Analysis of 17,576 Potentially Functional SNPs in Three Case–Control Studies of Myocardial Infarction

Myocardial infarction (MI) is a common complex disease with a genetic component. While several single nucleotide polymorphisms (SNPs) have been reported to be associated with risk of MI, they do not fully explain the observed genetic component of MI. We have been investigating the association between MI and SNPs that are located in genes and have the potential to affect gene function or expression. We have previously published studies that tested about 12,000 SNPs for association with risk of MI, early-onset MI, or coronary stenosis. In the current study we tested 17,576 SNPs that could affect gene function or expression. In order to use genotyping resources efficiently, we staged the testing of these SNPs in three case–control studies of MI. In the first study (762 cases, 857 controls) we tested 17,576 SNPs and found 1,949 SNPs that were associated with MI (P<0.05). We tested these 1,949 SNPs in a second study (579 cases and 1159 controls) and found that 24 SNPs were associated with MI (1-sided P<0.05) and had the same risk alleles in the first and second study. Finally, we tested these 24 SNPs in a third study (475 cases and 619 controls) and found that 5 SNPs in 4 genes (ENO1, FXN (2 SNPs), HLA-DPB2, and LPA) were associated with MI in the third study (1-sided P<0.05), and had the same risk alleles in all three studies. The false discovery rate for this group of 5 SNPs was 0.23. Thus, we have identified 5 SNPs that merit further examination for their potential association with MI. One of these SNPs (in LPA), has been previously shown to be associated with risk of cardiovascular disease in other studies

Altered Gene Expression by Low-Dose Arsenic Exposure in Humans and Cultured Cardiomyocytes: Assessment by Real-Time PCR Arrays

Chronic arsenic exposure results in higher risk of skin, lung, and bladder cancer, as well as cardiovascular disease and diabetes. The purpose of this study was to investigate the effects on expression of selected genes in the blood lymphocytes from 159 people exposed chronically to arsenic in their drinking water using a novel RT-PCR TaqMan low-density array (TLDA). We found that expression of tumor necrosis factor-α (TNF-α), which activates both inflammation and NF-κB-dependent survival pathways, was strongly associated with water and urinary arsenic levels. Expression of KCNA5, which encodes a potassium ion channel protein, was positively associated with water and toe nail arsenic levels. Expression of 2 and 11 genes were positively associated with nail and urinary arsenic, respectively. Because arsenic exposure has been reported to be associated with long QT intervals and vascular disease in humans, we also used this TLDA for analysis of gene expression in human cardiomyocytes exposed to arsenic in vitro. Expression of the ion-channel genes CACNA1, KCNH2, KCNQ1 and KCNE1 were down-regulated by 1-μM arsenic. Alteration of some common pathways, including those involved in oxidative stress, inflammatory signaling, and ion-channel function, may underlay the seemingly disparate array of arsenic-associated diseases, such as cancer, cardiovascular disease, and diabetes

Open source anaerobic and temperature-controlled <i>in vitro </i>model enabling real-time release studies with live bacteria

In vitro release and dissolution models are widely used in the development phases of oral drug delivery systems to measure how an active pharmaceutical ingredient (API) is released from a dosage form. However, additional requirements for these models arise when evaluating probiotic dosage forms since they are often sensitive to temperature and oxygen levels. As a solution to this, we propose a custom-designed anaerobic in vitro release setup, made mainly by 3D printing and laser cutting, to function together with state-of-the-art pharmaceutical dissolution equipment – in this case, a microDISS Profiler™. The in vitro release model makes it possible to study the release rate of oxygen-sensitive probiotics in simulated intestinal conditions, while ensuring their survival due to the anaerobic conditions. This has not been possible so far since the available in vitro dissolution models have not been compatible with anaerobic conditions. With two different case studies, the developed model combined with a microDISS Profiler™ has proven capable of measuring the release of a probiotic and a small-molecule API from microdevices for oral drug delivery. Further, the model facilitated the survival of anaerobic bacteria present in the release medium

Weight Change During the Postintervention Follow-up of Look AHEAD

OBJECTIVE: Patients with type 2 diabetes are encouraged to lose weight, but excessive weight loss in older adults may be a marker of poor health and subsequent mortality. We examined weight change during the postintervention period of Look AHEAD, a randomized trial comparing intensive lifestyle intervention (ILI) with diabetes support and education (DSE) (control) in overweight/obese individuals with type 2 diabetes and sought to identify predictors of excessive postintervention weight loss and its association with mortality. RESEARCH DESIGN AND METHODS: These secondary analyses compared postintervention weight change (year 8 to final visit; median 16 years) in ILI and DSE in 3,999 Look AHEAD participants. Using empirically derived trajectory categories, we compared four subgroups: weight gainers (n = 307), weight stable (n = 1,561), steady losers (n = 1,731), and steep losers (n = 380), on postintervention mortality, demographic variables, and health status at randomization and year 8. RESULTS: Postintervention weight change averaged -3.7 ± 9.5%, with greater weight loss in the DSE than the ILI group. The steep weight loss trajectory subgroup lost on average 17.7 ± 6.6%; 30% of steep losers died during postintervention follow-up versus 10-18% in other trajectories (P \u3c 0001). The following variables distinguished steep losers from weight stable: baseline, older, longer diabetes duration, higher BMI, and greater multimorbidity; intervention, randomization to control group and less weight loss in years 1-8; and year 8, higher prevalence of frailty, multimorbidity, and depressive symptoms and lower use of weight control strategies. CONCLUSIONS: Steep weight loss postintervention was associated with increased risk of mortality. Older individuals with longer duration of diabetes and multimorbidity should be monitored for excessive unintentional weight loss