Sudden cardiac death after early-onset myocardial infarction: a multicentre longitudinal cohort study with a 20-year follow-up.

Aims: Sudden cardiac death (SCD) is a serious consequence of a myocardial infarction (MI), but identifying patients at risk of developing SCD remains a major clinical challenge, especially in the case of juvenile MI. The aim of this study is to identify predictors of SCD after early-onset MI using long-term follow-up data relating to a large nationwide patient cohort.

Methods And Results: The Italian Genetic Study on Early-onset MI enrolled 2000 patients experiencing a first MI before the age of 45 years, who were followed up for a median of 19.

Interactive molecular causal networks of hypertension using a fast machine learning algorithm MRdualPC.

Background: Understanding the complex interactions between genes and their causal effects on diseases is crucial for developing targeted treatments and gaining insight into biological mechanisms. However, the analysis of molecular networks, especially in the context of high-dimensional data, presents significant challenges.

Methods: This study introduces MRdualPC, a computationally tractable algorithm based on the MRPC approach, to infer large-scale causal molecular networks.

Bayesian Mendelian randomization with an interval causal null hypothesis: ternary decision rules and loss function calibration.

We enhance the Bayesian Mendelian Randomization (MR) framework of Berzuini et al. (Biostatistics 21(1):86-101, 2018) by allowing for interval null causal hypotheses, where values of the causal effect parameter that fall within a user-specified interval of "practical equivalence" (ROPE) (Kruschke, Adv Methods Pract Psychol Sci 1(2):270-80, 2018) are regarded as equivalent to "no effect". We motivate this move in the context of MR analysis.

Clinical prediction models for aneurysmal subarachnoid hemorrhage: a systematic review update.

Background: A systematic review of clinical prediction models for aneurysmal subarachnoid hemorrhage (aSAH) reported in 2011 noted that clinical prediction models for aSAH were developed using poor methods and were not externally validated. This study aimed to update the above review to guide the future development of predictive models in aSAH.

Methods: We systematically searched Embase and MEDLINE databases (January 2010 to February 2022) for articles that reported the development of a clinical prediction model to predict functional outcomes in aSAH.

A review of causal discovery methods for molecular network analysis.

Background: With the increasing availability and size of multi-omics datasets, investigating the casual relationships between molecular phenotypes has become an important aspect of exploring underlying biology andgenetics. There are an increasing number of methodlogies that have been developed and applied to moleular networks to investigate these causal interactions.

Methods: We have introduced and reviewed the available methods for building large-scale causal molecular networks that have been developed and applied in the past decade.

Sex-Related Differences in Long-Term Outcomes After Early-Onset Myocardial Infarction.

Importance: There is growing awareness of sex-related differences in cardiovascular risk profiles, but less is known about whether these extend to pre-menopausal females experiencing an early-onset myocardial infarction (MI), who may benefit from the protective effects of estrogen exposure.

Methods: A nationwide study involving 125 Italian Coronary Care Units recruited 2,000 patients between 1998 and 2002 hospitalized for a type I myocardial infarction before the age of 45 years (male, = 1,778 (88.9%).

Hunting for protective drugs at the break of a pandemic: Causal inference from hospital data.

At the break of a pandemic, the protective efficacy of therapeutic interventions needs rapid evaluation. An experimental approach to the problem will not always be appropriate. An alternative route are observational studies, whether based on regional health service data or hospital records.

Bayesian mendelian randomization with study heterogeneity and data partitioning for large studies.

Background: Mendelian randomization (MR) is a useful approach to causal inference from observational studies when randomised controlled trials are not feasible. However, study heterogeneity of two association studies required in MR is often overlooked. When dealing with large studies, recently developed Bayesian MR can be computationally challenging, and sometimes even prohibitive.

Plasma Protein Levels Analysis in Multiple Sclerosis Sardinian Families Identified C9 and CYP24A1 as Candidate Biomarkers.

Here we investigate protein levels in 69 multiple sclerosis (MS) cases and 143 healthy controls (HC) from twenty Sardinian families to search for promising biomarkers in plasma. Using antibody suspension bead array technology, the plasma levels of 56 MS-related proteins were obtained. Differences between MS cases and HC were estimated using Linear Mixed Models or Linear Quantile Mixed Models.

Long-term outcomes of early-onset myocardial infarction with non-obstructive coronary artery disease (MINOCA).

Background: Acute myocardial infarction with non-obstructive coronary artery disease (MINOCA) is frequent in patients experiencing an early-onset MI, but data concerning its long-term prognosis are limited and conflicting.

Methods: The Italian Genetic Study on Early-onset MI enrolled 2000 patients experiencing a first MI before the age of 45 years, and had a median follow-up of 19.9 years.

Antecedent use of renin-angiotensin system inhibitors is associated with reduced mortality in elderly hypertensive Covid-19 patients.

Objectives: The effect of renin-angiotensin system inhibitors (RASIs) on mortality in patients with coronavirus disease (Covid-19) is debated. From a cohort of 1352 consecutive patients admitted with Covid-19 to Papa Giovanni XXIII Hospital in Bergamo, Italy, between February and April 2020, we selected and studied hypertensive patients to assess whether antecedent (prior to hospitalization) use of RASIs might affect mortality from Covid-19 according to age.

Methods And Results: Arterial hypertension was present in 688 patients.

Developing and Validating an Individualized Clinical Prediction Model to Forecast Psychotic Recurrence in Acute and Transient Psychotic Disorders: Electronic Health Record Cohort Study.

Acute and transient psychotic disorders (ATPDs) include short-lived psychotic episodes with a high probability of developing psychotic recurrences. Clinical care for ATPD is currently limited by the inability to predict outcomes. Real-world electronic health record (EHR)-based retrospective cohort study STROBE/RECORD compliant included all individuals accessing the South London and Maudsley NHS Trust between 2006 and 2017 and receiving a first diagnosis of ATPD (F23, ICD-10).

Uncovering genetic mechanisms of hypertension through multi-omic analysis of the kidney.

The kidney is an organ of key relevance to blood pressure (BP) regulation, hypertension and antihypertensive treatment. However, genetically mediated renal mechanisms underlying susceptibility to hypertension remain poorly understood. We integrated genotype, gene expression, alternative splicing and DNA methylation profiles of up to 430 human kidneys to characterize the effects of BP index variants from genome-wide association studies (GWASs) on renal transcriptome and epigenome.

Overlapping-sample Mendelian randomisation with multiple exposures: a Bayesian approach.

Background: Mendelian randomization (MR) has been widely applied to causal inference in medical research. It uses genetic variants as instrumental variables (IVs) to investigate putative causal relationship between an exposure and an outcome. Traditional MR methods have mainly focussed on a two-sample setting in which IV-exposure association study and IV-outcome association study are independent.

Value of dynamic clinical and biomarker data for mortality risk prediction in COVID-19: a multicentre retrospective cohort study.

Objectives: Being able to predict which patients with COVID-19 are going to deteriorate is important to help identify patients for clinical and research practice. Clinical prediction models play a critical role in this process, but current models are of limited value because they are typically restricted to baseline predictors and do not always use contemporary statistical methods. We sought to explore the benefits of incorporating dynamic changes in routinely measured biomarkers, non-linear effects and applying 'state-of-the-art' statistical methods in the development of a prognostic model to predict death in hospitalised patients with COVID-19.

Investigating the Causal Effect of Brain Expression of , , , , Genes on Multiple Sclerosis: A Two-Sample Mendelian Randomization Approach.

Multiple Sclerosis (MS) exhibits considerable heterogeneity in phenotypic expression, course, prognosis and response to therapy. This suggests this disease involves multiple, as yet poorly understood, causal mechanisms. In this work we assessed the possible causal link between gene expression level of five selected genes related to the pro-inflammatory NF-κB signaling pathway (i.

Integrative analysis of Mendelian randomization and Bayesian colocalization highlights four genes with putative BMI-mediated causal pathways to diabetes.

Genome-wide association studies have identified hundreds of single nucleotide polymorphisms (SNPs) that are associated with BMI and diabetes. However, lack of adequate data has for long time prevented investigations on the pathogenesis of diabetes where BMI was a mediator of the genetic causal effects on this disease. Of our particular interest is the underlying causal mechanisms of diabetes.

Sighting acute myocardial infarction through platelet gene expression.

Acute myocardial infarction is primarily due to coronary atherosclerotic plaque rupture and subsequent thrombus formation. Platelets play a key role in the genesis and progression of both atherosclerosis and thrombosis. Since platelets are anuclear cells that inherit their mRNA from megakaryocyte precursors and maintain it unchanged during their life span, gene expression profiling at the time of an acute myocardial infarction provides information concerning the platelet gene expression preceding the coronary event.

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.

Sensitivity to pain expectations: A Bayesian model of individual differences.

The thoughts and feelings people have about pain (referred to as 'pain expectations') are known to alter the perception of pain. However little is known about the cognitive processes that underpin pain expectations, or what drives the differing effect that pain expectations have between individuals. This paper details the testing of a model of pain perception which formalises the response to pain in terms of a Bayesian prior-to-posterior updating process.

A Bayesian approach to Mendelian randomization with multiple pleiotropic variants.

We propose a Bayesian approach to Mendelian randomization (MR), where instruments are allowed to exert pleiotropic (i.e. not mediated by the exposure) effects on the outcome.

Mendelian randomisation analysis of clustered causal effects of body mass on cardiometabolic biomarkers.

Background: Recent advances in data analysis methods based on principles of Mendelian Randomisation, such as Egger regression and the weighted median estimator, add to the researcher's ability to infer cause-effect links from observational data. Now is the time to gauge the potential of these methods within specific areas of biomedical research. In this paper, we choose a study in metabolomics as an illustrative testbed.

Women's Pregnancy Life History and Alzheimer's Risk: Can Immunoregulation Explain the Link?

Background: Pregnancy is associated with improvement in immunoregulation that persists into the geriatric phase. Impaired immunoregulation is implicated in Alzheimer's disease (AD) pathogenesis. Hence, we investigate the relationship between pregnancy and AD.