Acid sensing ion channel 2: A new potential player in the pathophysiology of multiple sclerosis

Acid-sensing ion channels (ASICs) are proton-gated channels involved in multiple biological functions such as: pain modulation, mechanosensation, neurotransmission, and neurodegeneration. Earlier, we described the genetic association, within the Nuoro population, between Multiple Sclerosis (MS) and rs28936, located in ASIC2 3′UTR. Here we investigated the potential involvement of ASIC2 in MS inflammatory process. We induced experimental autoimmune encephalomyelitis (EAE) in wild-type (WT), knockout Asic1 −/− and Asic2 −/− mice and observed a significant reduction of clinical score in Asic1 −/− mice and a significant reduction in the clinical score in Asic2 −/− mice in a limited time window (i.e., at days 20–23 after immunization). Immunohistochemistry confirmed the reduction in adaptive immune cell infiltrates in the spinal cord of EAE Asic1 −/− mice. Analysis of mechanical allodynia, showed a significant higher pain threshold in Asic2 −/− mice under physiological conditions, before immunization, as compared to WT mice and Asic1 −/−. A significant reduction in pain threshold was observed in all three strains of mice after immunization. More importantly, analysis of human autoptic brain tissue in MS and control samples showed an increase of ASIC2 mRNA in MS samples. Subsequently, in vitro luciferase reporter gene assays, showed that ASIC2 expression is under possible miRNA regulation, in a rs28936 allele-specific manner. Taken together, these findings suggest a potential role of ASIC2 in the pathophysiology of MS

Genetic Determinants of Lipids and Cardiovascular Disease Outcomes: A Wide-Angled Mendelian Randomization Investigation.

BACKGROUND: Evidence from randomized trials has shown that therapies that lower LDL (low-density lipoprotein)-cholesterol and triglycerides reduce coronary artery disease (CAD) risk. However, there is still uncertainty about their effects on other cardiovascular outcomes. We therefore performed a systematic investigation of causal relationships between circulating lipids and cardiovascular outcomes using a Mendelian randomization approach. METHODS: In the primary analysis, we performed 2-sample multivariable Mendelian randomization using data from participants of European ancestry. We also conducted univariable analyses using inverse-variance weighted and robust methods, and gene-specific analyses using variants that can be considered as proxies for specific lipid-lowering medications. We obtained associations with lipid fractions from the Global Lipids Genetics Consortium, a meta-analysis of 188 577 participants, and genetic associations with cardiovascular outcomes from 367 703 participants in UK Biobank. RESULTS: For LDL-cholesterol, in addition to the expected positive associations with CAD risk (odds ratio [OR] per 1 SD increase, 1.45 [95% CI, 1.35-1.57]) and other atheromatous outcomes (ischemic cerebrovascular disease and peripheral vascular disease), we found independent associations of genetically predicted LDL-cholesterol with abdominal aortic aneurysm (OR, 1.75 [95% CI, 1.40-2.17]) and aortic valve stenosis (OR, 1.46 [95% CI, 1.25-1.70]). Genetically predicted triglyceride levels were positively associated with CAD (OR, 1.25 [95% CI, 1.12-1.40]), aortic valve stenosis (OR, 1.29 [95% CI, 1.04-1.61]), and hypertension (OR, 1.17 [95% CI, 1.07-1.27]), but inversely associated with venous thromboembolism (OR, 0.79 [95% CI, 0.67-0.93]) and hemorrhagic stroke (OR, 0.78 [95% CI, 0.62-0.98]). We also found positive associations of genetically predicted LDL-cholesterol and triglycerides with heart failure that appeared to be mediated by CAD. CONCLUSIONS: Lowering LDL-cholesterol is likely to prevent abdominal aortic aneurysm and aortic stenosis, in addition to CAD and other atheromatous cardiovascular outcomes. Lowering triglycerides is likely to prevent CAD and aortic valve stenosis but may increase thromboembolic risk

HER2-enriched subtype and novel molecular subgroups drive aromatase inhibitor resistance and an increased risk of relapse in early ER+/HER2+ breast cancer

BACKGROUND: Oestrogen receptor positive/ human epidermal growth factor receptor positive (ER+/HER2+) breast cancers (BCs) are less responsive to endocrine therapy than ER+/HER2- tumours. Mechanisms underpinning the differential behaviour of ER+HER2+ tumours are poorly characterised. Our aim was to identify biomarkers of response to 2 weeks’ presurgical AI treatment in ER+/HER2+ BCs. METHODS: All available ER+/HER2+ BC baseline tumours (n=342) in the POETIC trial were gene expression profiled using BC360™ (NanoString) covering intrinsic subtypes and 46 key biological signatures. Early response to AI was assessed by changes in Ki67 expression and residual Ki67 at 2 weeks (Ki672wk). Time-To-Recurrence (TTR) was estimated using Kaplan-Meier methods and Cox models adjusted for standard clinicopathological variables. New molecular subgroups (MS) were identified using consensus clustering. FINDINGS: HER2-enriched (HER2-E) subtype BCs (44.7% of the total) showed poorer Ki67 response and higher Ki672wk (p<0.0001) than non-HER2-E BCs. High expression of ERBB2 expression, homologous recombination deficiency (HRD) and TP53 mutational score were associated with poor response and immune-related signatures with High Ki672wk. Five new MS that were associated with differential response to AI were identified. HER2-E had significantly poorer TTR compared to Luminal BCs (HR 2.55, 95% CI 1.14–5.69; p=0.0222). The new MS were independent predictors of TTR, adding significant value beyond intrinsic subtypes. INTERPRETATION: Our results show HER2-E as a standardised biomarker associated with poor response to AI and worse outcome in ER+/HER2+. HRD, TP53 mutational score and immune-tumour tolerance are predictive biomarkers for poor response to AI. Lastly, novel MS identify additional non-HER2-E tumours not responding to AI with an increased risk of relapse

Identification of plasma proteins causally related to Multiple Sclerosis via a Mendelian Randomization approach: a study on multiplex families from the founder population of the Nuoro province (Sardinia)

Background: The pathogenesis of Multiple Sclerosis (MS) is poorly understood. A better understanding of the causal pathways involved in this disease is needed as a basis for developing new therapies. Objectives: With this study we try to assess the existence of causal relationships between a large set of candidate plasma proteins and MS. Our analysis is based on 20 multiplex families from the founder and genetically homogeneous population of the Nuoro province, Sardinia (Italy). Our aim is to improve our understanding of the pathophysiological bases of this disease, providing important candidates to be prioritized for further studies on MS and for drug discovery possibly leading to the improvement of the clinical conditions of the subjects affected by this disabling disease. Methods: We investigated each protein, in turn, for a possible causal effect on MS, taking advantage of the use of Mendelian Randomization (MR) methods to avoid the classical biases that affects observational studies. To overcome the limitations of observational studies we adopted a MR approach to the analysis, where genetic variants act as instrumental variables for the assessment of the putative causal effect. We applied different MR methods based on summary statistics: Inverse-Variance Weighted as the main method and the Weighted Median Estimator and Egger regression for sensitivity analysis purpose. The data supported causality of a number of proteins, which we then checked via bidirectional MR analysis to assess potential reverse causation. Results: In the end, 3 proteins showed significant results with both Bonferroni and Benjamini-Hochberg corrections, in particular MOBP, ZMYND19 and EFCAB14. Following the bidirectional analysis though, ZMYND19 showed a significant result in the reverse-direction too, suggesting some reverse causation effect. It seems that, in this case, the disease itself could influence the level of this protein in plasma. The final and most interesting findings in the end are therefore MOBP and EFCAB14. Conclusion: Whereas MR methods are typically applied to high-level exposures, such as obesity and cholesterol, ours is one of the few studies that uses standard MR methods to identify genes that drive the disease by influencing the concentration of their coded proteins, applying a systematic routine of analysis on a very large set of candidate proteins in what seems to be a very promising and useful exploratory approach. We confirmed two proteins being causally related to MS. The variants in the genes coding for these proteins were found statistically associated to MS in previous studies

Prediction of mortality in patients with implantable defibrillator using CHADS2 score: data from a prospective observational investigation

CHADS2 (congestive heart failure, hypertension, age 6575 years, diabetes mellitus, previous stroke/TIA) score has been validated as a risk stratification score to predict stroke in patients with atrial fibrillation (AF). The objective of this analysis was to assess whether patient risk factors, in particular CHADS2 score, identified patients at risk of mortality

Impact of duration of neoadjuvant aromatase inhibitors on molecular expression profiles in estrogen receptor positive breast cancers

BACKGROUND: Aromatase inhibitors (AI) treatment is the standard of care for post-menopausal women with primary estrogen receptor positive breast cancer (BC). The impact of duration of neoadjuvant endocrine therapy (NET) on molecular characteristics is still unknown. We evaluated and compared changes of gene expression profiles under short-term (2-week) versus longer-term neoadjuvant AI. METHODS: Global gene expression profiles from POETIC trial (137 received 2 weeks of AI and 47 notreatment) and targeted gene expression from 80 BC patients treated with NET for more than one-month (NeoAI) were assessed. Intrinsic subtyping, module-scores covering different cancer-pathways and immune-related genes were calculated for pre- and post-treated tumours. RESULTS: The differences in intrinsic subtypes after NET were comparable between the two cohorts, with most Luminal B (90.0% in POETIC and 76.3% in NeoAI) and 50.0% of HER2-enriched at baseline re-classified as Luminal A or Normal-like after NET. Downregulation of proliferative-related pathways was observed after two-weeks of AI. However, more changes in genes from cancer-signaling pathways such as MAPK and PI3K/AKT/mTOR and immune response/immune-checkpoint components that were associated with AI resistant tumours and differential outcome were observed in the NeoAI study. CONCLUSIONS: Tumour transcriptional profiles undergo bigger changes in response to longer NET. Changes in HER2-enriched and Luminal B subtypes are similar between the two cohorts, thus AI sensitive intrinsic subtype tumours associated with good survival might be identified after 2 weeks of AI. The changes of immune-checkpoint component expression in early AI resistance and its impact on survival outcome warrants careful investigation in clinical trials

HER2-enriched subtype and novel molecular subgroups drive aromatase inhibitor resistance and an increased risk of relapse in early ER+/HER2+ breast cancer

BACKGROUND: Oestrogen receptor positive/ human epidermal growth factor receptor positive (ER+/HER2+) breast cancers (BCs) are less responsive to endocrine therapy than ER+/HER2- tumours. Mechanisms underpinning the differential behaviour of ER+HER2+ tumours are poorly characterised. Our aim was to identify biomarkers of response to 2 weeks’ presurgical AI treatment in ER+/HER2+ BCs. METHODS: All available ER+/HER2+ BC baseline tumours (n=342) in the POETIC trial were gene expression profiled using BC360™ (NanoString) covering intrinsic subtypes and 46 key biological signatures. Early response to AI was assessed by changes in Ki67 expression and residual Ki67 at 2 weeks (Ki67(2wk)). Time-To-Recurrence (TTR) was estimated using Kaplan-Meier methods and Cox models adjusted for standard clinicopathological variables. New molecular subgroups (MS) were identified using consensus clustering. FINDINGS: HER2-enriched (HER2-E) subtype BCs (44.7% of the total) showed poorer Ki67 response and higher Ki67(2wk) (p<0.0001) than non-HER2-E BCs. High expression of ERBB2 expression, homologous recombination deficiency (HRD) and TP53 mutational score were associated with poor response and immune-related signatures with High Ki67(2wk). Five new MS that were associated with differential response to AI were identified. HER2-E had significantly poorer TTR compared to Luminal BCs (HR 2.55, 95% CI 1.14–5.69; p=0.0222). The new MS were independent predictors of TTR, adding significant value beyond intrinsic subtypes. INTERPRETATION: Our results show HER2-E as a standardised biomarker associated with poor response to AI and worse outcome in ER+/HER2+. HRD, TP53 mutational score and immune-tumour tolerance are predictive biomarkers for poor response to AI. Lastly, novel MS identify additional non-HER2-E tumours not responding to AI with an increased risk of relapse. FUNDING: Cancer Research UK (CRUK/07/015)

HER2-enriched subtype and novel molecular subgroups drive aromatase inhibitor resistance and an increased risk of relapse in early ER+/HER2+ breast cancer

Background: oestrogen receptor positive/ human epidermal growth factor receptor positive (ER+/HER2+) breast cancers (BCs) are less responsive to endocrine therapy than ER+/HER2- tumours. Mechanisms underpinning the differential behaviour of ER+HER2+ tumours are poorly characterised. Our aim was to identify biomarkers of response to 2 weeks’ presurgical AI treatment in ER+/HER2+ BCs. Methods: all available ER+/HER2+ BC baseline tumours (n=342) in the POETIC trial were gene expression profiled using BC360™ (NanoString) covering intrinsic subtypes and 46 key biological signatures. Early response to AI was assessed by changes in Ki67 expression and residual Ki67 at 2 weeks (Ki67 2wk). Time-To-Recurrence (TTR) was estimated using Kaplan-Meier methods and Cox models adjusted for standard clinicopathological variables. New molecular subgroups (MS) were identified using consensus clustering. Findings: HER2-enriched (HER2-E) subtype BCs (44.7% of the total) showed poorer Ki67 response and higher Ki67 2wk (p&lt;0.0001) than non-HER2-E BCs. High expression of ERBB2 expression, homologous recombination deficiency (HRD) and TP53 mutational score were associated with poor response and immune-related signatures with High Ki67 2wk. Five new MS that were associated with differential response to AI were identified. HER2-E had significantly poorer TTR compared to Luminal BCs (HR 2.55, 95% CI 1.14–5.69; p=0.0222). The new MS were independent predictors of TTR, adding significant value beyond intrinsic subtypes. Interpretation: our results show HER2-E as a standardised biomarker associated with poor response to AI and worse outcome in ER+/HER2+. HRD, TP53 mutational score and immune-tumour tolerance are predictive biomarkers for poor response to AI. Lastly, novel MS identify additional non-HER2-E tumours not responding to AI with an increased risk of relapse. Funding: Cancer Research UK (CRUK/07/015). </p