Genetic Ancestry and Natural Selection Drive Population Differences in Immune Responses to Pathogens.

Individuals from different populations vary considerably in their susceptibility to immune-related diseases. To understand how genetic variation and natural selection contribute to these differences, we tested for the effects of African versus European ancestry on the transcriptional response of primary macrophages to live bacterial pathogens. A total of 9.3% of macrophage-expressed genes show ancestry-associated differences in the gene regulatory response to infection, and African ancestry specifically predicts a stronger inflammatory response and reduced intracellular bacterial growth. A large proportion of these differences are under genetic control: for 804 genes, more than 75% of ancestry effects on the immune response can be explained by a single cis- or trans-acting expression quantitative trait locus (eQTL). Finally, we show that genetic effects on the immune response are strongly enriched for recent, population-specific signatures of adaptation. Together, our results demonstrate how historical selective events continue to shape human phenotypic diversity today, including for traits that are key to controlling infection.

Dissecting human population variation in single-cell responses to SARS-CoV-2.

Humans display substantial interindividual clinical variability after SARS-CoV-2 infection1-3, the genetic and immunological basis of which has begun to be deciphered4. However, the extent and drivers of population differences in immune responses to SARS-CoV-2 remain unclear. Here we report single-cell RNA-sequencing data for peripheral blood mononuclear cells-from 222 healthy donors of diverse ancestries-that were stimulated with SARS-CoV-2 or influenza A virus. We show that SARS-CoV-2 induces weaker, but more heterogeneous, interferon-stimulated gene activity compared with influenza A virus, and a unique pro-inflammatory signature in myeloid cells. Transcriptional responses to viruses display marked population differences, primarily driven by changes in cell abundance including increased lymphoid differentiation associated with latent cytomegalovirus infection. Expression quantitative trait loci and mediation analyses reveal a broad effect of cell composition on population disparities in immune responses, with genetic variants exerting a strong effect on specific loci. Furthermore, we show that natural selection has increased population differences in immune responses, particularly for variants associated with SARS-CoV-2 response in East Asians, and document the cellular and molecular mechanisms by which Neanderthal introgression has altered immune functions, such as the response of myeloid cells to viruses. Finally, colocalization and transcriptome-wide association analyses reveal an overlap between the genetic basis of immune responses to SARS-CoV-2 and COVID-19 severity, providing insights into the factors contributing to current disparities in COVID-19 risk.

Comprehensive analysis of the functional impact of single nucleotide variants of human CHEK2.

Loss of function mutations in the checkpoint kinase gene CHEK2 are associated with increased risk of breast and other cancers. Most of the 3,188 unique amino acid changes that can result from non-synonymous single nucleotide variants (SNVs) of CHEK2, however, have not been tested for their impact on the function of the CHEK2-enocded protein (CHK2). One successful approach to testing the function of variants has been to test for their ability to complement mutations in the yeast ortholog of CHEK2, RAD53. This approach has been used to provide functional information on over 100 CHEK2 SNVs and the results align with functional assays in human cells and known pathogenicity. Here we tested all but two of the 4,887 possible SNVs in the CHEK2 open reading frame for their ability to complement RAD53 mutants using a high throughput technique of deep mutational scanning (DMS). Among the non-synonymous changes, 770 were damaging to protein function while 2,417 were tolerated. The results correlate well with previous structure and function data and provide a first or additional functional assay for all the variants of uncertain significance identified in clinical databases. Combined, this approach can be used to help predict the pathogenicity of CHEK2 variants of uncertain significance that are found in susceptibility screening and could be applied to other cancer risk genes.

Probabilistic integration of transcriptome-wide association studies and colocalization analysis identifies key molecular pathways of complex traits.

Integrative genetic association methods have shown great promise in post-GWAS (genome-wide association study) analyses, in which one of the most challenging tasks is identifying putative causal genes and uncovering molecular mechanisms of complex traits. Recent studies suggest that prevailing computational approaches, including transcriptome-wide association studies (TWASs) and colocalization analysis, are individually imperfect, but their joint usage can yield robust and powerful inference results. This paper presents INTACT, a computational framework to integrate probabilistic evidence from these distinct types of analyses and implicate putative causal genes. This procedure is flexible and can work with a wide range of existing integrative analysis approaches. It has the unique ability to quantify the uncertainty of implicated genes, enabling rigorous control of false-positive discoveries. Taking advantage of this highly desirable feature, we further propose an efficient algorithm, INTACT-GSE, for gene set enrichment analysis based on the integrated probabilistic evidence. We examine the proposed computational methods and illustrate their improved performance over the existing approaches through simulation studies. We apply the proposed methods to analyze the multi-tissue eQTL data from the GTEx project and eight large-scale complex- and molecular-trait GWAS datasets from multiple consortia and the UK Biobank. Overall, we find that the proposed methods markedly improve the existing putative gene implication methods and are particularly advantageous in evaluating and identifying key gene sets and biological pathways underlying complex traits.

Genetic control of the dynamic transcriptional response to immune stimuli and glucocorticoids at single-cell resolution.

Synthetic glucocorticoids, such as dexamethasone, have been used as a treatment for many immune conditions, such as asthma and, more recently, severe COVID-19. Single-cell data can capture more fine-grained details on transcriptional variability and dynamics to gain a better understanding of the molecular underpinnings of inter-individual variation in drug response. Here, we used single-cell RNA-seq to study the dynamics of the transcriptional response to glucocorticoids in activated peripheral blood mononuclear cells from 96 African American children. We used novel statistical approaches to calculate a mean-independent measure of gene expression variability and a measure of transcriptional response pseudotime. Using these approaches, we showed that glucocorticoids reverse the effects of immune stimulation on both gene expression mean and variability. Our novel measure of gene expression response dynamics, based on the diagonal linear discriminant analysis, separated individual cells by response status on the basis of their transcriptional profiles and allowed us to identify different dynamic patterns of gene expression along the response pseudotime. We identified genetic variants regulating gene expression mean and variability, including treatment-specific effects, and showed widespread genetic regulation of the transcriptional dynamics of the gene expression response.

Analyzing and reconciling colocalization and transcriptome-wide association studies from the perspective of inferential reproducibility.

Transcriptome-wide association studies and colocalization analysis are popular computational approaches for integrating genetic-association data from molecular and complex traits. They show the unique ability to go beyond variant-level genetic-association evidence and implicate critical functional units, e.g., genes, in disease etiology. However, in practice, when the two approaches are applied to the same molecular and complex-trait data, the inference results can be markedly different. This paper systematically investigates the inferential reproducibility between the two approaches through theoretical derivation, numerical experiments, and analyses of four complex trait GWAS and GTEx eQTL data. We identify two classes of inconsistent inference results. We find that the first class of inconsistent results (i.e., genes with strong colocalization but weak transcriptome-wide association study [TWAS] signals) might suggest an interesting biological phenomenon, i.e., horizontal pleiotropy; thus, the two approaches are truly complementary. The inconsistency in the second class (i.e., genes with weak colocalization but strong TWAS signals) can be understood and effectively reconciled. To this end, we propose a computational approach for locus-level colocalization analysis. We demonstrate that the joint TWAS and locus-level colocalization analysis improves specificity and sensitivity for implicating biologically relevant genes.

MIMESIS: minimal DNA-methylation signatures to quantify and classify tumor signals in tissue and cell-free DNA samples.

DNA-methylation alterations are common in cancer and display unique characteristics that make them ideal markers for tumor quantification and classification. Here we present MIMESIS, a computational framework exploiting minimal DNA-methylation signatures composed by a few dozen informative DNA-methylation sites to quantify and classify tumor signals in tissue and cell-free DNA samples. Extensive analyses of multiple independent and heterogenous datasets including >7200 samples demonstrate the capability of MIMESIS to provide precise estimations of tumor content and to enable accurate classification of tumor type and molecular subtype. To assess our framework for clinical applications, we designed a MIMESIS-informed assay incorporating the minimal signatures for breast cancer. Using both artificial samples and clinical serial cell-free DNA samples from patients with metastatic breast cancer, we show that our approach provides accurate estimations of tumor content, sensitive detection of tumor signal and the ability to capture clinically relevant molecular subtype in patients' circulation. This study provides evidence that our extremely parsimonious approach can be used to develop cost-effective and highly scalable DNA-methylation assays that could support and facilitate the implementation of precision oncology in clinical practice.

Probabilistic colocalization of genetic variants from complex and molecular traits: promise and limitations.

Colocalization analysis has emerged as a powerful tool to uncover the overlapping of causal variants responsible for both molecular and complex disease phenotypes. The findings from colocalization analysis yield insights into the molecular pathways of complex diseases. In this paper, we conduct an in-depth investigation of the promise and limitations of the available colocalization analysis approaches. Focusing on variant-level colocalization approaches, we first establish the connections between various existing methods. We proceed to discuss the impacts of various controllable analytical factors and uncontrollable practical factors on outcomes of colocalization analysis through realistic simulations and real data examples. We identify a single analytical factor, the specification of prior enrichment levels, which can lead to severe inflation of false-positive colocalization findings. Meanwhile, the combination of many other analytical and practical factors all lead to diminished power. Consequently, we recommend the following strategies for the best practice of colocalization analysis: (1) estimating prior enrichment level from the observed data and (2) separating fine-mapping and colocalization analysis. Our analysis of 4,091 complex traits and the multi-tissue expression quantitative trait loci (eQTL) data from the GTEx (v.8) suggests that colocalizations of molecular QTLs and causal complex trait associations are widespread. However, only a small proportion can be confidently identified from currently available data due to a lack of power. Our findings set a benchmark for current and future integrative genetic association analysis applications.

A pilocytic astrocytoma with novel ATG16L1::NTRK2 fusion responsive to larotrectinib: a case report with genomic and functional analysis.

The outcome of pilocytic astrocytoma (PA) depends heavily on the success of surgery. In cases where surgery alone is not curative, genetic analysis can be used to identify treatment targets for precision medicine. Here, we report a pediatric PA case that underwent incomplete surgical resection due to the tumor location. Clinical routine analyses demonstrated that the tumor did not carry any BRAF alteration. After postoperative surveillance, according to the low-grade glioma (LGG) protocol, recurrent tumor progressions resulted in multiple chemotherapy regimens. Screening formalin-fixed paraffin-embedded tumor material using an open-ended RNA sequencing panel revealed a novel in-frame autophagy related 16 like 1-neurotrophic receptor tyrosine kinase 2 (ATG16L1::NTRK2) fusion gene. The NTRK2 rearrangement was subsequently confirmed by fluorescent in situ hybridization on tumor tissue sections. Functional validation was performed by in vitro transient transfection of HEK293 cells and showed the ATG16L1::TRKB fusion protein to activate both the mitogen-activated protein kinase pathway and the phosphoinositide 3-kinase oncogenic pathways through increased phosphorylation of extracellular signal-regulated kinase, AKT, and S6. As a result of the identification of the NTRK fusion, the patient was enrolled in a phase I/II clinical trial of the highly selective TRK inhibitor larotrectinib. The patient responded well without significant side effects, and 8 months after the start of treatment, the contrast-enhancing tumor lesions were no longer detectable, consistent with a complete response as per Response Assessment in Neuro-Oncology (RANO) criteria. Presently, after 22 months of treatment, the patient's complete remission is sustained. Our findings highlight the importance of screening for other oncogenic drivers in BRAF-negative LGGs since rare fusion genes may serve as targets for precision oncology therapy.

2.5-Minute Fast Brain MRI with Multiple Contrasts in Acute Ischemic Stroke.

PURPOSE: To assess the performance of a 2.5-minute multi-contrast brain MRI sequence (NeuroMix) in diagnosing acute cerebral infarctions. METHODS: Adult patients with a clinical suspicion of acute ischemic stroke were retrospectively included. Brain MRI at 3 T included NeuroMix and routine clinical MRI (cMRI) sequences, with DWI/ADC, T2-FLAIR, T2-weighted, T2*, SWI-EPI, and T1-weighted contrasts. Three radiologists (R1-3) independently assessed NeuroMix and cMRI for the presence of acute infarcts (DWI ↑, ADC = or ↓) and infarct-associated abnormalities on other image contrasts. Sensitivity, specificity, and the area under the receiver operating characteristic curve (AUC) were calculated and compared using DeLong's test. Inter- and intra-rater agreements were studied with kappa statistics. Relative DWI (rDWI) and T2-FLAIR (rT2-FLAIR) signal intensity for infarctions were semi-automatically rendered, and the correlation between methods was evaluated. RESULTS: According to the reference standard, acute infarction was present in 34 out of 44 (77%) patients (63 ± 17 years, 31 men). Other infarct-associated signal abnormalities were reported in similar frequencies on NeuroMix and cMRI (p > .08). Sensitivity for infarction detection was 94%, 100%, and 94% evaluated by R1, R2, R3, for NeuroMix and 94%, 100%, and 100% for cMRI. Specificity was 100%, 90%, and 100% for NeuroMix and 100%, 100%, and 100% for cMRI. AUC for NeuroMix was .97, .95, and .97 and .97, 1, and 1 for cMRI (DeLong p = 1, .32, .15), respectively. Inter- and intra-rater agreement was κ = .88-1. The correlation between NeuroMix and cMRI was R = .73 for rDWI and R = .83 for rT2-FLAIR. CONCLUSION: Fast multi-contrast MRI NeuroMix has high diagnostic performance for detecting acute cerebral infarctions.

Elective one-minute full brain multi-contrast MRI versus brain CT in pediatric patients: a prospective feasibility study.

BACKGROUND: Brain CT can be used to evaluate pediatric patients with suspicion of cerebral pathology when anesthetic and MRI resources are scarce. This study aimed to assess if pediatric patients referred for an elective brain CT could endure a diagnostic fast brain MRI without general anesthesia using a one-minute multi-contrast EPI-based sequence (EPIMix) with comparable diagnostic performance. METHODS: Pediatric patients referred for an elective brain CT between March 2019 and March 2020 were prospectively included and underwent EPIMix without general anesthesia in addition to CT. Three readers (R1-3) independently evaluated EPIMix and CT images on two separate occasions. The two main study outcomes were the tolerance to undergo an EPIMix scan without general anesthesia and its performance to classify a scan as normal or abnormal. Secondary outcomes were assessment of disease category, incidental findings, diagnostic image quality, diagnostic confidence, and image artifacts. Further, a side-by-side evaluation of EPIMix and CT was performed. The signal-to-noise ratio (SNR) was calculated for EPIMix on T1-weighted, T2-weighted, and ADC images. Descriptive statistics, Fisher's exact test, and Chi-squared test were used to compare the two imaging modalities. RESULTS: EPIMix was well tolerated by all included patients (n = 15) aged 5-16 (mean 11, SD 3) years old. Thirteen cases on EPIMix and twelve cases on CT were classified as normal by all readers (R1-3), while two cases on EPIMix and three cases on CT were classified as abnormal by one reader (R1), (R1-3, p = 1.00). There was no evidence of a difference in diagnostic confidence, image quality, or the presence of motion artifacts between EPIMix and CT (R1-3, p ≥ 0.10). Side-by-side evaluation (R2 + R4 + R5) reviewed all scans as lacking significant pathological findings on EPIMix and CT images. CONCLUSIONS: Full brain MRI-based EPIMix sequence was well tolerated without general anesthesia with a diagnostic performance comparable to CT in elective pediatric patients. TRIAL REGISTRATION: This study was approved by the Swedish Ethical Review Authority (ethical approval number/ID Ethical approval 2017/2424-31/1). This study was a clinical trial study, with study protocol published at ClinicalTrials.gov with Trial registration number NCT03847051, date of registration 18/02/2019.

A signature of Neanderthal introgression on molecular mechanisms of environmental responses.

Ancient human migrations led to the settlement of population groups in varied environmental contexts worldwide. The extent to which adaptation to local environments has shaped human genetic diversity is a longstanding question in human evolution. Recent studies have suggested that introgression of archaic alleles in the genome of modern humans may have contributed to adaptation to environmental pressures such as pathogen exposure. Functional genomic studies have demonstrated that variation in gene expression across individuals and in response to environmental perturbations is a main mechanism underlying complex trait variation. We considered gene expression response to in vitro treatments as a molecular phenotype to identify genes and regulatory variants that may have played an important role in adaptations to local environments. We investigated if Neanderthal introgression in the human genome may contribute to the transcriptional response to environmental perturbations. To this end we used eQTLs for genes differentially expressed in a panel of 52 cellular environments, resulting from 5 cell types and 26 treatments, including hormones, vitamins, drugs, and environmental contaminants. We found that SNPs with introgressed Neanderthal alleles (N-SNPs) disrupt binding of transcription factors important for environmental responses, including ionizing radiation and hypoxia, and for glucose metabolism. We identified an enrichment for N-SNPs among eQTLs for genes differentially expressed in response to 8 treatments, including glucocorticoids, caffeine, and vitamin D. Using Massively Parallel Reporter Assays (MPRA) data, we validated the regulatory function of 21 introgressed Neanderthal variants in the human genome, corresponding to 8 eQTLs regulating 15 genes that respond to environmental perturbations. These findings expand the set of environments where archaic introgression may have contributed to adaptations to local environments in modern humans and provide experimental validation for the regulatory function of introgressed variants.

11C-methionine PET/MRI in postoperative patients after craniotomy: zero echo time and head atlas versus CT-based attenuation correction.

BACKGROUND: Attenuation correction (AC) is an important topic in PET/MRI and particularly challenging after brain tumor surgery, near metal implants, adjacent bone and burr holes. In this study, we evaluated the performance of two MR-driven AC methods, zero-echo-time AC (ZTE-AC) and atlas-AC, in comparison to reference standard CT-AC in patients with surgically treated brain tumors at 11C-methionine PET/MRI. METHODS: This retrospective study investigated seven postoperative patients with neuropathologically confirmed brain tumor at 11C-methionine PET/MRI. Three AC maps - ZTE-AC, atlas-AC and reference standard CT-AC - were generated for each patient. Standardized uptake values (SUV) were obtained at the metal implant, adjacent bone and burr hole. Standard uptake ratio (SUR) SURmetal/mirror, SURbone/mirror and SURburrhole/mirror were then calculated and analyzed with Bland-Altman, Pearson correlation and intraclass correlation reliability. RESULTS: Smaller mean percent bias range (Bland-Altman) was found for ZTE-AC than atlas-AC in all analyses (metal ZTE -0.46 to -0.02, metal atlas -3.57 to -3.26; bone ZTE -4.60 to -2.16, bone atlas -5.25 to -3.81; burr hole ZTE -0.95 to -0.52, burr hole atlas 7.86 to 8.87). Percent SD range (Bland-Altman) was large for both methods in all analyses, with lower absolute values for ZTE-AC (ZTE 7.02-8.49; atlas 11.47-14.83). A very strong correlation (Pearson correlation) was demonstrated for both methods compared to CT-AC (ZTE ρ 0.97-0.99, P<0.001; atlas ρ 0.88-0.91, P≤0.009) with higher absolute values for ZTE. An excellent intraclass correlation coefficient was found across all analyses for ZTE, atlas and CT maps (ICC ≥0.88). CONCLUSIONS: ZTE for MR-driven PET attenuation correction presented a more comparable performance to reference standard CT-AC at the postoperative site. ZTE-AC may serve as a useful diagnostic tool for MR-driven AC in patients with surgically treated brain tumors.

The heart of Detroit study: a window into urban middle-aged and older African Americans' daily lives to understand psychosocial determinants of cardiovascular disease risk.

BACKGROUND: Cardiovascular disease disproportionately affects African Americans. Psychosocial factors, including the experience of and emotional reactivity to racism and interpersonal stressors, contribute to the etiology and progression of cardiovascular disease through effects on health behaviors, stress-responsive neuroendocrine axes, and immune processes. The full pathway and complexities of these associations remain underexamined in African Americans. The Heart of Detroit Study aims to identify and model the biopsychosocial pathways that influence cardiovascular disease risk in a sample of urban middle-aged and older African American adults. METHODS: The proposed sample will be composed of 500 African American adults between the ages of 55 and 75 from the Detroit urban area. This longitudinal study will consist of two waves of data collection, two years apart. Biomarkers of stress, inflammation, and cardiovascular surrogate endpoints (i.e., heart rate variability and blood pressure) will be collected at each wave. Ecological momentary assessments will characterize momentary and daily experiences of stress, affect, and health behaviors during the first wave. A proposed subsample of 60 individuals will also complete an in-depth qualitative interview to contextualize quantitative results. The central hypothesis of this project is that interpersonal stressors predict poor cardiovascular outcomes, cumulative physiological stress, poor sleep, and inflammation by altering daily affect, daily health behaviors, and daily physiological stress. DISCUSSION: This study will provide insight into the biopsychosocial pathways through which experiences of stress and discrimination increase cardiovascular disease risk over micro and macro time scales among urban African American adults. Its discoveries will guide the design of future contextualized, time-sensitive, and culturally tailored behavioral interventions to reduce racial disparities in cardiovascular disease risk.

A 78 Seconds Complete Brain MRI Examination in Ischemic Stroke: A Prospective Cohort Study.

BACKGROUND: Fast 78-second multicontrast echo-planar MRI (EPIMix) has shown good diagnostic performance for detecting infarctions at a comprehensive stroke center, but its diagnostic performance has not been evaluated in a prospective study at a primary stroke center. PURPOSE: To prospectively determine whether EPIMix was noninferior in detecting ischemic lesions compared to routine clinical MRI. STUDY TYPE: Prospective cohort study. POPULATION: A total of 118 patients with acute MRI and symptoms of ischemic stroke. FIELD STRENGTH AND SEQUENCE: A 3 T. EPIMix (echo-planar based: T1-FLAIR, T2-weighted, T2-FLAIR, T2*, DWI) and routine clinical MRI sequences (T1-weighted fast spin echo, T2-weighted PROPELLER, T2-weighted-FLAIR fast spin echo, T2* gradient echo echo-planar, and DWI spin echo echo-planar). ASSESSMENT: Three radiologists, blinded for clinical information, assessed signs of ischemic lesions (DWI↑, ADC↓, and T2/T2-FLAIR↑) on EPIMix and routine clinical MRI, with disagreements solved in consensus with a fourth reader to establish the reference standard. STATISTICAL TESTS: Diagnostic performance including sensitivity and specificity against the reference standard was evaluated. EPIMix sensitivity was tested for noninferiority compared to the reference standard using Nam's restricted maximum likelihood estimation (RMLE) Score. A P-value < 0.05 was considered statistically significant. RESULTS: Of 118 patients (mean age 62 ± 16 years, 58% males), 25% (n = 30) had MRI signs of acute infarcts. EPIMix was noninferior with 97% (95% CI 83-100) sensitivity for reader 1, 100% (95% CI 88-100) sensitivity for reader 2, and 90% (95% CI 88-98) sensitivity for reader 3 vs. 93% (95% CI 78-99) sensitivity for readers 1 and 2 and 90% (95% CI 74-98) for reader 3 on routine clinical MRI. Specificity was 99% (95% CI 94-100) for reader 1, 100% (95% CI 96-100) for reader 2, and 98% (95% CI 92-100) for reader 3 on EPIMix vs. 100% (95% CI 96-100) for all readers on routine clinical MRI. CONCLUSION: EPIMix was noninferior to routine clinical MRI for the diagnosis of acute ischemic stroke. EVIDENCE LEVEL: 2 TECHNICAL EFFICACY: Stage 2.

A comparative study on the incidence of type 1 diabetes mellitus between children of North African migrants and Italian children in Emilia-Romagna region, Italy.

In the last few decades, many studies have reported an increasing global incidence of type 1 diabetes. Studies on migrant populations have underlined the importance of both environmental and genetic factors. AIMS: Evaluate the incidence of type 1 diabetes in North African vs Italian children aged 0-14 years from 1 January 2015, to 31st December 2018, in Emilia-Romagna region, Italy. METHODS: Clinical and epidemiological data about childhood onset type 1 diabetes in Emilia Romagna region were retrospectively collected by the regional centers of pediatric diabetology and matched using 3 different data sources. RESULTS: 365 new cases were diagnosed. Total cumulative incidence was 15.4/100,000/year. North African cases showed a cumulative incidence of 53.8/100,000/year, statistically significant compared to cumulative incidence of the Italian cases alone 13.1/100,000/year (p value < 0.001). The annual incidence did not differ in the 4 years for both groups.  Conclusion: The incidence of type 1 diabetes in the pediatric age (0 14 years) was significantly higher in the North African population than in the Italian one, suggesting that a mix of genetic and environmental factors may have caused the increase in newly diagnosed cases. WHAT IS KNOWN: • The incidence of type 1 diabetes largely varies worldwide. • Study on immigrants helped to better understand the interplay role between genetics and environment. WHAT IS NEW: • This is the first study focused on the incidence of children and adolescents of North African migrants in Italy. • The incidence of children and adolescents of North African migrants in Emilia Romagna region, Italy, seems to be higher than that reported in the host countries, and, above all, than that reported in highest-incidence countries in Europe and in the world.

It is not always positive: emotional bias in young and older adults.

Healthy ageing has been associated with a bias toward positive information and greater psychological well-being. However, to what extent this positivity bias also applies to prioritizing positive information under emotional competition is unclear. Old and young adults performed a word-face interference task, in which they responded to the valence of positive and negative target-words while ignoring happy or angry distractor-faces that could be affectively congruent or incongruent. A control condition with scrambled neutral distractor-faces was also used. Findings showed small facilitation effects with faster responses when targets and distractors were affectively congruent and large interference effects with slower responses when targets and distractors were affectively incongruent compared to the control condition. Importantly, whereas for younger adults there was a similar pattern of interference from happy and angry distractor-faces, for older adults there was greater interference from angry distractor-faces. The present findings are discussed in the context of emotional bias literature.

Molecular Phylogenetic Characterization of Anguina Tritici (Steinbuch, 1799) Filipjev, 1936 (Rhabditida: Anguinidae) on Barley from Iraq.

During a nematological survey in Iraq, in the Bashika area, Ninevah province, an anguinid nematode population was isolated from galls of infected barley plants. The morphological characteristics indicated that the recovered species is identical to Anguina tritici. The barley population of A. tritici was molecularly characterized by sequencing two ribosomal regions (ITS and 18S rRNA genes), and their phylogenetic analyses revealed the newly generated sequences are in sister relation to corresponding sequences of A. tritici from wheat in the Bayesian tree, providing further evidence that the host plant can contribute to the separation of new isolates of plant parasitic nematodes.

Circulating tumor cells and palbociclib treatment in patients with ER-positive, HER2-negative advanced breast cancer: results from a translational sub-study of the TREnd trial.

BACKGROUND: Circulating tumor cells (CTCs) are prognostic in patients with advanced breast cancer (ABC). However, no data exist about their use in patients treated with palbociclib. We analyzed the prognostic role of CTC counts in patients enrolled in the cTREnd study, a pre-planned translational sub-study of TREnd (NCT02549430), that randomized patients with ABC to palbociclib alone or palbociclib plus the endocrine therapy received in the prior line of treatment. Moreover, we evaluated RB1 gene expression on CTCs and explored its prognostic role within the cTREnd subpopulation. METHODS: Forty-six patients with ER-positive, HER2-negative ABC were analyzed. Blood samples were collected before starting palbociclib treatment (timepoint T0), after the first cycle of treatment (timepoint T1), and at disease progression (timepoint T2). CTCs were isolated and counted by CellSearch® System using the CellSearch™Epithelial Cell kit. Progression-free survival (PFS), clinical benefit (CB) during study treatment, and time to treatment failure (TTF) after study treatment were correlated with CTC counts. Samples with ≥ 5 CTCs were sorted by DEPArray system® (DA). RB1 and GAPDH gene expression levels were measured by ddPCR. RESULTS: All 46 patients were suitable for CTCs analysis. CTC count at T0 did not show significant prognostic value in terms of PFS and CB. Patients with at least one detectable CTC at T1 (n = 26) had a worse PFS than those with 0 CTCs (n = 16) (p = 0.02). At T1, patients with an increase of at least three CTCs showed reduced PFS compared to those with no increase (mPFS = 3 versus 9 months, (p = 0.004). Finally, patients with ≥ 5 CTCs at T2 (n = 6/23) who received chemotherapy as post-study treatment had a shorter TTF (p = 0.02). Gene expression data for RB1 were obtained from 19 patients. CTCs showed heterogeneous RB1 expression. Patients with detectable expression of RB1 at any timepoint showed better, but not statistically significant, outcomes than those with undetectable levels. CONCLUSIONS: CTC count seems to be a promising modality in monitoring palbociclib response. Moreover, CTC count at the time of progression could predict clinical outcome post-palbociclib. RB1 expression analysis on CTCs is feasible and may provide additional prognostic information. Results should be interpreted with caution given the small studied sample size.

Functional Genomics of Host-Microbiome Interactions in Humans.

The human microbiome has been linked to various host phenotypes and has been implicated in many complex human diseases. Recent genome-wide association studies (GWASs) have used microbiome variation as a complex trait and have uncovered human genetic variants that are associated with the microbiome. Here we summarize results from these studies and illustrate potential regulatory mechanisms by which host genetic variation can interact with microbiome composition. We argue that, similar to human GWASs, it is important to use functional genomics techniques to gain a mechanistic understanding of causal host-microbiome interactions and their role in human disease. We highlight experimental, functional, and computational genomics methodologies for the study of the genomic basis of host-microbiome interactions and describe how these approaches can be utilized to explain how human genetic variation can modulate the effects of the microbiome on the host.