Global, pathway and gene coverage of three Illumina arrays with respect to inflammatory and immune-related pathways

Improving CNV Detection Performance in Microarray Data Using a Machine Learning-Based Approach

Copy number variation (CNV) is a primary source of structural variation in the human genome, leading to several disorders. Therefore, analyzing neonatal CNVs is crucial for managing CNV-related chromosomal disabilities. However, genomic waves can hinder accurate CNV analysis. To mitigate the influences of the waves, we adopted a machine learning approach and developed a new method that uses a modified log R ratio instead of the commonly used log R ratio. Validation results using samples with known CNVs demonstrated the superior performance of our method. We analyzed a total of 16,046 Korean newborn samples using the new method and identified CNVs related to 39 genetic disorders were identified in 342 cases. The most frequently detected CNV-related disorder was Joubert syndrome 4. The accuracy of our method was further confirmed by analyzing a subset of the detected results using NGS and comparing them with our results. The utilization of a genome-wide single nucleotide polymorphism array with wave offset was shown to be a powerful method for identifying CNVs in neonatal cases. The accurate screening and the ability to identify various disease susceptibilities offered by our new method could facilitate the identification of CNV-associated chromosomal disease etiologies.

Study Protocol: Interactive Dynamics of Coral Reef Fisheries and the Nutrition Transition in Kiribati

The Kiribati 2019 Integrated Household Income and Expenditure Survey (Integrated HIES) embeds novel ecological and human health research into an ongoing social and economic survey infrastructure implemented by the Pacific Community in partnership with national governments. This study seeks to describe the health status of a large, nationally representative sample of a geographically and socially diverse I-Kiribati population through multiple clinical measurements and detailed socio-economic surveys, while also conducting supporting food systems research on ecological, social, and institutional drivers of change. The specific hypotheses within this research relate to access to seafood and the potential nutritional and health benefits of these foods. We conducted this research in 21 of the 23 inhabited islands of Kiribati, excluding the two inhabited islands-Kanton Islands in the Phoenix Islands group with a population of 41 persons (2020 census) and Banaba Island in the Gilbert Islands group with a population of 333 persons (2020 census)-and focusing exclusively on the remaining islands in the Gilbert and Line Islands groups. Within this sample, we focused our intensive human health and ecological research in 10 of the 21 selected islands to examine the relationship between ecological conditions, resource governance, food system dynamics, and dietary patterns. Ultimately, this research has created a baseline for future Integrated HIES assessments to simultaneously monitor change in ecological, social, economic, and human health conditions and how they co-vary over time.

Iam hiQ-a novel pair of accuracy indices for imputed genotypes

BACKGROUND

Imputation of untyped markers is a standard tool in genome-wide association studies to close the gap between directly genotyped and other known DNA variants. However, high accuracy with which genotypes are imputed is fundamental. Several accuracy measures have been proposed and some are implemented in imputation software, unfortunately diversely across platforms. In the present paper, we introduce Iam hiQ, an independent pair of accuracy measures that can be applied to dosage files, the output of all imputation software. Iam (imputation accuracy measure) quantifies the average amount of individual-specific versus population-specific genotype information in a linear manner. hiQ (heterogeneity in quantities of dosages) addresses the inter-individual heterogeneity between dosages of a marker across the sample at hand.

RESULTS

Applying both measures to a large case-control sample of the International Lung Cancer Consortium (ILCCO), comprising 27,065 individuals, we found meaningful thresholds for Iam and hiQ suitable to classify markers of poor accuracy. We demonstrate how Manhattan-like plots and moving averages of Iam and hiQ can be useful to identify regions enriched with less accurate imputed markers, whereas these regions would by missed when applying the accuracy measure info (implemented in IMPUTE2).

CONCLUSION

We recommend using Iam hiQ additional to other accuracy scores for variant filtering before stepping into the analysis of imputed GWAS data.

Longitudinal Changes in Fecal Calprotectin Levels Among Pregnant Women With and Without Inflammatory Bowel Disease and Their Babies

BACKGROUND & AIMS

The effect of pregnancy on inflammatory bowel disease (IBD) remains poorly understood. We aimed to monitor intestinal inflammation using fecal calprotectin (FC) in pregnant women and their babies during early life.

METHODS

Pregnant women with or without IBD and their infants were prospectively enrolled. FC levels were measured at each trimester of pregnancy and in babies throughout the first 3 years of life. Repeated-measures analysis was applied to investigate changes in FC levels while adjusting for confounders. The FC levels were correlated with the bacterial abundance in both mothers and babies.

RESULTS

Six hundred and fourteen fecal samples from 358 mothers (98 with IBD) and 1005 fecal samples from 289 infants (76 born to IBD mothers) were analyzed. Pregnant Patients with IBD maintained higher FC levels through pregnancy compared with controls (P = 7.5 × 10^-54). FC gradually increased in controls and declined in Patients with IBD throughout pregnancy (P for interaction = 5.8 × 10^-7). Babies born to mothers with IBD presented with significantly higher FC levels than those born to controls up to 3 years of age, after adjusting for sex, delivery mode, feeding behavior, and antibiotics exposure (2 weeks to 3 months of age, P = .015; 12-36 months of age, P = .00003). Subdoligranulum, Roseburia, Fusicatenibacter, and Alistipes negatively correlated, and Streptococcus, Prevotella, Escherichia-Shigella, and Bifidobacterium positively correlated with maternal FC levels at T3. Faecalibacterium, Bifidobacterium, and Alistipes showed negative correlations, and Streptococcus were positively correlated with FC levels within 3 months of birth.

CONCLUSIONS

Pregnancy is associated with decreased inflammatory activity in mothers with IBD. Higher FC levels in babies born to mothers with IBD suggest subclinical inflammation in early life, the long-term consequences of which are uncertain.