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Seasonal variations are rarely considered a contributing component to human tissue function or health, although many diseases and physiological process display annual periodicities. Here we find more than 4,000 protein-coding mRNAs in white blood cells and adipose tissue to have seasonal expression profiles, with inverted patterns observed between Europe and Oceania. We also find the cellular composition of blood to vary by season, and these changes, which differ between the United Kingdom and The Gambia, could explain the gene expression periodicity. With regards to tissue function, the immune system has a profound pro-inflammatory transcriptomic profile during European winter, with increased levels of soluble IL-6 receptor and C-reactive protein, risk biomarkers for cardiovascular, psychiatric and autoimmune diseases that have peak incidences in winter. Circannual rhythms thus require further exploration as contributors to various aspects of human physiology and disease. Infectious and chronic diseases display seasonal patterns, yet seasonal changes in physiology are rarely thought to affect human health. Here the authors show seasonal variation in all major blood cells and in gene and protein expression in diverse tissues, suggesting a mechanism for seasonal disease proneness and physiology.

Naïve CD4 + T cells coordinate the immune response by acquiring an effector phenotype in response to cytokines. However, the cytokine responses in memory T cells remain largely understudied. Here we use quantitative proteomics, bulk RNA-seq, and single-cell RNA-seq of over 40,000 human naïve and memory CD4 + T cells to show that responses to cytokines differ substantially between these cell types. Memory T cells are unable to differentiate into the Th2 phenotype, and acquire a Th17-like phenotype in response to iTreg polarization. Single-cell analyses show that T cells constitute a transcriptional continuum that progresses from naïve to central and effector memory T cells, forming an effectorness gradient accompanied by an increase in the expression of chemokines and cytokines. Finally, we show that T cell activation and cytokine responses are influenced by the effectorness gradient. Our results illustrate the heterogeneity of T cell responses, furthering our understanding of inflammation. Cytokines critically control the differentiation and functions of activated naïve and memory T cells. Here the authors show, using multi-omics and single-cell analyses, that naïve and memory T cells exhibit distinct cytokine responses, in which an ‘effectorness gradient’ is depicted by a transcriptional continuum, which shapes the downstream genetic programs.

The genetic basis of autoantibody production is largely unknown outside of associations located in the major histocompatibility complex (MHC) human leukocyte antigen (HLA) region. The aim of this study is the discovery of new genetic associations with autoantibody positivity using genome-wide association scan single nucleotide polymorphism (SNP) data in type 1 diabetes (T1D) patients with autoantibody measurements. We measured two anti-islet autoantibodies, glutamate decarboxylase (GADA, n = 2,506), insulinoma-associated antigen 2 (IA-2A, n = 2,498), antibodies to the autoimmune thyroid (Graves') disease (AITD) autoantigen thyroid peroxidase (TPOA, n = 8,300), and antibodies against gastric parietal cells (PCA, n = 4,328) that are associated with autoimmune gastritis. Two loci passed a stringent genome-wide significance level (p<10(-10)): 1q23/FCRL3 with IA-2A and 9q34/ABO with PCA. Eleven of 52 non-MHC T1D loci showed evidence of association with at least one autoantibody at a false discovery rate of 16%: 16p11/IL27-IA-2A, 2q24/IFIH1-IA-2A and PCA, 2q32/STAT4-TPOA, 10p15/IL2RA-GADA, 6q15/BACH2-TPOA, 21q22/UBASH3A-TPOA, 1p13/PTPN22-TPOA, 2q33/CTLA4-TPOA, 4q27/IL2/TPOA, 15q14/RASGRP1/TPOA, and 12q24/SH2B3-GADA and TPOA. Analysis of the TPOA-associated loci in 2,477 cases with Graves' disease identified two new AITD loci (BACH2 and UBASH3A).

Inflammation, which is directly regulated by interleukin-6 (IL-6) signaling, is implicated in the etiology of several chronic diseases. Although a common, non-synonymous variant in the IL-6 receptor gene (IL6R Asp358Ala; rs2228145 A>C) is associated with the risk of several common diseases, with the 358Ala allele conferring protection from coronary heart disease (CHD), rheumatoid arthritis (RA), atrial fibrillation (AF), abdominal aortic aneurysm (AAA), and increased susceptibility to asthma, the variant's effect on IL-6 signaling is not known. Here we provide evidence for the association of this non-synonymous variant with the risk of type 1 diabetes (T1D) in two independent populations and confirm that rs2228145 is the major determinant of the concentration of circulating soluble IL-6R (sIL-6R) levels (34.6% increase in sIL-6R per copy of the minor allele 358Ala; rs2228145 [C]). To further investigate the molecular mechanism of this variant, we analyzed expression of IL-6R in peripheral blood mononuclear cells (PBMCs) in 128 volunteers from the Cambridge BioResource. We demonstrate that, although 358Ala increases transcription of the soluble IL6R isoform (P = 8.3×10⁻²²) and not the membrane-bound isoform, 358Ala reduces surface expression of IL-6R on CD4+ T cells and monocytes (up to 28% reduction per allele; P≤5.6×10⁻²²). Importantly, reduced expression of membrane-bound IL-6R resulted in impaired IL-6 responsiveness, as measured by decreased phosphorylation of the transcription factors STAT3 and STAT1 following stimulation with IL-6 (P≤5.2×10⁻⁷). Our findings elucidate the regulation of IL-6 signaling by IL-6R, which is causally relevant to several complex diseases, identify mechanisms for new approaches to target the IL-6/IL-6R axis, and anticipate differences in treatment response to IL-6 therapies based on this common IL6R variant.

Type 1 diabetes and celiac disease, both of which are associated with HLA class II genes, cosegregate in populations, suggesting a common genetic origin. In this article, the authors tested whether any non-HLA loci are shared. They report susceptibility alleles shared by both diseases, indicating that common biologic mechanisms underlie these immune-mediated disorders. Type 1 diabetes and celiac disease cosegregate in populations, suggesting a common genetic origin. These authors report susceptibility alleles shared by both diseases, indicating that common biologic mechanisms underlie these immune-mediated disorders. Type 1 diabetes is caused by autoimmune destruction of the insulin-producing beta cells in the pancreatic islets. The disease affects approximately 0.4% of persons of European origin and is strongly clustered in families. The major susceptibility genes — the HLA class II loci, HLA-DQB1 and HLA-DRB1 on chromosome 6p21 — act in combination with many other non-HLA loci across the genome, 1 , 2 with unknown environmental factors playing a major role. 3 – 6 Celiac disease, which results from an immune, inflammatory reaction in the small intestine to proteins in ingested barley, wheat, and rye gluten, occurs in approximately 0.1% of persons of . . .

Jason Cooper and colleagues identify four new risk loci for type 1 diabetes through a meta-analysis of data from three genome-wide association studies, with replication in additional case-control and family-based samples, providing further insights into the genetic risk factors underlying this disease. We carried out a meta-analysis of data from three genome-wide association (GWA) studies of type 1 diabetes (T1D), testing 305,090 SNPs in 3,561 T1D cases and 4,646 controls of European ancestry. We obtained further support for 4q27 ( IL2-IL21 , P = 1.9 × 10 −8 ) and, after genotyping an additional 6,225 cases, 6,946 controls and 2,828 families, convincing evidence for four previously unknown and distinct risk loci in chromosome regions 6q15 ( BACH2 , P = 4.7 × 10 −12 ), 10p15 ( PRKCQ , P = 3.7 × 10 −9 ), 15q24 ( CTSH , P = 3.2 × 10 −15 ) and 22q13 ( C1QTNF6 , P = 2.0 × 10 −8 ).

IFIH1 (interferon induced with helicase C domain 1), also known as MDA5 (melanoma differentiation-associated protein 5), is one of a family of intracellular proteins known to recognise viral RNA and mediate the innate immune response. IFIH1 is causal in type 1 diabetes based on the protective associations of four rare variants, where the derived alleles are predicted to reduce gene expression or function. Originally, however, T1D protection was mapped to the common IFIH1 nsSNP, rs1990760 or Thr946Ala. This common amino acid substitution does not cause a loss of function and evidence suggests the protective allele, Ala(946), may mark a haplotype with reduced expression of IFIH1 in line with the protection conferred by the four rare loss of function alleles. We have performed allele specific expression analysis that supports this hypothesis: the T1D protective haplotype correlates with reduced IFIH1 transcription in interferon-β stimulated peripheral blood mononuclear cells (overall p = 0.012). In addition, we have used multiflow cytometry analysis and quantitative PCR assays to prove reduced expression of IFIH1 in individuals heterozygous for three of the T1D-associated rare alleles: a premature stop codon, rs35744605 (Glu627X) and predicted splice variants, rs35337543 (IVS8+1) and rs35732034 (IVS14+1). We also show that the nsSNP, Ile923V, does not alter pre-mRNA levels of IFIH1. These results confirm and extend the new autoimmune disease pathway of reduced IFIH1 expression and protein function protecting from T1D.

In this study we report convincing statistical support for a sixth type 1 diabetes (T1D) locus in the innate immunity viral RNA receptor gene region IFIH1 (also known as mda-5 or Helicard ) on chromosome 2q24.3. We found the association in an interim analysis of a genome-wide nonsynonymous SNP (nsSNP) scan, and we validated it in a case-control collection and replicated it in an independent family collection. In 4,253 cases, 5,842 controls and 2,134 parent-child trio genotypes, the risk ratio for the minor allele of the nsSNP rs1990760 A → G (A946T) was 0.86 (95% confidence interval = 0.82–0.90) at P = 1.42 × 10 −10 .

Genome-wide association studies are now identifying disease-associated chromosome regions. However, even after convincing replication, the localization of the causal variant(s) requires comprehensive resequencing, extensive genotyping and statistical analyses in large sample sets leading to targeted functional studies. Here, we have localized the type 1 diabetes (T1D) association in the interleukin 2 receptor alpha ( IL2RA ) gene region to two independent groups of SNPs, spanning overlapping regions of 14 and 40 kb, encompassing IL2RA intron 1 and the 5′ regions of IL2RA and RBM17 (odds ratio = 2.04, 95% confidence interval = 1.70–2.45; P = 1.92 × 10 −28 ; control frequency = 0.635). Furthermore, we have associated IL2RA T1D susceptibility genotypes with lower circulating levels of the biomarker, soluble IL-2RA ( P = 6.28 × 10 −28 ), suggesting that an inherited lower immune responsiveness predisposes to T1D.

FUT2 encodes the α(1,2) fucosyltransferase that determines blood group secretor status. Homozygotes (A/A) for the common nonsense mutation rs601338A>G (W143X) are nonsecretors and are unable to express histo-blood group antigens in secretions and on mucosal surfaces. This mutation has been reported to provide resistance to Norovirus and susceptibility to Crohn's disease, and hence we aimed to determine if it also affects risk of type 1 diabetes. rs601338A>G was genotyped in 8,344 patients with type 1 diabetes, 10,008 control subjects, and 3,360 type 1 diabetic families. Logistic regression models were used to analyze the case-control collection, and conditional logistic regression was used to analyze the family collection. RESULTS The nonsecretor A/A genotype of rs601338A>G was found to confer susceptibility to type 1 diabetes in both the case-control and family collections (odds ratio for AA 1.29 [95% CI 1.20-1.37] and relative risk for AA 1.22 [95% CI = 1.12-1.32]; combined P = 4.3 × 10(-18)), based on a recessive effects model. Our findings linking FUT2 and type 1 diabetes highlight the intriguing relationship between host resistance to infections and susceptibility to autoimmune disease.