Explore the vast range of titles available.

Research is needed to identify lipidomic markers associated with habitual physical activity (PA) among American Indian adults and examine their associations with diabetes risk. We performed LC-MS to quantify 1,542 fasting plasma lipids from 1,779 participants at baseline and 1,406 at follow-up (about 5.5-year apart). PA was objectively measured using pedometers at both visits. We identified lipids associated with PA using mixed-effects linear regression, adjusting for BMI and other covariates. Logistic and linear regression was used to evaluate the associations of PA-related lipids with incident diabetes/prediabetes and glucose/insulin metrics. Mediation role of lipids was examined. Among 1,047 participants with normal fasting glucose at baseline, 68 developed diabetes and 178 developed prediabetes. PA was associated with 127 lipids (q < 0.05), including positive associations with glycerophospholipids and inverse associations with triacylglycerols. Eighteen of the 36 annotated lipids were associated with incident diabetes/prediabetes, with 16 linked to lower PA and higher diabetes risk. Most PA-related lipids were also associated with changes in glucose/insulin metrics, and 28 lipids mediated the positive association between PA and insulin sensitivity. Overall, we identified lipidomic signatures of PA among American Indians. These lipids were associated with diabetes risk, potentially through mediating the protective effects of PA on insulin sensitivity.

Dyslipidemia has been associated with depression, but individual lipid species associated with depression remain largely unknown. The temporal relationship between lipid metabolism and the development of depression also remains to be determined. We studied 3721 fasting plasma samples from 1978 American Indians attending two exams (2001–2003, 2006–2009, mean ~5.5 years apart) in the Strong Heart Family Study. Plasma lipids were repeatedly measured by untargeted liquid chromatography-mass spectrometry (LC-MS). Depressive symptoms were assessed using the 20-item Center for Epidemiologic Studies for Depression (CES-D). Participants at risk for depression were defined as total CES-D score ≥16. Generalized estimating equation (GEE) was used to examine the associations of lipid species with incident or prevalent depression, adjusting for covariates. The associations between changes in lipids and changes in depressive symptoms were additionally adjusted for baseline lipids. We found that lower levels of sphingomyelins and glycerophospholipids and higher level of lysophospholipids were significantly associated with incident and/or prevalent depression. Changes in sphingomyelins, glycerophospholipids, acylcarnitines, fatty acids and triacylglycerols were associated with changes in depressive symptoms and other psychosomatic traits. We also identified differential lipid networks associated with risk of depression. The observed alterations in lipid metabolism may affect depression through increasing the activities of acid sphingomyelinase and phospholipase A2, disturbing neurotransmitters and membrane signaling, enhancing inflammation, oxidative stress, and lipid peroxidation, and/or affecting energy storage in lipid droplets or membrane formation. These findings illuminate the mechanisms through which dyslipidemia may contribute to depression and provide initial evidence for targeting lipid metabolism in developing preventive and therapeutic interventions for depression.

5-hydroxymethylcytosine, also known as the sixth DNA base of the genome, plays an important role in brain aging and neurological disorders such as Alzheimer’s disease. However, little is known about its genome-wide distribution and its association with Alzheimer’s disease pathology. Here, we report a genome-wide profiling of 5-hydroxymethylcytosine in 1079 autopsied brains (dorsolateral prefrontal cortex) of older individuals and assess its association with multiple measures of Alzheimer’s disease pathologies, including pathological diagnosis of Alzheimer’s disease, amyloid-β load, and PHFtau tangle density. Of 197,765 5-hydroxymethylcytosine regions detected, we identified 2821 differentially hydroxymethylated regions associated with Alzheimer’s disease neuropathology after controlling for multiple testing and covariates. Many differentially hydroxymethylated regions are located within known Alzheimer’s disease loci, such as RIN3, PLCG2, ITGA2B , and USP6NL . Integrative multi-omics analyses support a potential mechanistic role of 5-hydroxymethylcytosine alterations in Alzheimer’s disease. Our study presents a large-scale genome-wide atlas of 5-hydroxymethylcytosine in Alzheimer’s brain and offers insight into the mechanism underlying Alzheimer’s disease pathogenesis. 5-hydroxymethylcytosine, the sixth DNA base, plays a key role in brain aging and Alzheimer’s disease. Here, the authors study over 1000 deceased brains to identify genes with 5-hydroxymethylcytosine alterations linked to Alzheimer’s pathology.

Background Due to the high cost and high failure rate of Phase III trials where a classical group sequential design (GSD) is usually used, seamless Phase II/III designs are more and more popular to improve trial efficiency. A potential attraction of Phase II/III design is to allow a randomized proof-of-concept stage prior to committing to the full cost of a Phase III trial. Population selection during the trial allows a trial to adapt and focus investment where it is most likely to provide patient benefit. Previous methods have been developed for this problem when there is a single primary endpoint and two possible populations. Methods To find the population that potentially benefits with one or two primary endpoints (e.g., progression free survival (PFS), overall survival (OS)), we propose a gated group sequential design for a seamless Phase II/III trial design with adaptive population selection. Results The investigated design controls the familywise error rate and allows multiple interim analyses to enable early stopping for efficacy or futility. Simulations and an illustrative example suggest that the proposed gated group sequential design has more power and requires less time and resources compared to the group sequential design and adaptive design. Conclusions Combining the group sequential design and adaptive design, the gated group sequential design has more power and higher efficiency while controlling for the familywise error rate. It has the potential to save drug development cost and more quickly fulfill unmet medical needs.

Background Alterations in DNA methylation (DNAm) have been reported to be a mechanism by which bariatric surgeries resulted in considerable metabolic improvements. Previous studies have mostly focused on change in DNAm following weight-loss interventions, yet whether DNAm prior to intervention can explain the variability in glycemic outcomes has not been investigated. Here, we aim to examine whether baseline DNAm is differentially associated with glycemic outcomes induced by different types of weight-loss interventions. Methods Participants were 75 adults with severe obesity who underwent non-surgical intensive medical intervention (IMI), adjustable gastric band (BAND) or Roux-en-Y gastric bypass (RYGB) ( n  = 25 each). Changes in fasting plasma glucose (FPG) and glycated hemoglobin (HbA1c) were measured at 1-year after intervention. DNAm was quantified by Illumina 450 K arrays in baseline peripheral blood DNA. Epigenome-wide association studies were performed to identify CpG probes that modify the effects of different weight-loss interventions on glycemic outcomes, i.e., changes in FPG and HbA1c, by including an interaction term between types of intervention and DNAm. Models were adjusted for weight loss and baseline clinical factors. Results Baseline DNAm levels at 3216 and 117 CpGs were differentially associated with changes in FPG and HbA1c, respectively, when comparing RYGB versus IMI. Of these, 79 CpGs were significant for both FPG and HbA1c. The identified genes are enriched in adaptive thermogenesis, temperature homeostasis and regulation of cell population proliferation. Additionally, DNAm at 6 CpGs was differentially associated with changes in HbA1c when comparing RYGB versus BAND. Conclusions Baseline DNAm is differentially associated with glycemic outcomes in response to different types of weight-loss interventions, independent of weight loss and other clinical factors. Such findings provided initial evidence that baseline DNAm levels may serve as potential biomarkers predictive of differential glycemic outcomes in response to different types of weight-loss interventions.

It is well recognized that patients with severe obesity exhibit remarkable heterogeneity in response to different types of weight-loss interventions. Those who undergo Roux-en-Y gastric bypass (RYGB) usually exhibit more favorable glycemic outcomes than those who receive adjustable gastric banding (BAND) or intensive medical intervention (IMI). The molecular mechanisms behind these observations, however, remain largely unknown. To identify the plasma metabolites associated with differential glycemic outcomes induced by weight-loss intervention, we studied 75 patients with severe obesity (25 each in RYGB, BAND, or IMI). Using untargeted metabolomics, we repeatedly measured 364 metabolites in plasma samples at baseline and 1-year after intervention. Linear regression was used to examine whether baseline metabolites or changes in metabolites are associated with differential glycemic outcomes in response to different types of weight-loss intervention, adjusting for sex, baseline age, and BMI as well as weight loss. Network analyses were performed to identify differential metabolic pathways involved in the observed associations. After correction for multiple testing (q < 0.05), 33 (RYGB vs. IMI) and 28 (RYGB vs. BAND) baseline metabolites were associated with changes in fasting plasma glucose (FPG) or glycated hemoglobin (HbA1c). Longitudinal changes in 38 (RYGB vs. IMI) and 38 metabolites (RYGB vs. BAND) were significantly associated with changes in FPG or HbA1c. The identified metabolites are enriched in pathways involved in the biosynthesis of aminoacyl-tRNA and branched-chain amino acids. Weight-loss intervention evokes extensive changes in plasma metabolites, and the altered metabolome may underlie the differential glycemic outcomes in response to different types of weight-loss intervention, independent of weight loss itself.

Nearly one in three unconscious cardiac arrest survivors experience post-anoxic status epilepticus (PASE). Historically, PASE has been deemed untreatable resulting in its exclusion from status epilepticus clinical trials. However, emerging reports of survivors achieving functional independence following early and aggressive treatment of PASE challenged this widespread therapeutic nihilism. In the absence of proven therapies specific to PASE, standard of care treatment leans on general management strategies for status epilepticus. Vigabatrin-an approved therapy for refractory focal-onset seizures in adults-inhibits the enzyme responsible for GABA catabolism, increases brain GABA levels and may act synergistically with anesthetic agents to abort seizures. Our central hypothesis is that early inhibition of GABA breakdown is possible in the post-cardiac arrest period and may be an effective adjunctive treatment in PASE. This is a phase IIa, single-center, open-label, pilot clinical trial with blinded outcome assessment, of a single dose of vigabatrin in 12 consecutive PASE subjects. Subjects will receive a single loading dose of 4500 mg of vigabatrin (or dose adjusted in moderate and severe renal impairment) via enteric tube within 48 h of PASE onset. Vigabatrin levels will be monitored at 0- (baseline), 0.5-, 1-, 2-, 3-, 6-, 12-, 24-, 48-, 72- and 168-h (7 days) post-vigabatrin. Serum biomarkers of neuronal injury will be measured at 0-, 24-, 48-, 72- and 96-h post-vigabatrin. The primary feasibility endpoint is the proportion of enrolled subjects among identified eligible subjects receiving vigabatrin within 48 h of PASE onset. The primary pharmacokinetic endpoint is the measured vigabatrin level at 3 h post-administration. Descriptive statistics with rates and proportions will be obtained regarding feasibility outcomes, along with the noncompartmental method for pharmacokinetic analyses. The area under the vigabatrin concentration-time curve in plasma from zero to the time of the last quantifiable concentration (AUC ) will be calculated to estimate dose-linear pharmacokinetics. Vigabatrin demonstrates high potential for synergism with current standard of care therapies. Demonstration of the feasibility of vigabatrin administration and preliminary safety in PASE will pave the way for future efficacy and safety trials of this pharmacotherapeutic. Trial Registration NCT04772547.

BACKGROUNDLeft ventricular hypertrophy (LVH) and dyslipidemia are strong, independent predictors for cardiovascular disease, but their relationship is less well studied. A longitudinal lipidomic profiling of left ventricular mass (LVM) and LVH is still lacking.METHODSUsing liquid chromatography-mass spectrometry (LC-MS), we repeatedly measured 1,542 lipids from 1,755 unique American Indians attending 2 exams (mean, 5 years apart). Cross-sectional associations of individual lipid species with LVM index (LVMI) were examined by generalized estimating equation (GEE), followed by replication in an independent biracial cohort (65% White, 35% Black). Baseline plasma lipids associated with LVH risk beyond traditional risk factors were identified by logistic GEE model in American Indians. Longitudinal associations between changes in lipids and changes in LVMI were examined by GEE, adjusting for baseline lipids, baseline LVMI, and covariates.RESULTSMultiple lipid species were significantly associated with LVMI or the risk of LVH in American Indians. Some lipids were confirmed in Black and White individuals. Moreover, some LVH-related lipids were inversely associated with risk of coronary heart disease (CHD). Longitudinal changes in several lipid species were significantly associated with changes in LVMI.CONCLUSIONAltered fasting plasma lipidome and its longitudinal change over time were significantly associated with LVMI and risk for LVH in American Indians. Our results offer insight into the role of individual lipid species in LV remodeling and risk of LVH, independent of known risk factors.FUNDINGThis study was supported by the NIH grant (R01DK107532). The Strong Heart Study has been funded in whole or in part with federal funds from the National Heart, Lung, and Blood Institute, NIH, Department of Health and Human Services, under contract nos. 75N92019D00027, 75N92019D00028, 75N92019D00029, and 75N92019D00030.

Peripheral artery disease (PAD) and dyslipidemia are both independent predictors of cardiovascular disease, but the association between individual lipid species and subclinical PAD, assessed by ankle-brachial index (ABI), is lacking in large-scale longitudinal studies. We used liquid chromatography-mass spectrometry to repeatedly measure 1,542 lipid species from 1,886 American Indian adults attending 2 clinical examinations (mean ~5 years apart) in the Strong Heart Family Study. We used generalized estimating equation models to identify baseline lipid species associated with change in ABI and the Cox frailty regression to examine whether lipids associated with change in ABI were also associated with incident coronary heart disease (CHD). We also examined the longitudinal association between change in lipid species and change in ABI and the cross-sectional association of individual lipids with ABI. All models were adjusted for age, sex, body mass index, smoking, alcohol use, hypertension, estimated glomerular filtration rate, diabetes, and lipid-lowering medication. Baseline levels of 120 lipid species, including glycerophospholipids, glycerolipids, fatty acids, and sphingomyelins, were associated with change in ABI. Among these, higher baseline levels of 3 known lipids (phosphatidylinositol[16:0/20:4], triacylglycerol[48:2], triacylglycerol[55:1]) were associated with a lower risk of CHD (hazard ratios [95% CIs] ranged from 0.67 [0.46-0.99] to 0.76 [0.58-0.99]), while cholesterol was associated with a higher risk of CHD (hazard ratio [95% CI] = 1.37 [1.00-1.87]). Longitudinal changes in 32 lipids were significantly associated with change in ABI during 5-year follow-up. Plasma levels of glycerophospholipids, triacylglycerols, and glycosylceramides were significantly associated with ABI in the cross-sectional analysis. Altered plasma lipidome is significantly associated with subclinical PAD in American Indians beyond traditional risk factors. If validated, the identified lipid species may serve as novel biomarkers for PAD in this high-risk but understudied population.

Data privacy protection has become more and more important as the growth of the Internet and the increasing demand of data sharing. How to collect individual data privately and how to conduct data analysis without information disclosure are essential and many privacy preserving methods have been studied.This dissertation investigated privacy preserving data collection and analysis methods. First, we provided theoretical privacy analysis of the triple matrix-masking (TM2) data collection protocol designed for privacy preserving linear models. Parties cannot derive sensitive information using intermediate data and no individual level information is released from published data. Moreover, the published data keeps the exact values for sufficient statistics of linear regression model. Second, we developed privacy preserving protocols for linear regression and classification models. The proposed protocols can perform effective statistical analysis for horizontal and vertical partitioning scenarios and are simple to implement. Resilience of possible attacks were investigated. Experimental results were provided to show its efficiency in communication and computation cost compared with other privacy preserving linear models. Third, we investigated privacy preserving face recognition. Protocols were developed based on different state-of-the-art classification algorithms. Matrix masking techniques and dimension-reduced projection were used to transform face image data. Resilience to disclosure attacks and computation efficiency were analyzed for this protocol.