An interactive atlas of three-dimensional syndromic facial morphology.

Craniofacial phenotyping is critical for both syndrome delineation and diagnosis because craniofacial abnormalities occur in 30% of characterized genetic syndromes. Clinical reports, textbooks, and available software tools typically provide two-dimensional, static images and illustrations of the characteristic phenotypes of genetic syndromes. In this work, we provide an interactive web application that provides three-dimensional, dynamic visualizations for the characteristic craniofacial effects of 95 syndromes. Users can visualize syndrome facial appearance estimates quantified from data and easily compare craniofacial phenotypes of different syndromes. Our application also provides a map of morphological similarity between a target syndrome and other syndromes. Finally, users can upload 3D facial scans of individuals and compare them to our syndrome atlas estimates. In summary, we provide an interactive reference for the craniofacial phenotypes of syndromes that allows for precise, individual-specific comparisons of dysmorphology.

Molecular characterization of 13 patients with PIK3CA-related overgrowth spectrum using a targeted deep sequencing approach.

Activating variants in the PIK3CA gene cause a heterogeneous spectrum of disorders that involve congenital or early-onset segmental/focal overgrowth, now referred to as PIK3CA-related overgrowth spectrum (PROS). Historically, the clinical diagnoses of patients with PROS included a range of distinct syndromes, including CLOVES syndrome, dysplastic megalencephaly, hemimegalencephaly, focal cortical dysplasia, Klippel-Trenaunay syndrome, CLAPO syndrome, fibroadipose hyperplasia or overgrowth, hemihyperplasia multiple lipomatosis, and megalencephaly capillary malformation-polymicrogyria (MCAP) syndrome. MCAP is a sporadic overgrowth disorder that exhibits core features of progressive megalencephaly, vascular malformations, distal limb malformations, cortical brain malformations, and connective tissue dysplasia. In 2012, our research group contributed to the identification of predominantly mosaic, gain-of-function variants in PIK3CA as an underlying genetic cause of the syndrome. Mosaic variants are technically more difficult to detect and require implementation of more sensitive sequencing technologies and less stringent variant calling algorithms. In this study, we demonstrated the utility of deep sequencing using the Illumina TruSight Oncology 500 (TSO500) sequencing panel in identifying variants with low allele fractions in a series of patients with PROS and suspected mosaicism: pathogenic, mosaic PIK3CA variants were identified in all 13 individuals, including 6 positive controls. This study highlights the importance of screening for low-level mosaic variants in PROS patients. The use of targeted panels with deep sequencing in clinical genetic testing laboratories would improve diagnostic yield and accuracy within this patient population.

Biallelic variants in ribonuclease inhibitor (RNH1), an inflammasome modulator, are associated with a distinctive subtype of acute, necrotizing encephalopathy.

PURPOSE: Mendelian etiologies for acute encephalopathies in previously healthy children are poorly understood, with the exception of RAN binding protein 2 (RANBP2)-associated acute necrotizing encephalopathy subtype 1 (ANE1). We provide clinical, genetic, and neuroradiological evidence that biallelic variants in ribonuclease inhibitor (RNH1) confer susceptibility to a distinctive ANE subtype. METHODS: This study aimed to evaluate clinical data, neuroradiological studies, genomic sequencing, and protein immunoblotting results in 8 children from 4 families who experienced acute febrile encephalopathy. RESULTS: All 8 healthy children became acutely encephalopathic during a viral/febrile illness and received a variety of immune modulation treatments. Long-term outcomes varied from death to severe neurologic deficits to normal outcomes. The neuroradiological findings overlapped with ANE but had distinguishing features. All affected children had biallelic predicted damaging variants in RNH1: a subset that was studied had undetectable RNH1 protein. Incomplete penetrance of the RNH1 variants was evident in 1 family. CONCLUSION: Biallelic variants in RNH1 confer susceptibility to a subtype of ANE (ANE2) in previously healthy children. Intensive immunological treatments may alter outcomes. Genomic sequencing in children with unexplained acute febrile encephalopathy can detect underlying genetic etiologies, such as RNH1, and improve outcomes in the probands and at-risk siblings.

Developing a Framework of Cost Elements of Socioeconomic Burden of Rare Disease: A Scoping Review.

BACKGROUND AND OBJECTIVE: Rare diseases place a significant burden on patients, families, the healthcare system, and society. Evidence on the socioeconomic burden of rare disease is limited and mostly reflects diseases where treatments are available. We developed a framework encompassing recommended cost elements for studies of the socioeconomic burden of rare diseases. METHODS: A scoping review, conducted in five databases (Cochrane Library, EconLit, Embase, MEDLINE, and APA PsycINFO), identified English language publications from 2000 to 2021 presenting frameworks developed for determining, measuring or valuing costs for rare or chronic diseases. Cost elements were extracted and used to develop a literature-informed framework. Structured feedback was gathered from experts in rare diseases, health economics/health services, and policy research to revise the framework. RESULTS: Of 2990 records identified, eight papers were included and informed our preliminary framework; three focused on rare disease and five on chronic disease. Following expert input, we developed a framework consisting of nine cost categories (inpatient, outpatient, community, healthcare products/goods, productivity/education, travel/accommodation, government benefits, family impacts, and other), with several cost elements within each category. Our framework includes unique costs, added from the expert feedback, including genetic testing to inform treatment, use of private laboratories or out-of-country testing, family involvement in foundations and organizations, and advocacy costs for special access programs. CONCLUSIONS: Our work is the first to identify a comprehensive list of cost elements for rare disease for use by researchers and policy makers to fully capture socioeconomic burden. Use of the framework will increase the quality and comparability of future studies. Future work should focus on measuring and valuing these costs through onset, diagnosis, and post-diagnosis.

Comparing 2D and 3D representations for face-based genetic syndrome diagnosis.

Human genetic syndromes are often challenging to diagnose clinically. Facial phenotype is a key diagnostic indicator for hundreds of genetic syndromes and computer-assisted facial phenotyping is a promising approach to assist diagnosis. Most previous approaches to automated face-based syndrome diagnosis have analyzed different datasets of either 2D images or surface mesh-based 3D facial representations, making direct comparisons of performance challenging. In this work, we developed a set of subject-matched 2D and 3D facial representations, which we then analyzed with the aim of comparing the performance of 2D and 3D image-based approaches to computer-assisted syndrome diagnosis. This work represents the most comprehensive subject-matched analyses to date on this topic. In our analyses of 1907 subject faces representing 43 different genetic syndromes, 3D surface-based syndrome classification models significantly outperformed 2D image-based models trained and evaluated on the same subject faces. These results suggest that the clinical adoption of 3D facial scanning technology and continued collection of syndromic 3D facial scan data may substantially improve face-based syndrome diagnosis.

Detecting 3D syndromic faces as outliers using unsupervised normalizing flow models.

Many genetic syndromes are associated with distinctive facial features. Several computer-assisted methods have been proposed that make use of facial features for syndrome diagnosis. Training supervised classifiers, the most common approach for this purpose, requires large, comprehensive, and difficult to collect databases of syndromic facial images. In this work, we use unsupervised, normalizing flow-based manifold and density estimation models trained entirely on unaffected subjects to detect syndromic 3D faces as statistical outliers. Furthermore, we demonstrate a general, user-friendly, gradient-based interpretability mechanism that enables clinicians and patients to understand model inferences. 3D facial surface scans of 2471 unaffected subjects and 1629 syndromic subjects representing 262 different genetic syndromes were used to train and evaluate the models. The flow-based models outperformed unsupervised comparison methods, with the best model achieving an ROC-AUC of 86.3% on a challenging, age and sex diverse data set. In addition to highlighting the viability of outlier-based syndrome screening tools, our methods generalize and extend previously proposed outlier scores for 3D face-based syndrome detection, resulting in improved performance for unsupervised syndrome detection.

Care4Rare Canada: Outcomes from a decade of network science for rare disease gene discovery.

The past decade has witnessed a rapid evolution in rare disease (RD) research, fueled by the availability of genome-wide (exome and genome) sequencing. In 2011, as this transformative technology was introduced to the research community, the Care4Rare Canada Consortium was launched: initially as FORGE, followed by Care4Rare, and Care4Rare SOLVE. Over what amounted to three eras of diagnosis and discovery, the Care4Rare Consortium used exome sequencing and, more recently, genome and other 'omic technologies to identify the molecular cause of unsolved RDs. We achieved a diagnostic yield of 34% (623/1,806 of participating families), including the discovery of deleterious variants in 121 genes not previously associated with disease, and we continue to study candidate variants in novel genes for 145 families. The Consortium has made significant contributions to RD research, including development of platforms for data collection and sharing and instigating a Canadian network to catalyze functional characterization research of novel genes. The Consortium was instrumental to implementing genome-wide sequencing as a publicly funded test for RD diagnosis in Canada. Despite the successes of the past decade, the challenge of solving all RDs remains enormous, and the work is far from over. We must leverage clinical and 'omic data for secondary use, develop tools and policies to support safe data sharing, continue to explore the utility of new and emerging technologies, and optimize research protocols to delineate complex disease mechanisms. Successful approaches in each of these realms is required to offer diagnostic clarity to all families with RDs.

A Deep Invertible 3-D Facial Shape Model for Interpretable Genetic Syndrome Diagnosis.

One of the primary difficulties in treating patients with genetic syndromes is diagnosing their condition. Many syndromes are associated with characteristic facial features that can be imaged and utilized by computer-assisted diagnosis systems. In this work, we develop a novel 3D facial surface modeling approach with the objective of maximizing diagnostic model interpretability within a flexible deep learning framework. Therefore, an invertible normalizing flow architecture is introduced to enable both inferential and generative tasks in a unified and efficient manner. The proposed model can be used (1) to infer syndrome diagnosis and other demographic variables given a 3D facial surface scan and (2) to explain model inferences to non-technical users via multiple interpretability mechanisms. The model was trained and evaluated on more than 4700 facial surface scans from subjects with 47 different syndromes. For the challenging task of predicting syndrome diagnosis given a new 3D facial surface scan, age, and sex of a subject, the model achieves a competitive overall top-1 accuracy of 71%, and a mean sensitivity of 43% across all syndrome classes. We believe that invertible models such as the one presented in this work can achieve competitive inferential performance while greatly increasing model interpretability in the domain of medical diagnosis.

Hnrnpul1 controls transcription, splicing, and modulates skeletal and limb development in vivo.

Mutations in RNA-binding proteins can lead to pleiotropic phenotypes including craniofacial, skeletal, limb, and neurological symptoms. Heterogeneous nuclear ribonucleoproteins (hnRNPs) are involved in nucleic acid binding, transcription, and splicing through direct binding to DNA and RNA, or through interaction with other proteins in the spliceosome. We show a developmental role for Hnrnpul1 in zebrafish, resulting in reduced body and fin growth and missing bones. Defects in craniofacial tendon growth and adult-onset caudal scoliosis are also seen. We demonstrate a role for Hnrnpul1 in alternative splicing and transcriptional regulation using RNA-sequencing, particularly of genes involved in translation, ubiquitination, and DNA damage. Given its cross-species conservation and role in splicing, it would not be surprising if it had a role in human development. Whole-exome sequencing detected a homozygous frameshift variant in HNRNPUL1 in 2 siblings with congenital limb malformations, which is a candidate gene for their limb malformations. Zebrafish Hnrnpul1 mutants suggest an important developmental role of hnRNPUL1 and provide motivation for exploring the potential conservation of ancient regulatory circuits involving hnRNPUL1 in human development.

The complexity of diagnosing rare disease: An organizing framework for outcomes research and health economics based on real-world evidence.

PURPOSE: To facilitate robust economic analyses of clinical exome and genome sequencing, this study was taken up with the objective of establishing a framework for organizing diagnostic testing trajectories for patients with rare disease. METHODS: We collected diagnostic investigations-related data before exome sequencing from the medical records of 228 cases. Medical geneticist experts participated in a consensus building process to develop the SOLVE Framework for organizing the complex range of observed tests. Experts categorized tests as indicator or nonindicator tests on the basis of their specificity for diagnosing rare diseases. Face validity was assessed using case vignettes. RESULTS: Most cases had symptom onset at birth (42.5%) or during childhood (43.4%) and had intellectual disability (73.3%). On average, the time spent seeking a diagnosis before sequencing was 1989 days (SD = 2137) and included 16 tests (SD = 14). Agreement across experts on test categories ranged from 83% to 96%. The SOLVE Framework comprised observed tests, including 186 indicator and 39 nonindicator tests across cytogenetic/molecular, biochemical, imaging, electrical, and pathology test categories. CONCLUSION: Real-world diagnostic testing data can be ascertained and organized to reflect the complexity of the journey of the patients with rare diseases. SOLVE Framework will improve the accuracy and certainty associated with value-based assessments of genomic sequencing.

IMPACT webinars: Improving Patient Access to genetic Counselling and Testing using webinars-the Alberta experience with hypertrophic cardiomyopathy.

Growing demand for genetic counselling and testing has created a need for innovative service delivery models to provide quality care in an efficient manner. The goal of this study was to develop and evaluate a patient-facing webinar providing pre-test genetic counselling to individuals with hypertrophic cardiomyopathy. A patient-facing webinar was developed and implemented between April 2019 and January 2021. It was evaluated using the Alberta Quality Matrix for Health framework, which considers the patient experience across the domains of effectiveness, appropriateness, acceptability, accessibility, and efficiency. The webinar group showed comparable scores to controls with regard to self-perceived knowledge and decisional conflict. The majority of patients reported that the webinar met their expectations and was an acceptable replacement for a 1:1 genetic counselling appointment. Finally, the webinar reduced genetic counsellor time to an average of 24 min per patient. Providing pre-test genetic counselling to index hypertrophic cardiomyopathy patients via a group webinar has achieved a high quality of care, and optimized use of provider and space resources.

Early Death of 2 Siblings Related to Mutations in LMOD2, a Recently Discovered Cause of Neonatal Dilated Cardiomyopathy.

We report a family with 2 neonatal deaths related to dilated cardiomyopathy (DCM) and compound heterozygous loss-of-function variants (c.1243_1244del, p.Leu415Valfs*108 and c.1537C > T, p.Arg513*) in Leiomodin 2 (LMOD2), a recently documented cause of early DCM. The phenotype in mice and humans consists of early, severe cardiac dilation and dysfunction related to decreased functional LMOD2, which results in abnormal actin filaments and abnormal myocardial contractility. Our cases confirm mutations in LMOD2 as a cause of DCM in humans and highlight the rapid changes occurring in cardiac genetics and the importance of reviewing previously negative genetic test results in the context of emerging literature.

Notre compte rendu concerne une famille dont deux nouveau-nés sont décédés des suites d'une cardiomyopathie dilatée (CMD) et qui présentaient une perte hétérozygote composite de variants fonctionnels (c.1243_1244del, p.Leu415Valfs*108 et c.1537C > T, p.Arg513*) du gène Leiomodin 2 (LMOD2), une cause récemment avérée de CMD précoce. Chez la souris et l'humain, le phénotype de cette anomalie consiste en une dilatation et une dysfonction cardiaques sévères précoces liées à une diminution de la fonction du gène LMOD2 entraînant des anomalies dans les filaments d'actine et la contractilité du myocarde. Nos cas permettent de confirmer que les mutations du gène LMOD2 sont une cause de CMD chez l'humain. Ils mettent en évidence les modifications rapides se produisant dans la génétique cardiaque et l'importance de revoir les résultats négatifs d'anciens tests génétiques à la lumière des nouvelles données publiées.

(Un)standardized testing: the diagnostic odyssey of children with rare genetic disorders in Alberta, Canada.

PURPOSE: We provide a description of the diagnostic odyssey for a cohort of children seeking diagnosis of a rare genetic disorder in terms of the time from initial consultation to most recent visit or receipt of diagnosis, the number of tests per patient, and the types of tests received. METHODS: Retrospective chart review of 299 children seen at the Alberta Children's Hospital (ACH) Genetics Clinic (GC) for whom the result of at least one single-gene test, gene panel, or chromosome microarray analysis (CMA) was recorded. RESULTS: Of 299 patients, 90 (30%) received a diagnosis in the period of the review. Patients had an average of 5.4 tests each; 236 (79%) patients received CMA; 172 (58%) patients received single-gene tests and 34 (11%) received gene panels; 167 (56%) underwent imaging/electrical activity studies. The mean observation period was 898 days (95% confidence interval [CI] 791, 1004). Among patients with visits recorded prior to visiting ACH GC, 43% of the total observation time occurred prior to the GC. CONCLUSION: As genomic technologies expand, the nature of the diagnostic odyssey will change. This study has outlined the current standard of care in the ACH GC, providing a baseline against which future changes can be assessed.

Effects of prenatal exposure and co-exposure to metallic or metalloid elements on early infant neurodevelopmental outcomes in areas with small-scale gold mining activities in Northern Tanzania.

BACKGROUND: Artisanal and small-scale gold mining (ASGM) is associated with release of neurotoxic metallic or metalloid chemical elements including lead (Pb), mercury (Hg), cadmium (Cd) and arsenic (As). OBJECTIVE: To examine associations between prenatal exposure and co-exposure to total lead (T-Pb), total mercury (T-Hg), total cadmium (T-Cd) and total arsenic (T-As) and infant neurodevelopment at 6 to 12 months of age in areas with ASGM activities in Tanzania. METHODS: Women in their second trimester of pregnancy who resided in ASGM areas were enrolled from 2015 to 2017 (n = 883). At 6 to 12 months of age, children were assessed with the Malawi Developmental Assessment Tool (MDAT) (n = 439). We measured T-Pb, T-Hg, and T-Cd in maternal dried blood spots and T-As in maternal urines. Poisson regression was used to examine associations between prenatal concentrations of these elements and neurodevelopmental outcomes. RESULTS: Prenatal T-Hg concentration was associated with global neurodevelopment status (aPR 1.03, CI:1.01-1.04; p < 0.001) and language impairment (aPR 1.05, CI:1.03-1.07; p < 0.001) on the MDAT. When prenatal T-Hg and T-As values were at or above the human biomonitoring reference values (≥95%) of the German Environmental Survey for Human Biomonitoring, that is 0.80 µg/L and 15 µg/L, respectively, the prevalence ratio of global neurodevelopmental impairment was two times higher (aPR 2.1, CI:1.0-4.3; p = 0.034). There was a 40% increase in the prevalence ratio of global neurodevelopmental impairment (aPR 1.4, CI:0.90-2.10, p = 0.027), when prenatal T-Hg was at or above the reference value of 0.80 µg/L and T-Pb was at or above the reference value of 35 µg/L. When prenatal T-Hg was at or above the reference value of 0.80 µg/L and T-As was at or above the reference value of 15 µg/L, the prevalence ratio of global neurodevelopmental impairment was two times higher (aPR 2.1, CI:1.0-4.3; p < 0.034). DISCUSSION: Infants born to women in areas with ASGM activities are at significant risk for neurodevelopmental impairment and this is associated with exposure to higher concentrations of Hg prenatally. Co-exposure to high concentrations of Hg and Pb, or Hg and As appeared to have negative potentiated effects on infants' neurodevelopment.

De novo variants in MPP5 cause global developmental delay and behavioral changes.

Membrane Protein Palmitoylated 5 (MPP5) is a highly conserved apical complex protein essential for cell polarity, fate and survival. Defects in cell polarity are associated with neurologic disorders including autism and microcephaly. MPP5 is essential for neurogenesis in animal models, but human variants leading to neurologic impairment have not been described. We identified three patients with heterozygous MPP5 de novo variants (DNV) and global developmental delay (GDD) and compared their phenotypes and magnetic resonance imaging (MRI) to ascertain how MPP5 DNV leads to GDD. All three patients with MPP5 DNV experienced GDD with language delay/regression and behavioral changes. MRI ranged from normal to decreased gyral folding and microcephaly. The effects of MPP5 depletion on the developing brain were assessed by creating a heterozygous conditional knock out (het CKO) murine model with central nervous system (CNS)-specific Nestin-Cre drivers. In the het CKO model, Mpp5 depletion led to microcephaly, decreased cerebellar volume and cortical thickness. Het CKO mice had decreased ependymal cells and Mpp5 at the apical surface of cortical ventricular zone compared with wild type. Het CKO mice also failed to maintain progenitor pools essential for neurogenesis. The proportion of cortical cells undergoing apoptotic cell death increased, suggesting that cell death reduces progenitor population and neuron number. Het CKO mice also showed behavioral changes, similar to our patients. To our knowledge, this is the first report to show that variants in MPP5 are associated with GDD, behavioral abnormalities and language regression/delay. Murine modeling shows that neurogenesis is likely altered in these individuals, with cell death and skewed cellular composition playing significant roles.

Prevalence rates study of selected isolated non-Mendelian congenital anomalies in the Hutterite population of Alberta, 1980-2016.

A study of the prevalence rates for selected isolated non-Mendelian congenital anomalies in the Hutterite Brethren of Alberta, Canada was undertaken to further examine longitudinal data in this isolated community that was last reported in 1985 (Lowry et al., 1985), although there are numerous publications on recessive disorders (Boycott et al., 2008; Triggs-Raine et al., 2016). Cases were ascertained from the Alberta Congenital Anomaly Surveillance System for the years 1997-2016. Since our initial results showed some surprising findings in the Hutterite Brethren, such as zero cases of spina bifida, cleft lip and palate, gastroschisis, and omphalocele, and a significant excess of cases with hypospadias, we extended the study to prior years (1980-1996) for selected anomalies. For the extended study period (1980-2016), there was a significant increased prevalence of hypospadias, tetralogy of Fallot and tricuspid atresia in the Hutterite population, and although not statistically significant, zero cases of cleft lip with cleft palate, gastroschisis and omphalocele were confirmed. Further research is needed to determine the precise effects of rural environmental exposures, lifestyle factors, and genetic associations for selected multifactorial congenital anomalies.

Automated syndrome diagnosis by three-dimensional facial imaging.

PURPOSE: Deep phenotyping is an emerging trend in precision medicine for genetic disease. The shape of the face is affected in 30-40% of known genetic syndromes. Here, we determine whether syndromes can be diagnosed from 3D images of human faces. METHODS: We analyzed variation in three-dimensional (3D) facial images of 7057 subjects: 3327 with 396 different syndromes, 727 of their relatives, and 3003 unrelated, unaffected subjects. We developed and tested machine learning and parametric approaches to automated syndrome diagnosis using 3D facial images. RESULTS: Unrelated, unaffected subjects were correctly classified with 96% accuracy. Considering both syndromic and unrelated, unaffected subjects together, balanced accuracy was 73% and mean sensitivity 49%. Excluding unrelated, unaffected subjects substantially improved both balanced accuracy (78.1%) and sensitivity (56.9%) of syndrome diagnosis. The best predictors of classification accuracy were phenotypic severity and facial distinctiveness of syndromes. Surprisingly, unaffected relatives of syndromic subjects were frequently classified as syndromic, often to the syndrome of their affected relative. CONCLUSION: Deep phenotyping by quantitative 3D facial imaging has considerable potential to facilitate syndrome diagnosis. Furthermore, 3D facial imaging of "unaffected" relatives may identify unrecognized cases or may reveal novel examples of semidominant inheritance.

Fully Automatic Landmarking of Syndromic 3D Facial Surface Scans Using 2D Images.

3D facial landmarks are known to be diagnostically relevant biometrics for many genetic syndromes. The objective of this study was to extend a state-of-the-art image-based 2D facial landmarking algorithm for the challenging task of 3D landmark identification on subjects with genetic syndromes, who often have moderate to severe facial dysmorphia. The automatic 3D facial landmarking algorithm presented here uses 2D image-based facial detection and landmarking models to identify 12 landmarks on 3D facial surface scans. The landmarking algorithm was evaluated using a test set of 444 facial scans with ground truth landmarks identified by two different human observers. Three hundred and sixty nine of the subjects in the test set had a genetic syndrome that is associated with facial dysmorphology. For comparison purposes, the manual landmarks were also used to initialize a non-linear surface-based registration of a non-syndromic atlas to each subject scan. Compared to the average intra- and inter-observer landmark distances of 1.1 mm and 1.5 mm respectively, the average distance between the manual landmark positions and those produced by the automatic image-based landmarking algorithm was 2.5 mm. The average error of the registration-based approach was 3.1 mm. Comparing the distributions of Procrustes distances from the mean for each landmarking approach showed that the surface registration algorithm produces a systemic bias towards the atlas shape. In summary, the image-based automatic landmarking approach performed well on this challenging test set, outperforming a semi-automatic surface registration approach, and producing landmark errors that are comparable to state-of-the-art 3D geometry-based facial landmarking algorithms evaluated on non-syndromic subjects.

Maternal exposure to arsenic and mercury and associated risk of adverse birth outcomes in small-scale gold mining communities in Northern Tanzania.

BACKGROUND: Exposure to arsenic and mercury in artisanal and small-scale gold mining (ASGM) communities is an issue that predominantly affects low and middle-income countries. Large epidemiology studies in these communities are rare, and the impact of such exposures on reproductive outcomes are not well understood. OBJECTIVE: To examine associations between prenatal maternal arsenic and mercury exposure and birth outcomes in both ASGM and non-ASGM communities in Northern Tanzania. METHODS: This longitudinal prospective study included 961 women (ASGM = 788, non-ASGM = 173) of the original cohort of 1056 who were followed until a pregnancy outcome was registered. Maternal spot urine samples and dried blood spots were used to measure total arsenic (T-As) and total mercury (T-Hg) in the second trimester of pregnancy. Data on adverse birth outcomes were collected in 5 categories: spontaneous abortion, stillbirth, preterm birth, low birth weight, and visible congenital anomalies. Mann-Whitney U-tests were used to test for differences between median T-As and T-Hg by area of residence. Logistic regression models were used to estimate the odds of stillbirth and visible congenital anomalies given maternal T-As and T-Hg levels. Modified Poisson regressions were used to estimate relative risk ratios between maternal T-As and T-Hg levels and composite adverse birth outcome, spontaneous abortion, low birth weight, and preterm birth. RESULTS: Statistically significant differences were found in median T-As (9.6 vs. 6.3 µg/L, Mann-Whitney U-tests, Z = -3.50, p < 0.001) and median T-Hg blood concentrations (1.2 vs. 0.70 µg/L, Z = -9.88, p-value < 0.001) between women living in ASGM and non-ASGM areas respectively. In ASGM areas, the adjusted relative risk (aRR) of a composite adverse birth outcome increased with increasing T-As (aRR 1.23, 95%CI: 1.14-1.33, p < 0.0001) and T-Hg (aRR 1.17, 95%CI: 1.1-1.25, p < 0.0001) exposure. Spontaneous abortion (aRR 1.53, 95%CI: 1.28-1.83), stillbirth (adjusted odds ratio (aOR) 1.97, 95%CI: 1.45-2.66) and preterm birth (1.17, 95%CI: 1.01-1.36) were significantly associated with elevated T-As, whereas elevated T-Hg was significantly associated with stillbirth (aOR 2.49, 95%CI: 1.88-3.29) and visible congenital anomalies (aOR 2.24, 95%CI: 1.3-3.87). CONCLUSION: Over half (54.7%) of women in ASGM areas of Northern Tanzania had adverse birth outcomes and the risk of adverse birth outcomes was significantly associated with increased prenatal exposure to arsenic and mercury.

Enabling Global Clinical Collaborations on Identifiable Patient Data: The Minerva Initiative.

The clinical utility of computational phenotyping for both genetic and rare diseases is increasingly appreciated; however, its true potential is yet to be fully realized. Alongside the growing clinical and research availability of sequencing technologies, precise deep and scalable phenotyping is required to serve unmet need in genetic and rare diseases. To improve the lives of individuals affected with rare diseases through deep phenotyping, global big data interrogation is necessary to aid our understanding of disease biology, assist diagnosis, and develop targeted treatment strategies. This includes the application of cutting-edge machine learning methods to image data. As with most digital tools employed in health care, there are ethical and data governance challenges associated with using identifiable personal image data. There are also risks with failing to deliver on the patient benefits of these new technologies, the biggest of which is posed by data siloing. The Minerva Initiative has been designed to enable the public good of deep phenotyping while mitigating these ethical risks. Its open structure, enabling collaboration and data sharing between individuals, clinicians, researchers and private enterprise, is key for delivering precision public health.