Genetic Associations with C-peptide Levels before Type 1 Diabetes Diagnosis in At-Risk Relatives.

OBJECTIVE: We sought to determine whether the type 1 diabetes genetic risk score-2 (T1D-GRS2) and single nucleotide polymorphisms (SNPs) are associated with C-peptide preservation before type 1 diabetes diagnosis. METHODS: We conducted a retrospective analysis of 713 autoantibody-positive participants who developed type 1 diabetes in the TrialNet Pathway to Prevention Study who had T1DExomeChip data. We evaluated the relationships of 16 known SNPs and T1D-GRS2 with area under the curve (AUC) C-peptide levels during oral glucose tolerance tests conducted in the 9 months before diagnosis. RESULTS: Higher T1D-GRS2 was associated with lower C-peptide AUC in the 9 months before diagnosis in univariate (ß=-0.06, P<0.0001) and multivariate (ß=-0.03, P=0.005) analyses. Participants with the JAZF1 rs864745 T allele had lower C-peptide AUC in both univariate (ß=-0.11, P=0.002) and multivariate (ß=-0.06, P=0.018) analyses. CONCLUSIONS: The type 2 diabetes-associated JAZF1 rs864745 T allele and higher T1D-GRS2 are associated with lower C-peptide AUC prior to diagnosis of type 1 diabetes, with implications for the design of prevention trials.

Islet autoantibodies as precision diagnostic tools to characterize heterogeneity in type 1 diabetes: a systematic review.

BACKGROUND: Islet autoantibodies form the foundation for type 1 diabetes (T1D) diagnosis and staging, but heterogeneity exists in T1D development and presentation. We hypothesized that autoantibodies can identify heterogeneity before, at, and after T1D diagnosis, and in response to disease-modifying therapies. METHODS: We systematically reviewed PubMed and EMBASE databases (6/14/2022) assessing 10 years of original research examining relationships between autoantibodies and heterogeneity before, at, after diagnosis, and in response to disease-modifying therapies in individuals at-risk or within 1 year of T1D diagnosis. A critical appraisal checklist tool for cohort studies was modified and used for risk of bias assessment. RESULTS: Here we show that 152 studies that met extraction criteria most commonly characterized heterogeneity before diagnosis (91/152). Autoantibody type/target was most frequently examined, followed by autoantibody number. Recurring themes included correlations of autoantibody number, type, and titers with progression, differing phenotypes based on order of autoantibody seroconversion, and interactions with age and genetics. Only 44% specifically described autoantibody assay standardization program participation. CONCLUSIONS: Current evidence most strongly supports the application of autoantibody features to more precisely define T1D before diagnosis. Our findings support continued use of pre-clinical staging paradigms based on autoantibody number and suggest that additional autoantibody features, particularly in relation to age and genetic risk, could offer more precise stratification. To improve reproducibility and applicability of autoantibody-based precision medicine in T1D, we propose a methods checklist for islet autoantibody-based manuscripts which includes use of precision medicine MeSH terms and participation in autoantibody standardization workshops.

Islet autoantibodies are markers found in the blood when insulin-producing cells in the pancreas become damaged and can be used to predict future development of type 1 diabetes. We evaluated published literature to determine whether characteristics of islet antibodies (type, levels, numbers) could improve prediction and help understand differences in how individuals with type 1 diabetes respond to treatments. We found existing evidence shows that islet autoantibody type and number are most useful to predict disease progression before diagnosis. In addition, the age when islet autoantibodies first appear strongly influences rate of progression. These findings provide important information for patients and care providers on how islet autoantibodies can be used to understand future type 1 diabetes development and to identify individuals who have the potential to benefit from intervention or prevention therapy.

An Epigenome-Wide Association Study of DNA Methylation and Proliferative Retinopathy over 28 Years in Type 1 Diabetes.

Purpose: To perform a prospective epigenome-wide association study of DNA methylation (DNAm) and 28-year proliferative diabetic retinopathy (PDR) incidence in type 1 diabetes (T1D). Design: Prospective observational cohort study. Participants: The Pittsburgh Epidemiology of Diabetes Complications (EDC) study of childhood-onset (< 17 years) T1D. Methods: Stereoscopic fundus photographs were taken in fields 1, 2, and 4 at baseline, 2, 4, 6, 8, 16, 23, and 28 years after DNAm measurements. The photos were graded using the modified Airlie House System. In those free of PDR at baseline (n = 265; mean T1D duration of 18 years at baseline), whole blood DNAm (EPIC array) at 683 597 CpGs was analyzed in Cox models for time to event. Associations between significant CpGs and clinical risk factors were assessed; genetic variants associated with DNAm were identified (methylation quantitative trait loci [meQTLs]). Mendelian randomization was used to examine evidence of causal associations between DNAm and PDR. Post hoc regional and functional analyses were performed. Main Outcome Measures: Proliferative diabetic retinopathy was defined as the first instance of a grade of ≥ 60 in at least 1 eye or pan-retinal photocoagulation for PDR. Follow-up time was calculated from the study visit at which DNAm data were available (baseline) until PDR incidence or censoring (December 31, 2018 or last follow-up). Results: PDR incidence was 53% over 28-years' follow-up. Greater DNAm of cg27512687 (KIF16B) was associated with reduced PDR incidence (P = 6.3 × 10-9; false discovery rate [FDR]: < 0.01); 113 cis-meQTLs (P < 5 × 10-8) were identified. Mendelian randomization analysis using the sentinel meQTL as the instrumental variable supported a potentially causal association between cg27512687 and PDR. Cg27512687 was also associated with lower pulse rate and albumin excretion rate and higher estimated glomerular filtration rate, but its association with PDR remained independently significant after adjustment for those factors. In regional analyses, DNAm of FUT4, FKBP1A, and RIN2 was also associated with PDR incidence. Conclusions: DNA methylation of KIF16B, FUT4, FKBP1A, and RIN2 was associated with PDR incidence, supporting roles for epigenetic regulation of iron clearance, developmental pathways, and autophagy in PDR pathogenesis. Further study of those loci may provide insight into novel targets for interventions to prevent or delay PDR in T1D. Financial Disclosures: Proprietary or commercial disclosure may be found in the Footnotes and Disclosures at the end of this article.

A multi-ancestry genome-wide association study in type 1 diabetes.

Type 1 diabetes (T1D) is an autoimmune disease caused by destruction of the pancreatic ß-cells. Genome-wide association (GWAS) and fine mapping studies have been conducted mainly in European ancestry (EUR) populations. We performed a multi-ancestry GWAS to identify SNPs and HLA alleles associated with T1D risk and age at onset. EUR families (N = 3223), and unrelated individuals of African (AFR, N = 891) and admixed (Hispanic/Latino) ancestry (AMR, N = 308) were genotyped using the Illumina HumanCoreExome BeadArray, with imputation to the TOPMed reference panel. The Multi-Ethnic HLA reference panel was utilized to impute HLA alleles and amino acid residues. Logistic mixed models (T1D risk) and frailty models (age at onset) were used for analysis. In GWAS meta-analysis, seven loci were associated with T1D risk at genome-wide significance: PTPN22, HLA-DQA1, IL2RA, RNLS, INS, IKZF4-RPS26-ERBB3, and SH2B3, with four associated with T1D age at onset (PTPN22, HLA-DQB1, INS, and ERBB3). AFR and AMR meta-analysis revealed NRP1 as associated with T1D risk and age at onset, although NRP1 variants were not associated in EUR ancestry. In contrast, the PTPN22 variant was significantly associated with risk only in EUR ancestry. HLA alleles and haplotypes most significantly associated with T1D risk in AFR and AMR ancestry differed from that seen in EUR ancestry; in addition, the HLA-DRB1*08:02-DQA1*04:01-DQB1*04:02 haplotype was 'protective' in AMR while HLA-DRB1*08:01-DQA1*04:01-DQB1*04:02 haplotype was 'risk' in EUR ancestry, differing only at HLA-DRB1*08. These results suggest that much larger sample sizes in non-EUR populations are required to capture novel loci associated with T1D risk.

Implementation of type 1 diabetes genetic risk screening in children in diverse communities: the Virginia PrIMeD project.

BACKGROUND: Population screening for risk of type 1 diabetes (T1D) has been proposed to identify those with islet autoimmunity (presence of islet autoantibodies). As islet autoantibodies can be transient, screening with a genetic risk score has been proposed as an entry into autoantibody testing. METHODS: Children were recruited from eight general pediatric and specialty clinics across Virginia with diverse community settings. Recruiters in each clinic obtained informed consent/assent, a medical history, and a saliva sample for DNA extraction in children with and without a history of T1D. A custom genotyping panel was used to define T1D genetic risk based upon associated SNPs in European- and African-genetic ancestry. Subjects at "high genetic risk" were offered a separate blood collection for screening four islet autoantibodies. A follow-up contact (email, mail, and telephone) in one half of the participants determined interest and occurrence of subsequent T1D. RESULTS: A total of 3818 children aged 2-16 years were recruited, with 14.2% (n = 542) having a "high genetic risk." Of children with "high genetic risk" and without pre-existing T1D (n = 494), 7.0% (34/494) consented for autoantibody screening; 82.4% (28/34) who consented also completed the blood collection, and 7.1% (2/28) of them tested positive for multiple autoantibodies. Among children with pre-existing T1D (n = 91), 52% (n = 48) had a "high genetic risk." In the sample of children with existing T1D, there was no relationship between genetic risk and age at T1D onset. A major factor in obtaining islet autoantibody testing was concern over SARS-CoV-2 exposure. CONCLUSIONS: Minimally invasive saliva sampling implemented using a genetic risk score can identify children at genetic risk of T1D. Consent for autoantibody screening, however, was limited largely due to the SARS-CoV-2 pandemic and need for blood collection.

Decrease in multiple complement proteins associated with development of islet autoimmunity and type 1 diabetes.

Type 1 diabetes (T1D) is a chronic condition caused by autoimmune destruction of the insulin-producing pancreatic ß cells. While it is known that gene-environment interactions play a key role in triggering the autoimmune process leading to T1D, the pathogenic mechanism leading to the appearance of islet autoantibodies-biomarkers of autoimmunity-is poorly understood. Here we show that disruption of the complement system precedes the detection of islet autoantibodies and persists through disease onset. Our results suggest that children who exhibit islet autoimmunity and progress to clinical T1D have lower complement protein levels relative to those who do not progress within a similar time frame. Thus, the complement pathway, an understudied mechanistic and therapeutic target in T1D, merits increased attention for use as protein biomarkers of prediction and potentially prevention of T1D.

Multi-ancestry genetic analysis of gene regulation in coronary arteries prioritizes disease risk loci.

Genome-wide association studies (GWASs) have identified hundreds of risk loci for coronary artery disease (CAD). However, non-European populations are underrepresented in GWASs, and the causal gene-regulatory mechanisms of these risk loci during atherosclerosis remain unclear. We incorporated local ancestry and haplotypes to identify quantitative trait loci for expression (eQTLs) and splicing (sQTLs) in coronary arteries from 138 ancestrally diverse Americans. Of 2,132 eQTL-associated genes (eGenes), 47% were previously unreported in coronary artery; 19% exhibited cell-type-specific expression. Colocalization revealed subgroups of eGenes unique to CAD and blood pressure GWAS. Fine-mapping highlighted additional eGenes, including TBX20 and IL5. We also identified sQTLs for 1,690 genes, among which TOR1AIP1 and ULK3 sQTLs demonstrated the importance of evaluating splicing to accurately identify disease-relevant isoform expression. Our work provides a patient-derived coronary artery eQTL resource and exemplifies the need for diverse study populations and multifaceted approaches to characterize gene regulation in disease processes.

Genetic variants in the complement system and their potential link in the aetiology of type 1 diabetes.

Type 1 diabetes is an autoimmune disease in which one's own immune system destroys insulin-secreting beta cells in the pancreas. This process results in life-long dependence on exogenous insulin for survival. Both genetic and environmental factors play a role in disease initiation, progression, and ultimate clinical diagnosis of type 1 diabetes. This review will provide background on the natural history of type 1 diabetes and the role of genetic factors involved in the complement system, as several recent studies have identified changes in levels of these proteins as the disease evolves from pre-clinical through to clinically apparent disease.

Disease-modifying therapies and features linked to treatment response in type 1 diabetes prevention: a systematic review.

BACKGROUND: Type 1 diabetes (T1D) results from immune-mediated destruction of insulin-producing beta cells. Prevention efforts have focused on immune modulation and supporting beta cell health before or around diagnosis; however, heterogeneity in disease progression and therapy response has limited translation to clinical practice, highlighting the need for precision medicine approaches to T1D disease modification. METHODS: To understand the state of knowledge in this area, we performed a systematic review of randomized-controlled trials with ≥50 participants cataloged in PubMed or Embase from the past 25 years testing T1D disease-modifying therapies and/or identifying features linked to treatment response, analyzing bias using a Cochrane-risk-of-bias instrument. RESULTS: We identify and summarize 75 manuscripts, 15 describing 11 prevention trials for individuals with increased risk for T1D, and 60 describing treatments aimed at preventing beta cell loss at disease onset. Seventeen interventions, mostly immunotherapies, show benefit compared to placebo (only two prior to T1D onset). Fifty-seven studies employ precision analyses to assess features linked to treatment response. Age, beta cell function measures, and immune phenotypes are most frequently tested. However, analyses are typically not prespecified, with inconsistent methods of reporting, and tend to report positive findings. CONCLUSIONS: While the quality of prevention and intervention trials is overall high, the low quality of precision analyses makes it difficult to draw meaningful conclusions that inform clinical practice. To facilitate precision medicine approaches to T1D prevention, considerations for future precision studies include the incorporation of uniform outcome measures, reproducible biomarkers, and prespecified, fully powered precision analyses into future trial design.

Type 1 diabetes (T1D) is a condition that results from the destruction of a type of cell in the pancreas that produces the hormone insulin, leading to lifelong dependence on insulin injections. T1D prevention remains a challenging goal, largely due to the immense variability in disease processes and progression. Therapies tested to date in medical research settings (clinical trials) work only in a subset of individuals, highlighting the need for more tailored prevention approaches. We reviewed clinical trials of therapies targeting the disease process in T1D. While the overall quality of trials was high, studies testing individual features affecting responses to treatments were low. This review reveals an important need to carefully plan high-quality analyses of features that affect treatment response in T1D, to ensure that tailored approaches may one day be applied to clinical practice.

Shifts in isoform usage underlie transcriptional differences in regulatory T cells in type 1 diabetes.

Genome-wide association studies have identified numerous loci with allelic associations to Type 1 Diabetes (T1D) risk. Most disease-associated variants are enriched in regulatory sequences active in lymphoid cell types, suggesting that lymphocyte gene expression is altered in T1D. Here we assay gene expression between T1D cases and healthy controls in two autoimmunity-relevant lymphocyte cell types, memory CD4+/CD25+ regulatory T cells (Treg) and memory CD4+/CD25- T cells, using a splicing event-based approach to characterize tissue-specific transcriptomes. Limited differences in isoform usage between T1D cases and controls are observed in memory CD4+/CD25- T-cells. In Tregs, 402 genes demonstrate differences in isoform usage between cases and controls, particularly RNA recognition and splicing factor genes. Many of these genes are regulated by the variable inclusion of exons that can trigger nonsense mediated decay. Our results suggest that dysregulation of gene expression, through shifts in alternative splicing in Tregs, contributes to T1D pathophysiology.

Precision Medicine in Type 1 Diabetes.

Type 1 diabetes is a complex, chronic disease in which the insulin-producing beta cells in the pancreas are sufficiently altered or impaired to result in requirement of exogenous insulin for survival. The development of type 1 diabetes is thought to be an autoimmune process, in which an environmental (unknown) trigger initiates a T cell-mediated immune response in genetically susceptible individuals. The presence of islet autoantibodies in the blood are signs of type 1 diabetes development, and risk of progressing to clinical type 1 diabetes is correlated with the presence of multiple islet autoantibodies. Currently, a "staging" model of type 1 diabetes proposes discrete components consisting of normal blood glucose but at least two islet autoantibodies (Stage 1), abnormal blood glucose with at least two islet autoantibodies (Stage 2), and clinical diagnosis (Stage 3). While these stages may, in fact, not be discrete and vary by individual, the format suggests important applications of precision medicine to diagnosis, prevention, prognosis, treatment and monitoring. In this paper, applications of precision medicine in type 1 diabetes are discussed, with both opportunities and barriers to global implementation highlighted. Several groups have implemented components of precision medicine, yet the integration of the necessary steps to achieve both short- and long-term solutions will need to involve researchers, patients, families, and healthcare providers to fully impact and reduce the burden of type 1 diabetes.

DNA methylation and 28-year cardiovascular disease risk in type 1 diabetes: the Epidemiology of Diabetes Complications (EDC) cohort study.

BACKGROUND: The potential for DNA methylation (DNAm) as an early marker for cardiovascular disease (CVD) and how such an association might differ by glycemic exposure has not been examined in type 1 diabetes, a population at increased CVD risk. We thus performed a prospective epigenome-wide association study of blood leukocyte DNAm (EPIC array) and time to CVD incidence over 28 years in a childhood-onset (< 17 years) type 1 diabetes cohort, the Pittsburgh Epidemiology of Diabetes Complications (EDC) study (n = 368 with DNA and no CVD at baseline), both overall and separately by glycemic exposure, as measured by HbA1c at baseline (split at the median: < 8.9% and ≥ 8.9%). We also assessed whether DNAm-CVD associations were independent of established cardiometabolic risk factors, including body mass index, estimated glucose disposal rate, cholesterol, triglycerides, blood pressure, pulse rate, albumin excretion rate, and estimated glomerular filtration rate. RESULTS: CVD (first instance of CVD death, myocardial infarction, coronary revascularization, ischemic ECG, angina, or stroke) developed in 172 participants (46.7%) over 28 years. Overall, in Cox regression models for time to CVD, none of the 683,597 CpGs examined reached significance at a false discovery rate (FDR) ≤ 0.05. In participants with HbA1c < 8.9% (n = 180), again none reached FDR ≤ 0.05, but three were associated at the a priori nominal significance level FDR ≤ 0.10: cg07147033 in MIB2, cg12324048 (intergenic, chromosome 3), and cg15883830 (intergenic, chromosome 1). In participants with HbA1c ≥ 8.9% (n = 188), two CpGs in loci involved in calcium channel activity were significantly associated with CVD (FDR ≤ 0.05): cg21823999 in GPM6A and cg23621817 in CHRNA9; four additional CpGs were nominally associated (FDR ≤ 0.10). In participants with HbA1c ≥ 8.9%, DNAm-CVD associations were only modestly attenuated after cardiometabolic risk factor adjustment, while attenuation was greater in those with HbA1c < 8.9%. No pathways were enriched in those with HbA1c < 8.9%, while pathways for calcium channel activity and integral component of synaptic membrane were significantly enriched in those with HbA1c ≥ 8.9%. CONCLUSIONS: These results provide novel evidence that DNAm at loci involved in calcium channel activity and development may contribute to long-term CVD risk beyond known risk factors in type 1 diabetes, particularly in individuals with greater glycemic exposure, warranting further study.

Leveraging type 1 diabetes human genetic and genomic data in the T1D knowledge portal.

To address the challenge of translating genetic discoveries for type 1 diabetes (T1D) into mechanistic insight, we have developed the T1D Knowledge Portal (T1DKP), an open-access resource for hypothesis development and target discovery in T1D.

Single-Cell Transcriptomics of Bone Marrow Stromal Cells in Diversity Outbred Mice: A Model for Population-Level scRNA-Seq Studies.

Genome-wide association studies (GWASs) have advanced our understanding of the genetics of osteoporosis; however, the challenge has been converting associations to causal genes. Studies have utilized transcriptomics data to link disease-associated variants to genes, but few population transcriptomics data sets have been generated on bone at the single-cell level. To address this challenge, we profiled the transcriptomes of bone marrow-derived stromal cells (BMSCs) cultured under osteogenic conditions from five diversity outbred (DO) mice using single-cell RNA-seq (scRNA-seq). The goal of the study was to determine if BMSCs could serve as a model to generate cell type-specific transcriptomic profiles of mesenchymal lineage cells from large populations of mice to inform genetic studies. By enriching for mesenchymal lineage cells in vitro, coupled with pooling of multiple samples and downstream genotype deconvolution, we demonstrate the scalability of this model for population-level studies. We demonstrate that dissociation of BMSCs from a heavily mineralized matrix had little effect on viability or their transcriptomic signatures. Furthermore, we show that BMSCs cultured under osteogenic conditions are diverse and consist of cells with characteristics of mesenchymal progenitors, marrow adipogenic lineage precursors (MALPs), osteoblasts, osteocyte-like cells, and immune cells. Importantly, all cells were similar from a transcriptomic perspective to cells isolated in vivo. We employed scRNA-seq analytical tools to confirm the biological identity of profiled cell types. SCENIC was used to reconstruct gene regulatory networks (GRNs), and we observed that cell types show GRNs expected of osteogenic and pre-adipogenic lineage cells. Further, CELLECT analysis showed that osteoblasts, osteocyte-like cells, and MALPs captured a significant component of bone mineral density (BMD) heritability. Together, these data suggest that BMSCs cultured under osteogenic conditions coupled with scRNA-seq can be used as a scalable and biologically informative model to generate cell type-specific transcriptomic profiles of mesenchymal lineage cells in large populations. © 2023 The Authors. Journal of Bone and Mineral Research published by Wiley Periodicals LLC on behalf of American Society for Bone and Mineral Research (ASBMR).

Decrease in multiple complement protein levels is associated with the development of islet autoimmunity and type 1 diabetes.

Type 1 diabetes (T1D) is a chronic condition caused by autoimmune destruction of the insulin-producing pancreatic ß-cells. While it is known that gene-environment interactions play a key role in triggering the autoimmune process leading to T1D, the pathogenic mechanism leading to the appearance of islet autoantibodies - biomarkers of autoimmunity - is poorly understood. Here we show that disruption of the complement system precedes the detection of islet autoantibodies and persists through disease onset. Our results suggest that children who exhibit islet autoimmunity and progress to clinical T1D have lower complement protein levels relative to those who do not progress within a similar timeframe. Thus, the complement pathway, an understudied mechanistic and therapeutic target in T1D, merits increased attention for use as protein biomarkers of prediction and potentially prevention of T1D.

Type 1 Diabetes Prevention: a systematic review of studies testing disease-modifying therapies and features linked to treatment response.

Background: Type 1 diabetes (T1D) results from immune-mediated destruction of insulin-producing beta cells. Efforts to prevent T1D have focused on modulating immune responses and supporting beta cell health; however, heterogeneity in disease progression and responses to therapies have made these efforts difficult to translate to clinical practice, highlighting the need for precision medicine approaches to T1D prevention. Methods: To understand the current state of knowledge regarding precision approaches to T1D prevention, we performed a systematic review of randomized-controlled trials from the past 25 years testing disease-modifying therapies in T1D and/or identifying features linked to treatment response, analyzing bias using a Cochrane-risk-of-bias instrument. Results: We identified 75 manuscripts, 15 describing 11 prevention trials for individuals with increased risk for T1D, and 60 describing treatments aimed at preventing beta cell loss in individuals at disease onset. Seventeen agents tested, mostly immunotherapies, showed benefit compared to placebo (only two prior to T1D onset). Fifty-seven studies employed precision analyses to assess features linked to treatment response. Age, measures of beta cell function and immune phenotypes were most frequently tested. However, analyses were typically not prespecified, with inconsistent methods reporting, and tended to report positive findings. Conclusions: While the quality of prevention and intervention trials was overall high, low quality of precision analyses made it difficult to draw meaningful conclusions that inform clinical practice. Thus, prespecified precision analyses should be incorporated into the design of future studies and reported in full to facilitate precision medicine approaches to T1D prevention. Plain Language Summary: Type 1 diabetes (T1D) results from the destruction of insulin-producing cells in the pancreas, necessitating lifelong insulin dependence. T1D prevention remains an elusive goal, largely due to immense variability in disease progression. Agents tested to date in clinical trials work in a subset of individuals, highlighting the need for precision medicine approaches to prevention. We systematically reviewed clinical trials of disease-modifying therapy in T1D. While age, measures of beta cell function, and immune phenotypes were most commonly identified as factors that influenced treatment response, the overall quality of these studies was low. This review reveals an important need to proactively design clinical trials with well-defined analyses to ensure that results can be interpreted and applied to clinical practice.

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.

Leveraging type 1 diabetes human genetic and genomic data in the T1D Knowledge Portal.

Translating genetic discoveries for type 1 diabetes (T1D) into mechanistic insight can reveal novel biology and therapeutic targets but remains a major challenge. We developed the T1D Knowledge Portal (T1DKP), a disease-specific resource of genetic and functional annotation data that enables users to develop hypotheses for T1D-based research and target discovery. The T1DKP can be used to query genes and genomic regions for genetic associations, identify epigenomic features, access results of bioinformatic analyses, and obtain expert-curated resources. The T1DKP is available at http://t1d.hugeamp.org .

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.

Integrative multi-ancestry genetic analysis of gene regulation in coronary arteries prioritizes disease risk loci.

Genome-wide association studies (GWAS) have identified hundreds of genetic risk loci for coronary artery disease (CAD). However, non-European populations are underrepresented in GWAS and the causal gene-regulatory mechanisms of these risk loci during atherosclerosis remain unclear. We incorporated local ancestry and haplotype information to identify quantitative trait loci (QTL) for gene expression and splicing in coronary arteries obtained from 138 ancestrally diverse Americans. Of 2,132 eQTL-associated genes (eGenes), 47% were previously unreported in coronary arteries and 19% exhibited cell-type-specific expression. Colocalization analysis with GWAS identified subgroups of eGenes unique to CAD and blood pressure. Fine-mapping highlighted additional eGenes of interest, including TBX20 and IL5 . Splicing (s)QTLs for 1,690 genes were also identified, among which TOR1AIP1 and ULK3 sQTLs demonstrated the importance of evaluating splicing events to accurately identify disease-relevant gene expression. Our work provides the first human coronary artery eQTL resource from a patient sample and exemplifies the necessity of diverse study populations and multi-omic approaches to characterize gene regulation in critical disease processes.