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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., (© 2021. Crown.)

A common strategy for conditional knockout alleles is to "flox" (flank with loxP sites) a 5' exon within the target gene. Typically, the floxed exon does not contain a unit number of codons so that the Cre-mediated recombination event yields a frameshift and a null allele. Documenting recombination within the genomic DNA is often regarded as sufficient proof of a frameshift, and the analysis of transcripts is neglected. We evaluated a previously reported conditional knockout allele for the beta-subunit of protein farnesyltransferase. The recombination event in that allele-the excision of exon 3-was predicted to yield a frameshift. However, following the excision of exon 3, exon 4 was skipped by the mRNA splicing machinery, and the predominant transcript from the mutant allele lacked exon 3 and exon 4 sequences. The "Deltaexon 3-4 transcript" does not contain a frameshift but rather is predicted to encode a protein with a short in-frame deletion. This represents a significant concern when studying an enzyme, since an enzyme with partial function could lead to erroneous conclusions. With thousands of new conditional knockout alleles under construction within mouse mutagenesis consortiums, the protein farnesyltransferase allele holds an important lesson-to characterize knockout alleles at both the DNA and RNA levels.

ObjectiveGenetic risk scores (GRS) have been developed that differentiate individuals with type 1 diabetes from those with other forms of diabetes and are starting to be used for population screening; however, most studies were conducted in European-ancestry populations. This study identifies novel genetic variants associated with type 1 diabetes risk in African-ancestry participants and develops an African-specific GRS.Research design and methodsWe generated single nucleotide polymorphism (SNP) data with the ImmunoChip on 1,021 African-ancestry participants with type 1 diabetes and 2,928 control participants. HLA class I and class II alleles were imputed using SNP2HLA. Logistic regression models were used to identify genome-wide significant (P < 5.0 × 10-8) SNPs associated with type 1 diabetes in the African-ancestry samples and validate SNPs associated with risk in known European-ancestry loci (P < 2.79 × 10-5).ResultsAfrican-specific (HLA-DQA1*03:01-HLA-DQB1*02:01) and known European-ancestry HLA haplotypes (HLA-DRB1*03:01-HLA-DQA1*05:01-HLA-DQB1*02:01, HLA-DRB1*04:01-HLA-DQA1*03:01-HLA-DQB1*03:02) were significantly associated with type 1 diabetes risk. Among European-ancestry defined non-HLA risk loci, six risk loci were significantly associated with type 1 diabetes in subjects of African ancestry. An African-specific GRS provided strong prediction of type 1 diabetes risk (area under the curve 0.871), performing significantly better than a European-based GRS and two polygenic risk scores in independent discovery and validation cohorts.ConclusionsGenetic risk of type 1 diabetes includes ancestry-specific, disease-associated variants. The GRS developed here provides improved prediction of type 1 diabetes in African-ancestry subjects and a means to identify groups of individuals who would benefit from immune monitoring for early detection of islet autoimmunity.

Large granular lymphocyte (LGL) leukemia arises spontaneously in elderly Fischer (F344) rats. This rodent model has been shown to emulate many aspects of the natural killer (NK) variant of human LGL leukemia. Previous transplantation of leukemic material into young F344 rats resulted in several strains of rat NK (RNK) primary leukemic cells. One strain, RNK-16, was adapted into the RNK-16 cell line and established as an aggressive NK-LGL leukemia model. Whole genome sequencing of the RNK-16 cell line identified 255,838 locations where the RNK16 had an alternate allele that was different from F344, including a mutation in Jak1. Functional studies showed Jak1 Y1034C to be a somatic activating mutation that mediated increased STAT signaling, as assessed by phosphoprotein levels. Sanger sequencing of Jak1 in RNK-1, -3, -7, and -16 found only RNK-16 to harbor the Y1034C Jak1 mutation. In vivo studies revealed that rats engrafted with RNK-16 primary material developed leukemia more rapidly than those engrafted with RNK-1, -3, and -7. Additionally, ex vivo RNK-16 spleen cells from leukemic rats exhibited increased STAT1, STAT3, and STAT5 phosphorylation compared to other RNK strains. Therefore, we report and characterize a novel gain-of-function Jak1 mutation in a spontaneous LGL leukemia model that results in increased downstream STAT signaling. [ABSTRACT FROM AUTHOR]