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Motivation: Reliable tools and software for penetrance (age-specific risk among those who carry a genetic variant) estimation are critical to improving clinical decision making and risk assessment for hereditary syndromes. However, there is a lack of easily usable software for penetrance estimation in family-based studies that implements a Bayesian estimation approach.
Results: We introduce , an open-source R package available on CRAN, to estimate age-specific penetrance using family-history pedigree data. The package uses a Bayesian estimation approach, allowing for the incorporation of prior knowledge through the specification of priors for the parameters of the carrier distribution. It also includes options to impute missing ages during the estimation process, addressing incomplete age information which is not uncommon in pedigree datasets. Our open-source software provides a flexible and user-friendly tool for researchers to estimate penetrance in complex family-based studies, facilitating improved genetic risk assessment in hereditary syndromes.
Availability And Implementation: The package is freely available on CRAN. Source code and documentation are available at https://github.com/nicokubi/penetrance.
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http://dx.doi.org/10.1093/bioadv/vbaf154 | DOI Listing |
Eat Disord
September 2025
Calgary Eating Disorders Program, Alberta Children's Hospital, Calgary, Alberta, Canada.
Family-based treatment (FBT) is the recommended approach for adolescents with eating disorders (EDs), but long waitlists hinder its delivery. This study aimed to explore the feasibility and acceptability of a brief 5-week outpatient FBT psychoeducation group for parents/caregivers of adolescents with anorexia nervosa (AN). The secondary aim of this study was to examine its preliminary effectiveness of increasing parental self-efficacy and decreasing expressed emotion and accommodation of the eating disorder.
View Article and Find Full Text PDFBrain Behav
September 2025
Child Development Department, Faculty of Health Sciences, Hacettepe University, Ankara, Turkey.
Purpose: The study aims to assess familial and environmental characteristics and daily routines (nutrition, sleep, and screen time) associated with attention-deficit/hyperactivity disorder (ADHD) in Turkish children and compare them with typically developing peers.
Methods: A case-control study was conducted with 106 ADHD-diagnosed children and 100 typically developing peers. Data were analyzed using descriptive statistics and logistic regression models to determine risk factors for ADHD.
HGG Adv
September 2025
Department of Epidemiology, Bloomberg School of Public Health, Johns Hopkins University, Baltimore, MD 21205, USA; Department of Biostatistics, Bloomberg School of Public Health, Johns Hopkins University, Baltimore, MD 21205, USA. Electronic address:
Pleiotropy, the phenomenon where a genetic region confers risk to multiple traits, is widely observed, even among seemingly unrelated traits. Knowledge of pleiotropy can improve understanding of biological mechanisms of diseases/traits, and can potentially guide identification of molecular targets or help predict side-effects in drug development. However, statistical approaches for identifying pleiotropy genome-wide are limited, particularly for two correlated traits or case-control traits with unknown sample overlap or for disease traits from family studies.
View Article and Find Full Text PDFFam Cancer
September 2025
Cancer Genetics Service, Division of Medical Oncology, National Cancer Centre Singapore, Singapore, Singapore.
This study compares three hereditary colorectal cancer (CRC) registries-the Iranian Hereditary Colorectal Cancer Registry (IHCCR), the Singapore Polyposis Registry (SPR), and the University of Cape Town Familial CRC Registry-to illuminate diverse approaches to identification, management, and research across different healthcare systems. Each registry, while emphasizing patient diversity, employed unique strategies reflecting available resources and epidemiological contexts. The IHCCR, leveraging WES, revealed considerable genetic heterogeneity, including novel mutations.
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