Longitudinal changes in DNA methylation during the onset of islet autoimmunity differentiate between reversion versus progression of islet autoimmunity.

Background: Type 1 diabetes (T1D) is preceded by a heterogenous pre-clinical phase, islet autoimmunity (IA). We aimed to identify pre vs. post-IA seroconversion (SV) changes in DNAm that differed across three IA progression phenotypes, those who lose autoantibodies (reverters), progress to clinical T1D (progressors), or maintain autoantibody levels (maintainers). Methods: This epigenome-wide association study (EWAS) included longitudinal DNAm measurements in blood (Illumina 450K and EPIC) from participants in Diabetes Autoimmunity Study in the Young (DAISY) who developed IA, one or more islet autoantibodies on at least two consecutive visits. We compared reverters - individuals who sero-reverted, negative for all autoantibodies on at least two consecutive visits and did not develop T1D (n=41); maintainers - continued to test positive for autoantibodies but did not develop T1D (n=60); progressors - developed clinical T1D (n=42). DNAm data were measured before (pre-SV visit) and after IA (post-SV visit). Linear mixed models were used to test for differences in pre- vs post-SV changes in DNAm across the three groups. Linear mixed models were also used to test for group differences in average DNAm. Cell proportions, age, and sex were adjusted for in all models. Median follow-up across all participants was 15.5 yrs. (interquartile range (IQR): 10.8-18.7). Results: The median age at the pre-SV visit was 2.2 yrs. (IQR: 0.8-5.3) in progressors, compared to 6.0 yrs. (IQR: 1.3-8.4) in reverters, and 5.7 yrs. (IQR: 1.4-9.7) in maintainers. Median time between the visits was similar in reverters 1.4 yrs. (IQR: 1-1.9), maintainers 1.3 yrs. (IQR: 1.0-2.0), and progressors 1.8 yrs. (IQR: 1.0-2.0). Changes in DNAm, pre- vs post-SV, differed across the groups at one site (cg16066195) and 11 regions. Average DNAm (mean of pre- and post-SV) differed across 22 regions. Conclusion: Differentially changing DNAm regions were located in genomic areas related to beta cell function, immune cell differentiation, and immune cell function.

Investigating iron intake in risk of progression from islet autoimmunity to type 1 diabetes: The diabetes autoimmunity study in the young.

Background: Studies of the role of iron in the risk of type 1 diabetes (T1D) have been inconsistent. Given that iron generates reactive oxygen radicals, which can lead to oxidative damage and apoptosis in the beta cells of the pancreas, we examined whether iron intake was associated with the risk of progressing to T1D in individuals with islet autoimmunity (IA), the pre-clinical phase of T1D. Methods: DAISY is a prospective cohort following 2,547 children at increased risk for IA and progression to T1D. IA is defined as at least two consecutive serum samples positive for at least one autoantibody (insulin, GAD, IA-2, or ZnT8). We measured dietary intake at the time of IA seroconversion in 175 children with IA, and of these, 64 progressed to T1D. We used Cox regression to examine the association between energy-adjusted iron intake and progression to T1D, adjusting for HLA-DR3/4 genotype, race/ethnicity, age at seroconversion, presence of multiple autoantibodies at seroconversion, and multiple vitamin use. In addition, we tested whether this association was modified by vitamin C or calcium intake. Results: In children with IA, high iron intake (as defined as above the 75th percentile, > 20.3 mg/day) was associated with decreased risk of progression to T1D compared to moderate iron intake (as defined by the middle 25-75th percentiles, 12.7-20.3 mg/day) (adjusted hazard ratio (HR): 0.35; 95% confidence interval (CI): 0.15, 0.79). The association between iron intake and T1D was not modified by vitamin C nor calcium intake. In a sensitivity analysis, the removal of six children who had been diagnosed with celiac disease prior to IA seroconversion did not affect this association. Conclusion: Higher iron intake at the time of IA seroconversion is associated with a lower risk of progression to T1D, independent of multivitamin supplement use. Further research that includes plasma biomarkers of iron status is needed to investigate the relationship between iron and the risk of T1D.

Genome-wide analysis of oxylipins and oxylipin profiles in a pediatric population.

Background: Oxylipins are inflammatory biomarkers derived from omega-3 and-6 fatty acids implicated in inflammatory diseases but have not been studied in a genome-wide association study (GWAS). The aim of this study was to identify genetic loci associated with oxylipins and oxylipin profiles to identify biologic pathways and therapeutic targets for oxylipins. Methods: We conducted a GWAS of plasma oxylipins in 316 participants in the Diabetes Autoimmunity Study in the Young (DAISY). DNA samples were genotyped using the TEDDY-T1D Exome array, and additional variants were imputed using the Trans-Omics for Precision Medicine (TOPMed) multi-ancestry reference panel. Principal components analysis of 36 plasma oxylipins was used to capture oxylipin profiles. PC1 represented linoleic acid (LA)- and alpha-linolenic acid (ALA)-related oxylipins, and PC2 represented arachidonic acid (ARA)-related oxylipins. Oxylipin PC1, PC2, and the top five loading oxylipins from each PC were used as outcomes in the GWAS (genome-wide significance: p < 5×10-8). Results: The SNP rs143070873 was associated with (p < 5×10-8) the LA-related oxylipin 9-HODE, and rs6444933 (downstream of CLDN11) was associated with the LA-related oxylipin 13 S-HODE. A locus between MIR1302-7 and LOC100131146, rs10118380 and an intronic variant in TRPM3 were associated with the ARA-related oxylipin 11-HETE. These loci are involved in inflammatory signaling cascades and interact with PLA2, an initial step to oxylipin biosynthesis. Conclusion: Genetic loci involved in inflammation and oxylipin metabolism are associated with oxylipin levels.

Propensity scores as a novel method to guide sample allocation and minimize batch effects during the design of high throughput experiments.

BACKGROUND: We developed a novel approach to minimize batch effects when assigning samples to batches. Our algorithm selects a batch allocation, among all possible ways of assigning samples to batches, that minimizes differences in average propensity score between batches. This strategy was compared to randomization and stratified randomization in a case-control study (30 per group) with a covariate (case vs control, represented as ß1, set to be null) and two biologically relevant confounding variables (age, represented as ß2, and hemoglobin A1c (HbA1c), represented as ß3). Gene expression values were obtained from a publicly available dataset of expression data obtained from pancreas islet cells. Batch effects were simulated as twice the median biological variation across the gene expression dataset and were added to the publicly available dataset to simulate a batch effect condition. Bias was calculated as the absolute difference between observed betas under the batch allocation strategies and the true beta (no batch effects). Bias was also evaluated after adjustment for batch effects using ComBat as well as a linear regression model. In order to understand performance of our optimal allocation strategy under the alternative hypothesis, we also evaluated bias at a single gene associated with both age and HbA1c levels in the 'true' dataset (CAPN13 gene). RESULTS: Pre-batch correction, under the null hypothesis (ß1), maximum absolute bias and root mean square (RMS) of maximum absolute bias, were minimized using the optimal allocation strategy. Under the alternative hypothesis (ß2 and ß3 for the CAPN13 gene), maximum absolute bias and RMS of maximum absolute bias were also consistently lower using the optimal allocation strategy. ComBat and the regression batch adjustment methods performed well as the bias estimates moved towards the true values in all conditions under both the null and alternative hypotheses. Although the differences between methods were less pronounced following batch correction, estimates of bias (average and RMS) were consistently lower using the optimal allocation strategy under both the null and alternative hypotheses. CONCLUSIONS: Our algorithm provides an extremely flexible and effective method for assigning samples to batches by exploiting knowledge of covariates prior to sample allocation.

An Oxylipin-Related Nutrient Pattern and Risk of Type 1 Diabetes in the Diabetes Autoimmunity Study in the Young (DAISY).

Oxylipins, pro-inflammatory and pro-resolving lipid mediators, are associated with the risk of type 1 diabetes (T1D) and may be influenced by diet. This study aimed to develop a nutrient pattern related to oxylipin profiles and test their associations with the risk of T1D among youth. The nutrient patterns were developed with a reduced rank regression in a nested case-control study (n = 335) within the Diabetes Autoimmunity Study in the Young (DAISY), a longitudinal cohort of children at risk of T1D. The oxylipin profiles (adjusted for genetic predictors) were the response variables. The nutrient patterns were tested in the case-control study (n = 69 T1D cases, 69 controls), then validated in the DAISY cohort using a joint Cox proportional hazards model (n = 1933, including 81 T1D cases). The first nutrient pattern (NP1) was characterized by low beta cryptoxanthin, flavanone, vitamin C, total sugars and iron, and high lycopene, anthocyanidins, linoleic acid and sodium. After adjusting for T1D family history, the HLA genotype, sex and race/ethnicity, NP1 was associated with a lower risk of T1D in the nested case-control study (OR: 0.44, p = 0.0126). NP1 was not associated with the risk of T1D (HR: 0.54, p-value = 0.1829) in the full DAISY cohort. Future studies are needed to confirm the nested case-control findings and investigate the modifiable factors for oxylipins.

Changes in the Coexpression of Innate Immunity Genes During Persistent Islet Autoimmunity Are Associated With Progression of Islet Autoimmunity: Diabetes Autoimmunity Study in the Young (DAISY).

Longitudinal changes in gene expression during islet autoimmunity (IA) may provide insight into biological processes that explain progression to type 1 diabetes (T1D). We identified individuals from Diabetes Autoimmunity Study in the Young (DAISY) who developed IA, autoantibodies present on two or more visits. Illumina's NovaSeq 6000 was used to quantify gene expression in whole blood. With linear mixed models we tested for changes in expression after IA that differed across individuals who progressed to T1D (progressors) (n = 25), reverted to an autoantibody-negative stage (reverters) (n = 47), or maintained IA positivity but did not develop T1D (maintainers) (n = 66). Weighted gene coexpression network analysis was used to identify coexpression modules. Gene Ontology pathway analysis of the top 150 differentially expressed genes (nominal P < 0.01) identified significantly enriched pathways including leukocyte activation involved in immune response, innate immune response, and regulation of immune response. We identified a module of 14 coexpressed genes with roles in the innate immunity. The hub gene, LTF, is known to have immunomodulatory properties. Another gene within the module, CAMP, is potentially relevant based on its role in promoting ß-cell survival in a murine model. Overall, results provide evidence of alterations in expression of innate immune genes prior to onset of T1D.

Epigenome-Wide Association Study of Infant Feeding and DNA Methylation in Infancy and Childhood in a Population at Increased Risk for Type 1 Diabetes.

We assessed associations between infant diet (e.g., breastfeeding and introduction to solid foods) and DNA methylation in infancy and childhood. We measured DNA methylation in peripheral blood collected in infancy (9-15 months of age) in 243 children; and in a subset of 50 children, we also measured methylation in childhood (6-9 years of age) to examine persistence, and at birth (in cord blood) to examine temporality. We performed multivariable linear regression of infant diet on the outcome of methylation using epigenome-wide and candidate site approaches. We identified six novel CpG sites associated with breastfeeding duration using an EWAS approach. One differentially methylated site presented directionally consistent associations with breastfeeding (cg00574958, CPT1A) in infancy and childhood but not at birth. Two differentially methylated sites in infancy (cg19693031, TXNIP; cg23307264, KHSRP) were associated with breastfeeding and were not present at birth; however, these associations did not persist into childhood. Associations between infant diet and methylation in infancy at three sites (cg22369607, AP001525.1; cg2409200, TBCD; cg27173510, PGBD5) were also present at birth, suggesting the influence of exposures other than infant diet. Infant diet exposures are associated with persistent methylation differences in CPT1A, which may be one mechanism behind infant diet's long-term health effects.

Inverse probability weighting is an effective method to address selection bias during the analysis of high dimensional data.

Omics studies frequently use samples collected during cohort studies. Conditioning on sample availability can cause selection bias if sample availability is nonrandom. Inverse probability weighting (IPW) is purported to reduce this bias. We evaluated IPW in an epigenome-wide analysis testing the association between DNA methylation (261,435 probes) and age in healthy adolescent subjects (n = 114). We simulated age and sex to be correlated with sample selection and then evaluated four conditions: complete population/no selection bias (all subjects), naïve selection bias (no adjustment), and IPW selection bias (selection bias with IPW adjustment). Assuming the complete population condition represented the "truth," we compared each condition to the complete population condition. Bias or difference in associations between age and methylation was reduced in the IPW condition versus the naïve condition. However, genomic inflation and type 1 error were higher in the IPW condition relative to the naïve condition. Postadjustment using bacon, type 1 error and inflation were similar across all conditions. Power was higher under the IPW condition compared with the naïve condition before and after inflation adjustment. IPW methods can reduce bias in genome-wide analyses. Genomic inflation is a potential concern that can be minimized using methods that adjust for inflation.

The oxylipin profile is associated with development of type 1 diabetes: the Diabetes Autoimmunity Study in the Young (DAISY).

AIMS/HYPOTHESIS: Oxylipins are lipid mediators derived from polyunsaturated fatty acids. Some oxylipins are proinflammatory (e.g. those derived from arachidonic acid [ARA]), others are pro-resolving of inflammation (e.g. those derived from α-linolenic acid [ALA], docosahexaenoic acid [DHA] and eicosapentaenoic acid [EPA]) and others may be both (e.g. those derived from linoleic acid [LA]). The goal of this study was to examine whether oxylipins are associated with incident type 1 diabetes. METHODS: We conducted a nested case-control analysis in the Diabetes Autoimmunity Study in the Young (DAISY), a prospective cohort study of children at risk of type 1 diabetes. Plasma levels of 14 ARA-derived oxylipins, ten LA-derived oxylipins, six ALA-derived oxylipins, four DHA-derived oxylipins and two EPA-related oxylipins were measured by ultra-HPLC-MS/MS at multiple timepoints related to autoantibody seroconversion in 72 type 1 diabetes cases and 71 control participants, which were frequency matched on age at autoantibody seroconversion (of the case), ethnicity and sample availability. Linear mixed models were used to obtain an age-adjusted mean of each oxylipin prior to type 1 diabetes. Age-adjusted mean oxylipins were tested for association with type 1 diabetes using logistic regression, adjusting for the high risk HLA genotype HLA-DR3/4,DQB1*0302. We also performed principal component analysis of the oxylipins and tested principal components (PCs) for association with type 1 diabetes. Finally, to investigate potential critical timepoints, we examined the association of oxylipins measured before and after autoantibody seroconversion (of the cases) using PCs of the oxylipins at those visits. RESULTS: The ARA-related oxylipin 5-HETE was associated with increased type 1 diabetes risk. Five LA-related oxylipins, two ALA-related oxylipins and one DHA-related oxylipin were associated with decreased type 1 diabetes risk. A profile of elevated LA- and ALA-related oxylipins (PC1) was associated with decreased type 1 diabetes risk (OR 0.61; 95% CI 0.40, 0.94). A profile of elevated ARA-related oxylipins (PC2) was associated with increased diabetes risk (OR 1.53; 95% CI 1.03, 2.29). A critical timepoint analysis showed type 1 diabetes was associated with a high ARA-related oxylipin profile at post-autoantibody-seroconversion but not pre-seroconversion. CONCLUSIONS/INTERPRETATION: The protective association of higher LA- and ALA-related oxylipins demonstrates the importance of both inflammation promotion and resolution in type 1 diabetes. Proinflammatory ARA-related oxylipins may play an important role once the autoimmune process has begun.

Phospholipid Levels at Seroconversion Are Associated With Resolution of Persistent Islet Autoimmunity: The Diabetes Autoimmunity Study in the Young.

Reversion of islet autoimmunity (IA) may point to mechanisms that prevent IA progression. We followed 199 individuals who developed IA during the Diabetes Autoimmunity Study in the Young. Untargeted metabolomics was performed in serum samples following IA. Cox proportional hazards models were used to test whether the metabolites (2,487) predicted IA reversion: two or more consecutive visits negative for all autoantibodies. We conducted a principal components analysis (PCA) of the top metabolites; |hazard ratio (HR) >1.25| and nominal P < 0.01. Phosphatidylcholine (16:0_18:1(9Z)) was the strongest individual metabolite (HR per 1 SD 2.16, false discovery rate (FDR)-adjusted P = 0.0037). Enrichment analysis identified four clusters (FDR P < 0.10) characterized by an overabundance of sphingomyelin (d40:0), phosphatidylcholine (16:0_18:1(9Z)), phosphatidylcholine (30:0), and l-decanoylcarnitine. Overall, 63 metabolites met the criteria for inclusion in the PCA. PC1 (HR 1.4, P < 0.0001), PC2 (HR 0.85, P = 0.0185), and PC4 (HR 1.28, P = 0.0103) were associated with IA reversion. Given the potential influence of diet on the metabolome, we investigated whether nutrients were correlated with PCs. We identified 20 nutrients that were correlated with the PCs (P < 0.05). Total sugar intake was the top nutrient. Overall, we identified an association between phosphatidylcholine, sphingomyelin, and carnitine levels and reversion of IA.

Association of apolipoprotein C3 with insulin resistance and coronary artery calcium in patients with type 1 diabetes.

BACKGROUND: Apolipoprotein C3 (APOC3) is a risk factor for incident coronary artery disease in people with type 1 diabetes (T1D). The pathways that link elevated APOC3 levels to an increased risk of incident cardiovascular disease in people with T1D are not understood. OBJECTIVE: To explore potential mechanisms, we investigated the association of APOC3 with insulin resistance and coronary artery calcium (CAC). METHODS: In a random subcohort of participants with T1D from Coronary Artery Calcification in Type 1 Diabetes (n = 134), serum APOC3, high-density lipoprotein (HDL)-associated APOC3, and retinol binding protein 4 (RBP4; a potential marker of insulin resistance) were measured by targeted mass spectrometry. We used linear regression to evaluate associations of serum APOC3 and HDL-APOC3 with APOB, non-HDL cholesterol, serum- and HDL-associated RBP4, and estimated insulin sensitivity and logistic regression to evaluate association with presence of CAC, adjusted for age, sex, and diabetes duration. RESULTS: Serum APOC3 correlated positively with APOB and non-HDL cholesterol and was associated with increased odds of CAC (odds ratio: 1.68, P = .024). Estimated insulin sensitivity was not associated with serum- or HDL-RBP4 but was negatively associated with serum APOC3 in men (ß estimate: -0.318, P = .0040) and decreased odds of CAC (odds ratio: 0.434, P = .0023). CONCLUSIONS: Serum APOC3 associates with increased insulin resistance and CAC in T1D.

Predictors of oxylipins in a healthy pediatric population.

BACKGROUND: Oxylipins are formed from oxidation of omega-6 (n6) and omega-3 (n3) fatty acids (FAs). Evidence for inflammatory effects comes mostly from adults. METHODS: Oxylipins from n6 FA (27 n6-oxylipins) and n3 FA (12 n3-oxylipins) were measured through ultra-high-performance liquid chromatography-mass spectrometry (LC-MS/MS) in plasma from 111 children at risk of type 1 diabetes (age 1-17 years) studied longitudinally. Oxylipin precursor FAs (arachidonic acid, linoleic acid, alpha-linolenic acid, docosahexaenoic acid, eicosapentaenoic acid) were measured in red blood cell (RBC) membrane and plasma. Precursor FAs dietary intake was measured through food frequency questionnaire and environmental tobacco smoke (ETS) through questionnaires. Linear mixed models were used to test oxylipins with predictors. RESULTS: Age associated with 15 n6- and 6 n3-oxylipins; race/ethnicity associated with 3 n6- and 1 n3-oxylipins; sex associated with 2 n6-oxylipins. ETS associated with lipoxin-A4. Oxylipins associated with precursor FAs in plasma more often than RBC. RBC levels and dietary intake of precursor FAs more consistently associated with n3-oxylipins than with n6-oxylipins. CONCLUSIONS: In healthy children, oxylipin levels change with age. Oxylipins associated with precursor FAs more often in plasma than RBC or diet, suggesting that inflammatory regulation leading to FA release into plasma may also be a determinant of oxylipin generation. IMPACT: This is the first study to examine predictors of oxylipins in healthy children at risk of type 1 diabetes. In healthy children at risk of type 1 diabetes, many oxylipins change with age, and most oxylipins do not differ by sex or race/ethnicity. Environmental tobacco smoke exposure was associated with the presence of lipoxin A4. Omega-6- and omega-3-related oxylipin levels were consistently associated with their respective precursor fatty acid levels measured in the plasma. Proportionally more omega-3 compared to omega-6 oxylipins were associated with dietary intake and red blood cell membrane levels of the respective precursor fatty acid.

Annatto Tocotrienol Attenuates NLRP3 Inflammasome Activation in Macrophages.

Accumulating evidence suggests that aberrant innate immunity is closely linked to metabolic diseases, including type 2 diabetes. In particular, activation of the NOD-like receptor family pyrin domain-containing 3 (NLRP3) inflammasome and subsequent secretion of interleukin 1ß (IL-1ß) are critical determinants that precipitate disease progression. The seeds of annatto (Bixa orellana L.) contain tocotrienols (T3s), mostly (>90%) in the δ form (δT3). The aim of this study was to determine whether annatto T3 is effective in attenuating NLRP3 inflammasome activation in macrophages. Our results showed that annatto δT3 significantly attenuated NLRP3 inflammasome by decreasing IL-1ß reporter activity, IL-1ß secretion, and caspase-1 cleavage against lipopolysaccharide (LPS) followed by nigericin stimulation. With regard to mechanism, annatto δT3 1) reduced LPS-mediated priming of the inflammasome and 2) dampened reactive oxygen species production, the second signal required for assembly of the NLRP3 inflammasome in macrophages. Our work suggests that annatto δT3 may hold therapeutic potential for delaying the onset of NLRP3 inflammasome-associated chronic metabolic diseases.

Improvements in Metabolic Health with Consumption of Ellagic Acid and Subsequent Conversion into Urolithins: Evidence and Mechanisms.

Ellagic acid (EA) is a naturally occurring polyphenol found in some fruits and nuts, including berries, pomegranates, grapes, and walnuts. EA has been investigated extensively because of its antiproliferative action in some cancers, along with its anti-inflammatory effects. A growing body of evidence suggests that the intake of EA is effective in attenuating obesity and ameliorating obesity-mediated metabolic complications, such as insulin resistance, type 2 diabetes, nonalcoholic fatty liver disease, and atherosclerosis. In this review, we summarize how intake of EA regulates lipid metabolism in vitro and in vivo, and delineate the potential mechanisms of action of EA on obesity-mediated metabolic complications. We also discuss EA as an epigenetic effector, as well as a modulator of the gut microbiome, suggesting that EA may exert a broader spectrum of health benefits than has been demonstrated to date. Therefore, this review aims to suggest the potential metabolic benefits of consumption of EA-containing fruits and nuts against obesity-associated health conditions.