The availability of molecular genetic testing for retinoblastoma (RB) in Malaysia has enabled patients with a heritable predisposition to the disease to be identified, which thus improves the clinical management of these patients and their families. In this paper, we presented our strategy for performing molecular genetic testing of the RB1 gene and the findings from our first 2 years of starting this service.
Casein kinase 2 (CK2) is a serine threonine kinase ubiquitously expressed in eukaryotic cells and involved in various cellular processes. In recent studies, de novo variants in CSNK2A1 and CSNK2B, which encode the subunits of CK2, have been identified in individuals with intellectual disability syndrome. In this study, we describe four patients with neurodevelopmental disorders possessing de novo variants in CSNK2A1 or CSNK2B. Using whole-exome sequencing, we detected two de novo variants in CSNK2A1 in two unrelated Japanese patients, a novel variant c.571C>T, p.(Arg191*) and a recurrent variant c.593A>G, p.(Lys198Arg), and two novel de novo variants in CSNK2B in Japanese and Malaysian patients, c.494A>G, p.(His165Arg) and c.533_534insGT, p.(Pro179Tyrfs*49), respectively. All four patients showed mild to profound intellectual disabilities, developmental delays, and various types of seizures. This and previous studies have found a total of 20 CSNK2A1 variants in 28 individuals with syndromic intellectual disability. The hotspot variant c.593A>G, p.(Lys198Arg) was found in eight of 28 patients. Meanwhile, only five CSNK2B variants were identified in five individuals with neurodevelopmental disorders. We reviewed the previous literature to verify the phenotypic spectrum of CSNK2A1- and CSNK2B-related syndromes.
With the increasing number of cancer cases worldwide, genetic testing for familiar cancers seems inevitable, yet little is known on population interest and the monetary value for cancer genetic risk information. The current study aimed to determine the willingness to undergo and pay for cancer genetic testing among the Malaysian population. A self-administered questionnaire was distributed to cancer patients and their family members in the oncology and daycare units in several government hospitals. Of 641 respondents (354 patients, 287 family members), 267 (41.7%) were willing to undergo cancer genetic testing. The median that respondents were willing to pay was USD 48.31 (MYR 200.00) IQR USD 96.91 (MYR 400), while 143 (22.3%) respondents were willing to pay a shared cost with the insurance company. Regression analysis identified independent positive predictors of willingness to pay as respondent's status as a family member, high education level, and willingness to undergo cancer genetic testing in general, while in patients, female gender and high level of education were identified as independent positive predictors. Generally, the population needs more information to undergo and pay for cancer genetic testing. This will increase the utilization of the services offered, and with cost-sharing practices with the provider, it can be implemented population-wide.
Many algorithms to detect copy number variations (CNVs) using exome sequencing (ES) data have been reported and evaluated on their sensitivity and specificity, reproducibility, and precision. However, operational optimization of such algorithms for a better performance has not been fully addressed. ES of 1199 samples including 763 patients with different disease profiles was performed. ES data were analyzed to detect CNVs by both the eXome Hidden Markov Model (XHMM) and modified Nord's method. To efficiently detect rare CNVs, we aimed to decrease sequencing biases by analyzing, at the same time, the data of all unrelated samples sequenced in the same flow cell as a batch, and to eliminate sex effects of X-linked CNVs by analyzing female and male sequences separately. We also applied several filtering steps for more efficient CNV selection. The average number of CNVs detected in one sample was <5. This optimization together with targeted CNV analysis by Nord's method identified pathogenic/likely pathogenic CNVs in 34 patients (4.5%, 34/763). In particular, among 142 patients with epilepsy, the current protocol detected clinically relevant CNVs in 19 (13.4%) patients, whereas the previous protocol identified them in only 14 (9.9%) patients. Thus, this batch-based XHMM analysis efficiently selected rare pathogenic CNVs in genetic diseases.