Increased diagnostic yield from negative whole genome-slice panels using automated reanalysis.

We evaluated the diagnostic yield using genome-slice panel reanalysis in the clinical setting using an automated phenotype/gene ranking system. We analyzed whole genome sequencing (WGS) data produced from clinically ordered panels built as bioinformatic slices for 16 clinically diverse, undiagnosed cases referred to the Pediatric Mendelian Genomics Research Center, an NHGRI-funded GREGoR Consortium site. Genome-wide reanalysis was performed using Moon™, a machine-learning-based tool for variant prioritization. In five out of 16 cases, we discovered a potentially clinically significant variant. In four of these cases, the variant was found in a gene not included in the original panel due to phenotypic expansion of a disorder or incomplete initial phenotyping of the patient. In the fifth case, the gene containing the variant was included in the original panel, but being a complex structural rearrangement with intronic breakpoints outside the clinically analyzed regions, it was not initially identified. Automated genome-wide reanalysis of clinical WGS data generated during targeted panels testing yielded a 25% increase in diagnostic findings and a possibly clinically relevant finding in one additional case, underscoring the added value of analyses versus those routinely performed in the clinical setting.

Food insecurity among women of reproductive age in Nepal: prevalence and correlates.

BACKGROUND: Food insecurity is widely prevalent in certain sections of society in low and middle-income countries. The United Nations has challenged all member countries to eliminate hunger for all people by 2030. This study examines the prevalence and correlates of household food insecurity among women, especially Dalit women of reproductive age in Nepal. METHODS: Data came from 2016 Nepal Demographic Health Survey, a cross-sectional, nationally representative survey that included 12,862 women between 15 and 49 years of age of which 12% were Dalit. Descriptive analysis was used to assess the prevalence of household food insecurity while logistic regression examined the relationship between women's ethnicity and the risk of food insecurity after accounting for demographic, economic, cultural, and geo-ecological characteristics. RESULTS: About 56% of all women and 76% of Dalit women had experienced food insecurity. Ethnicity is strongly related to food insecurity. Dalit women were most likely to be food insecure, even after accounting for factors such as education and wealth. They were 82, 85, 89 and 92% more vulnerable to food insecurity than Muslims, Brahmin/Chhetri, Terai Indigenous, and Hill Indigenous populations, respectively. Education was a protective factor-women with secondary education (6th to 10th grade) were 39% less likely to be food insecure compared to their counterparts without education. With a more than 10th grade education, women were 2.27 times more likely to be food secure compared to their counterparts without education. Marriage was also protective. Economically, household wealth is inversely correlated with food insecurity. Finally, residence in the Mid-Western, Far-Western and Central Development regions was correlated with food insecurity. CONCLUSION: To reduce food insecurity in Nepal, interventions should focus on improving women's education and wealth, especially among Dalit and those residing in the Far- and Mid-Western regions.

Racial and Ethnic Disparities in the Lifetime Prevalence of Homelessness in the United States.

Homelessness in the United States is often examined using cross-sectional, point-in-time samples. Any experience of homelessness is a risk factor for adverse outcomes, so it is also useful to understand the incidence of homelessness over longer periods. We estimate the lifetime prevalence of homelessness among members of the Baby Boom cohort (n = 6,545) using the 2012 and 2014 waves of the Health and Retirement Study (HRS), a nationally representative survey of older Americans. Our analysis indicates that 6.2 % of respondents had a period of homelessness at some point in their lives. We also identify dramatic disparities in lifetime incidence of homelessness by racial and ethnic subgroups. Rates of homelessness were higher for non-Hispanic blacks (16.8 %) or Hispanics of any race (8.1 %) than for non-Hispanic whites (4.8 %; all differences significant with p < .05). The black-white gap, but not the Hispanic-white gap, remained significant after adjustment for covariates such as education, veteran status, and geographic region.

A Python package for parsing, validating, mapping and formatting sequence variants using HGVS nomenclature.

UNLABELLED: Biological sequence variants are commonly represented in scientific literature, clinical reports and databases of variation using the mutation nomenclature guidelines endorsed by the Human Genome Variation Society (HGVS). Despite the widespread use of the standard, no freely available and comprehensive programming libraries are available. Here we report an open-source and easy-to-use Python library that facilitates the parsing, manipulation, formatting and validation of variants according to the HGVS specification. The current implementation focuses on the subset of the HGVS recommendations that precisely describe sequence-level variation relevant to the application of high-throughput sequencing to clinical diagnostics. AVAILABILITY AND IMPLEMENTATION: The package is released under the Apache 2.0 open-source license. Source code, documentation and issue tracking are available at http://bitbucket.org/hgvs/hgvs/. Python packages are available at PyPI (https://pypi.python.org/pypi/hgvs). SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

A systems approach to designing effective clinical trials using simulations.

BACKGROUND: Pharmacogenetics in warfarin clinical trials have failed to show a significant benefit in comparison with standard clinical therapy. This study demonstrates a computational framework to systematically evaluate preclinical trial design of target population, pharmacogenetic algorithms, and dosing protocols to optimize primary outcomes. METHODS AND RESULTS: We programmatically created an end-to-end framework that systematically evaluates warfarin clinical trial designs. The framework includes options to create a patient population, multiple dosing strategies including genetic-based and nongenetic clinical-based, multiple-dose adjustment protocols, pharmacokinetic/pharmacodynamics modeling and international normalization ratio prediction, and various types of outcome measures. We validated the framework by conducting 1000 simulations of the applying pharmacogenetic algorithms to individualize dosing of warfarin (CoumaGen) clinical trial primary end points. The simulation predicted a mean time in therapeutic range of 70.6% and 72.2% (P=0.47) in the standard and pharmacogenetic arms, respectively. Then, we evaluated another dosing protocol under the same original conditions and found a significant difference in the time in therapeutic range between the pharmacogenetic and standard arm (78.8% versus 73.8%; P=0.0065), respectively. CONCLUSIONS: We demonstrate that this simulation framework is useful in the preclinical assessment phase to study and evaluate design options and provide evidence to optimize the clinical trial for patient efficacy and reduced risk.

Using a chat-based informed consent tool in large-scale genomic research.

OBJECTIVE: We implemented a chatbot consent tool to shift the time burden from study staff in support of a national genomics research study. MATERIALS AND METHODS: We created an Institutional Review Board-approved script for automated chat-based consent. We compared data from prospective participants who used the tool or had traditional consent conversations with study staff. RESULTS: Chat-based consent, completed on a user's schedule, was shorter than the traditional conversation. This did not lead to a significant change in affirmative consents. Within affirmative consents and declines, more prospective participants completed the chat-based process. A quiz to assess chat-based consent user understanding had a high pass rate with no reported negative experiences. CONCLUSION: Our report shows that a structured script can convey important information while realizing the benefits of automation and burden shifting. Analysis suggests that it may be advantageous to use chatbots to scale this rate-limiting step in large research projects.

Heterozygous loss-of-function SMC3 variants are associated with variable growth and developmental features.

Heterozygous missense variants and in-frame indels in SMC3 are a cause of Cornelia de Lange syndrome (CdLS), marked by intellectual disability, growth deficiency, and dysmorphism, via an apparent dominant-negative mechanism. However, the spectrum of manifestations associated with SMC3 loss-of-function variants has not been reported, leading to hypotheses of alternative phenotypes or even developmental lethality. We used matchmaking servers, patient registries, and other resources to identify individuals with heterozygous, predicted loss-of-function (pLoF) variants in SMC3, and analyzed population databases to characterize mutational intolerance in this gene. Here, we show that SMC3 behaves as an archetypal haploinsufficient gene: it is highly constrained against pLoF variants, strongly depleted for missense variants, and pLoF variants are associated with a range of developmental phenotypes. Among 14 individuals with SMC3 pLoF variants, phenotypes were variable but coalesced on low growth parameters, developmental delay/intellectual disability, and dysmorphism, reminiscent of atypical CdLS. Comparisons to individuals with SMC3 missense/in-frame indel variants demonstrated an overall milder presentation in pLoF carriers. Furthermore, several individuals harboring pLoF variants in SMC3 were nonpenetrant for growth, developmental, and/or dysmorphic features, and some had alternative symptomatologies with rational biological links to SMC3. Analyses of tumor and model system transcriptomic data and epigenetic data in a subset of cases suggest that SMC3 pLoF variants reduce SMC3 expression but do not strongly support clustering with functional genomic signatures of typical CdLS. Our finding of substantial population-scale LoF intolerance in concert with variable growth and developmental features in subjects with SMC3 pLoF variants expands the scope of cohesinopathies, informs on their allelic architecture, and suggests the existence of additional clearly LoF-constrained genes whose disease links will be confirmed only by multilayered genomic data paired with careful phenotyping.

Racial and Ethnic Disparities in Food Insufficiency in Families with Children During the COVID-19 Pandemic: the Role of Risk and Protective Factors.

BACKGROUND: Black and Hispanic households are at elevated risk of food insecurity and insufficiency-correlates of adverse outcomes in areas such as health and mental health-relative to White households in the USA. The COVID-19 pandemic and its economic shock threatened to further exacerbate these issues. Research has identified a number of risk and protective factors for food insecurity and insufficiency. These could relate to racial and ethnic disparities in two ways-through aggregate differences in the distribution of characteristics such as educational attainment and employment or through differences in the degree of risk or protection associated with a factor. We examined the relationship between four factors-household head age, educational attainment, single mother household composition, and employment-and disparities in food insufficiency between White, Black, and Hispanic households with children during the COVID-19 pandemic to consider these pathways. METHODS: We analyzed data from the Census Bureau's Household Pulse Survey using bivariate statistics, multivariable regression, and decomposition methods to understand differences in the prevalence and consequences of underlying risk and protective factors for food insufficiency in households with children. RESULTS: Consistent with prior literature, we documented higher rates of food insufficiency among Black and Hispanic households compared to White households. Differences in the distributions of education and employment accounted for a substantial fraction of the disparities in risk. Both the distribution and degree of risk associated with single mother household composition also related to disparities, but these differences were muted after accounting for economic resources. Much, though not all, of the relationship between the distributions of education and disparate risk of food insufficiency were also captured by differences in economic resources. CONCLUSION: This study provides insight into the structure underlying racial and ethnic disparities in food insufficiency during the COVID-19 pandemic, highlighting the importance of human capital, income, and assets.

"Development and Implementation of Novel Chatbot-based Genomic Research Consent".

Objective: To conduct a retrospective analysis comparing traditional human-based consenting to an automated chat-based consenting process. Materials and Methods: We developed a new chat-based consent using our IRB-approved consent forms. We leveraged a previously developed platform (GiaⓇ, or "Genetic Information Assistant") to deliver the chat content to candidate participants. The content included information about the study, educational information, and a quiz to assess understanding. We analyzed 144 families referred to our study during a 6-month time period. A total of 37 families completed consent using the traditional process, while 35 families completed consent using Gia. Results: Engagement rates were similar between both consenting methods. The median length of the consent conversation was shorter for Gia users compared to traditional (44 vs. 76 minutes). Additionally, the total time from referral to consent completion was faster with Gia (5 vs. 16 days). Within Gia, understanding was assessed with a 10-question quiz that most participants (96%) passed. Feedback about the chat consent indicated that 86% of participants had a positive experience. Discussion: Using Gia resulted in time savings for both the participant and study staff. The chatbot enables studies to reach more potential candidates. We identified five key features related to human-centered design for developing a consent chat. Conclusion: This analysis suggests that it is feasible to use an automated chatbot to scale obtaining informed consent for a genomics research study. We further identify a number of advantages when using a chatbot.

Heterozygous loss-of-function SMC3 variants are associated with variable and incompletely penetrant growth and developmental features.

Heterozygous missense variants and in-frame indels in SMC3 are a cause of Cornelia de Lange syndrome (CdLS), marked by intellectual disability, growth deficiency, and dysmorphism, via an apparent dominant-negative mechanism. However, the spectrum of manifestations associated with SMC3 loss-of-function variants has not been reported, leading to hypotheses of alternative phenotypes or even developmental lethality. We used matchmaking servers, patient registries, and other resources to identify individuals with heterozygous, predicted loss-of-function (pLoF) variants in SMC3, and analyzed population databases to characterize mutational intolerance in this gene. Here, we show that SMC3 behaves as an archetypal haploinsufficient gene: it is highly constrained against pLoF variants, strongly depleted for missense variants, and pLoF variants are associated with a range of developmental phenotypes. Among 13 individuals with SMC3 pLoF variants, phenotypes were variable but coalesced on low growth parameters, developmental delay/intellectual disability, and dysmorphism reminiscent of atypical CdLS. Comparisons to individuals with SMC3 missense/in-frame indel variants demonstrated a milder presentation in pLoF carriers. Furthermore, several individuals harboring pLoF variants in SMC3 were nonpenetrant for growth, developmental, and/or dysmorphic features, some instead having intriguing symptomatologies with rational biological links to SMC3 including bone marrow failure, acute myeloid leukemia, and Coats retinal vasculopathy. Analyses of transcriptomic and epigenetic data suggest that SMC3 pLoF variants reduce SMC3 expression but do not result in a blood DNA methylation signature clustering with that of CdLS, and that the global transcriptional signature of SMC3 loss is model-dependent. Our finding of substantial population-scale LoF intolerance in concert with variable penetrance in subjects with SMC3 pLoF variants expands the scope of cohesinopathies, informs on their allelic architecture, and suggests the existence of additional clearly LoF-constrained genes whose disease links will be confirmed only by multi-layered genomic data paired with careful phenotyping.

Biomedical cloud computing with Amazon Web Services.

In this overview to biomedical computing in the cloud, we discussed two primary ways to use the cloud (a single instance or cluster), provided a detailed example using NGS mapping, and highlighted the associated costs. While many users new to the cloud may assume that entry is as straightforward as uploading an application and selecting an instance type and storage options, we illustrated that there is substantial up-front effort required before an application can make full use of the cloud's vast resources. Our intention was to provide a set of best practices and to illustrate how those apply to a typical application pipeline for biomedical informatics, but also general enough for extrapolation to other types of computational problems. Our mapping example was intended to illustrate how to develop a scalable project and not to compare and contrast alignment algorithms for read mapping and genome assembly. Indeed, with a newer aligner such as Bowtie, it is possible to map the entire African genome using one m2.2xlarge instance in 48 hours for a total cost of approximately $48 in computation time. In our example, we were not concerned with data transfer rates, which are heavily influenced by the amount of available bandwidth, connection latency, and network availability. When transferring large amounts of data to the cloud, bandwidth limitations can be a major bottleneck, and in some cases it is more efficient to simply mail a storage device containing the data to AWS (http://aws.amazon.com/importexport/). More information about cloud computing, detailed cost analysis, and security can be found in references.

State Variation in TANF Expenditures: Implications for Social Work and Social Policy.

The Temporary Assistance for Needy Families (TANF) program is a federal block grant to the states, with a required state contribution. Although often viewed as a cash assistance program with work requirements and services targeted at extremely low-income families with children, only about one-quarter of all state and federal TANF funds are now used for traditional cash aid. Uses of funds vary widely by state, and alternatives range from refundable tax credits to support of state child welfare systems. In this article, the author examines the relationship between state categorical TANF spending and key social, political, and economic characteristics using data from 2015 to 2017 and multilevel linear models. Racial and ethnic demographics of the cash assistance caseload are associated with differences in spending, with states with larger proportions of the caseload composed of people of color devoting a lower percentage of effort to traditional benefits and more to alternative cash transfers. Changes in unemployment rate within states are associated with greater spending on basic assistance and reduced spending on alternative transfers. These findings indicate that, although TANF cash benefits spending may be economically responsive within the program's overall flexible structure, spending patterns raise issues of equity for disadvantaged families.

Trans-ethnic variation in germline variants of patients with renal cell carcinoma.

Prior studies of the renal cell carcinoma (RCC) germline landscape investigated predominantly patients of European ancestry. We examine the frequency of germline pathogenic and likely pathogenic (P/LP) variants in 1,829 patients with RCC from various ancestries. Overall, P/LP variants are found in 17% of patients, among whom 10.3% harbor one or more clinically actionable variants with potential preventive or therapeutic utility. Patients of African ancestry with RCC harbor significantly more P/LP variants in FH compared to patients of non-African ancestry with RCC and African controls from the Genome Aggregation Database (gnomAD). Patients of non-African ancestry have significantly more P/LP variants in CHEK2 compared to patients of African ancestry with RCC and non-Finnish Europeans controls. Non-Africans with RCC have more actionable variants compared to Africans with RCC. This work helps understand the underlying biological differences in RCC between Africans and non-Africans and paves the way to more comprehensive genomic characterization of underrepresented populations.

Cloud computing for comparative genomics.

BACKGROUND: Large comparative genomics studies and tools are becoming increasingly more compute-expensive as the number of available genome sequences continues to rise. The capacity and cost of local computing infrastructures are likely to become prohibitive with the increase, especially as the breadth of questions continues to rise. Alternative computing architectures, in particular cloud computing environments, may help alleviate this increasing pressure and enable fast, large-scale, and cost-effective comparative genomics strategies going forward. To test this, we redesigned a typical comparative genomics algorithm, the reciprocal smallest distance algorithm (RSD), to run within Amazon's Elastic Computing Cloud (EC2). We then employed the RSD-cloud for ortholog calculations across a wide selection of fully sequenced genomes. RESULTS: We ran more than 300,000 RSD-cloud processes within the EC2. These jobs were farmed simultaneously to 100 high capacity compute nodes using the Amazon Web Service Elastic Map Reduce and included a wide mix of large and small genomes. The total computation time took just under 70 hours and cost a total of $6,302 USD. CONCLUSIONS: The effort to transform existing comparative genomics algorithms from local compute infrastructures is not trivial. However, the speed and flexibility of cloud computing environments provides a substantial boost with manageable cost. The procedure designed to transform the RSD algorithm into a cloud-ready application is readily adaptable to similar comparative genomics problems.

Immunoaffinity enrichment and liquid chromatography-selected reaction monitoring mass spectrometry for quantitation of carbonic anhydrase 12 in cultured renal carcinoma cells.

Liquid chromatography-selected reaction monitoring (LC-SRM) is a highly specific and sensitive mass spectrometry (MS) technique that is widely being applied to selectively qualify and validate candidate markers within complex biological samples. However, in order for LC-SRM methods to take on these attributes, target-specific optimization of sample processing is required, in order to reduce analyte complexity, prior to LC-SRM. In this study, we have developed a targeted platform consisting of protein immunoaffinity enrichment on magnetic beads and LC-SRM for measuring carbonic anhydrase 12 (CA12) protein in a renal cell carcinoma (RCC) cell line (PRC3), a candidate biomarker for RCC whose expression at the protein level has not been previously reported. Sample processing and LC-SRM assay were optimized for signature peptides selected as surrogate markers of CA12 protein. Using LC-SRM coupled with stable isotope dilution, we achieved limits of quantitation in the low fmol range sufficient for measuring clinically relevant biomarkers with good intra- and interassay accuracy and precision (≤17%). Our results show that using a quantitative immunoaffinity capture approach provides specific, accurate, and robust assays amenable to high-throughput verification of potential biomarkers.

Many Microbe Microarrays Database: uniformly normalized Affymetrix compendia with structured experimental metadata.

Many Microbe Microarrays Database (M3D) is designed to facilitate the analysis and visualization of expression data in compendia compiled from multiple laboratories. M3D contains over a thousand Affymetrix microarrays for Escherichia coli, Saccharomyces cerevisiae and Shewanella oneidensis. The expression data is uniformly normalized to make the data generated by different laboratories and researchers more comparable. To facilitate computational analyses, M3D provides raw data (CEL file) and normalized data downloads of each compendium. In addition, web-based construction, visualization and download of custom datasets are provided to facilitate efficient interrogation of the compendium for more focused analyses. The experimental condition metadata in M3D is human curated with each chemical and growth attribute stored as a structured and computable set of experimental features with consistent naming conventions and units. All versions of the normalized compendia constructed for each species are maintained and accessible in perpetuity to facilitate the future interpretation and comparison of results published on M3D data. M3D is accessible at http://m3d.bu.edu/.

Accurate diagnosis of acute graft-versus-host disease using serum proteomic pattern analysis.

OBJECTIVE: The rapid diagnosis of acute graft-versus-host disease (GVHD) following allogeneic hematopoietic cell transplantation (HCT) is important for optimizing the management of this life-threatening complication. Current diagnostic techniques are time-consuming and require invasive tissue sampling. We investigated serum protein pattern analysis using surface-enhanced laser desorption ionization time-of-flight (SELDI-TOF) mass spectrometry as a tool to diagnose GVHD. PATIENTS AND METHODS: Eighty-eight serum samples were obtained from 34 patients undergoing HCT either pretransplant (n = 28 samples) or at various time points posttransplant (n = 60 samples), including 22 samples obtained on the day of onset of acute GVHD symptoms. Serum proteomic spectra generated from a "training set" of known samples were used to identify distinct proteomic patterns that best categorized a sample as either pretransplant, posttransplant non-GVHD, or GVHD; these distinct proteomic signatures were subsequently used to classify samples from a masked "test" sample set into the appropriate diagnostic category. RESULTS: Proteomic pattern analysis accurately distinguished GVHD samples from both posttransplant non-GVHD samples and pretransplant samples (100% specificity and 100% sensitivity in both cases). Furthermore, distinct serum proteomic signatures were identified that distinguished pretransplant from posttransplant non-GVHD samples (100% specificity and 94% sensitivity). CONCLUSION: These preliminary data suggest a potential application of SELDI-TOF-based proteomic analysis as a rapid and accurate method to diagnose acute GVHD.

Creating a scalable clinical pharmacogenomics service with automated interpretation and medical record result integration - experience from a pediatric tertiary care facility.

OBJECTIVE: This paper outlines the implementation of a comprehensive clinical pharmacogenomics (PGx) service within a pediatric teaching hospital and the integration of clinical decision support in the electronic health record (EHR). MATERIALS AND METHODS: An approach to clinical decision support for medication ordering and dispensing driven by documented PGx variant status in an EHR is described. A web-based platform was created to automatically generate a clinical report from either raw assay results or specified diplotypes, able to parse and combine haplotypes into an interpretation for each individual and compared to the reference lab call for accuracy. RESULTS: Clinical decision support rules built within an EHR provided guidance to providers for 31 patients (100%) who had actionable PGx variants and were written for interacting medications. A breakdown of the PGx alerts by practitioner service, and alert response for the initial cohort of patients tested is described. In 90% (355/394) of the cases, thiopurine methyltranferase genotyping was ordered pre-emptively. DISCUSSION: This paper outlines one approach to implementing a clinical PGx service in a pediatric teaching hospital that cares for a heterogeneous patient population. There is a focus on incorporation of PGx clinical decision support rules and a program to standardize report text within the electronic health record with subsequent exploration of clinician behavior in response to the alerts. CONCLUSION: The incorporation of PGx data at the time of prescribing and dispensing, if done correctly, has the potential to impact the incidence of adverse drug events, a significant cause of morbidity and mortality.

Nanoporous alumina capsules for cellular macroencapsulation: transport and biocompatibility.

BACKGROUND: Currently, the most widely used treatment for diabetes is the daily subcutaneous injection of recombinant human insulin. Daily injections, however, cannot match the physiological biphasic behavior of normal insulin release, nor can they precisely meet the demands of food intake, exercise, and stress. Cellular encapsulation, or immunoisolation, is a possible solution to this problem. This cell-based therapy allows patients to receive the benefits of more physiological insulin and blood glucose regulation, without the need for immunosuppressants that are associated with organ or cell transplantation. METHODS: Immunoisolation capsules were fabricated out of aluminum and aluminum oxide using a two-step anodization procedure. The diffusion behavior of glucose, immunoglobulin G (IgG), and insulin were measured. Furthermore, the functionality and viability of encapsulated MIN6 cells were tested. Finally, live cells were stained and imaged using confocal microscopy. RESULTS: Data indicated that this device is effective in allowing the transport of relevant molecules such as glucose and insulin, while at the same time significantly impeding the transport of IgG, suggesting that it would be efficacious in protecting cell grafts in vivo. Furthermore, encapsulated cells were able to respond dynamically to glucose input signals. Finally, cell staining showed that the viability of encapsulated cells is maintained after 24 h, although the cells appear to be more heavily concentrated at the area that is closest to the membrane. CONCLUSIONS: This study has shown that nanoporous alumina membranes, with well-controlled pore sizes, can be used for the encapsulation of therapeutic cells and may provide an alternative encapsulation strategy for the treatment of diabetes.