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BackgroundHeterogeneity exists in type 1 diabetes (T1D) development and presentation. Islet autoantibodies form the foundation for T1D diagnostic and staging efforts. We hypothesized that autoantibodies can be used to identify heterogeneity in T1D before, at, and after diagnosis, and in response to disease modifying therapies. at clinically relevant timepoints throughout T1D progression.MethodsWe performed a systematic review assessing 10 years of original research studies examining relationships between autoantibodies and heterogeneity during disease progression, at the time of diagnosis, after diagnosis, and in response to disease modifying therapies in individuals at risk for T1D or within 1 year of T1D diagnosis.Results10,067 papers were screened. Out of 151 that met data extraction criteria, 90 studies characterized heterogeneity before clinical diagnosis. Autoantibody type/target was most commonly examined, followed by autoantibody number, titer, order of seroconversion, affinity, and novel islet autoantibodies/epitopes. Recurring themes included positive relationships of autoantibody number and specific types and titers with disease progression, differing clinical phenotypes based on the order of autoantibody seroconversion, and interactions with age and genetics. Overall, reporting of autoantibody assay performance was commonly included; however, only 43% (65/151) included information about autoantibody assay standardization efforts. Populations studied were almost exclusively of European ancestry.ConclusionsCurrent evidence most strongly supports the application of autoantibody features to more precisely define T1D before clinical diagnosis. Our findings support continued use of pre-clinical staging paradigms based on autoantibody number and suggest that additional autoantibody features, particularly when considered in relation to age and genetic risk, could offer more precise stratification. Increased participation in autoantibody standardization efforts is a critical step to improving future applicability of autoantibody-based precision medicine in T1D.Plain Language SummaryWe performed a systematic review to ascertain whether islet autoantibodies, biomarkers of autoimmunity against insulin-producing cells, could aid in stratifying individuals with different clinical presentations of type 1 diabetes. We found existing evidence most strongly supporting the application of these biomarkers to the period before clinical diagnosis, when certain autoantibody features (number, type) and the age when they develop, can provide important information for patients and care providers on what to expect for future type 1 diabetes progression.

BackgroundType 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.MethodsTo 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.ResultsWe 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.ConclusionsWhile 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 SummaryType 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.

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.

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, includingTBX20andIL5. Splicing (s)QTLs for 1,690 genes were also identified, among whichTOR1AIP1andULK3sQTLs 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.Study Design Overview

Identifying genetic determinants for longitudinal changes in albumin excretion in individuals with type 1 diabetes may help identify those that are predisposed to renal, retinal and cardiovascular complications. Most studies have focussed on genetic predisposition to diabetic kidney disease and used cross-sectional measurements of urinary albumin excretion, but with limited success. Here, we utilise the wealth of longitudinal data and bio-samples collected from cohorts of childhood-onset type 1 diabetes followed over the last 30 years to describe a novel trajectory phenotype quantifying urinary albumin excretion changes during childhood and adolescence. We conducted a genome-wide association study and fine-mapping analysis for albumin excretion in 1584 individuals, finding one signal for cross-sectional albumin excretion close toGALNTL6(rs150766792), which validated in a previous independent study, and a novel genome-wide significant signal for albumin excretion trajectory in theCDH18gene region (rs145715205). Our trajectory phenotype quantifies albumin progression and offers a complementary measure to an albumin excretion phenotype based on a single measurement (i.e. most recent data collection) or an average of repeated measurements in longitudinal studies. It can be used to identify genetic or other risk factors which predict better or worse prognosis, thus facilitating the development of new preventive and therapeutic approaches.

Genome-wide association studies (GWASs) have revolutionized our understanding of the genetics of complex diseases, such as osteoporosis; however, the challenge has been converting associations to causal genes. Studies have demonstrated the utility of transcriptomics data in linking disease-associated variants to genes; though for osteoporosis, few population transcriptomics datasets have been generated on bone or bone cells, and an even smaller number have profiled individual cell-types. To begin to evaluate approaches to address this challenge, we profiled the transcriptomes of bone marrow-derived stromal cells (BMSCs) cultured under osteogenic conditions, a popular model of osteoblast differentiation and activity, 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 for the generation of cell-type specific transcriptomic profiles of mesenchymal lineage cells derived from large populations of mice to inform genetic 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 nearly identical from a transcriptomic perspective to cells isolated directly from bone. We also demonstrated the ability to multiplex single cells and subsequently assign cells to their “mouse-of-origin” using demultiplexing approaches based on genotypes inferred from coding SNPs. 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 showed that identified 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 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 mouse, and potentially human, populations.

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. We assayed gene expression between T1D cases and healthy controls in two autoimmunity-relevant lymphocyte cell types, memory CD4+/CD25+ T-regulatory 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 were observed in memory CD4+/CD25- T-cells. In Tregs, 553 genes demonstrated 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 etiology.

Type 1 diabetes (T1D) is a complex disease and more than 100 genetic loci influencing T1D risk have been identified to date. Discovering the genes and biological mechanisms through which these variants impact T1D requires the integration of multiple data types. We have created the T1D Knowledge Portal (T1DKP; type1diabetesgenetics.org) to help researchers utilize genetic and functional genomic data to generate hypotheses about the genes involved in T1D and its complications. The T1DKP aggregates genetic association data from the T1D community along with relevant functional genomics (e.g., accessible chromatin, 3D conformation, gene expression, gene perturbation) data, which are loaded via a sister resource, the Common Metabolic Diseases Genome Atlas (cmdga.org) . Using the HuGeAMP software platform developed for the Common Metabolic Diseases Knowledge Portal (CMDKP; cmdkp.org) within the Accelerating Medicines Partnership for Common Metabolic Diseases, the T1DKP integrates data by applying bioinformatic methods such as meta-analysis of genetic association results to generate “bottom-line” p-values, enrichment of genetic association within tissue-specific genomic annotations, and more. Interactive visualizations allow the user to explore results and to perform custom, on-the-fly analyses. The T1DKP also includes expert-curated lists of predicted effector genes of T1D loci, displaying the supporting evidence behind each prediction. Since the T1DKP is nested within and built upon the same framework as the CMDKP, users may navigate seamlessly to see results relevant to other metabolic disorders. In total the T1DKP project aims to accelerate our understanding and treatment of T1D by providing decision support for researchers as they prioritize loci, variants, and genes for experimental study. Disclosure M.C.Costanzo: Other Relationship; Pfizer Inc. P.V.Kudtarkar: None. U.Nayak: None. S.Onengut-gumuscu: None. Y.Sun: None. S.S.Rich: None. J.Flannick: None. K.J.Gaulton: Consultant; Genentech, Inc., Stock/Shareholder; Neurocrine Biosciences, Inc., Vertex Pharmaceuticals Incorporated. N.Burtt: n/a. Funding National Institutes of Health (5UM1DK105554-07)

DNAme is associated with past HbA1c in DCCT/EDIC but these associations were examined when there was separation in HbA1c distribution by trial intervention arm. Thus, we performed an epigenome-wide association study (EWAS) of DNAme and HbA1c in a T1D cohort without intervention or risk factor exclusion to identify loci with DNAme associated with concurrent and future HbA1c over 28 years. Whole blood DNAme was assayed via Illumina EPIC beadchip in the Pittsburgh Epidemiology of Diabetes Complications (EDC) study of childhood onset ( Disclosure R.G.Miller: Stock/Shareholder; Becton, Dickinson and Company. J.Mychaleckyj: None. S.Onengut-gumuscu: None. T.J.Orchard: None. T.Costacou: None. Funding American Diabetes Association (1-19-JDF-109) ; NIH/NIDDK (R01-DK034818) , Rossi Memorial Fund

DNA methylation (DNAme) has been associated with risk of future CAD in the general population and is a potential target for pharmacological intervention. In T1D, DNAme has been associated with microvascular complications but its association with CAD has not been examined in this high risk population. Thus, we performed an epigenome-wide association study (EWAS) of DNAme and 28-year major CAD (CAD death, nonfatal myocardial infarction) incidence in an observational T1D cohort. Whole blood DNAme was assayed via Illumina EPIC beadchip in the Pittsburgh Epidemiology of Diabetes Complications (EDC) study of childhood onset ( Disclosure R.G.Miller: Stock/Shareholder; Becton, Dickinson and Company. J.Mychaleckyj: None. S.Onengut-gumuscu: None. T.J.Orchard: None. T.Costacou: None. Funding American Diabetes Association (1-19-JDF-109) ; NIH/NIDDK R01-DK034818, Rossi Memorial Fund

Modeling the course of C-peptide decline in autoantibody (Ab) positive individuals is important for type 1 diabetes (T1D) prediction and implementation of T1D prevention trials. Single nucleotide polymorphisms in TCF7L2, JAZF1, SLC30A8, INS, PTPRK, G6CP2, CLEC16, PTPN22 and HLA genes are associated with persistent C-peptide at or after T1D diagnosis. We sought to determine whether 12 SNPs in these genes and the T1D genetic risk score-2 (GRS2) can predict C-peptide trajectory before diagnosis of T1D. We studied Ab positive at-risk participants in the TrialNet Pathway to Prevention Study who had ImmunoChip data (N=1217, age at initial screen (mean±SD) 16.1±12.7 years, 51.5% female, 81.0% non-Hispanic white) . Over a mean follow up of 3.4±2. years, 255 (21.0%) developed multiple Ab and 336 (27.6%) developed clinical T1D. We analyzed the influence of these 12 SNPs and the T1D GRS2 on C-peptide AUC during progression from single to multiple Abs, from single Ab to clinical T1D, and from multiple Abs to clinical T1D. Analyses were adjusted for baseline C-peptide AUC, age, glucose AUC, BMI Z-score and HbA1c; the presence of high-risk HLA haplotypes (DR3 and DR4-DQ8) ; and the first 3 principal components. The type 2 diabetes (T2D) -associated TCF7L2 rs7901695 and rs4506565 SNPs were significantly associated with higher C-peptide AUC during progression from multiple Abs to T1D (p In conclusion, T2D-associated SNPs in the TCF7L2 gene and lower T1D GRS2 predict higher C-peptide particularly in progression from multiple Abs to clinical T1D. Disclosure T.M.Triolo: None. M.J.Redondo: Advisory Panel; Provention Bio, Inc. H.M.Parikh: None. M.Tosur: Advisory Panel; Provention Bio, Inc. P.Gottlieb: Advisory Panel; Janssen Research & Development, LLC, ViaCyte, Inc., Other Relationship; IM Therapeutics, Research Support; Caladrius Biosciences, Inc., Immune Tolerance Network, National Institute of Diabetes and Digestive and Kidney Diseases, Novo Nordisk, Precigen, Inc., Tolerion, Inc. R.A.Oram: Consultant; Janssen Research & Development, LLC, Research Support; Randox R & D. S.Onengut-gumuscu: None. J.Krischer: None. S.S.Rich: None. A.Steck: None. Funding NIH K12 DK094712NIH RDK121843NIH RDK124395

Alzheimer’s disease (AD) is the most prevalent cause of dementia1. Although there is no effective treatment for AD, passive immunotherapy with monoclonal antibodies against amyloid beta (Aβ) is a promising therapeutic strategy2,3. Meningeal lymphatic drainage has an important role in the accumulation of Aβ in the brain4, but it is not known whether modulation of meningeal lymphatic function can influence the outcome of immunotherapy in AD. Here we show that ablation of meningeal lymphatic vessels in 5xFAD mice (a mouse model of amyloid deposition that expresses five mutations found in familial AD) worsened the outcome of mice treated with anti-Aβ passive immunotherapy by exacerbating the deposition of Aβ, microgliosis, neurovascular dysfunction, and behavioural deficits. By contrast, therapeutic delivery of vascular endothelial growth factor C improved clearance of Aβ by monoclonal antibodies. Notably, there was a substantial overlap between the gene signature of microglia from 5xFAD mice with impaired meningeal lymphatic function and the transcriptional profile of activated microglia from the brains of individuals with AD. Overall, our data demonstrate that impaired meningeal lymphatic drainage exacerbates the microglial inflammatory response in AD and that enhancement of meningeal lymphatic function combined with immunotherapies could lead to better clinical outcomes. Meningeal lymphatic drainage can affect the microglial inflammatory response and anti-amyloid-β immunotherapy in mouse models of Alzheimer’s disease.

Chronic natural killer large granular lymphocyte (NK-LGL) leukemia, also referred to as chronic lymphoproliferative disorder of NK cells, is a rare disorder defined by prolonged expansion of clonal NK cells. Similar prevalence of STAT3 mutations in chronic T-LGL and NK-LGL leukemia is suggestive of common pathogenesis. We undertook whole-genome sequencing to identify mutations unique to NK-LGL leukemia. The results were analyzed to develop a resequencing panel that was applied to 58 patients. Phosphatidylinositol 3-kinase pathway gene mutations (PIK3CD/PIK3AP1) and TNFAIP3 mutations were seen in 5% and 10% of patients, respectively. TET2 was exceptional in that mutations were present in 16 (28%) of 58 patient samples, with evidence that TET2 mutations can be dominant and exclusive to the NK compartment. Reduced-representation bisulfite sequencing revealed that methylation patterns were significantly altered in TET2 mutant samples. The promoter of TET2 and that of PTPRD, a negative regulator of STAT3, were found to be methylated in additional cohort samples, largely confined to the TET2 mutant group. Mutations in STAT3 were observed in 19 (33%) of 58 patient samples, 7 of which had concurrent TET2 mutations. Thrombocytopenia and resistance to immunosuppressive agents were uniquely observed in those patients with only TET2 mutation (Games-Howell post hoc test, P = .0074; Fisher’s exact test, P = .00466). Patients with STAT3 mutation, inclusive of those with TET2 comutation, had lower hematocrit, hemoglobin, and absolute neutrophil count compared with STAT3 wild-type patients (Welch’s t test, P ≤ .015). We present the discovery of TET2 mutations in chronic NK-LGL leukemia and evidence that it identifies a unique molecular subtype.

Background: Defective alleles within the PRF1 gene, encoding the pore-forming protein perforin, in combination with environmental factors, cause familial type 2 hemophagocytic lymphohistiocytosis (FHL2), a rare, severe autosomal recessive childhood disorder characterized by massive release of cytokines—cytokine storm. Objective: The aim of this study was to determine the function of hypomorph PRF1:p.A91V g.72360387 G > A on multiple sclerosis (MS) and type 1 diabetes (T1D). Methods: We cross-compare the association data for PRF1:p.A91V mutation derived from GWAS on adult MS and pediatric T1D in Sardinians. The novel association with T1D was replicated in metanalysis in 12,584 cases and 17,692 controls from Sardinia, the United Kingdom, and Scotland. To dissect this mutation function, we searched through the coincident association immunophenotypes in additional set of general population Sardinians. Results: We report that PRF1:p.A91V, is associated with increase of lymphocyte levels, especially within the cytotoxic memory T-cells, at general population level with reduced interleukin 7 receptor expression on these cells. The minor allele increased risk of MS, in 2903 cases and 2880 controls from Sardinia p = 2.06 × 10−4, odds ratio OR = 1.29, replicating a previous finding, whereas it protects from T1D p = 1.04 × 10−5, OR = 0.82. Conclusion: Our results indicate opposing contributions of the cytotoxic T-cell compartment to MS and T1D pathogenesis.

Apoptotic cell clearance (efferocytosis) elicits an anti-inflammatory response by phagocytes, but the mechanisms that underlie this response are still being defined. Here, we uncover a chloride-sensing signalling pathway that controls both the phagocyte 'appetite' and its anti-inflammatory response. Efferocytosis transcriptionally altered the genes that encode the solute carrier (SLC) proteins SLC12A2 and SLC12A4. Interfering with SLC12A2 expression or function resulted in a significant increase in apoptotic corpse uptake per phagocyte, whereas the loss of SLC12A4 inhibited corpse uptake. In SLC12A2-deficient phagocytes, the canonical anti-inflammatory program was replaced by pro-inflammatory and oxidative-stress-associated gene programs. This 'switch' to pro-inflammatory sensing of apoptotic cells resulted from the disruption of the chloride-sensing pathway (and not due to corpse overload or poor degradation), including the chloride-sensing kinases WNK1, OSR1 and SPAK-which function upstream of SLC12A2-had a similar effect on efferocytosis. Collectively, the WNK1-OSR1-SPAK-SLC12A2/SLC12A4 chloride-sensing pathway and chloride flux in phagocytes are key modifiers of the manner in which phagocytes interpret the engulfed apoptotic corpse.

Background Rare variants in gene coding regions likely have a greater impact on disease-related phenotypes than common variants through disruption of their encoded protein. We searched for rare variants associated with onset of end stage kidney disease (ESKD) in individuals with type 1 diabetes at advanced kidney disease stage. Methods Gene-based exome array analysis of 15,449 genes in 5 large incidence cohorts of individuals with type 1 diabetes and proteinuria were analyzed for survival time-to-ESKD, testing the top gene in a 6th cohort (N=2,372/1,115 events all cohorts) and replicating in two retrospective case-control studies (N=1,072 cases, 752 controls). Deep resequencing of the top associated gene in 5 cohorts confirmed the findings. We performed immunohistochemistry and gene expression experiments in human control and diseased cells, and in mouse ischemia reperfusion and aristolochic acid nephropathy models. Results Protein coding variants in the hydroxysteroid 17-beta dehydrogenase 14 gene (HSD17B14), predicted to affect protein structure, had a net protective effect against development of ESKD at exome-wide significance (N=4,196; p-value=3.3x10-7). The HSD17B14 gene and encoded enzyme were robustly expressed in healthy human kidney, maximally in proximal tubular cells. Paradoxically, gene and protein expression were attenuated in human diabetic proximal tubules and in mouse kidney injury models. Expressed HSD17B14 gene and protein levels remained low without recovery after 21 days in a murine ischemic reperfusion injury model. Decreased gene expression was found in other chronic kidney disease-associated renal pathologies. Conclusions HSD17B14 gene is mechanistically involved in diabetic kidney disease. The encoded sex steroid enzyme is a druggable target, potentially opening a new avenue for therapeutic development.

Coronary artery disease (CAD) is a complex inflammatory disease involving genetic influences across several cell types. Genome-wide association studies (GWAS) have identified over 170 loci associated with CAD, where the majority of risk variants reside in noncoding DNA sequences impacting cis -regulatory elements (CREs). Here, we applied single-cell ATAC-seq to profile 28,316 cells across coronary artery segments from 41 patients with varying stages of CAD, which revealed 14 distinct cellular clusters. We mapped over 320,000 accessible sites across all cells, identified cell type-specific elements, transcription factors, and prioritized functional CAD risk variants via quantitative trait locus and sequence-based predictive modeling. Using differential peak analyses we identified a number of candidate mechanisms for smooth muscle cell transition states (e.g. fibromyocytes). By integrating these profiles with GWAS meta-analysis summary data we resolved cell type-specific putative binding sites for the majority of CAD risk variants. In particular, we prioritized functional variants predicted to alter MEF2 binding in smooth muscle cells at the MRAS locus. We also identify variants predicted to alter macrophage-specific regulation of LIPA. We further employed DNA to gene linkage to nominate disease-associated key driver transcription factors such as PRDM16 and TBX2. Together, this single cell atlas provides a critical step towards interpreting cis -regulatory mechanisms in the vessel wall across the continuum of CAD risk.

Multiple cross-sectional and longitudinal studies have shown that serum levels of the chemokine ligand 2 (CCL-2) are associated with type 1 diabetes (T1D), although the direction of effect differs. We assessed CCL-2 serum levels in a longitudinal cohort to clarify this association, combined with genetic data to elucidate the regulatory role of CCL-2 in T1D pathogenesis. The Diabetes Autoimmunity Study in the Young (DAISY) followed 310 subjects with high risk of developing T1D. Of these, 42 became persistently seropositive for islet autoantibodies but did not develop T1D (non-progressors); 48 did develop T1D (progressors). CCL-2 serum levels among the three study groups were compared using linear mixed models adjusting for age, sex, HLA genotype, and family history of T1D. Summary statistics were obtained from the CCL-2 protein quantitative trait loci (pQTL) and CCR2 expression QTL (eQTL) studies. The T1D fine mapping association data were provided by the Type 1 Diabetes Genetics Consortium (T1DGC). Serum CCL-2 levels were significantly lower in both progressors (p = 0.004) and non-progressors (p = 0.005), compared to controls. Two SNPs (rs1799988 and rs746492) in the 3p21.31 genetic locus, which includes the CCL-2 receptor, CCR2, were associated with increased CCR2 expression (p = 8.2e-5 and 5.2e-5, respectively), decreased CCL-2 serum level (p = 2.41e-9 and 6.21e-9, respectively), and increased risk of T1D (p = 7.9e-5 and 7.9e-5, respectively). The 3p21.31 genetic region is associated with developing T1D through regulatory control of the CCR2/CCL2 immune pathway., Highlights • Serum CCL-2 levels are lower in individuals with islet autoantibodies and type 1 diabetes compared to controls. • Serum CCL-2 levels are associated with the 3p21.31 genetic locus. • The 3p21.31 genetic locus is associated with type 1 diabetes. • The 3p21.31 genetic locus is associated with gene expression of the CCL-2 receptor, CCR2.

Osteoporosis affects millions worldwide and is often caused by osteoclast induced bone loss. Here, we identify the cytoplasmic protein ELMO1 as an important ‘signaling node’ in osteoclasts. We note that ELMO1 SNPs associate with bone abnormalities in humans, and that ELMO1 deletion in mice reduces bone loss in four in vivo models: osteoprotegerin deficiency, ovariectomy, and two types of inflammatory arthritis. Our transcriptomic analyses coupled with CRISPR/Cas9 genetic deletion identify Elmo1 associated regulators of osteoclast function, including cathepsin G and myeloperoxidase. Further, we define the ‘ELMO1 interactome’ in osteoclasts via proteomics and reveal proteins required for bone degradation. ELMO1 also contributes to osteoclast sealing zone on bone-like surfaces and distribution of osteoclast-specific proteases. Finally, a 3D structure-based ELMO1 inhibitory peptide reduces bone resorption in wild type osteoclasts. Collectively, we identify ELMO1 as a signaling hub that regulates osteoclast function and bone loss, with relevance to osteoporosis and arthritis., Osteoporosis and bone fractures affect millions of patients worldwide and are often due to increased bone resorption. Here the authors identify the cytoplasmic protein ELMO1 as an important ‘signaling node’ promoting the bone resorption function of osteoclasts.

Coronary artery disease (CAD) is a complex inflammatory disease involving genetic influences across several cell types. Genome-wide association studies (GWAS) have identified over 170 loci associated with CAD, where the majority of risk variants reside in noncoding DNA sequences impacting cis-regulatory elements (CREs). Here, we applied single-cell ATAC-seq to profile 28,316 cells across coronary artery segments from 41 patients with varying stages of CAD, which revealed 14 distinct cellular clusters. We mapped ~320,000 accessible sites across all cells, identified cell type-specific elements, transcription factors, and prioritized functional CAD risk variants via quantitative trait locus and sequence-based predictive modeling. We identified a number of candidate mechanisms for smooth muscle cell transition states and identified putative binding sites for risk variants. We further employed CRE to gene linkage to nominate disease-associated key driver transcription factors such as PRDM16 and TBX2. This single cell atlas provides a critical step towards interpreting cis-regulatory mechanisms in the vessel wall across the continuum of CAD risk.

Coronary artery disease (CAD) is a complex inflammatory disease involving genetic influences across cell types. Genome-wide association studies have identified over 200 loci associated with CAD, where the majority of risk variants reside in noncoding DNA sequences impacting cis-regulatory elements. Here, we applied single-nucleus assay for transposase-accessible chromatin with sequencing to profile 28,316 nuclei across coronary artery segments from 41 patients with varying stages of CAD, which revealed 14 distinct cellular clusters. We mapped ~320,000 accessible sites across all cells, identified cell-type-specific elements and transcription factors, and prioritized functional CAD risk variants. We identified elements in smooth muscle cell transition states (for example, fibromyocytes) and functional variants predicted to alter smooth muscle cell- and macrophage-specific regulation of MRAS (3q22) and LIPA (10q23), respectively. We further nominated key driver transcription factors such as PRDM16 and TBX2. Together, this single-nucleus atlas provides a critical step towards interpreting regulatory mechanisms across the continuum of CAD risk.

Development of islet autoimmunity (IA) and type 1 diabetes (T1D) are associated with high-risk HLA class II loci as well as non-HLA genes. Monozygotic (MZ) twins have a high rate of concordance to T1D progression after the first twin develops T1D, especially for those diagnosed at a young age. We analyzed 52 T1D-associated non-HLA SNPs from ImmunoChip data in 159 MZ twins from the Twin Family Study: 79 twin probands with T1D and their 80 unaffected cotwins/triplets (including one set of triplets). Subjects are enrolled into the Twin Study when the proband is diagnosed with T1D and cotwins are followed longitudinally for the development of IA and/or T1D. In the cotwins, we analyzed the association between each of the non-HLA SNPs and IA after adjusting for HLA DR3/4*0302. In the twin probands with T1D, we used a linear regression model to evaluate the association of non-HLA SNPs with diabetes age at onset after adjusting for HLA DR3/4*0302. Median (IQR) age of diagnosis of the twin probands was 9.9 (5.4-13.9) years and age of last visit for the cotwins was 17.5 (11.2-26.7) years. Of the 80 cotwins, 41 (51.3%) developed IA and 15 (18.8%) were diagnosed with T1D. After adjusting for HLA DR3/4*0302, SNPs in CTLA4 (rs3087243), IL2 (rs4505848), IKZF1 (rs62447205), and INS (rs7111341) were found to be associated with the development of IA in cotwin subjects (all p Disclosure T. M. Triolo: None. F. Dong: None. H. C. Broncucia: None. S. Onengut-gumuscu: None. A. Steck: None. S. S. Rich: None. Funding National Institute of Diabetes and Digestive and Kidney Diseases (K12DK094712)

Genome-wide association studies (GWASs) for osteoporotic traits have identified over 1000 associations; however, their impact has been limited by the difficulties of causal gene identification and a strict focus on bone mineral density (BMD). Here, we use Diversity Outbred (DO) mice to directly address these limitations by performing a systems genetics analysis of 55 complex skeletal phenotypes. We apply a network approach to cortical bone RNA-seq data to discover 66 genes likely to be causal for human BMD GWAS associations, including the genes SERTAD4 and GLT8D2. We also perform GWAS in the DO for a wide-range of bone traits and identify Qsox1 as a gene influencing cortical bone accrual and bone strength. In this work, we advance our understanding of the genetics of osteoporosis and highlight the ability of the mouse to inform human genetics., Osteoporosis GWAS faces two challenges, causal gene discovery and a lack of phenotypic diversity. Here, the authors use the Diversity Outbred mouse population to inform human GWAS using networks and map genetic loci for 55 bone traits, identifying new potential bone strength genes.

Background: Type 1 diabetes (T1D) genetic risk score (GRS) and islet autoantibody (AAb) specificity and titers influence T1D risk; however, these factors collected at baseline in cross sectional studies have not been effectively incorporated in the current models for prediction of progression along pre-clinical stages of T1D. Our aim was to develop an updated model of T1D prediction for research and clinical practice. Methods: AAb-positive relatives of individuals with T1D (n=1,233, 52% female, 88% European ancestry, age mean 15 yrs [SD 12.2]) from the TrialNet Pathway to Prevention were followed for a median of 3.1 years (IQR 1.1 -7.1). T1D developed in 498/1,233 (40.4%). T1D GRS, AAb number, AAb combination, AAb titer, age and sex were evaluated on the combined T1D prediction model, estimating its performance using 3-fold cross-validation (10x repeated). Results: Machine learning (survival random forest) and traditional methods (Cox models, extended Cox model) performed equivalently as measured by 5 yr horizon time-dependent AUC ROC (respectively 0.74, 0.74, 0.72), on calibration by integrated Brier score (respectively 0.15, 0.15, 0.16), and by calibration plots. AAb combinations with specific variables predicted T1D. In multivariate analysis, T1D GRS was a significant predictor of T1D in individuals positive for GADA, IAA or both. For any autoantibody combination including IA2A, the IA2A titer was predictive while the T1D GRS was not. Variable importance analyses showed that T1D was predicted by IA2A titer level, followed by T1D GRS and combinations of specific AAbs. Conclusion: We modeled individual estimates of T1D risk with T1D GRS, AAb characteristics, age, and sex. T1D prediction improved by adding T1D GRS and AAb characteristics to other variables, and was similar using machine learning or traditional models. T1D GRS was a significant predictor only in the absence of IA2A. In the presence of IA2A, IA2A titer was the most influential factor. Disclosure L. A. Ferrat: None. M. J. Redondo: Advisory Panel; Self; Provention Bio, Inc. A. Steck: None. H. M. Parikh: None. L. You: None. S. Onengut-gumuscu: None. P. Gottlieb: Advisory Panel; Self; Janssen Research & Development, LLC, Tolerion, Inc., Viacyte, Inc., Other Relationship; Self; ImmunoMolecular Therapeutics, Inc., Research Support; Self; Caladrius Biosciences, Inc., Immune Tolerance Network, Mercia Pharma Inc., National Institute of Diabetes and Digestive and Kidney Diseases, Precigen, Inc., Tolerion, Inc. S. S. Rich: None. J. Krischer: None. R. A. Oram: Consultant; Self; Janssen Research & Development, LLC. Funding National Institute of Diabetes and Digestive and Kidney Diseases (1R01DK121843-01); JDRF (3-SRA-2019-827-S-B)

The risk for autoimmunity and subsequently type 1 diabetes is 10-fold higher in children with a first-degree family history of type 1 diabetes (FDR children) than in children in the general population (GP children). We analyzed children with high-risk HLA genotypes (n = 4,573) in the longitudinal TEDDY birth cohort to determine how much of the divergent risk is attributable to genetic enrichment in affected families. Enrichment for susceptible genotypes of multiple type 1 diabetes–associated genes and a novel risk gene, BTNL2, was identified in FDR children compared with GP children. After correction for genetic enrichment, the risks in the FDR and GP children converged but were not identical for multiple islet autoantibodies (hazard ratio [HR] 2.26 [95% CI 1.6–3.02]) and for diabetes (HR 2.92 [95% CI 2.05–4.16]). Convergence varied depending upon the degree of genetic susceptibility. Risks were similar in the highest genetic susceptibility group for multiple islet autoantibodies (14.3% vs .12.7%) and diabetes (4.8% vs. 4.1%) and were up to 5.8-fold divergent for children in the lowest genetic susceptibility group, decreasing incrementally in GP children but not in FDR children. These findings suggest that additional factors enriched within affected families preferentially increase the risk of autoimmunity and type 1 diabetes in lower genetic susceptibility strata.