008-March 2011), 5320 from the AGES-Reykjavik Study (Age Gene/Environment Susceptibility; recruited January 2002-February 2006), 2068 from the COPDGene Study (Chronic Obstructive Pulmonary Disease; recruited November 2007-April 2010), and 1670 from ECLIPSE (Evaluation of COPD Longitudinally to Identify Predictive Surrogate Endpoints; between December 2005-December 2006). EXPOSURES: Interstitial lung abnormality status as determined by chest CT evaluation. MAIN OUTCOMES AND MEASURES: All-cause mortality over an approximate 3- to 9-year median follow-up time. Cause-of-death information was also examined in the AGES-Reykjavik cohort. RESULTS: Interstitial lung abnormalities were present in 177 (7%) of the 2633 participants from FHS, 378 (7%) of 5320 from AGES-Reykjavik, 156 (8%) of 2068 from COPDGene, and in 157 (9%) of 1670 from ECLIPSE. Over median follow-up times of approximately 3 to 9 years, there were more deaths (and a greater absolute rate of mortality) among participants with interstitial lung abnormalities when compared with those who did not have interstitial lung abnormalities in the following cohorts: 7% vs 1% in FHS (6% difference [95% CI, 2% to 10%]), 56% vs 33% in AGES-Reykjavik (23% difference [95% CI, 18% to 28%]), and 11% vs 5% in ECLIPSE (6% difference [95% CI, 1% to 11%]). After adjustment for covariates, interstitial lung abnormalities were associated with a higher risk of death in the FHS (hazard ratio [HR], 2.7 [95% CI, 1.1 to 6.5]; P = .03), AGES-Reykjavik (HR, 1.3 [95% CI, 1.2 to 1.4]; P < .001), COPDGene (HR, 1.8 [95% CI, 1.1 to 2.8]; P = .01), and ECLIPSE (HR, 1.4 [95% CI, 1.1 to 2.0]; P = .02) cohorts. In the AGES-Reykjavik cohort, the higher rate of mortality could be explained by a higher rate of death due to respiratory disease, specifically pulmonary fibrosis. CONCLUSIONS AND RELEVANCE: In 4 separate research cohorts, interstitial lung abnormalities were associated with a greater risk of all-cause mortality. The clinical implications of this association require further investigation.
AU  - Putman, R.K.*
AU  - Hatabu, H.*
AU  - Araki, T.*
AU  - Gudmundsson, G.*
AU  - Gao, W.*
AU  - Nishino, M.*
AU  - Okajima, Y.*
AU  - Dupuis, J.*
AU  - Latourelle, J.C.*
AU  - Cho, M.H.*
AU  - El-Chemaly, S.*
AU  - Coxson, H.O.*
AU  - Celli, B.R.*
AU  - Fernandez, I.E.
AU  - Zazueta, O.E.*
AU  - Ross, J.C.*
AU  - Harmouche, R.*
AU  - Estépar, R.S.*
AU  - Diaz, A.A.*
AU  - Sigurdsson, S.*
AU  - Gudmundsson, E.F.*
AU  - Eiriksdottir, G.*
AU  - Aspelund, T.*
AU  - Budoff, M.J.*
AU  - Kinney, G.L.*
AU  - Hokanson, J.E.*
AU  - Williams, M.C.*
AU  - Murchison, J.T.*
AU  - MacNee, W.*
AU  - Hoffmann, U.*
AU  - O'Donnell, C.J.*
AU  - Launer, L.J.*
AU  - Harrris, T.B.*
AU  - Gudnason, V.*
AU  - Silverman, E.K.*
AU  - O'Connor, G.T.*
AU  - Washko, G.R.*
AU  - Rosas, I.O.*
AU  - Hunninghake, G.M.*
C1  - 48057
C2  - 39882
CY  - Chicago
SP  - 672-681
TI  - Association between interstitial lung abnormalities and all-cause mortality.
JO  - JAMA
VL  - 315
IS  - 7
PB  - Amer Medical Assoc
PY  - 2016
SN  - 0098-7484
ER  - 

TY  - JOUR
AB  - Importance: Exposing the oral mucosa to antigen may stimulate immune tolerance. It is unknown whether treatment with oral insulin can induce a tolerogenic immune response in children genetically susceptible to type 1 diabetes. Objective: To assess the immune responses and adverse events associated with orally administered insulin in autoantibody-negative, genetically at-risk children. Design, Setting, and Participants: The Pre-POINT study, a double-blind, placebo-controlled, dose-escalation, phase 1/2 clinical pilot study performed between 2009 and 2013 in Germany, Austria, the United States, and the United Kingdom and enrolling 25 islet autoantibody-negative children aged 2 to 7 years with a family history of type 1 diabetes and susceptible human leukocyte antigen class II genotypes. Follow-up was completed in August 2013. Interventions: Children were randomized to receive oral insulin (n = 15) or placebo (n = 10) once daily for 3 to 18 months. Nine children received insulin with dose escalations from 2.5 to 7.5 mg (n = 3), 2.5 to 22.5 mg (n = 3), or 7.5 to 67.5 mg (n = 3) after 6 months; 6 children only received doses of 22.5 mg (n = 3) or 67.5 mg (n = 3). Main Outcomes and Measures: An immune response to insulin, measured as serum IgG and saliva IgA binding to insulin, and CD4+ T-cell proliferative responses to insulin. Results: Increases in IgG binding to insulin, saliva IgA binding to insulin, or CD4+ T-cell proliferative responses to insulin were observed in 2 of 10 (20% [95% CI, 0.1%-45%]) placebo-treated children and in 1 of 6 (16.7% [95% CI, 0.1%-46%]) children treated with 2.5 mg of insulin, 1 of 6 (16.7%[ 95% CI, 0.1%-46%]) treated with 7.5 mg, 2 of 6 (33.3% [95% CI, 0.1%-71%]) treated with 22.5 mg, and 5 of 6 (83.3% [ 95% CI, 53%-99.9%]) treated with 67.5 mg (P = .02). Insulin-responsive T cells displayed regulatory T-cell features after oral insulin treatment. No hypoglycemia, IgE responses to insulin, autoantibodies to glutamic acid decarboxylase or insulinoma-associated antigen 2, or diabetes were observed. Adverse events were reported in 12 insulin-treated children (67 events) and 10 placebo-treated children (35 events). Conclusions and Relevance: In this pilot study of children at high risk for type 1 diabetes, daily oral administration of 67.5 mg of insulin, compared with placebo, resulted in an immune response without hypoglycemia. These findings support the need for a phase 3 trial to determine whether oral insulin can prevent islet autoimmunity and diabetes in such children. Trial Registration: isrctn.org Identifier: ISRCTN76104595.
AU  - Bonifacio, E.
AU  - Ziegler, A.-G.
AU  - Klingensmith, G.*
AU  - Schober, E.*
AU  - Bingley, P.J.*
AU  - Rottenkolber, M.*
AU  - Theil, A.*
AU  - Eugster, A.*
AU  - Puff, R.
AU  - Peplow, C.
AU  - Buettner, F.
AU  - Lange, K.*
AU  - Hasford, J.*
AU  - Achenbach, P.
C1  - 44455
C2  - 36870
CY  - Chicago
SP  - 1541-1549
TI  - Effects of high-dose oral insulin on immune responses in children at high risk for type 1 diabetes: The Pre-POINT randomized clinical trial.
JO  - JAMA
VL  - 313
IS  - 15
PB  - Amer Medical Assoc
PY  - 2015
SN  - 0098-7484
ER  - 

TY  - JOUR
AB  - Importance: The prevalence of cardiometabolic multimorbidity is increasing. Objective: To estimate reductions in life expectancy associated with cardiometabolic multimorbidity. Design, Setting, and Participants: Age- and sex-adjusted mortality rates and hazard ratios (HRs) were calculated using individual participant data from the Emerging Risk Factors Collaboration (689 300 participants; 91 cohorts; years of baseline surveys: 1960-2007; latest mortality follow-up: April 2013; 128 843 deaths). The HRs from the Emerging Risk Factors Collaboration were compared with those from the UK Biobank (499 808 participants; years of baseline surveys: 2006-2010; latest mortality follow-up: November 2013; 7995 deaths). Cumulative survival was estimated by applying calculated age-specific HRs for mortality to contemporary US age-specific death rates. Exposures: A history of 2 or more of the following: diabetes mellitus, stroke, myocardial infarction (MI). Main Outcomes and Measures: All-cause mortality and estimated reductions in life expectancy. Results: In participants in the Emerging Risk Factors Collaboration without a history of diabetes, stroke, or MI at baseline (reference group), the all-cause mortality rate adjusted to the age of 60 years was 6.8 per 1000 person-years. Mortality rates per 1000 person-years were 15.6 in participants with a history of diabetes, 16.1 in those with stroke, 16.8 in those with MI, 32.0 in those with both diabetes and MI, 32.5 in those with both diabetes and stroke, 32.8 in those with both stroke and MI, and 59.5 in those with diabetes, stroke, and MI. Compared with the reference group, the HRs for all-cause mortality were 1.9 (95% CI, 1.8-2.0) in participants with a history of diabetes, 2.1 (95% CI, 2.0-2.2) in those with stroke, 2.0 (95% CI, 1.9-2.2) in those with MI, 3.7 (95% CI, 3.3-4.1) in those with both diabetes and MI, 3.8 (95% CI, 3.5-4.2) in those with both diabetes and stroke, 3.5 (95% CI, 3.1-4.0) in those with both stroke and MI, and 6.9 (95% CI, 5.7-8.3) in those with diabetes, stroke, and MI. The HRs from the Emerging Risk Factors Collaboration were similar to those from the more recently recruited UK Biobank. The HRs were little changed after further adjustment for markers of established intermediate pathways (eg, levels of lipids and blood pressure) and lifestyle factors (eg, smoking, diet). At the age of 60 years, a history of any 2 of these conditions was associated with 12 years of reduced life expectancy and a history of all 3 of these conditions was associated with 15 years of reduced life expectancy. Conclusions and Relevance: Mortality associated with a history of diabetes, stroke, or MI was similar for each condition. Because any combination of these conditions was associated with multiplicative mortality risk, life expectancy was substantially lower in people with multimorbidity.
AU  - Emerging Risk Factors Collaboration (di Angelantonio, E.*
AU  - Kaptoge, S.*
AU  - Wormser, D.*
AU  - Willeit, P.*
AU  - Butterworth, A.S.*
AU  - Bansal, N.*
AU  - O'Keeffe, L.M.*
AU  - Gao, P.*
AU  - Wood, A.M.*
AU  - Burgess, S.L.*
AU  - Freitag, D.F.*
AU  - Pennells, L.*
AU  - Peters, S.A.*
AU  - Hart, C.L.*
AU  - Håheim, L.L.*
AU  - Gillum, R.F.*
AU  - Nørdestgaard, B.G.*
AU  - Psaty, B.M.*
AU  - Yeap, B.B.*
AU  - Knuiman, M.W.*
AU  - Nietert, P.J.*
AU  - Kauhanen, J.*
AU  - Salonen, J.T.*
AU  - Kuller, L.H.*
AU  - Simons, L.A.*
AU  - van der Schouw, Y.T.*
AU  - Barrett-Connor, E.*
AU  - Selmer, R.*
AU  - Crespo, C.J.*
AU  - Rodriguez, B.*
AU  - Verschuren, W.M.*
AU  - Salomaa, V.*
AU  - Svärdsudd, K.*
AU  - van der Harst, P.*
AU  - Björkelund, C.*
AU  - Wilhelmsen, L.*
AU  - Wallace, R.B.*
AU  - Brenner, H.*
AU  - Amouyel, P.*
AU  - Barr, E.L.*
AU  - Iso, H.*
AU  - Onat, A.*
AU  - Trevisan, M.*
AU  - D'Agostino, R.B.*
AU  - Cooper, C.*
AU  - Kavousi, M.*
AU  - Welin, L.*
AU  - Roussel, R.*
AU  - Hu, F.B.*
AU  - Sato, S.*
AU  - Davidson, K.W.*
AU  - Howard, B.V.*
AU  - Leening, M.*
AU  - Rosengren, A.*
AU  - Dörr, M.*
AU  - Deeg, D.J.*
AU  - Kiechl, S.*
AU  - Stehouwer, C.D.*
AU  - Nissinen, A.*
AU  - Giampaoli, S.*
AU  - Donfrancesco, C.*
AU  - Kromhout, D.*
AU  - Price, J.F.*
AU  - Peters, A.
AU  - Meade, T.W.*
AU  - Casiglia, E.*
AU  - Lawlor, D.A.*
AU  - Gallacher, J.*
AU  - Nagel, D.*
AU  - Franco, O.H.*
AU  - Assmann, G.*
AU  - Dagenais, G.R.*
AU  - Jukema, J.W.*
AU  - Sundström, J.*
AU  - Woodward, M.*
AU  - Brunner, E.J.*
AU  - Khaw, K.T.*
AU  - Wareham, N.J.*
AU  - Whitsel, E.A.*
AU  - Njølstad, I.*
AU  - Hedblad, B.*
AU  - Wassertheil-Smoller, S.*
AU  - Engström, G.*
AU  - Rosamond, W.D.*
AU  - Selvin, E.*
AU  - Sattar, N.*
AU  - Thompson, S.G.*
AU  - Danesh, J.*)
C1  - 46293
C2  - 37493
CY  - Chicago
SP  - 52-60
TI  - Association of cardiometabolic multimorbidity with mortality.
JO  - JAMA
VL  - 314
IS  - 1
PB  - Amer Medical Assoc
PY  - 2015
SN  - 0098-7484
ER  - 

TY  - JOUR
AB  - IMPORTANCE: The value of measuring levels of glycated hemoglobin (HbA1c) for the prediction of first cardiovascular events is uncertain. OBJECTIVE: To determine whether adding information on HbA1c values to conventional cardiovascular risk factors is associated with improvement in prediction of cardiovascular disease (CVD) risk. DESIGN, SETTING, AND PARTICIPANTS: Analysis of individual-participant data available from 73 prospective studies involving 294,998 participants without a known history of diabetes mellitus or CVD at the baseline assessment. MAIN OUTCOMES AND MEASURES: Measures of risk discrimination for CVD outcomes (eg, C-index) and reclassification (eg, net reclassification improvement) of participants across predicted 10-year risk categories of low (<5%), intermediate (5% to <7.5%), and high (≥7.5%) risk. RESULTS: During a median follow-up of 9.9 (interquartile range, 7.6-13.2) years, 20,840 incident fatal and nonfatal CVD outcomes (13,237 coronary heart disease and 7603 stroke outcomes) were recorded. In analyses adjusted for several conventional cardiovascular risk factors, there was an approximately J-shaped association between HbA1c values and CVD risk. The association between HbA1c values and CVD risk changed only slightly after adjustment for total cholesterol and triglyceride concentrations or estimated glomerular filtration rate, but this association attenuated somewhat after adjustment for concentrations of high-density lipoprotein cholesterol and C-reactive protein. The C-index for a CVD risk prediction model containing conventional cardiovascular risk factors alone was 0.7434 (95% CI, 0.7350 to 0.7517). The addition of information on HbA1c was associated with a C-index change of 0.0018 (0.0003 to 0.0033) and a net reclassification improvement of 0.42 (-0.63 to 1.48) for the categories of predicted 10-year CVD risk. The improvement provided by HbA1c assessment in prediction of CVD risk was equal to or better than estimated improvements for measurement of fasting, random, or postload plasma glucose levels. CONCLUSIONS AND RELEVANCE: In a study of individuals without known CVD or diabetes, additional assessment of HbA1c values in the context of CVD risk assessment provided little incremental benefit for prediction of CVD risk.
AU  - Emerging Risk Factors Collaboration (Meisinger, C.)
AU  - di Angelantonio, E.*
AU  - Gao, P.*
AU  - Khan, H.*
AU  - Butterworth, A.S.*
AU  - Wormser, D.*
AU  - Kaptoge, S.*
AU  - Kondapally Seshasai, S.R.*
AU  - Thompson, A.*
AU  - Sarwar, N.*
AU  - Willeit, P.*
AU  - Ridker, P.M.*
AU  - Barr, E.L.*
AU  - Khaw, K.T.*
AU  - Psaty, B.M.*
AU  - Brenner, H.*
AU  - Balkau, B.*
AU  - Dekker, J.M.*
AU  - Lawlor, D.A.*
AU  - Daimon, M.*
AU  - Willeit, J.*
AU  - Njølstad, I.*
AU  - Nissinen, A.*
AU  - Brunner, E.J.*
AU  - Kuller, L.H.*
AU  - Price, J.F.*
AU  - Sundström, J.*
AU  - Knuiman, M.W.*
AU  - Feskens, E.J.*
AU  - Verschuren, W.M.*
AU  - Wald, N.*
AU  - Bakker, S.J.*
AU  - Whincup, P.H.*
AU  - Ford, I.*
AU  - Goldbourt, U.*
AU  - Gómez de la Cámara, A.*
AU  - Gallacher, J.*
AU  - Simons, L.A.*
AU  - Rosengren, A.*
AU  - Sutherland, S.E.*
AU  - Björkelund, C.*
AU  - Blazer, D.G.*
AU  - Wassertheil-Smoller, S.*
AU  - Onat, A.*
AU  - Marin Ibañez, A.*
AU  - Casiglia, E.*
AU  - Jukema, J.W.*
AU  - Simpson, L.M.*
AU  - Giampaoli, S.*
AU  - Nørdestgaard, B.G.*
AU  - Selmer, R.*
AU  - Wennberg, P.*
AU  - Kauhanen, J.*
AU  - Salonen, J.T.*
AU  - Dankner, R.*
AU  - Barrett-Connor, E.*
AU  - Kavousi, M.*
AU  - Gudnason, V.*
AU  - Evans, D.*
AU  - Wallace, R.B.*
AU  - Cushman, M.*
AU  - D'Agostino, R.B.*
AU  - Umans, J.G.*
AU  - Kiyohara, Y.*
AU  - Nakagawa, H.*
AU  - Sato, S.*
AU  - Gillum, R.F.*
AU  - Folsom, A.R.*
AU  - van der Schouw, Y.T.*
AU  - Moons, K.G.*
AU  - Griffin, S.J.*
AU  - Sattar, N.*
AU  - Wareham, N.J.*
AU  - Selvin, E.*
AU  - Thompson, S.G.*
AU  - Danesh, J.*
C1  - 31281
C2  - 34314
CY  - Chicago
SP  - 1225-1233
TI  - Glycated hemoglobin measurement and prediction of cardiovascular disease.
JO  - JAMA
VL  - 311
IS  - 12
PB  - Amer Medical Assoc
PY  - 2014
SN  - 0098-7484
ER  - 

TY  - JOUR
AB  - IMPORTANCE: Intrauterine fetal death or stillbirth occurs in approximately 1 out of every 160 pregnancies and accounts for 50% of all perinatal deaths. Postmortem evaluation fails to elucidate an underlying cause in many cases. Long QT syndrome (LQTS) may contribute to this problem. OBJECTIVE: To determine the spectrum and prevalence of mutations in the 3 most common LQTS susceptible genes (KCNQ1, KCNH2, and SCN5A) for a cohort of unexplained cases. DESIGN, SETTING, AND PATIENTS: In this case series, retrospective postmortem genetic testing was conducted on a convenience sample of 91 unexplained intrauterine fetal deaths (mean [SD] estimated gestational age at fetal death, 26.3 [8.7] weeks) that were collected from 2006-2012 by the Mayo Clinic, Rochester, Minnesota, or the Fondazione IRCCS Policlinico San Matteo, Pavia, Italy. More than 1300 ostensibly healthy individuals served as controls. In addition, publicly available exome databases were assessed for the general population frequency of identified genetic variants. MAIN OUTCOMES AND MEASURES: Comprehensive mutational analyses of KCNQ1 (KV7.1, LQTS type 1), KCNH2 (HERG/KV11.1, LQTS type 2), and SCN5A (NaV1.5, LQTS type 3) were performed using denaturing high-performance liquid chromatography and direct DNA sequencing on genomic DNA extracted from decedent tissue. Functional analyses of novel mutations were performed using heterologous expression and patch-clamp recording. RESULTS: The 3 putative LQTS susceptibility missense mutations (KCNQ1, p.A283T; KCNQ1, p.R397W; and KCNH2 [1b], p.R25W), with a heterozygous frequency of less than 0.05% in more than 10 000 publicly available exomes and absent in more than 1000 ethnically similar control patients, were discovered in 3 intrauterine fetal deaths (3.3% [95% CI, 0.68%-9.3%]). Both KV7.1-A283T (16-week male) and KV7.1-R397W (16-week female) mutations were associated with marked KV7.1 loss-of-function consistent with in utero LQTS type 1, whereas the HERG1b-R25W mutation (33.2-week male) exhibited a loss of function consistent with in utero LQTS type 2. In addition, 5 intrauterine fetal deaths hosted SCN5A rare nonsynonymous genetic variants (p.T220I, p.R1193Q, involving 2 cases, and p.P2006A, involving 2 cases) that conferred in vitro electrophysiological characteristics consistent with potentially proarrhythmic phenotypes. CONCLUSIONS AND RELEVANCE: In this molecular genetic evaluation of 91 cases of intrauterine fetal death, missense mutations associated with LQTS susceptibility were discovered in 3 cases (3.3%) and overall, genetic variants leading to dysfunctional LQTS-associated ion channels in vitro were discovered in 8 cases (8.8%). These preliminary findings may provide insights into mechanisms of some cases of stillbirth.
AU  - Crotti, L.
AU  - Tester, D.J.*
AU  - White, W.M.*
AU  - Bartos, D.C.*
AU  - Insolia, R.*
AU  - Besana, A.*
AU  - Kunic, J.D.*
AU  - Will, M.L.*
AU  - Velasco, E.J.*
AU  - Bair, J.J.*
AU  - Ghidoni, A.*
AU  - Cetin, I.*
AU  - van Dyke, D.L.*
AU  - Wick, M.J.*
AU  - Brost, B.*
AU  - Delisle, B.P.*
AU  - Facchinetti, F.*
AU  - George, A.L.*
AU  - Schwartz, P.J.*
AU  - Ackerman, M.J.*
C1  - 26116
C2  - 32077
SP  - 1473-1482
TI  - Long QT syndrome-associated mutations in intrauterine fetal death.
JO  - JAMA
VL  - 309
IS  - 14
PB  - Amer. Medical Assoc.
PY  - 2013
SN  - 0098-7484
ER  - 

TY  - JOUR
AB  - Importance Helicobacter pylori is a major cause of gastritis and gastroduodenal ulcer disease and can cause cancer. H pylori prevalence is as high as 90% in some developing countries but 10% of a given population is never colonized, regardless of exposure. Genetic factors are hypothesized to confer H pylori susceptibility. Objective To identify genetic loci associated with H pylori seroprevalence in 2 independent population-based cohorts and to determine their putative pathophysiological role by whole-blood RNA gene expression profiling. Design, Setting, and Participants Two independent genome-wide association studies (GWASs) and a subsequent meta-analysis were conducted for anti-H pylori IgG serology in the Study of Health in Pomerania (SHIP) (recruitment, 1997-2001 [n=3830]) as well as the Rotterdam Study (RS-I) (recruitment, 1990-1993) and RS-II (recruitment, 2000-2001 [n=7108]) populations. Whole-blood RNA gene expression profiles were analyzed in RS-III (recruitment, 2006-2008 [n=762]) and SHIP-TREND (recruitment, 2008-2012 [n=991]), and fecal H pylori antigen in SHIP-TREND (n=961). Main Outcomes and Measures H pylori seroprevalence. Results Of 10 938 participants, 6160 (56.3%) were seropositive for H pylori. GWASs identified the toll-like receptor (TLR) locus (4p14; top-ranked single-nucleotide polymorphism (SNP), rs10004195; P=1.4 x 10(-18); odds ratio, 0.70 [95% CI, 0.65 to 0.76]) and the FCGR2A locus (1q23.3; top-ranked SNP, rs368433; P=2.1 x 10(-8); odds ratio, 0.73 [95% CI, 0.65 to 0.81]) as associated with H pylori seroprevalence. Among the 3 TLR genes at 4p14, only TLR1 was differentially expressed per copy number of the minor rs10004195-A allele (beta =-0.23 [95% CI, -0.34 to -0.11]; P=2.1 x 10(-4)). Individuals with high fecal H pylori antigen titers (optical density >1) also exhibited the highest 25% of TLR1 expression levels (P=.01 by chi(2) test). Furthermore, TLR1 exhibited an Asn248Ser substitution in the extracellular domain strongly linked to the rs10004195 SNP. Conclusions and Relevance GWAS meta-analysis identified an association between TLR1 and H pylori seroprevalence, a finding that requires replication in non-white populations. If confirmed, genetic variations in TLR1 may help explain some of the observed variation in individual risk for H pylori infection.
AU  - Mayerle, J.*
AU  - den Hoed, C.M.*
AU  - Schurmann, C.*
AU  - Stolk, L.*
AU  - Homuth, G.*
AU  - Peters, M.J.*
AU  - Capelle, L.G.*
AU  - Zimmermann, K.*
AU  - Rivadeneira, F.*
AU  - Gruska, S.*
AU  - Völzke, H.*
AU  - de Vries, A.C.*
AU  - Völker, U.*
AU  - Teumer, A.*
AU  - van Meurs, J.B.J.*
AU  - Steinmetz, I.*
AU  - Nauck, M.*
AU  - Ernst, F.*
AU  - Weiss, F.U.*
AU  - Hofman, A.*
AU  - Zenker, M.*
AU  - Kroemer, H.K.*
AU  - Prokisch, H.
AU  - Uitterlinden, A.G.*
AU  - Lerch, M.M.*
AU  - Kuipers, E.*
C1  - 24670
C2  - 31646
SP  - 1912-1920
TI  - Identification of genetic loci associated with Helicobacter pylori serologic status.
JO  - JAMA
VL  - 309
IS  - 18
PB  - Amer. Medical Assoc.
PY  - 2013
SN  - 0098-7484
ER  - 

TY  - JOUR
AB  - IMPORTANCE: Type 1 diabetes usually has a preclinical phase identified by circulating islet autoantibodies, but the rate of progression to diabetes after seroconversion to islet autoantibodies is uncertain. OBJECTIVE: To determine the rate of progression to diabetes after islet autoantibody seroconversion. DESIGN, SETTING, AND PARTICIPANTS: Data were pooled from prospective cohort studies performed in Colorado (recruitment, 1993-2006), Finland (recruitment, 1994-2009), and Germany (recruitment, 1989-2006) examining children genetically at risk for type 1 diabetes for the development of insulin autoantibodies, glutamic acid decarboxylase 65 (GAD65) autoantibodies, insulinoma antigen 2 (IA2) autoantibodies, and diabetes. Participants were all children recruited and followed up in the 3 studies (Colorado, 1962; Finland, 8597; Germany, 2818). Follow-up assessment in each study was concluded by July 2012. MAIN OUTCOMES AND MEASURES: The primary analysis was the diagnosis of type 1 diabetes in children with 2 or more autoantibodies. The secondary analysis was the diagnosis of type 1 diabetes in children with 1 autoantibody or no autoantibodies. RESULTS: Progression to type 1 diabetes at 10-year follow-up after islet autoantibody seroconversion in 585 children with multiple islet autoantibodies was 69.7% (95% CI, 65.1%-74.3%), and in 474 children with a single islet autoantibody was 14.5% (95% CI, 10.3%-18.7%). Risk of diabetes in children who had no islet autoantibodies was 0.4% (95% CI, 0.2%-0.6%) by the age of 15 years. Progression to type 1 diabetes in the children with multiple islet autoantibodies was faster for children who had islet autoantibody seroconversion younger than age 3 years (hazard ratio [HR], 1.65 [95% CI, 1.30-2.09; P < .001]; 10-year risk, 74.9% [95% CI, 69.7%-80.1%]) vs children 3 years or older (60.9% [95% CI, 51.5%-70.3%]); for children with the human leukocyte antigen (HLA) genotype DR3/DR4-DQ8 (HR, 1.35 [95% CI, 1.09-1.68; P = .007]; 10-year risk, 76.6% [95% CI, 69.2%-84%]) vs other HLA genotypes (66.2% [95% CI, 60.2%-72.2%]); and for girls (HR, 1.28 [95% CI, 1.04-1.58; P = .02];10-year risk, 74.8% [95% CI, 68.0%-81.6%]) vs boys (65.7% [95% CI, 59.3%-72.1%]). CONCLUSIONS AND RELEVANCE: The majority of children at risk of type 1 diabetes who had multiple islet autoantibody seroconversion progressed to diabetes over the next 15 years. Future prevention studies should focus on this high-risk population.
AU  - Ziegler, A.-G.
AU  - Rewers, M.*
AU  - Simell, O.*
AU  - Simell, T.*
AU  - Lempainen, J.*
AU  - Steck, A.*
AU  - Winkler, C.
AU  - Ilonen, J.*
AU  - Veijola, R.*
AU  - Knip, M.*
AU  - Bonifacio, E.*
AU  - Eisenbarth, G.S.*
C1  - 25529
C2  - 31867
SP  - 2473-2479
TI  - Seroconversion to multiple islet autoantibodies and risk of progression to diabetes in children.
JO  - JAMA
VL  - 309
IS  - 23
PB  - Amer. Medical Assoc.
PY  - 2013
SN  - 0098-7484
ER  - 

TY  - JOUR
AB  - CONTEXT: The value of assessing various emerging lipid-related markers for prediction of first cardiovascular events is debated. OBJECTIVE: To determine whether adding information on apolipoprotein B and apolipoprotein A-I, lipoprotein(a), or lipoprotein-associated phospholipase A2 to total cholesterol and high-density lipoprotein cholesterol (HDL-C) improves cardiovascular disease (CVD) risk prediction. DESIGN, SETTING, AND PARTICIPANTS: Individual records were available for 165,544 participants without baseline CVD in 37 prospective cohorts (calendar years of recruitment: 1968-2007) with up to 15,126 incident fatal or nonfatal CVD outcomes (10,132 CHD and 4994 stroke outcomes) during a median follow-up of 10.4 years (interquartile range, 7.6-14 years). MAIN OUTCOME MEASURES: Discrimination of CVD outcomes and reclassification of participants across predicted 10-year risk categories of low (<10%), intermediate (10%-<20%), and high (≥20%) risk. RESULTS: The addition of information on various lipid-related markers to total cholesterol, HDL-C, and other conventional risk factors yielded improvement in the model's discrimination: C-index change, 0.0006 (95% CI, 0.0002-0.0009) for the combination of apolipoprotein B and A-I; 0.0016 (95% CI, 0.0009-0.0023) for lipoprotein(a); and 0.0018 (95% CI, 0.0010-0.0026) for lipoprotein-associated phospholipase A2 mass. Net reclassification improvements were less than 1% with the addition of each of these markers to risk scores containing conventional risk factors. We estimated that for 100,000 adults aged 40 years or older, 15,436 would be initially classified at intermediate risk using conventional risk factors alone. Additional testing with a combination of apolipoprotein B and A-I would reclassify 1.1%; lipoprotein(a), 4.1%; and lipoprotein-associated phospholipase A2 mass, 2.7% of people to a 20% or higher predicted CVD risk category and, therefore, in need of statin treatment under Adult Treatment Panel III guidelines. CONCLUSION: In a study of individuals without known CVD, the addition of information on the combination of apolipoprotein B and A-I, lipoprotein(a), or lipoprotein-associated phospholipase A2 mass to risk scores containing total cholesterol and HDL-C led to slight improvement in CVD prediction.  
AU  - Emerging Risk Factors Collaboration (di Angelantonio, E.*
AU  - Döring, A.
AU  - Meisinger, C.
AU  - Danesh, J.*)
C1  - 28624
C2  - 33496
SP  - 2499-2506
TI  - Lipid-related markers and cardiovascular disease prediction.
JO  - JAMA
VL  - 307
IS  - 23
PB  - Amer. Medical Assoc.
PY  - 2012
SN  - 0098-7484
ER  - 

TY  - JOUR
AB  - CONTEXT: Associations of major lipids and apolipoproteins with the risk of vascular disease have not been reliably quantified. OBJECTIVE: To assess major lipids and apolipoproteins in vascular risk. DESIGN, SETTING, AND PARTICIPANTS: Individual records were supplied on 302,430 people without initial vascular disease from 68 long-term prospective studies, mostly in Europe and North America. During 2.79 million person-years of follow-up, there were 8857 nonfatal myocardial infarctions, 3928 coronary heart disease [CHD] deaths, 2534 ischemic strokes, 513 hemorrhagic strokes, and 2536 unclassified strokes. MAIN OUTCOME MEASURES: Hazard ratios (HRs), adjusted for several conventional factors, were calculated for 1-SD higher values: 0.52 log(e) triglyceride, 15 mg/dL high-density lipoprotein cholesterol (HDL-C), 43 mg/dL non-HDL-C, 29 mg/dL apolipoprotein AI, 29 mg/dL apolipoprotein B, and 33 mg/dL directly measured low-density lipoprotein cholesterol (LDL-C). Within-study regression analyses were adjusted for within-person variation and combined using meta-analysis. RESULTS: The rates of CHD per 1000 person-years in the bottom and top thirds of baseline lipid distributions, respectively, were 2.6 and 6.2 with triglyceride, 6.4 and 2.4 with HDL-C, and 2.3 and 6.7 with non-HDL-C. Adjusted HRs for CHD were 0.99 (95% CI, 0.94-1.05) with triglyceride, 0.78 (95% CI, 0.74-0.82) with HDL-C, and 1.50 (95% CI, 1.39-1.61) with non-HDL-C. Hazard ratios were at least as strong in participants who did not fast as in those who did. The HR for CHD was 0.35 (95% CI, 0.30-0.42) with a combination of 80 mg/dL lower non-HDL-C and 15 mg/dL higher HDL-C. For the subset with apolipoproteins or directly measured LDL-C, HRs were 1.50 (95% CI, 1.38-1.62) with the ratio non-HDL-C/HDL-C, 1.49 (95% CI, 1.39-1.60) with the ratio apo B/apo AI, 1.42 (95% CI, 1.06-1.91) with non-HDL-C, and 1.38 (95% CI, 1.09-1.73) with directly measured LDL-C. Hazard ratios for ischemic stroke were 1.02 (95% CI, 0.94-1.11) with triglyceride, 0.93 (95% CI, 0.84-1.02) with HDL-C, and 1.12 (95% CI, 1.04-1.20) with non-HDL-C. CONCLUSION: Lipid assessment in vascular disease can be simplified by measurement of either total and HDL cholesterol levels or apolipoproteins without the need to fast and without regard to triglyceride.
AU  - di Angelantonio, E.*
AU  - Sarwar, N.*
AU  - Perry, P.*
AU  - Kaptoge, S.*
AU  - Ray, K.K.*
AU  - Thompson, A.*
AU  - Wood, A.M.*
AU  - Lewington, S.*
AU  - Sattar, N.*
AU  - Packard, C.J.*
AU  - Collins, R.*
AU  - Thompson, S.G.*
AU  - Tipping, R.W.*
AU  - Ford, C.E.*
AU  - Pressel, S.L.*
AU  - Walldius, G.*
AU  - Jungner, I.*
AU  - Folsom, A.R.*
AU  - Chambless, L.E.*
AU  - Panagiotakos, D.B.*
AU  - Pitsavos, C.*
AU  - Chrysohoou, C.*
AU  - Stefanadis, C.*
AU  - Knuiman, M.*
AU  - Goldbourt, U.*
AU  - Benderly, M.*
AU  - Tanne, D.*
AU  - Whincup, P.H.*
AU  - Wannamethee, S.G.*
AU  - Morris, R.W.*
AU  - Kiechl, S.*
AU  - Willeit, J.*
AU  - Santer, P.*
AU  - Mayr, A.*
AU  - Wald, N.*
AU  - Ebrahim, S.*
AU  - Lawlor, D.A.*
AU  - Yarnell, J.W.*
AU  - Gallacher, J.*
AU  - Casiglia, E.*
AU  - Tikhonoff, V.*
AU  - Nietert, P.J.*
AU  - Sutherland, S.E.*
AU  - Bachman, D.L.*
AU  - Keil, J.E.*
AU  - Cushman, M.*
AU  - Psaty, B.M.*
AU  - Tracy, R.P.*
AU  - Tybjaerg-Hansen, A.*
AU  - Nørdestgaard, B.G.*
AU  - Benn, M.*
AU  - Frikke-Schmidt, R.*
AU  - Giampaoli, S.*
AU  - Palmieri, L.*
AU  - Panico, S.*
AU  - Vanuzzo, D.*
AU  - Pilotto, L.*
AU  - Gómez de la Cámara, A.*
AU  - Gómez-Gerique, J.A.*
AU  - Simons, L.*
AU  - McCallum, J.*
AU  - Friedlander, Y.*
AU  - Fowkes, F.G.*
AU  - Lee, A.J.*
AU  - Smith, F.B.*
AU  - Taylor, J.*
AU  - Guralnik, J.M.*
AU  - Phillips, C.L.*
AU  - Wallace, R.*
AU  - Guralnik, J.*
AU  - Blazer, D.G.*
AU  - Khaw, K.T.*
AU  - Brenner, H.*
AU  - Raum, E.*
AU  - Müller, H.*
AU  - Rothenbacher, D.*
AU  - Jansson, J.H.*
AU  - Wennberg, P.*
AU  - Nissinen, A.*
AU  - Donfrancesco, C.*
AU  - Salomaa, V.*
AU  - Harald, K.*
AU  - Jousilahti, P.*
AU  - Vartiainen, E.*
AU  - Woodward, M.*
AU  - D'Agostino, R.B.*
AU  - Wolf, P.A.*
AU  - Vasan, R.S.*
AU  - Pencina, M.J.*
AU  - Bladbjerg, E.M.*
AU  - Jørgensen, T.*
AU  - Møller, L.*
AU  - Jespersen, J.*
AU  - Dankner, R.*
AU  - Chetrit, A.*
AU  - Lubin, F.*
AU  - Rosengren, A.*
AU  - Wilhelmsen, L.*
AU  - Lappas, G.*
AU  - Eriksson, H.*
AU  - Björkelund, C.*
AU  - Lissner, L.*
AU  - Bengtsson, C.*
AU  - Cremer, P.*
AU  - Nagel, D.*
AU  - Tilvis, R.S.*
AU  - Strandberg, T.E.*
AU  - Rodriguez, B.*
AU  - Dekker, J.M.*
AU  - Nijpels, G.*
AU  - Stehouwer, C.D.*
AU  - Rimm, E.*
AU  - Pai, J.K.*
AU  - Sato, S.*
AU  - Iso, H.*
AU  - Kitamura, A.*
AU  - Noda, H.*
AU  - Salonen, J.T.*
AU  - Nyyssönen, K.*
AU  - Tuomainen, T.P.*
AU  - Deeg, D.J.*
AU  - Poppelaars, J.L.*
AU  - Cooper, J.A.*
AU  - Hedblad, B.*
AU  - Berglund, G.*
AU  - Engström, G.*
AU  - Verschuren, W.M.*
AU  - Döring, A.
AU  - Koenig, W.*
AU  - Meisinger, C.
AU  - Mraz, W.*
AU  - Verschure, W.M.*
AU  - Blokstra, A.*
AU  - Bas, Bueno-de-Mesquita, H.*
AU  - Kuller, L.H.*
AU  - Grandits, G.*
AU  - Selmer, R.*
AU  - Tverdal, A.*
AU  - Nystad, W.*
AU  - Gillum, R.*
AU  - Mussolino, M.*
AU  - Hankinson, S.*
AU  - Manson, J.*
AU  - Knottenbelt, C.*
AU  - Bauer, K.A.*
AU  - Naito, Y.*
AU  - Holme, I.*
AU  - Nakagawa, H.*
AU  - Miura, K.*
AU  - Ducimetiere, P.*
AU  - Jouven, X.*
AU  - Crespo, C.J.
AU  - Garcia Palmieri, M.R.*
AU  - Amouyel, P.*
AU  - Arveiler, D.*
AU  - Evans, A.*
AU  - Ferrieres, J.*
AU  - Schulte, H.*
AU  - Assmann, G.*
AU  - Shepherd, J.*
AU  - Ford, I.*
AU  - Cantin, B.*
AU  - Lamarche, B.*
AU  - Després, J.P.*
AU  - Dagenais, G.R.*
AU  - Barrett-Connor, E.*
AU  - Wingard, D.L.*
AU  - Bettencourt, R.*
AU  - Gudnason, V.*
AU  - Aspelund, T.*
AU  - Sigurdsson, G.*
AU  - Thorsson, B.*
AU  - Trevisan, M.*
AU  - Witteman, J.*
AU  - Kardys, I.*
AU  - Breteler, M.*
AU  - Hofman, A.*
AU  - Tunstall-Pedoe, H.*
AU  - Tavendale, R.*
AU  - Lowe, G.D.*
AU  - Howard, B.V.*
AU  - Zhang, Y.*
AU  - Best, L.*
AU  - Umans, J.*
AU  - Ben-Shlomo, Y.*
AU  - Davey Smith, G.*
AU  - Onat, A.*
AU  - Njølstad, I.*
AU  - Mathiesen, E.B.*
AU  - Løchen, M.L.*
AU  - Wilsgaard, T.*
AU  - Ingelsson, E.*
AU  - Lind, L.*
AU  - Giedraitis, V.*
AU  - Lannfelt, L.*
AU  - Gaziano, J.M.*
AU  - Stampfer, M.*
AU  - Ridker, P.*
AU  - Ulmer, H.*
AU  - Diem, G.*
AU  - Concin, H.*
AU  - Tosetto, A.*
AU  - Rodeghiero, F.*
AU  - Marmot, M.*
AU  - Clarke, R.*
AU  - Fletcher, A.*
AU  - Brunner, E.*
AU  - Shipley, M.*
AU  - Buring, J.*
AU  - Cobbe, S.M.*
AU  - Robertson, M.*
AU  - He, Y.*
AU  - Marin Ibañez, A.*
AU  - Feskens, E.J.*
AU  - Kromhout, D.*
AU  - Walker, M.
AU  - Watson, S.*
AU  - Erqou, S.*
AU  - Orfei, L.*
AU  - Pennells, L.*
AU  - Perry, P.L.*
AU  - Alexander, M.*
AU  - Wensley, F.*
AU  - White, I.R.*
AU  - Danesh, J.*
C1  - 461
C2  - 27232
SP  - 1993-2000
TI  - Major lipids, apolipoproteins, and risk of vascular disease.
JO  - JAMA
VL  - 302
IS  - 18
PB  - American Medical Assoc.
PY  - 2009
SN  - 0098-7484
ER  - 

TY  - JOUR
AB  - CONTEXT: Circulating concentration of lipoprotein(a) (Lp[a]), a large glycoprotein attached to a low-density lipoprotein-like particle, may be associated with risk of coronary heart disease (CHD) and stroke. OBJECTIVE: To assess the relationship of Lp(a) concentration with risk of major vascular and nonvascular outcomes. STUDY SELECTION: Long-term prospective studies that recorded Lp(a) concentration and subsequent major vascular morbidity and/or cause-specific mortality published between January 1970 and March 2009 were identified through electronic searches of MEDLINE and other databases, manual searches of reference lists, and discussion with collaborators. DATA EXTRACTION: Individual records were provided for each of 126,634 participants in 36 prospective studies. During 1.3 million person-years of follow-up, 22,076 first-ever fatal or nonfatal vascular disease outcomes or nonvascular deaths were recorded, including 9336 CHD outcomes, 1903 ischemic strokes, 338 hemorrhagic strokes, 751 unclassified strokes, 1091 other vascular deaths, 8114 nonvascular deaths, and 242 deaths of unknown cause. Within-study regression analyses were adjusted for within-person variation and combined using meta-analysis. Analyses excluded participants with known preexisting CHD or stroke at baseline. DATA SYNTHESIS: Lipoprotein(a) concentration was weakly correlated with several conventional vascular risk factors and it was highly consistent within individuals over several years. Associations of Lp(a) with CHD risk were broadly continuous in shape. In the 24 cohort studies, the rates of CHD in the top and bottom thirds of baseline Lp(a) distributions, respectively, were 5.6 (95% confidence interval [CI], 5.4-5.9) per 1000 person-years and 4.4 (95% CI, 4.2-4.6) per 1000 person-years. The risk ratio for CHD, adjusted for age and sex only, was 1.16 (95% CI, 1.11-1.22) per 3.5-fold higher usual Lp(a) concentration (ie, per 1 SD), and it was 1.13 (95% CI, 1.09-1.18) following further adjustment for lipids and other conventional risk factors. The corresponding adjusted risk ratios were 1.10 (95% CI, 1.02-1.18) for ischemic stroke, 1.01 (95% CI, 0.98-1.05) for the aggregate of nonvascular mortality, 1.00 (95% CI, 0.97-1.04) for cancer deaths, and 1.00 (95% CI, 0.95-1.06) for nonvascular deaths other than cancer. CONCLUSION: Under a wide range of circumstances, there are continuous, independent, and modest associations of Lp(a) concentration with risk of CHD and stroke that appear exclusive to vascular outcomes.
AU  - Erqou, S.*
AU  - Kaptoge, S.*
AU  - Perry, P.L.*
AU  - di Angelantonio, E.*
AU  - Thompson, A.*
AU  - White, I.R.*
AU  - Marcovina, S.M.*
AU  - Collins, R.*
AU  - Thompson, S.G.*
AU  - Danesh, J.*
AU  - Tipping, R.W.*
AU  - Ford, C.E.*
AU  - Simpson, L.M.*
AU  - Walldius, G.*
AU  - Jungner, I.*
AU  - Folsom, A.R.*
AU  - Chambless, L.*
AU  - Panagiotakos, D.*
AU  - Pitsavos, C.*
AU  - Chrysohoou, C.*
AU  - Stefanadis, C.*
AU  - Goldbourt, U.*
AU  - Benderly, M.*
AU  - Tanne, D.*
AU  - Whincup, P.*
AU  - Wannamethee, S.G.*
AU  - Morris, R.W.*
AU  - Kiechl, S.*
AU  - Willeit, J.*
AU  - Santer, P.*
AU  - Mayr, A.*
AU  - Wald, N.*
AU  - Ebrahim, S.*
AU  - Lawlor, D.*
AU  - Yarnell, J.*
AU  - Gallacher, J.*
AU  - Casiglia, E.*
AU  - Tikhonoff, V.*
AU  - Nietert, P.J.*
AU  - Sutherland, S.E.*
AU  - Bachman, D.L.*
AU  - Cushman, M.*
AU  - Psaty, B.M.*
AU  - Tracy, R.*
AU  - Tybjaerg-Hansen, A.*
AU  - Nørdestgaard, B.G.*
AU  - Frikke-Schmidt, R.*
AU  - Kamstrup, P.R.*
AU  - Giampaoli, S.*
AU  - Palmieri, L.*
AU  - Panico, S.*
AU  - Vanuzzo, D.*
AU  - Pilotto, L.*
AU  - Gómez de la Cámara, A.*
AU  - Gómez Gerique, J.A.*
AU  - Simons, L.*
AU  - McCallum, J.*
AU  - Friedlander, Y.*
AU  - Fowkes, F.G.*
AU  - Lee, A.*
AU  - Smith, F.B.*
AU  - Taylor, J.*
AU  - Wallace, R.B.*
AU  - Phillips, C.L.*
AU  - Blazer, D.G.*
AU  - Guralnik, J.M.*
AU  - Brenner, H.*
AU  - Raum, E.*
AU  - Müller, H.*
AU  - Rothenbacher, D.*
AU  - Jansson, J.H.*
AU  - Wennberg, P.*
AU  - Nissinen, A.*
AU  - Donfrancesco, C.*
AU  - Salomaa, V.*
AU  - Harald, K.*
AU  - Jousilahti, P.*
AU  - Vartiainen, E.*
AU  - Woodward, M.*
AU  - D'Agostino, R.B.*
AU  - Wolf, P.A.*
AU  - Vasan, R.S.*
AU  - Pencina, M.J.*
AU  - Bladbjerg, E.M.*
AU  - Jørgensen, T.*
AU  - Møller, L.*
AU  - Jespersen, J.*
AU  - Dankner, R.*
AU  - Chetrit, A.*
AU  - Lubin, F.*
AU  - Rosengren, A.*
AU  - Wilhelmsen, L.*
AU  - Lappas, G.*
AU  - Eriksson, H.*
AU  - Björkelund, C.*
AU  - Lissner, L.*
AU  - Bengtsson, C.*
AU  - Cremer, P.*
AU  - Nagel, D.*
AU  - Tilvis, R.S.*
AU  - Strandberg, T.E.*
AU  - Rodriguez, B.*
AU  - Dekker, J.*
AU  - Nijpels, G.*
AU  - Stehouwer, C.D.*
AU  - Rimm, E.*
AU  - Pai, J.K.*
AU  - Sato, S.*
AU  - Iso, H.*
AU  - Kitamura, A.*
AU  - Noda, H.*
AU  - Salonen, J.T.*
AU  - Nyyssönen, K.*
AU  - Tuomainen, T.P.*
AU  - Deeg, D.J.*
AU  - Poppelaars, J.L.*
AU  - Hedblad, B.*
AU  - Berglund, G.*
AU  - Engström, G.*
AU  - Verschuren, W.M.*
AU  - Blokstra, A.*
AU  - Döring, A.
AU  - Koenig, W.*
AU  - Meisinger, C.
AU  - Mraz, W.*
AU  - Bueno-de-Mesquita, H.B.*
AU  - Kuller, L.H.*
AU  - Grandits, G.*
AU  - Selmer, R.*
AU  - Tverdal, A.*
AU  - Nystad, W.*
AU  - Gillum, R.F.*
AU  - Mussolino, M.*
AU  - Hankinson, S.*
AU  - Manson, J.E.*
AU  - Cooper, J.A.*
AU  - Bauer, K.A.*
AU  - Naito, Y.*
AU  - Holme, I.*
AU  - Nakagawa, H.*
AU  - Miura, K.*
AU  - Ducimetiere, P.*
AU  - Jouven, X.*
AU  - Luc, G.*
AU  - Crespo, C.J.*
AU  - Garcia Palmieri, M.R.*
AU  - Amouyel, P.*
AU  - Arveiler, D.*
AU  - Evans, A.*
AU  - Ferrieres, J.*
AU  - Schulte, H.*
AU  - Assmann, G.*
AU  - Shepherd, J.*
AU  - Packard, C.J.*
AU  - Sattar, N.*
AU  - Ford, I.*
AU  - Cantin, B.*
AU  - Lamarche, B.*
AU  - Després, J.P.*
AU  - Dagenais, G.R.*
AU  - Barrett-Connor, E.*
AU  - Daniels, L.B.*
AU  - Laughlin, G.A.*
AU  - Gudnason, V.*
AU  - Aspelund, T.*
AU  - Sigurdsson, G.*
AU  - Thorsson, B.*
AU  - Trevisan, M.*
AU  - Witteman, J.*
AU  - Kardys, I.*
AU  - Breteler, M.M.*
AU  - Hofman, A.*
AU  - Tunstall-Pedoe, H.*
AU  - Tavendale, R.*
AU  - Lowe, G.*
AU  - Ben-Shlomo, Y.*
AU  - Davey Smith, G.*
AU  - Howard, B.V.*
AU  - Zhang, Y.*
AU  - Best, L.*
AU  - Umans, J.*
AU  - Onat, A.*
AU  - Njølstad, I.*
AU  - Mathiesen, E.B.*
AU  - Løchen, M.L.*
AU  - Wilsgaard, T.*
AU  - Ingelsson, E.*
AU  - Sundström, J.*
AU  - Lind, L.*
AU  - Lannfelt, L.*
AU  - Gaziano, J.M.*
AU  - Stampfer, M.*
AU  - Ridker, P.M.*
AU  - Ulmer, H.*
AU  - Diem, G.*
AU  - Concin, H.*
AU  - Tosetto, A.*
AU  - Rodeghiero, F.*
AU  - Marmot, M.*
AU  - Clarke, R.*
AU  - Fletcher, A.*
AU  - Brunner, E.*
AU  - Shipley, M.*
AU  - Buring, J.*
AU  - Cobbe, S.*
AU  - Robertson, M.*
AU  - He, Y.*
AU  - Marin Ibanñez, A.*
AU  - Feskens, E.*
AU  - Kromhout, D.*
AU  - Walker, M.*
AU  - Watson, S.*
AU  - Lewington, S.*
AU  - Orfei, L.*
AU  - Pennells, L.*
AU  - Ray, K.K.*
AU  - Sarwar, N.*
AU  - Alexander, M.*
AU  - Wensley, F.*
AU  - Wood, A.M.
C1  - 276
C2  - 27129
SP  - 412-423
TI  - Lipoprotein(a) concentration and the risk of coronary heart disease, stroke, and nonvascular mortality.
JO  - JAMA
VL  - 302
IS  - 4
PB  - American Medical Assoc.
PY  - 2009
SN  - 0098-7484
ER  - 

TY  - JOUR
AB  - CONTEXT: Echocardiographic measures of left ventricular (LV) structure and function are heritable phenotypes of cardiovascular disease. OBJECTIVE: To identify common genetic variants associated with cardiac structure and function by conducting a meta-analysis of genome-wide association data in 5 population-based cohort studies (stage 1) with replication (stage 2) in 2 other community-based samples. DESIGN, SETTING, AND PARTICIPANTS: Within each of 5 community-based cohorts comprising the EchoGen consortium (stage 1; n = 12 612 individuals of European ancestry; 55% women, aged 26-95 years; examinations between 1978-2008), we estimated the association between approximately 2.5 million single-nucleotide polymorphisms (SNPs; imputed to the HapMap CEU panel) and echocardiographic traits. In stage 2, SNPs significantly associated with traits in stage 1 were tested for association in 2 other cohorts (n = 4094 people of European ancestry). Using a prespecified P value threshold of 5 x 10(-7) to indicate genome-wide significance, we performed an inverse variance-weighted fixed-effects meta-analysis of genome-wide association data from each cohort. MAIN OUTCOME MEASURES: Echocardiographic traits: LV mass, internal dimensions, wall thickness, systolic dysfunction, aortic root, and left atrial size. RESULTS: In stage 1, 16 genetic loci were associated with 5 echocardiographic traits: 1 each with LV internal dimensions and systolic dysfunction, 3 each with LV mass and wall thickness, and 8 with aortic root size. In stage 2, 5 loci replicated (6q22 locus associated with LV diastolic dimensions, explaining <1% of trait variance; 5q23, 12p12, 12q14, and 17p13 associated with aortic root size, explaining 1%-3% of trait variance). CONCLUSIONS: We identified 5 genetic loci harboring common variants that were associated with variation in LV diastolic dimensions and aortic root size, but such findings explained a very small proportion of variance. Further studies are required to replicate these findings, identify the causal variants at or near these loci, characterize their functional significance, and determine whether they are related to overt cardiovascular disease.
AU  - Vasan, R.S.*
AU  - Glazer, N.L.*
AU  - Felix, J.F.*
AU  - Lieb, W.*
AU  - Wild, P.S.*
AU  - Felix, S.B.*
AU  - Watzinger, N.*
AU  - Larson, M.G.*
AU  - Smith, N.L.*
AU  - Dehghan, A.*
AU  - Grosshennig, A.*
AU  - Schillert, A.*
AU  - Teumer, A.*
AU  - Schmidt, R.*
AU  - Kathiresan, S.*
AU  - Lumley, T.*
AU  - Aulchenko, Y.S.*
AU  - König, I.R.*
AU  - Zeller, T.*
AU  - Homuth, G.*
AU  - Struchalin, M.*
AU  - Aragam, J.*
AU  - Bis, J.C.*
AU  - Rivadeneira, F.*
AU  - Erdmann, J.*
AU  - Schnabel, R.B.*
AU  - Dörr, M.*
AU  - Zweiker, R.*
AU  - Lind, L.*
AU  - Rodeheffer, R.J.*
AU  - Greiser, K.H.*
AU  - Levy, D.*
AU  - Haritunians, T.*
AU  - Deckers, J.W.*
AU  - Stritzke, J.*
AU  - Lackner, K.J.*
AU  - Völker, U.*
AU  - Ingelsson, E.*
AU  - Kullo, I.*
AU  - Haerting, J.*
AU  - O'Donnell, C.J.*
AU  - Heckbert, S.R.*
AU  - Stricker, B.H.*
AU  - Ziegler, A.*
AU  - Reffelmann, T.*
AU  - Redfield, M.M.*
AU  - Werdan, K.*
AU  - Mitchell, G.F.*
AU  - Rice, K.*
AU  - Arnett, D.K.*
AU  - Hofman, A.*
AU  - Gottdiener, J.S.*
AU  - Uitterlinden, A.G.*
AU  - Meitinger, T.*
AU  - Blettner, M.*
AU  - Friedrich, N.*
AU  - Wang, T.J.*
AU  - Psaty, B.M.*
AU  - van Duijn, C.M.
AU  - Wichmann, H.-E.
AU  - Munzel, T.F.*
AU  - Kroemer, H.K.*
AU  - Benjamin, E.J.*
AU  - Rotter, J.I.*
AU  - Witteman, J.C.*
AU  - Schunkert, H.*
AU  - Schmidt, H.*
AU  - Völzke, H.*
AU  - Blankenberg, S.*
C1  - 589
C2  - 26913
CY  - CHICAGO, USA
SP  - 168-178
TI  - Genetic variants associated with cardiac structure and function: A meta-analysis and replication of genome-wide association data.
JO  - JAMA
VL  - 302
IS  - 2
PB  - AMER MEDICAL ASSOC
PY  - 2009
SN  - 0098-7484
ER  - 

TY  - JOUR
AU  - Schneider, E.C.*
AU  - Riehl, V.*
AU  - Courté-Wienecke, S.
AU  - Eddy, D.M.*
AU  - Sennett, C.*
C1  - 21031
C2  - 19229
SP  - 1184-1190
TI  - Enhancing performance measurement. NCAQ's road map for a health information framework.
JO  - JAMA
VL  - 282 (12)
PY  - 1999
SN  - 0098-7484
ER  -