Publications by authors named "M J Friez"

Rett Syndrome (RTT) is a severe neurodevelopmental disorder predominately diagnosed in females and primarily caused by pathogenic variants in the X-linked gene (). Most often, the disease causing the allele resides on the paternal X chromosome while a healthy copy is maintained on the maternal X chromosome with inactivation (XCI), resulting in mosaic expression of one allele in each cell. Preferential inactivation of the paternal X chromosome is theorized to result in reduced disease severity; however, establishing such a correlation is complicated by known genotype effects and an age-dependent increase in severity.

View Article and Find Full Text PDF

The molecular basis of mullerian aplasia, also known as Mayer-Rokitansky-Kuster Hauser (MRKH) or congenital absence of the uterus and vagina, is largely unknown. We applied a multifaceted genetic approach to studying the pathogenesis of MRKH including exome sequencing of trios and duos, genome sequencing of families, qPCR, RT-PCR, and Sanger sequencing to detect intragenic deletions, insertions, splice variants, single nucleotide variants, and rearrangements in 132 persons with MRKH. We identified two heterozygous variants in ZNHIT3 localized to a commonly involved CNV region at chromosome 17q12 in two different families with MRKH.

View Article and Find Full Text PDF

Introduction: X-linked gene has recently been pointed as one of the most interesting candidates for involvement in neurodevelopmental disorders (NDs), such as intellectual disability (ID) and autism spectrum disorder (ASD). encodes the patched domain-containing protein 1 (), which is mainly expressed in the developing brain and adult brain tissues. To date, major studies have focused on the biological function of the gene, while the mechanisms underlying neuronal alterations and the cognitive-behavioral phenotype associated with mutations still remain unclear.

View Article and Find Full Text PDF

Purpose: This study aims to assess the diagnostic utility and provide reporting recommendations for clinical DNA methylation episignature testing based on the cohort of patients tested through the EpiSign Clinical Testing Network.

Methods: The EpiSign assay utilized unsupervised clustering techniques and a support vector machine-based classification algorithm to compare each patient's genome-wide DNA methylation profile with the EpiSign Knowledge Database, yielding the result that was reported. An international working group, representing distinct EpiSign Clinical Testing Network health jurisdictions, collaborated to establish recommendations for interpretation and reporting of episignature testing.

View Article and Find Full Text PDF