Thymocyte regulatory variant alters transcription factor binding and protects from type 1 diabetes in infants.

We recently mapped a genetic susceptibility locus on chromosome 6q22.33 for type 1 diabetes (T1D) diagnosed below the age of 7 years between the PTPRK and thymocyte-selection-associated (THEMIS) genes. As the thymus plays a central role in shaping the T cell repertoire, we aimed to identify the most likely causal genetic factors behind this association using thymocyte genomic data. In four thymocyte populations, we identified 253 DNA sequence motifs underlying histone modifications. The G insertion allele of rs138300818, associated with protection from diabetes, created thymocyte motifs for multiple histone modifications and thymocyte types. In a parallel approach to identifying variants that alter transcription factor binding motifs, the same variant disrupted a predicted motif for Rfx7, which is abundantly expressed in the thymus. Chromatin state and RNA sequencing data suggested strong transcription overlapping rs138300818 in fetal thymus, while expression quantitative trait locus and chromatin conformation data associate the insertion with lower THEMIS expression. Extending the analysis to other T1D loci further highlighted rs66733041 affecting the GATA3 transcription factor binding in the AFF3 locus. Taken together, our results support a role for thymic THEMIS gene expression and the rs138300818 variant in promoting the development of early-onset T1D.

Circulating C-Peptide Levels in Living Children and Young People and Pancreatic ß-Cell Loss in Pancreas Donors Across Type 1 Diabetes Disease Duration.

C-peptide declines in type 1 diabetes, although many long-duration patients retain low, but detectable levels. Histological analyses confirm that ß-cells can remain following type 1 diabetes onset. We explored the trends observed in C-peptide decline in the UK Genetic Resource Investigating Diabetes (UK GRID) cohort (N = 4,079), with ß-cell loss in pancreas donors from the network for Pancreatic Organ donors with Diabetes (nPOD) biobank and the Exeter Archival Diabetes Biobank (EADB) (combined N = 235), stratified by recently reported age at diagnosis endotypes (<7, 7-12, ≥13 years) across increasing diabetes durations. The proportion of individuals with detectable C-peptide declined beyond the first year after diagnosis, but this was most marked in the youngest age group (<1-year duration: age <7 years: 18 of 20 [90%], 7-12 years: 107 of 110 [97%], ≥13 years: 58 of 61 [95%] vs. 1-5 years postdiagnosis: <7 years: 172 of 522 [33%], 7-12 years: 604 of 995 [61%], ≥13 years: 225 of 289 [78%]). A similar profile was observed in ß-cell loss, with those diagnosed at younger ages experiencing more rapid loss of islets containing insulin-positive (insulin+) ß-cells <1 year postdiagnosis: age <7 years: 23 of 26 (88%), 7-12 years: 32 of 33 (97%), ≥13 years: 22 of 25 (88%) vs. 1-5 years postdiagnosis: <7 years: 1 of 12 (8.3%), 7-12 years: 7 of 13 (54%), ≥13 years: 7 of 8 (88%). These data should be considered in the planning and interpretation of intervention trials designed to promote ß-cell retention and function.

Childhood body size directly increases type 1 diabetes risk based on a lifecourse Mendelian randomization approach.

The rising prevalence of childhood obesity has been postulated as an explanation for the increasing rate of individuals diagnosed with type 1 diabetes (T1D). In this study, we use Mendelian randomization (MR) to provide evidence that childhood body size has an effect on T1D risk (OR = 2.05 per change in body size category, 95% CI = 1.20 to 3.50, P = 0.008), which remains after accounting for body size at birth and during adulthood using multivariable MR (OR = 2.32, 95% CI = 1.21 to 4.42, P = 0.013). We validate this direct effect of childhood body size using data from a large-scale T1D meta-analysis based on n = 15,573 cases and n = 158,408 controls (OR = 1.94, 95% CI = 1.21 to 3.12, P = 0.006). We also provide evidence that childhood body size influences risk of asthma, eczema and hypothyroidism, although multivariable MR suggested that these effects are mediated by body size in later life. Our findings support a causal role for higher childhood body size on risk of being diagnosed with T1D, whereas its influence on the other immune-associated diseases is likely explained by a long-term effect of remaining overweight for many years over the lifecourse.

Fine-mapping, trans-ancestral and genomic analyses identify causal variants, cells, genes and drug targets for type 1 diabetes.

We report the largest and most diverse genetic study of type 1 diabetes (T1D) to date (61,427 participants), yielding 78 genome-wide-significant (P < 5 × 10-8) regions, including 36 that are new. We define credible sets of T1D-associated variants and show that they are enriched in immune-cell accessible chromatin, particularly CD4+ effector T cells. Using chromatin-accessibility profiling of CD4+ T cells from 115 individuals, we map chromatin-accessibility quantitative trait loci and identify five regions where T1D risk variants co-localize with chromatin-accessibility quantitative trait loci. We highlight rs72928038 in BACH2 as a candidate causal T1D variant leading to decreased enhancer accessibility and BACH2 expression in T cells. Finally, we prioritize potential drug targets by integrating genetic evidence, functional genomic maps and immune protein-protein interactions, identifying 12 genes implicated in T1D that have been targeted in clinical trials for autoimmune diseases. These findings provide an expanded genomic landscape for T1D.

Analysis of overlapping genetic association in type 1 and type 2 diabetes.

AIMS/HYPOTHESIS: Given the potential shared aetiology between type 1 and type 2 diabetes, we aimed to identify any genetic regions associated with both diseases. For associations where there is a shared signal and the allele that increases risk to one disease also increases risk to the other, inference about shared aetiology could be made, with the potential to develop therapeutic strategies to treat or prevent both diseases simultaneously. Alternatively, if a genetic signal co-localises with divergent effect directions, it could provide valuable biological insight into how the association affects the two diseases differently. METHODS: Using publicly available type 2 diabetes summary statistics from a genome-wide association study (GWAS) meta-analysis of European ancestry individuals (74,124 cases and 824,006 controls) and type 1 diabetes GWAS summary statistics from a meta-analysis of studies on individuals from the UK and Sardinia (7467 cases and 10,218 controls), we identified all regions of 0.5 Mb that contained variants associated with both diseases (false discovery rate <0.01). In each region, we performed forward stepwise logistic regression to identify independent association signals, then examined co-localisation of each type 1 diabetes signal with each type 2 diabetes signal using coloc. Any association with a co-localisation posterior probability of ≥0.9 was considered a genuine shared association with both diseases. RESULTS: Of the 81 association signals from 42 genetic regions that showed association with both type 1 and type 2 diabetes, four association signals co-localised between both diseases (posterior probability ≥0.9): (1) chromosome 16q23.1, near CTRB1/BCAR1, which has been previously identified; (2) chromosome 11p15.5, near the INS gene; (3) chromosome 4p16.3, near TMEM129 and (4) chromosome 1p31.3, near PGM1. In each of these regions, the effect of genetic variants on type 1 diabetes was in the opposite direction to the effect on type 2 diabetes. Use of additional datasets also supported the previously identified co-localisation on chromosome 9p24.2, near the GLIS3 gene, in this case with a concordant direction of effect. CONCLUSIONS/INTERPRETATION: Four of five association signals that co-localise between type 1 diabetes and type 2 diabetes are in opposite directions, suggesting a complex genetic relationship between the two diseases.

Author Correction: Approaches and advances in the genetic causes of autoimmune disease and their implications.

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

Genetic Variants Predisposing Most Strongly to Type 1 Diabetes Diagnosed Under Age 7 Years Lie Near Candidate Genes That Function in the Immune System and in Pancreatic ß-Cells.

OBJECTIVE: Immunohistological analyses of pancreata from patients with type 1 diabetes suggest distinct autoimmune islet ß-cell pathology between those diagnosed at <7 years (<7 group) and those diagnosed at age ≥13 years (≥13 group), with both B- and T-lymphocyte islet inflammation common in children in the <7 group, whereas B cells are rare in the ≥13 group. Based on these observations, we sought to identify differences in genetic susceptibility between these prespecified age-at-diagnosis groups to inform on the etiology of the most aggressive form of type 1 diabetes that initiates in the first years of life. RESEARCH DESIGN AND METHODS: Using multinomial logistic regression models, we tested if known type 1 diabetes loci (17 within the HLA and 55 non-HLA loci) had significantly stronger effect sizes in the <7 group compared with the ≥13 group, using genotype data from 27,071 individuals (18,485 control subjects and 3,121 case subjects diagnosed at <7 years, 3,757 at 7-13 years, and 1,708 at ≥13 years). RESULTS: Six HLA haplotypes/classical alleles and six non-HLA regions, one of which functions specifically in ß-cells (GLIS3) and the other five likely affecting key T-cell (IL2RA, IL10, IKZF3, and THEMIS), thymus (THEMIS), and B-cell development/functions (IKZF3 and IL10) or in both immune and ß-cells (CTSH), showed evidence for stronger effects in the <7 group. CONCLUSIONS: A subset of type 1 diabetes-associated variants are more prevalent in children diagnosed under the age of 7 years and are near candidate genes that act in both pancreatic ß- and immune cells.

The impact of proinflammatory cytokines on the ß-cell regulatory landscape provides insights into the genetics of type 1 diabetes.

The early stages of type 1 diabetes (T1D) are characterized by local autoimmune inflammation and progressive loss of insulin-producing pancreatic ß cells. Here we show that exposure to proinflammatory cytokines reveals a marked plasticity of the ß-cell regulatory landscape. We expand the repertoire of human islet regulatory elements by mapping stimulus-responsive enhancers linked to changes in the ß-cell transcriptome, proteome and three-dimensional chromatin structure. Our data indicate that the ß-cell response to cytokines is mediated by the induction of new regulatory regions as well as the activation of primed regulatory elements prebound by islet-specific transcription factors. We find that T1D-associated loci are enriched with newly mapped cis-regulatory regions and identify T1D-associated variants disrupting cytokine-responsive enhancer activity in human ß cells. Our study illustrates how ß cells respond to a proinflammatory environment and implicate a role for stimulus response islet enhancers in T1D.

Publisher Correction: Approaches and advances in the genetic causes of autoimmune disease and their implications.

In the version of this article initially published, the bibliographic information for reference 2 was incorrect in the reference list, and reference 2 was cited incorrectly at the end of the second sentence in the second paragraph ("...were identified2."). The correct reference 2 is as follows: "Kong, A. et al. The nature of nurture: Effects of parental genotypes. Science 359, 424-428 (2018)." The reference that should be cited at the end of the aforementioned sentence, which should be numbered '5' ("...were identified5."), is as follows: "Okada, Y. et al. Genetics of rheumatoid arthritis contributes to biology and drug discovery. Nature 506, 376-381 (2014)." All subsequent references (5-161) should be renumbered accordingly (6-162) in the list and text. Also, several of the gene symbols in Table 2 were formatted incorrectly (without commas); the correct gene symbols are as follows: column 3 row 13, RBM17, IL2RA; column 3 row 30, DEXI, CLEC16A; column 3 row 39, UBASH3A, ICOSLG; column 4 row 15, PTEN, KLLN; column 4 row 21, CLEC7A, CLEC9A; and column 5 rows 7-9, AL391559.1, ENSG00000238747, RP11-63K6.7, RP3-512E2.2. The errors have been corrected in the HTML and PDF version of the article.

Approaches and advances in the genetic causes of autoimmune disease and their implications.

Genome-wide association studies are transformative in revealing the polygenetic basis of common diseases, with autoimmune diseases leading the charge. Although the field is just over 10 years old, advances in understanding the underlying mechanistic pathways of these conditions, which result from a dense multifactorial blend of genetic, developmental and environmental factors, have already been informative, including insights into therapeutic possibilities. Nevertheless, the challenge of identifying the actual causal genes and pathways and their biological effects on altering disease risk remains for many identified susceptibility regions. It is this fundamental knowledge that will underpin the revolution in patient stratification, the discovery of therapeutic targets and clinical trial design in the next 20 years. Here we outline recent advances in analytical and phenotyping approaches and the emergence of large cohorts with standardized gene-expression data and other phenotypic data that are fueling a bounty of discovery and improved understanding of human physiology.

The chromosome 6q22.33 region is associated with age at diagnosis of type 1 diabetes and disease risk in those diagnosed under 5 years of age.

AIMS/HYPOTHESIS: The genetic risk of type 1 diabetes has been extensively studied. However, the genetic determinants of age at diagnosis (AAD) of type 1 diabetes remain relatively unexplained. Identification of AAD genes and pathways could provide insight into the earliest events in the disease process. METHODS: Using ImmunoChip data from 15,696 cases, we aimed to identify regions in the genome associated with AAD. RESULTS: Two regions were convincingly associated with AAD (p < 5 × 10-8): the MHC on 6p21, and 6q22.33. Fine-mapping of 6q22.33 identified two AAD-associated haplotypes in the region nearest to the genes encoding protein tyrosine phosphatase receptor kappa (PTPRK) and thymocyte-expressed molecule involved in selection (THEMIS). We examined the susceptibility to type 1 diabetes at these SNPs by performing a meta-analysis including 19,510 control participants. Although these SNPs were not associated with type 1 diabetes overall (p > 0.001), the SNP most associated with AAD, rs72975913, was associated with susceptibility to type 1 diabetes in those individuals diagnosed at less than 5 years old (p = 2.3 × 10-9). CONCLUSION/INTERPRETATION: PTPRK and its neighbour THEMIS are required for early development of the thymus, which we can assume influences the initiation of autoimmunity. Non-HLA genes may only be detectable as risk factors for the disease in individuals diagnosed under the age 5 years because, after that period of immune development, their role in disease susceptibility has become redundant.

Pharmacokinetics of pediatric lopinavir/ritonavir tablets in children when administered twice daily according to FDA weight bands.

BACKGROUND: Lopinavir/ritonavir (LPV/r) pediatric tablets (100/25 mg) are approved by the United States Food and Drug Administration (FDA) and European Medicines Agency (EMA) as part of combination antiretroviral therapy. Dosing is based on body weight bands or body surface area under FDA approval and only body surface area by the EMA. This can lead to a different recommended dose. In addition, weight band-based dosing has not been formally studied in the target population. We evaluated the pharmacokinetics (PK) of LPV/r in children, administered twice daily according to the FDA weight bands, using pediatric tablets. METHODS: Fifty-three HIV-infected children were included in the PK substudy of the Paediatric European Network for the Treatment of AIDS 18 trial (KONCERT). In this study, children were randomized to receive LPV/r twice or once daily, according to FDA weight bands. A PK assessment was performed in 17, 16 and 20 children in the 15-25 kg, ≥ 25-35 kg and >35 kg weight band, respectively, while children took the tablets twice daily. Rich sampling was performed, and PK parameters were calculated by noncompartmental analysis. Given the high percentage of Asian children, it was also tested whether there was a difference in PK parameters between Asian and non-Asian children. RESULTS: For the total group, LPV geometric mean AUC0-12, Cmax and C12 were 106.9 h × mg/L, 12.0 mg/L and 4.9 mg/L, respectively. There were no significant differences in LPV PK parameters between the weight bands. In addition, weight was not found to be associated with variability in Cmax, C12 or AUC0-12 for the LPV PK parameters. CONCLUSIONS: FDA weight band-based dosing recommendations provide adequate exposure to LPV when using LPV/r pediatric tablets.