Characterizing the SARS-CoV-2 antibody response and associations with patient factors: Serological profiling of participants enrolled in the GENCOV study.

Introduction: The GENCOV study sought to evaluate serological differences between individuals with differing COVID-19 severity and outcomes. We assessed the SARS-CoV-2 antibody response of GENCOV participants cross-sectionally 1-, 6-, and 12-months following COVID-19 diagnosis to identify patient factors associated with more robust and durable humoral immune responses.

Materials And Methods: COVID-19 patients and a control cohort of vaccinated infection-naïve participants were recruited at hospital sites across the Greater Toronto Area in Ontario, Canada.

Trivariate Joint Modeling for Family Data with Longitudinal Counts, Recurrent Events and a Terminal Event with Application to Lynch Syndrome.

Trivariate joint modeling for longitudinal count data, recurrent events, and a terminal event for family data has increased interest in medical studies. For example, families with Lynch syndrome (LS) are at high risk of developing colorectal cancer (CRC), where the number of polyps and the frequency of colonoscopy screening visits are highly associated with the risk of CRC among individuals and families. To assess how screening visits influence polyp detection, which in turn influences time to CRC, we propose a clustered trivariate joint model.

COVID-19 vaccine reactogenicity among participants enrolled in the GENCOV study.

Background: GENCOV is a prospective, observational cohort study of COVID-19-positive adults. Here, we characterize and compare side effects between COVID-19 vaccines and determine whether reactogenicity is exacerbated by prior SARS-CoV-2 infection.

Methods: Participants were recruited across Ontario, Canada.

Modeling multiple correlated end-organ disease trajectories: A tutorial for multistate and joint models with applications in diabetes complications.

State-of-the-art biostatistics methods allow for the simultaneous modeling of several correlated non-fatal disease processes over time, but there is no clear guidance on the optimal analysis in most settings. An example occurs in diabetes, where it is not known with certainty how microvascular complications of the eyes, kidneys, and nerves co-develop over time. In this article, we propose and contrast two general model frameworks for studying complications (sequential state and parallel trajectory frameworks) and review multivariate methods for their analysis, focusing on multistate and joint modeling.

THE SCALABLE BIRTH-DEATH MCMC ALGORITHM FOR MIXED GRAPHICAL MODEL LEARNING WITH APPLICATION TO GENOMIC DATA INTEGRATION.

Recent advances in biological research have seen the emergence of high-throughput technologies with numerous applications that allow the study of biological mechanisms at an unprecedented depth and scale. A large amount of genomic data is now distributed through consortia like The Cancer Genome Atlas (TCGA), where specific types of biological information on specific type of tissue or cell are available. In cancer research, the challenge is now to perform integrative analyses of high-dimensional multi-omic data with the goal to better understand genomic processes that correlate with cancer outcomes, e.

Large-scale whole exome sequencing studies identify two genes,CTSL and APOE, associated with lung cancer.

Common genetic variants associated with lung cancer have been well studied in the past decade. However, only 12.3% heritability has been explained by these variants.

A marginalized two-part joint model for a longitudinal biomarker and a terminal event with application to advanced head and neck cancers.

The sum of the longest diameter (SLD) of the target lesions is a longitudinal biomarker used to assess tumor response in cancer clinical trials, which can inform about early treatment effect. This biomarker is semicontinuous, often characterized by an excess of zeros and right skewness. Conditional two-part joint models were introduced to account for the excess of zeros in the longitudinal biomarker distribution and link it to a time-to-event outcome.

Characterizing Risk Factors for Hospitalization and Clinical Characteristics in a Cohort of COVID-19 Patients Enrolled in the GENCOV Study.

The GENCOV study aims to identify patient factors which affect COVID-19 severity and outcomes. Here, we aimed to evaluate patient characteristics, acute symptoms and their persistence, and associations with hospitalization. Participants were recruited at hospital sites across the Greater Toronto Area in Ontario, Canada.

Public knowledge of SARS-CoV-2 serological and viral lineage laboratory testing and result interpretation: A GENCOV study cross-sectional survey.

Objectives: Concepts related to SARS-CoV-2 laboratory testing and result interpretation can be challenging to understand. A cross-sectional survey of COVID-19 positive adults residing in Ontario, Canada was conducted to explore how well people understand SARS-CoV-2 laboratory tests and their associated results.

Design And Methods: Participants were recruited through fliers or by prospective recruitment of outpatients and hospitalized inpatients with COVID-19.

Evaluating colonoscopy screening intervals in patients with Lynch syndrome from a large Canadian registry.

Background: Lynch syndrome (LS) screening guidelines originally recommended colonoscopy every 1 to 2 years, beginning between the ages of 20 and 25 years. Recent studies have questioned the benefits of these short screening intervals in preventing colorectal cancer (CRC). Our goal is to determine how colonoscopy screening intervals impact CRC in patients with LS.

Cord blood myostatin concentrations by gestational diabetes mellitus and fetal sex.

Introduction: Myostatin is a member of the transforming growth factor β superfamily, and is mainly secreted from skeletal muscle. Animal studies have demonstrated that deficiency in myostatin promotes muscle growth and protects against insulin resistance. In humans, gestational diabetes mellitus (GDM) affects fetal insulin sensitivity.

Bayesian estimation of two-part joint models for a longitudinal semicontinuous biomarker and a terminal event with INLA: Interests for cancer clinical trial evaluation.

Two-part joint models for a longitudinal semicontinuous biomarker and a terminal event have been recently introduced based on frequentist estimation. The biomarker distribution is decomposed into a probability of positive value and the expected value among positive values. Shared random effects can represent the association structure between the biomarker and the terminal event.

Highly efficient reprogrammable mouse lines with integrated reporters to track the route to pluripotency.

Revealing the molecular events associated with reprogramming different somatic cell types to pluripotency is critical for understanding the characteristics of induced pluripotent stem cell (iPSC) therapeutic derivatives. Inducible reprogramming factor transgenic cells or animals-designated as secondary (2°) reprogramming systems-not only provide excellent experimental tools for such studies but also offer a strategy to study the variances in cellular reprogramming outcomes due to different in vitro and in vivo environments. To make such studies less cumbersome, it is desirable to have a variety of efficient reprogrammable mouse systems to induce successful mass reprogramming in somatic cell types.

DNA methylation profiles in the blood of newborn term infants born to mothers with obesity.

Maternal obesity is an important risk factor for childhood obesity and influences the prevalence of metabolic diseases in offspring. As childhood obesity is influenced by postnatal factors, it is critical to determine whether children born to women with obesity during pregnancy show alterations that are detectable at birth. Epigenetic mechanisms such as DNA methylation modifications have been proposed to mediate prenatal programming.

Building knowledge, optimising physical and mental health and setting up healthier life trajectories in South African women (): a preconception randomised control trial part of the Healthy Life Trajectories Initiative (HeLTI).

Introduction: South Africa's evolving burden of disease is challenging due to a persistent infectious disease, burgeoning obesity, most notably among women and rising rates of non-communicable diseases (NCDs). With two thirds of women presenting at their first antenatal visit either overweight or obese in urban South Africa (SA), the preconception period is an opportunity to optimise health and offset transgenerational risk of both obesity and NCDs.

Methods And Analysis: is the first individual randomised controlled trial in Africa to test the efficacy of a complex continuum of care intervention and forms part of the Healthy Life Trajectories Initiative (HeLTI) consortium implementing harmonised trials in Canada, China, India and SA.

Maternal BMI, breastfeeding and perinatal factors that influence early childhood growth trajectories: a scoping review.

Obesity rates among children are rapidly rising internationally and have been linked to noncommunicable diseases in adulthood. Individual preventive strategies have not effectively reduced global obesity rates, leading to a gap in clinical services regarding the development of early perinatal interventions. The objective of this scoping review is to explore the relationship between maternal BMI and breastfeeding behaviors on child growth trajectories to determine their relevance in developing interventions aimed at preventing childhood obesity.

DNA methylation mediates the association between breastfeeding and early-life growth trajectories.

Background: The role of breastfeeding in modulating epigenetic factors has been suggested as a possible mechanism conferring its benefits on child development but it lacks evidence. Using extensive DNA methylation data from the ALSPAC child cohort, we characterized the genome-wide landscape of DNA methylation variations associated with the duration of exclusive breastfeeding and assessed whether these variations mediate the association between exclusive breastfeeding and BMI over different epochs of child growth.

Results: Exclusive breastfeeding elicits more substantial DNA methylation variations during infancy than at other periods of child growth.

A competing risks model with binary time varying covariates for estimation of breast cancer risks in families.

Mammographic screening and prophylactic surgery such as risk-reducing salpingo oophorectomy can potentially reduce breast cancer risks among mutation carriers of families. The evaluation of these interventions is usually complicated by the fact that their effects on breast cancer may change over time and by the presence of competing risks. We introduce a correlated competing risks model to model breast and ovarian cancer risks within families that accounts for time-varying covariates.

Association of Risk-Reducing Salpingo-Oophorectomy With Breast Cancer Risk in Women With BRCA1 and BRCA2 Pathogenic Variants.

Importance: Women with pathogenic variants in BRCA1 and BRCA2 are at high risk of developing breast and ovarian cancers. They usually undergo intensive cancer surveillance and may also consider surgical interventions, such as risk-reducing mastectomy or risk-reducing salpingo-oophorectomy (RRSO). Risk-reducing salpingo-oophorectomy has been shown to reduce ovarian cancer risk, but its association with breast cancer risk is less clear.

Early life risk and resiliency factors and their influences on developmental outcomes and disease pathways: a rapid evidence review of systematic reviews and meta-analyses.

The Developmental Origins of Health and Disease (DOHaD) framework aims to understand how environmental exposures in early life shape lifecycle health. Our understanding and the ability to prevent poor health outcomes and enrich for resiliency remain limited, in part, because exposure-outcome relationships are complex and poorly defined. We, therefore, aimed to determine the major DOHaD risk and resilience factors.

Exclusive breastfeeding can attenuate body-mass-index increase among genetically susceptible children: A longitudinal study from the ALSPAC cohort.

Recent discoveries from large-scale genome-wide association studies (GWASs) explain a larger proportion of the genetic variability to BMI and obesity. The genetic risk associated with BMI and obesity can be assessed by an obesity-specific genetic risk score (GRS) constructed from genome-wide significant genetic variants. The aim of our study is to examine whether the duration and exclusivity of breastfeeding can attenuate BMI increase during childhood and adolescence due to genetic risks.