Reproductive health for refugees by refugees in Guinea III: maternal health

BACKGROUND: Maternal mortality can be particularly high in conflict and chronic emergency settings, partly due to inaccessible maternal care. This paper examines associations of refugee-led health education, formal education, age, and parity on maternal knowledge, attitudes, and practices among reproductive-age women in refugee camps in Guinea. METHODS: Data comes from a 1999 cross-sectional survey of 444 female refugees in 23 camps. Associations of reported maternal health outcomes with exposure to health education (exposed versus unexposed), formal education (none versus some), age (adolescent versus adult), or parity (nulliparous, parous, grand multiparous), were analysed using logistic regression. RESULTS: No significant differences were found in maternal knowledge or attitudes. Virtually all respondents said pregnant women should attend antenatal care and knew the importance of tetanus vaccination. Most recognised abdominal pain (75%) and headaches (24%) as maternal danger signs and recommended facility attendance for danger signs. Most had last delivered at a facility (67%), mainly for safety reasons (99%). Higher odds of facility delivery were found for those exposed to RHG health education (adjusted odds ratio 2.03, 95%CI 1.23-3.01), formally educated (adjusted OR 1.93, 95%CI 1.05-3.92), or grand multipara (adjusted OR 2.13, 95%CI 1.21-3.75). Main reasons for delivering at home were distance to a facility (94%) and privacy (55%). CONCLUSIONS: Refugee-led maternal health education appeared to increase facility delivery for these refugee women. Improved knowledge of danger signs and the importance of skilled birth attendance, while vital, may be less important in chronic emergency settings than improving facility access where quality of care is acceptable

Finding Diagnostically Useful Patterns in Quantitative Phenotypic Data.

Trio-based whole-exome sequence (WES) data have established confident genetic diagnoses in ∼40% of previously undiagnosed individuals recruited to the Deciphering Developmental Disorders (DDD) study. Here we aim to use the breadth of phenotypic information recorded in DDD to augment diagnosis and disease variant discovery in probands. Median Euclidean distances (mEuD) were employed as a simple measure of similarity of quantitative phenotypic data within sets of ≥10 individuals with plausibly causative de novo mutations (DNM) in 28 different developmental disorder genes. 13/28 (46.4%) showed significant similarity for growth or developmental milestone metrics, 10/28 (35.7%) showed similarity in HPO term usage, and 12/28 (43%) showed no phenotypic similarity. Pairwise comparisons of individuals with high-impact inherited variants to the 32 individuals with causative DNM in ANKRD11 using only growth z-scores highlighted 5 likely causative inherited variants and two unrecognized DNM resulting in an 18% diagnostic uplift for this gene. Using an independent approach, naive Bayes classification of growth and developmental data produced reasonably discriminative models for the 24 DNM genes with sufficiently complete data. An unsupervised naive Bayes classification of 6,993 probands with WES data and sufficient phenotypic information defined 23 in silico syndromes (ISSs) and was used to test a "phenotype first" approach to the discovery of causative genotypes using WES variants strictly filtered on allele frequency, mutation consequence, and evidence of constraint in humans. This highlighted heterozygous de novo nonsynonymous variants in SPTBN2 as causative in three DDD probands

Prevalence, phenotype and architecture of developmental disorders caused by de novo mutation: The Deciphering Developmental Disorders Study

Individuals with severe, undiagnosed developmental disorders (DDs) are enriched for damaging de novo mutations (DNMs) in developmentally important genes. We exome sequenced 4,293 families with individuals with DDs, and meta-analysed these data with published data on 3,287 individuals with similar disorders. We show that the most significant factors influencing the diagnostic yield of de novo mutations are the sex of the affected individual, the relatedness of their parents and the age of both father and mother. We identified 94 genes enriched for damaging de novo mutation at genome-wide significance (P < 7 × 10−7), including 14 genes for which compelling data for causation was previously lacking. We have characterised the phenotypic diversity among these genetic disorders. We demonstrate that, at current cost differentials, exome sequencing has much greater power than genome sequencing for novel gene discovery in genetically heterogeneous disorders. We estimate that 42% of our cohort carry pathogenic DNMs (single nucleotide variants and indels) in coding sequences, with approximately half operating by a loss-of-function mechanism, and the remainder resulting in altered-function (e.g. activating, dominant negative). We established that most haplo insufficient developmental disorders have already been identified, but that many altered-function disorders remain to be discovered. Extrapolating from the DDD cohort to the general population, we estimate that developmental disorders caused by DNMs have an average birth prevalence of 1 in 213 to 1 in 448 (0.22-0.47% of live births), depending on parental age