BACKGROUND: Efficient presentation of mutant peptide fragments by the human leukocyte antigen class I (HLA-I) genes is necessary for immune-mediated killing of cancer cells. According to recent reports, patient HLA-I genotypes can impact the efficacy of cancer immunotherapy, and the somatic loss of HLA-I heterozygosity has been established as a factor in immune evasion. While global deregulated expression of HLA-I has also been reported in different tumor types, the role of HLA-I allele-specific expression loss - that is, the preferential RNA expression loss of specific HLA-I alleles - has not been fully characterized in cancer. METHODS: Here, we use RNA and whole-exome sequencing data to quantify HLA-I allele-specific expression (ASE) in cancer using our novel method arcasHLA-quant. RESULTS: We show that HLA-I ASE loss in at least one of the three HLA-I genes is a pervasive phenomenon across TCGA tumor types. In pancreatic adenocarcinoma, tumor-specific HLA-I ASE loss is associated with decreased overall survival specifically in the basal-like subtype, a finding that we validated in an independent cohort through laser-capture microdissection. Additionally, we show that HLA-I ASE loss is associated with poor immunotherapy outcomes in metastatic melanoma through retrospective analyses. CONCLUSIONS: Together, our results highlight the prevalence of HLA-I ASE loss and provide initial evidence of its clinical significance in cancer prognosis and immunotherapy treatment.

BACKGROUND: Epigenetic clocks can track both chronological age (cAge) and biological age (bAge). The latter is typically defined by physiological biomarkers and risk of adverse health outcomes, including all-cause mortality. As cohort sample sizes increase, estimates of cAge and bAge become more precise. Here, we aim to develop accurate epigenetic predictors of cAge and bAge, whilst improving our understanding of their epigenomic architecture. METHODS: First, we perform large-scale (N = 18,413) epigenome-wide association studies (EWAS) of chronological age and all-cause mortality. Next, to create a cAge predictor, we use methylation data from 24,674 participants from the Generation Scotland study, the Lothian Birth Cohorts (LBC) of 1921 and 1936, and 8 other cohorts with publicly available data. In addition, we train a predictor of time to all-cause mortality as a proxy for bAge using the Generation Scotland cohort (1214 observed deaths). For this purpose, we use epigenetic surrogates (EpiScores) for 109 plasma proteins and the 8 component parts of GrimAge, one of the current best epigenetic predictors of survival. We test this bAge predictor in four external cohorts (LBC1921, LBC1936, the Framingham Heart Study and the Women's Health Initiative study). RESULTS: Through the inclusion of linear and non-linear age-CpG associations from the EWAS, feature pre-selection in advance of elastic net regression, and a leave-one-cohort-out (LOCO) cross-validation framework, we obtain cAge prediction with a median absolute error equal to 2.3 years. Our bAge predictor was found to slightly outperform GrimAge in terms of the strength of its association to survival (HRGrimAge = 1.47 [1.40, 1.54] with p = 1.08 × 10-52, and HRbAge = 1.52 [1.44, 1.59] with p = 2.20 × 10-60). Finally, we introduce MethylBrowsR, an online tool to visualise epigenome-wide CpG-age associations. CONCLUSIONS: The integration of multiple large datasets, EpiScores, non-linear DNAm effects, and new approaches to feature selection has facilitated improvements to the blood-based epigenetic prediction of biological and chronological age.

BACKGROUND: TREM2 is a transmembrane receptor expressed by myeloid cells and acts to regulate their immune response. TREM2 governs the response of microglia to amyloid and tau pathologies in the Alzheimer's disease (AD) brain. TREM2 is also present in a soluble form (sTREM2), and its CSF levels fluctuate as a function of AD progression. Analysis of stroke and AD mouse models revealed that sTREM2 proteins bind to neurons, which suggests sTREM2 may act in a non-cell autonomous manner to influence neuronal function. sTREM2 arises from the proteolytic cleavage of the membrane-associated receptor. However, alternatively spliced TREM2 species lacking a transmembrane domain have been postulated to contribute to the pool of sTREM2. Thus, both the source of sTREM2 species and its actions in the brain remain unclear. METHODS: The expression of TREM2 isoforms in the AD brain was assessed through the analysis of the Accelerating Medicines Partnership for Alzheimer's Disease Consortium transcriptomics data, as well as qPCR analysis using post-mortem samples of AD patients and of the AD mouse model 5xFAD. TREM2 cleavage and secretion were studied in vitro using HEK-293T and HMC3 cell lines. Synaptic plasticity, as evaluated by induction of LTP in hippocampal brain slices, was employed as a measure of sTREM2 actions. RESULTS: Three distinct TREM2 transcripts, namely ENST00000373113 (TREM2230), which encodes the full-length transmembrane receptor, and the alternatively spliced isoforms ENST00000373122 (TREM2222) and ENST00000338469 (TREM2219), are moderately increased in specific brain regions of patients with AD. We provide experimental evidence that TREM2 alternatively spliced isoforms are translated and secreted as sTREM2. Furthermore, our functional analysis reveals that all sTREM2 species inhibit LTP induction, and this effect is abolished by the GABAA receptor antagonist picrotoxin. CONCLUSIONS: TREM2 transcripts can give rise to a heterogeneous pool of sTREM2 which acts to inhibit LTP. These results provide novel insight into the generation, regulation, and function of sTREM2 which fits into the complex biology of TREM2 and its role in human health and disease. Given that sTREM2 levels are linked to AD pathogenesis and progression, our finding that sTREM2 species interfere with LTP furthers our understanding about the role of TREM2 in AD.

BACKGROUND: Very low-coverage (0.1 to 1×) whole genome sequencing (WGS) has become a promising and affordable approach to discover genomic variants of human populations for genome-wide association study (GWAS). To support genetic screening using preimplantation genetic testing (PGT) in a large population, the sequencing coverage goes below 0.1× to an ultra-low level. However, the feasibility and effectiveness of ultra-low-coverage WGS (ulcWGS) for GWAS remains undetermined. METHODS: We built a pipeline to carry out analysis of ulcWGS data for GWAS. To examine its effectiveness, we benchmarked the accuracy of genotype imputation at the combination of different coverages below 0.1× and sample sizes from 2000 to 16,000, using 17,844 embryo PGT samples with approximately 0.04× average coverage and the standard Chinese sample HG005 with known genotypes. We then applied the imputed genotypes of 1744 transferred embryos who have gestational ages and complete follow-up records to GWAS. RESULTS: The accuracy of genotype imputation under ultra-low coverage can be improved by increasing the sample size and applying a set of filters. From 1744 born embryos, we identified 11 genomic risk loci associated with gestational ages and 166 genes mapped to these loci according to positional, expression quantitative trait locus, and chromatin interaction strategies. Among these mapped genes, CRHBP, ICAM1, and OXTR were more frequently reported as preterm birth related. By joint analysis of gene expression data from previous studies, we constructed interrelationships of mainly CRHBP, ICAM1, PLAGL1, DNMT1, CNTLN, DKK1, and EGR2 with preterm birth, infant disease, and breast cancer. CONCLUSIONS: This study not only demonstrates that ulcWGS could achieve relatively high accuracy of adequate genotype imputation and is capable of GWAS, but also provides insights into the associations between gestational age and genetic variations of the fetal embryos from Chinese population.

BACKGROUND: Klebsiella pneumoniae, which is frequently associated with hospital- and community-acquired infections, contains multidrug-resistant (MDR), hypervirulent (hv), non-MDR/non-hv as well as convergent representatives. It is known that mostly international high-risk clonal lineages including sequence types (ST) 11, 147, 258, and 307 drive their global spread. ST395, which was first reported in the context of a carbapenemase-associated outbreak in France in 2010, is a less well-characterized, yet emerging clonal lineage. METHODS: We computationally analyzed a large collection of K. pneumoniae ST395 genomes (n = 297) both sequenced in this study and reported previously. By applying multiple bioinformatics tools, we investigated the core-genome phylogeny and evolution of ST395 as well as distribution of accessory genome elements associated with antibiotic resistance and virulence features. RESULTS: Clustering of the core-SNP alignment revealed four major clades with eight smaller subclades. The subclades likely evolved through large chromosomal recombination, which involved different K. pneumoniae donors and affected, inter alia, capsule and lipopolysaccharide antigen biosynthesis regions. Most genomes contained acquired resistance genes to extended-spectrum cephalosporins, carbapenems, and other antibiotic classes carried by multiple plasmid types, and many were positive for hypervirulence markers, including the siderophore aerobactin. The detection of "hybrid" resistance and virulence plasmids suggests the occurrence of the convergent ST395 pathotype. CONCLUSIONS: To the best of our knowledge, this is the first study that investigated a large international collection of K. pneumoniae ST395 genomes and elucidated phylogenetics and detailed genomic characteristics of this emerging high-risk clonal lineage.