Identifying primary and secondary MLH1 epimutation carriers displaying low-level constitutional MLH1 methylation using droplet digital PCR and genome-wide DNA methylation profiling of colorectal cancers.

BACKGROUND: MLH1 epimutation is characterised by constitutional monoallelic MLH1 promoter hypermethylation, which can cause colorectal cancer (CRC). Tumour molecular profiles of MLH1 epimutation CRCs were used to classify germline MLH1 promoter variants of uncertain significance and MLH1 methylated early-onset CRCs (EOCRCs). Genome-wide DNA methylation and somatic mutational profiles of tumours from two germline MLH1: c.-11C > T and one MLH1: c.-[28A > G; 7C > T] carriers and three MLH1 methylated EOCRCs (< 45 years) were compared with 38 reference CRCs. Methylation-sensitive droplet digital PCR (ddPCR) was used to detect mosaic MLH1 methylation in blood, normal mucosa and buccal DNA. RESULTS: Genome-wide methylation-based Consensus Clustering identified four clusters where the tumour methylation profiles of germline MLH1: c.-11C > T carriers and MLH1 methylated EOCRCs clustered with the constitutional MLH1 epimutation CRCs but not with the sporadic MLH1 methylated CRCs. Furthermore, monoallelic MLH1 methylation and APC promoter hypermethylation in tumour were observed in both MLH1 epimutation and germline MLH1: c.-11C > T carriers and MLH1 methylated EOCRCs. Mosaic constitutional MLH1 methylation in MLH1: c.-11C > T carriers and 1 of 3 MLH1 methylated EOCRCs was identified by methylation-sensitive ddPCR. CONCLUSIONS: Mosaic MLH1 epimutation underlies the CRC aetiology in MLH1: c.-11C > T germline carriers and a subset of MLH1 methylated EOCRCs. Tumour profiling and ultra-sensitive ddPCR methylation testing can be used to identify mosaic MLH1 epimutation carriers.

Implementing autonomy in a diabetes management system.

We have developed a speech-based telemedicine system which enables patients with hypertension and type 2 diabetes mellitus to send frequent, home-monitored health data via the telephone to the point of care. The decision support module in the system was tested using data from a cohort of 10 patients generated over a two-year period. Results from the tests indicate that the system is effective in providing personalized feedback to the patient and in generating alerts for the clinical user. The work suggests that this method of care delivery is practical, informative, and may improve the efficiency of chronic health-care delivery by reducing costs and improving patient-physician communication between hospital visits.