Background: Improvements in mobile telecommunication technologies have enabled clinicians to collect patient-reported outcome (PRO) data more frequently, but there is as yet limited evidence regarding the frequency with which PRO data can be collected via smartphone applications (apps) in breast cancer patients receiving chemotherapy. Objective: The primary objective of this study was to determine the feasibility of an app for sleep disturbance-related data collection from breast cancer patients receiving chemotherapy. A secondary objective was to identify the variables associated with better compliance in order to identify the optimal subgroups to include in future studies of smartphone-based interventions. Methods: Between March 2013 and July 2013, patients who planned to receive neoadjuvant chemotherapy for breast cancer at Asan Medical Center who had access to a smartphone app were enrolled just before the start of their chemotherapy and asked to self-report their sleep patterns, anxiety severity, and mood status via a smartphone app on a daily basis during the 90-day study period. Push notifications were sent to participants daily at 9 am and 7 pm. Data regarding the patients’ demographics, interval from enrollment to first self-report, baseline Beck’s Depression Inventory (BDI) score, and health-related quality of life score (as assessed using the EuroQol Five Dimensional [EQ5D-3L] questionnaire) were collected to ascertain the factors associated with compliance with the self-reporting process. Results: A total of 30 participants (mean age 45 years, SD 6; range 35-65 years) were analyzed in this study. In total, 2700 daily push notifications were sent to these 30 participants over the 90-day study period via their smartphones, resulting in the collection of 1215 self-reporting sleep-disturbance data items (overall compliance rate=45.0%, 1215/2700). The median value of individual patient-level reporting rates was 41.1% (range 6.7-95.6%). The longitudinal day-level compliance curve fell to 50.0% at day 34 and reached a nadir of 13.3% at day 90. The cumulative longitudinal compliance curve exhibited a steady decrease by about 50% at day 70 and continued to fall to 45% on day 90. Women without any form of employment exhibited the higher compliance rate. There was no association between any of the other patient characteristics (ie, demographics, and BDI and EQ5D-3L scores) and compliance. The mean individual patient-level reporting rate was higher for the subgroup with a 1-day lag time, defined as starting to self-report on the day immediately after enrollment, than for those with a lag of 2 or more days (51.6%, SD 24.0 and 29.6%, SD 25.3, respectively; P=.03). Conclusions: The 90-day longitudinal collection of daily self-reporting sleep-disturbance data via a smartphone app was found to be feasible. Further research should focus on how to sustain compliance with this self-reporting for a longer time and select subpopulations with higher rates of compliance for mobile health care.

To estimate the current cancer burden in Korea, newly diagnosed cancer cases and cancer incidence rates were calculated for the years 2003~2005. The cancer incidence cases and rates were calculated from the Korea National Cancer Incidence Database. Crude and age-standardized incidence rates were calculated by gender for specified cancer sites in 5-year age groups. From 2003 to 2005, 398,824 cases of cancer were newly diagnosed in Korea (218,856 in men and 179,968 in women). For all sites combined, the crude incidence rate (CR) was 300.0 and 248.2 for men and women and the age-standardized incidence rate (ASR) was 297.0 and 191.2 per 100,000, respectively. Among men, five leading cancers were stomach (CR 66.0, ASR 64.2), lung (CR 48.5, ASR 50.3), liver (CR 44.9, ASR 42.1), colon and rectum (CR 37.9, ASR 37.2), and prostate cancer (CR 12.7, ASR 13.8). Among women, five leading cancers were breast (CR 37.3, ASR 29.0), thyroid (CR 36.2, ASR 28.8), stomach (CR 34.1, ASR 25.4), colon and rectum (CR 28.0, ASR 21.1), and lung cancer (CR 17.9, ASR 12.8). In the 0~14-year-old group, leukemia was the most common in both sexes; in the 15~34 group, the most common cancer was stomach cancer for men and thyroid cancer for women; in the 35~64 group, stomach cancer for men and breast cancer for women; among those 65 and over, lung cancer for men and stomach cancer, for women, respectively. The cancer incidence rates have increased in recent years, and more cancers are expected to develop as Korea is quickly becoming an aged society. The cancer incidence statistics in this report can be used as an important source to effectively plan and evaluate the cancer control program in Korea.

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Several recent studies showed that next-generation sequencing (NGS)-based human leukocyte antigen (HLA) typing is a feasible and promising technique for variant calling of highly polymorphic regions. To date, however, no method with sufficient read depth has completely solved the allele phasing issue. In this study, we developed a new method (HLAscan) for HLA genotyping using NGS data. HLAscan performs alignment of reads to HLA sequences from the international ImMunoGeneTics project/human leukocyte antigen (IMGT/HLA) database. The distribution of aligned reads was used to calculate a score function to determine correctly phased alleles by progressively removing false-positive alleles. Comparative HLA typing tests using public datasets from the 1000 Genomes Project and the International HapMap Project demonstrated that HLAscan could perform HLA typing more accurately than previously reported NGS-based methods such as HLAreporter and PHLAT. In addition, the results of HLA-A, −B, and -DRB1 typing by HLAscan using data generated by NextGen were identical to those obtained using a Sanger sequencing–based method. We also applied HLAscan to a family dataset with various coverage depths generated on the Illumina HiSeq X-TEN platform. HLAscan identified allele types of HLA-A, −B, −C, −DQB1, and -DRB1 with 100% accuracy for sequences at ≥ 90× depth, and the overall accuracy was 96.9%. HLAscan, an alignment-based program that takes read distribution into account to determine true allele types, outperformed previously developed HLA typing tools. Therefore, HLAscan can be reliably applied for determination of HLA type across the whole-genome, exome, and target sequences.

The skin is the outermost layer of the human body and one of the key sites for host-microbe interactions. Both environmental and host genetic factors influence microbial communities in distinct anatomical niches, but little is known about their interplay in shaping the skin microbiome. Here, we investigate the heritable components of the skin microbiome and their association with host genetic factors. Based on our analysis of the microbiota from 45 individuals including monozygotic and dizygotic twins aged 26–55 years and their mothers, we found that skin microbial diversity was significantly influenced by age and skin pigmentation. Heritability analysis revealed genetic and shared environmental impacts on the skin microbiome. Furthermore, we observed a strong association between the abundance of Corynebacterium jeikeium and single nucleotide polymorphisms (SNPs) in the host FLG gene related to epidermal barrier function. This study reveals an intimate association of the human skin microbiome and host genes, and increases our understanding of the role of human genetic factors in establishing a microbial ecosystem on the body surface.

Determining valid zygosity is a basic and important requirement in a twin study, because misdiagnosing zygosity leads to biased results. The Healthy Twin Study has collected data from adult like-sex twins and their families since 2005. In the study, a questionnaire to determine zygosity was developed comprising four questions; one concerning the degree of resemblance, and three concerning the degree of confusion by the resemblance. Among 2,761 individuals (624 twin pairs) of twin and their families, 406 pairs of twins (mean age 38.3, 63.5% women) with both questionnaire and genotype information were selected to examine the validity of the zygosity questionnaire using 16 short tandem repeat markers. We first determined individual zygosity including undetermined category, and then decided the zygosity of a twin pair using a decision tree. Sensitivity of questionnaire diagnosis was 98.8% for monozygotic (MZ) and 88.9% for dizygotic (DZ) twins, and positive predictive value was 97.2% for MZ and 95.0% for DZ. When we compared correctly and wrongly diagnosed twin pairs, misdiagnosed DZ twins (nine pairs) showed striking similarity in stature or obesity even exceeding that of true MZ twins. Our finding suggests that a parsimonious questionnaire method of diagnosing the zygosity will be useful, and adding physical or physiological measurements to a questionnaire of zygosity diagnosis will either confound the correct diagnosis or reduce the efficiency of the study compared with using questionnaire alone or with introducing genotyping.