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Differences in immune function and responses contribute to health- and life-span disparities between sexes. However, the role of sex in immune system aging is not well understood. Here, we characterize peripheral blood mononuclear cells from 172 healthy adults 22–93 years of age using ATAC-seq, RNA-seq, and flow cytometry. These data reveal a shared epigenomic signature of aging including declining naïve T cell and increasing monocyte and cytotoxic cell functions. These changes are greater in magnitude in men and accompanied by a male-specific decline in B-cell specific loci. Age-related epigenomic changes first spike around late-thirties with similar timing and magnitude between sexes, whereas the second spike is earlier and stronger in men. Unexpectedly, genomic differences between sexes increase after age 65, with men having higher innate and pro-inflammatory activity and lower adaptive activity. Impact of age and sex on immune phenotypes can be visualized at https://immune-aging.jax.org to provide insights into future studies., Whether the immune system aging differs between men and women is barely known. Here the authors characterize gene expression, chromatin state and immune subset composition in the blood of healthy humans 22 to 93 years of age, uncovering shared as well as sex-unique alterations, and create a web resource to interactively explore the data.

Genome-wide association studies (GWAS) have linked single nucleotide polymorphisms (SNPs) at >250 loci in the human genome to type 2 diabetes (T2D) risk. For each locus, identifying the functional variant(s) among multiple SNPs in high linkage disequilibrium is critical to understand molecular mechanisms underlying T2D genetic risk. Using massively parallel reporter assays (MPRA), we test the cis-regulatory effects of SNPs associated with T2D and altered in vivo islet chromatin accessibility in MIN6 β cells under steady state and pathophysiologic endoplasmic reticulum (ER) stress conditions. We identify 1,982/6,621 (29.9%) SNP-containing elements that activate transcription in MIN6 and 879 SNP alleles that modulate MPRA activity. Multiple T2D-associated SNPs alter the activity of short interspersed nuclear element (SINE)-containing elements that are strongly induced by ER stress. We identify 220 functional variants at 104 T2D association signals, narrowing 54 signals to a single candidate SNP. Together, this study identifies elements driving β cell steady state and ER stress-responsive transcriptional activation, nominates causal T2D SNPs, and uncovers potential roles for repetitive elements in β cell transcriptional stress response and T2D genetics., Identifying causal variants at GWAS loci is important to understand disease mechanisms. Here the authors use massively parallel reporter assays to identify type 2 diabetes-associated variants that alter cis-regulatory activity, narrowing in on the causal variants and genetic mechanisms behind the disease.

The precise identity of a tumour's cell of origin can influence disease prognosis and outcome. Methods to reliably define tumour cell of origin from primary, bulk tumour cell samples has been a challenge. Here we use a well-defined model of MLL-rearranged acute myeloid leukaemia (AML) to demonstrate that transforming haematopoietic stem cells (HSCs) and multipotent progenitors results in more aggressive AML than transforming committed progenitor cells. Transcriptome profiling reveals a gene expression signature broadly distinguishing stem cell-derived versus progenitor cell-derived AML, including genes involved in immune escape, extravasation and small GTPase signal transduction. However, whole-genome profiling of open chromatin reveals precise and robust biomarkers reflecting each cell of origin tested, from bulk AML tumour cell sampling. We find that bulk AML tumour cells exhibit distinct open chromatin loci that reflect the transformed cell of origin and suggest that open chromatin patterns may be leveraged as prognostic signatures in human AML., A tumour's cell of origin may influence tumour progression and response to therapy. Here, the authors demonstrate that the cell of origin determines the aggressiveness of AML in a mouse model and identify unique biomarkers of the specific leukaemia cell of origin by profiling open chromatin regions of AML samples.