Springer Science and Business Media LLC

Emerging evidence from mouse models is beginning to elucidate the brain’s immune response to tau pathology, but little is known about the nature of this response in humans. In addition, it remains unclear to what extent tau pathology and the local inflammatory response within the brain influence the broader immune system. To address these questions, we performed single-cell RNA sequencing (scRNA-seq) of peripheral blood mononuclear cells (PBMCs) from carriers of pathogenic variants in MAPT, the gene encoding tau (n = 8), and healthy non-carrier controls (n = 8). Primary findings from our scRNA-seq analyses were confirmed and extended via flow cytometry, droplet digital (dd)PCR, and secondary analyses of publicly available transcriptomics datasets. Analysis of ~ 181,000 individual PBMC transcriptomes demonstrated striking differential expression in monocytes and natural killer (NK) cells in MAPT pathogenic variant carriers. In particular, we observed a marked reduction in the expression of CX3CR1—the gene encoding the fractalkine receptor that is known to modulate tau pathology in mouse models—in monocytes and NK cells. We also observed a significant reduction in the abundance of nonclassical monocytes and dysregulated expression of nonclassical monocyte marker genes, including FCGR3A. Finally, we identified reductions in TMEM176A and TMEM176B, genes thought to be involved in the inflammatory response in human microglia but with unclear function in peripheral monocytes. We confirmed the reduction in nonclassical monocytes by flow cytometry and the differential expression of select biologically relevant genes dysregulated in our scRNA-seq data using ddPCR. Our results suggest that human peripheral immune cell expression and abundance are modulated by tau-associated pathophysiologic changes. CX3CR1 and nonclassical monocytes in particular will be a focus of future work exploring the role of these peripheral signals in additional tau-associated neurodegenerative diseases.

There is strong evidence that genetic factors make substantial contributions to the etiology of autism, schizophrenia and bipolar disorders, with heritability estimates being at least 80% for each. These illnesses have complex inheritance, with multiple genetic and environmental factors influencing disease risk; however, in psychiatry, complex genetics is further compounded by phenotypic complexity. Autism, schizophrenia and bipolar disorder are effectively syndromic constellations of symptoms that define groups of patients with broadly similar outcomes and responses to treatment. As such the diagnostic categories are likely to be heterogeneous and the boundaries between them somewhat arbitrary. Recent applications of whole-genome technologies have discovered rare copy number variants and common single-nucleotide polymorphisms that are associated with risk of developing these disorders. Furthermore, these studies have shown an overlap between the genetic loci and even alleles that predispose to the different phenotypes. The findings have several implications. First, they show that copy number variations are likely to be important risk factors for autism and schizophrenia, whereas common single-nucleotide polymorphism alleles have a role in all disorders. Second, they imply that there are specific genetic loci and alleles that increase an individual's risk of developing any of these disorders. Finally, the findings suggest that some of the specific genetic loci implicated so far encode proteins, such as neurexins and neuroligins, that function in synaptic development and plasticity, and therefore may represent a common biological pathway for these disorders.

Mutations in KRAS are frequent in human cancer, yet effective targeted therapeutics for these cancers are still lacking. Attempts to drug the MEK kinases downstream of KRAS have had limited success in clinical trials. Understanding the specific genomic vulnerabilities of KRAS-driven cancers may uncover novel patient-tailored treatment options. We first searched for synthetic lethal (SL) genetic interactions with mutant RAS in yeast with the ultimate aim to identify novel cancer-specific targets for therapy. Our method used selective ploidy ablation, which enables replication of cancer-specific gene expression changes in the yeast gene disruption library. Second, we used a genome-wide CRISPR/Cas9-based genetic screen in KRAS mutant human colon cancer cells to understand the mechanistic connection between the synthetic lethal interaction discovered in yeast and downstream RAS signaling in human cells. We identify loss of the endoplasmic reticulum (ER) stress sensor IRE1 as synthetic lethal with activated RAS mutants in yeast. In KRAS mutant colorectal cancer cell lines, genetic ablation of the human ortholog of IRE1, ERN1, does not affect growth but sensitizes to MEK inhibition. However, an ERN1 kinase inhibitor failed to show synergy with MEK inhibition, suggesting that a non-kinase function of ERN1 confers MEK inhibitor resistance. To investigate how ERN1 modulates MEK inhibitor responses, we performed genetic screens in ERN1 knockout KRAS mutant colon cancer cells to identify genes whose inactivation confers resistance to MEK inhibition. This genetic screen identified multiple negative regulators of JUN N-terminal kinase (JNK) /JUN signaling. Consistently, compounds targeting JNK/MAPK8 or TAK1/MAP3K7, which relay signals from ERN1 to JUN, display synergy with MEK inhibition. We identify the ERN1-JNK-JUN pathway as a novel regulator of MEK inhibitor response in KRAS mutant colon cancer. The notion that multiple signaling pathways can activate JUN may explain why KRAS mutant tumor cells are traditionally seen as highly refractory to MEK inhibitor therapy. Our findings emphasize the need for the development of new therapeutics targeting JUN activating kinases, TAK1 and JNK, to sensitize KRAS mutant cancer cells to MEK inhibitors.

Advances in mass spectrometry have had a great impact on the field of proteomics. A major challenge of proteomic analysis has been the elucidation of glycan modifications of proteins in complex proteomes. Glycosylation is the most structurally elaborate and diverse type of protein post-translational modification and, because of this, proteomics and glycomics have largely developed independently. However, given that such a large proportion of proteins contain glycan modifications, and that these may be important for their function or may produce biologically relevant protein variation, a convergence of the fields of glycomics and proteomics would be highly desirable. Here we review the current status of glycoproteomic efforts, focusing on the identification of glycoproteins as cancer biomarkers.

We discuss the current state of genomic medicine in Arab countries of the Middle East, a region with outsized contribution to Mendelian genetics due to inbreeding yet has poor representation in global variome datasets. We focus on genomic testing, clinical genetics, and genetic counseling services along with associated training and research programs. Finally, we highlight opportunities for improvement in genomic medicine services in this region.

As public health interventions drive parasite populations to elimination, genetic epidemiology models that incorporate population genomics can be powerful tools for evaluating the effectiveness of continued intervention. However, current genetic epidemiology models may not accurately simulate the population genetic profile of parasite populations, particularly with regard to polygenomic (multi-strain) infections. Current epidemiology models simulate polygenomic infections via superinfection (multiple mosquito bites), despite growing evidence that cotransmission (a single mosquito bite) may contribute to polygenomic infections. Here, we quantified the relatedness of strains within 31 polygenomic infections collected from patients in Thiès, Senegal using a hidden Markov model to measure the proportion of the genome that is inferred to be identical by descent. We found that polygenomic infections can be composed of highly related parasites and that superinfection models drastically underestimate the relatedness of strains within polygenomic infections. Our findings suggest that cotransmission is a major contributor to polygenomic infections in Thiès, Senegal. The incorporation of cotransmission into existing genetic epidemiology models may enhance our ability to characterize and predict changes in population structure associated with reduced transmission intensities and the emergence of important phenotypes like drug resistance that threaten to undermine malaria elimination activities.