Genetic Counseling and Genome Sequencing in Pediatrics

A special issue of Journal of Personalized Medicine (ISSN 2075-4426). This special issue belongs to the section "Omics/Informatics".

Deadline for manuscript submissions: 25 June 2026 | Viewed by 902

Special Issue Editor


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Guest Editor
Independent Laboratory of Genetic Diagnostics, Medical University of Lublin, 20-059 Lublin, Poland
Interests: genetic diagnostics; leukemia; hematologic diseases; pediatrics; target therapy

Special Issue Information

Dear Colleagues,

Many pediatric diseases are caused by genetic mutations. Traditional diagnosis and treatment models mainly rely on clinical symptom observation and limited genetic testing technology, which often faces challenges such as a long diagnosis cycle and limited accuracy. With the advent of personalized medicine, the rapid development of high-throughput genome sequencing technology and genetic counseling has delivered revolutionary breakthroughs in the precise diagnosis, risk prediction and personalized treatment of pediatric genetic diseases, significantly improving the diagnosis and treatment effects and long-term survival quality of children.

This Special Issue aims to promote deep integration of the precise diagnosis and treatment of pediatric diseases with personalized medicine, promote the clinical transformation of genome sequencing technology, standardize the practice of genetic counseling, and optimize multidisciplinary collaborative diagnosis and treatment models. We hope to provide new ideas for early intervention and personalized management of pediatric diseases by bringing together cutting-edge research results and clinical practice experience.

We welcome submissions of original research articles and reviews covering but not limited to the following: the application of pediatric genome sequencing, genetic counseling strategies, bioinformatics analysis, personalized treatment, etc., to jointly promote innovation and development in this field!

Dr. Monika Lejman
Guest Editor

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Keywords

  • pediatric disease
  • genome sequencing
  • genetic counseling
  • personalized medicine
  • genetic diagnostics

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Published Papers (1 paper)

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Research

25 pages, 2817 KB  
Article
Genetic Burden and APOE Methylation in a Korean Multi-Generational Alzheimer’s Disease Family: An Exploratory Multi-Omics Case Study
by Je-Hyun Eom, Mu-Yeol Cho, Ji-Won Kim, Yunwoo Kim, Seung-Jo Yang, Jiyoung Hwang, Dahye Lee, Hye-Sung Kim, Young-Youn Kim and Hanseung Baek
J. Pers. Med. 2026, 16(2), 66; https://doi.org/10.3390/jpm16020066 - 29 Jan 2026
Viewed by 718
Abstract
Background/Objectives: Alzheimer’s disease (AD) exhibits high heritability (60–80%), yet individual-level genetic risk prediction remains challenging. While APOE ε4 is the strongest genetic risk factor, incomplete penetrance complicates risk assessment. Methods: We analyzed seven blood-related members across three generations using the Korean [...] Read more.
Background/Objectives: Alzheimer’s disease (AD) exhibits high heritability (60–80%), yet individual-level genetic risk prediction remains challenging. While APOE ε4 is the strongest genetic risk factor, incomplete penetrance complicates risk assessment. Methods: We analyzed seven blood-related members across three generations using the Korean Chip v2.0 genotyping (~1.2 M SNPs) and Illumina EPICv2 DNA methylation profiling. Genetic burden score (GBS) was calculated by summing risk alleles across 320 variants in six AD-associated genes (APOE, PICALM, CLU, CR1, BIN1, and ABCA7). Results: An unexpected pattern was observed in this family: the affected individual (J-003) had the lowest GBS (39 alleles), while individuals with higher genetic burden (51–61 alleles) remained cognitively healthy. J-003 also exhibited lower APOE methylation (β = 0.495) compared to the family mean (β = 0.523). CR1 contributed the most risk alleles across the family, followed by PICALM. Conclusions: This single-case observation cannot establish causality, generalizability, or biological significance. The affected individual’s lower APOE methylation may represent a causal factor, disease consequence, or coincidental variation—scenarios that cannot be distinguished from this dataset. Validation in larger cohorts with multiple affected individuals is required to determine whether integrated multi-omics approaches can inform personalized risk assessment in familial contexts. Full article
(This article belongs to the Special Issue Genetic Counseling and Genome Sequencing in Pediatrics)
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