Publications

    Grégoire Versmée, Laura Versmée, Mikaël Dusenne, Niloofar Jalali, and Paul Avillach. 2020. “dbgap2x: an R package to explore and extract data from the database of Genotypes and Phenotypes (dbGaP).” Bioinformatics, 36, 4, Pp. 1305-1306.Abstract
    SUMMARY: Based on the Genomic Data Sharing Policy issued in August 2007, the National Institutes of Health (NIH) has supported several repositories such as the database of Genotypes and Phenotypes (dbGaP). dbGaP is an online repository that provides access to large-scale genetic and phenotypic datasets with more than 1000 studies. However, navigating the website and understanding the relationship between the studies are not easy tasks. Moreover, the decryption of the files is a complex procedure. In this study we propose the dbgap2x R package that covers a broad range of functions for searching dbGaP studies, exploring the characteristics of a study and easily decrypting the files from dbGaP. AVAILABILITY AND IMPLEMENTATION: dbgap2x is an R package with the code available at https://github.com/gversmee/dbgap2x. A containerized version including the package, a Jupyter server and with a Notebook example is available at https://hub.docker.com/r/gversmee/dbgap2x. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
    Kenneth D Mandl, Tracy Glauser, Ian D Krantz, Paul Avillach, Anna Bartels, Alan H Beggs, Sawona Biswas, Florence T Bourgeois, Jeremy Corsmo, Andrew Dauber, Batsal Devkota, Gary R Fleisher, Allison P Heath, Ingo Helbig, Joel N Hirschhorn, Judson Kilbourn, Sek Won Kong, Susan Kornetsky, Joseph A Majzoub, Keith Marsolo, Lisa J Martin, Jeremy Nix, Amy Schwarzhoff, Jason Stedman, Arnold Strauss, Kristen L Sund, Deanne M Taylor, Peter S White, Eric Marsh, Adda Grimberg, and Colin Hawkes. 2020. “The Genomics Research and Innovation Network: creating an interoperable, federated, genomics learning system.” Genet Med, 22, 2, Pp. 371-380.Abstract
    PURPOSE: Clinicians and researchers must contextualize a patient's genetic variants against population-based references with detailed phenotyping. We sought to establish globally scalable technology, policy, and procedures for sharing biosamples and associated genomic and phenotypic data on broadly consented cohorts, across sites of care. METHODS: Three of the nation's leading children's hospitals launched the Genomic Research and Innovation Network (GRIN), with federated information technology infrastructure, harmonized biobanking protocols, and material transfer agreements. Pilot studies in epilepsy and short stature were completed to design and test the collaboration model. RESULTS: Harmonized, broadly consented institutional review board (IRB) protocols were approved and used for biobank enrollment, creating ever-expanding, compatible biobanks. An open source federated query infrastructure was established over genotype-phenotype databases at the three hospitals. Investigators securely access the GRIN platform for prep to research queries, receiving aggregate counts of patients with particular phenotypes or genotypes in each biobank. With proper approvals, de-identified data is exported to a shared analytic workspace. Investigators at all sites enthusiastically collaborated on the pilot studies, resulting in multiple publications. Investigators have also begun to successfully utilize the infrastructure for grant applications. CONCLUSIONS: The GRIN collaboration establishes the technology, policy, and procedures for a scalable genomic research network.
    Charlotte Heleniak and Katie A. McLaughlin. 2020. “Social-cognitive mechanisms in the cycle of violence: Cognitive and affective theory of mind, and externalizing psychopathology in children and adolescents.” Development and Psychopathology, 32, 2, Pp. 735-750. Publisher's VersionAbstract
    Children who are victims of interpersonal violence have a markedly elevated risk of engaging in aggressive behavior and perpetrating violence in adolescence and adulthood. Although alterations in social information processing have long been understood as a core mechanism underlying the link between violence exposure and externalizing behavior, scant research has examined more basic social cognition abilities that might underlie this association. To that end, this study examined the associations of interpersonal violence exposure with cognitive and affective theory of mind (ToM), core social-cognitive processes that underlie many aspects of social information processing. In addition, we evaluated whether difficulties with ToM were associated with externalizing psychopathology. Data were collected in a community-based sample of 246 children and adolescents aged 8–16 who had a high concentration of exposure to interpersonal violence. Violence exposure was associated with lower accuracy during cognitive and affective ToM, and the associations persisted after adjusting for co-occurring forms of adversity characterized by deprivation, including poverty and emotional neglect. Poor ToM performance, in turn, was associated with externalizing behaviors. These findings shed light on novel pathways that increase risk for aggression in children who have experienced violence.
    H. Parviainen, E. Palle, M. R. Zapatero-Osorio, P. Montanes Rodriguez, F. Murgas, N. Narita, D. Hidalgo Soto, V. J. S. Béjar, J. Korth, M. Monelli, N. Casasayas Barris, N. Crouzet, J. P. de Leon, A. Fukui, A. Hernandez, P. Klagyivik, N. Kusakabe, R. Luque, M. Mori, T. Nishiumi, J. Prieto-Arranz, M. Tamura, N. Watanabe, C. Burke, D. Charbonneau, K. A. Collins, K. I. Collins, D. Conti, A. Garcia Soto, J. S. Jenkins, J. M. Jenkins, A. Levine, J. Li, S. Rinehart, S. Seager, P. Tenenbaum, E. B. Ting, R. Vanderspek, M. Vezie, and J. N. Winn. 2020. “MuSCAT2 multicolour validation of TESS candidates: an ultra-short-period substellar object around an M dwarf.” \aap, 633, Pp. A28.
    Anniina Färkkliä, Doga C. Gulhan, Julia Casado, Connor A. Jacobson, Huy Nguyen, Bose Kochupurakkal, Zoltan Maliga, Clarence Yapp, Yu-An Chen, Denis Schapiro, Yinghui Zhou, Julie R. Graham, Bruce J. Dezube, Pamela Munster, Sandro Santagata, Elizabeth Garcia, Scott Rodig, Ana Lako, Dipanjan Chowdhury, Geoffrey I. Shapiro, Ursula A. Matulonis, Peter J. Park, Sampsa Hautaniemi, Peter K. Sorger, Elizabeth M. Swisher, Alan D. D'Andrea, and Panagiotis A. Konstantinopoulos. 2020. “Immunogenomic profiling determines responses to combined PARP and PD-1 inhibition in ovarian cancer.” Nature Communications, 11, 1, Pp. 1459.Abstract
    Combined PARP and immune checkpoint inhibition has yielded encouraging results in ovarian cancer, but predictive biomarkers are lacking. We performed immunogenomic profiling and highly multiplexed single-cell imaging on tumor samples from patients enrolled in a Phase I/II trial of niraparib and pembrolizumab in ovarian cancer (NCT02657889). We identify two determinants of response; mutational signature 3 reflecting defective homologous recombination DNA repair, and positive immune score as a surrogate of interferon-primed exhausted CD8 + T-cells in the tumor microenvironment. Presence of one or both features associates with an improved outcome while concurrent absence yields no responses. Single-cell spatial analysis reveals prominent interactions of exhausted CD8 + T-cells and PD-L1 + macrophages and PD-L1 + tumor cells as mechanistic determinants of response. Furthermore, spatial analysis of two extreme responders shows differential clustering of exhausted CD8 + T-cells with PD-L1 + macrophages in the first, and exhausted CD8 + T-cells with cancer cells harboring genomic PD-L1 and PD-L2 amplification in the second.
    Eduardo Levy-Yeyati and Martin Montane. 2020. “Specificity of Human Capital: An Occupation Space Based on Job-to-Job Transitions”.Abstract
    Using job transition data from Argentina’s Household Survey, we document the extent to which human capital is specific to occupations and activities. Based on workers’ propensity to move between occupations/industries, we build Occupation and Industry Spaces to illustrate job similarities, and we compute an occupation and industry similarity measures that, in turn, we use to explain wage transition dynamics. We show that our similarity measures influence positively post-transition wages. Inasmuch as wages capture a worker´s marginal productivity and this productivity reflects the degree to which a worker matches the job’s skill demand, our results indicate that a worker´s human capital is specific to both occupation and activity: closer occupations share similar skill demands and task composition (in other words, demand similar workers) and imply a smaller human capital loss in the event of a transition.
    Anniina Färkkilä, Doga C Gulhan, Julia Casado, Connor A Jacobson, Huy Nguyen, Bose Kochupurakkal, Zoltan Maliga, Clarence Yapp, Yu-An Chen, Denis Schapiro, Yinghui Zhou, Julie R Graham, Bruce J Dezube, Pamela Munster, Sandro Santagata, Elizabeth Garcia, Scott Rodig, Ana Lako, Dipanjan Chowdhury, Geoffrey I Shapiro, Ursula A Matulonis, Peter J Park, Sampsa Hautaniemi, Peter K Sorger, Elizabeth M Swisher, Alan D D'Andrea, and Panagiotis A Konstantinopoulos. 2020. “Immunogenomic profiling determines responses to combined PARP and PD-1 inhibition in ovarian cancer.” Nat Commun, 11, 1, Pp. 1459.Abstract
    Combined PARP and immune checkpoint inhibition has yielded encouraging results in ovarian cancer, but predictive biomarkers are lacking. We performed immunogenomic profiling and highly multiplexed single-cell imaging on tumor samples from patients enrolled in a Phase I/II trial of niraparib and pembrolizumab in ovarian cancer (NCT02657889). We identify two determinants of response; mutational signature 3 reflecting defective homologous recombination DNA repair, and positive immune score as a surrogate of interferon-primed exhausted CD8 + T-cells in the tumor microenvironment. Presence of one or both features associates with an improved outcome while concurrent absence yields no responses. Single-cell spatial analysis reveals prominent interactions of exhausted CD8 + T-cells and PD-L1 + macrophages and PD-L1 + tumor cells as mechanistic determinants of response. Furthermore, spatial analysis of two extreme responders shows differential clustering of exhausted CD8 + T-cells with PD-L1 + macrophages in the first, and exhausted CD8 + T-cells with cancer cells harboring genomic PD-L1 and PD-L2 amplification in the second.
    Stephanie L Guerra, Ophélia Maertens, Ryan Kuzmickas, Thomas De Raedt, Richard O Adeyemi, Caroline J Guild, Shawna Guillemette, Amanda J Redig, Emily S Chambers, Man Xu, Hong Tiv, Sandro Santagata, Pasi A Jänne, Stephen J Elledge, and Karen Cichowski. 2020. “A Deregulated HOX Gene Axis Confers an Epigenetic Vulnerability in KRAS-Mutant Lung Cancers.” Cancer Cell.Abstract
    While KRAS mutations are common in non-small cell lung cancer (NSCLC), effective treatments are lacking. Here, we report that half of KRAS-mutant NSCLCs aberrantly express the homeobox protein HOXC10, largely due to unappreciated defects in PRC2, which confers sensitivity to combined BET/MEK inhibitors in xenograft and PDX models. Efficacy of the combination is dependent on suppression of HOXC10 by BET inhibitors. We further show that HOXC10 regulates the expression of pre-replication complex (pre-RC) proteins in sensitive tumors. Accordingly, BET/MEK inhibitors suppress pre-RC proteins in cycling cells, triggering stalled replication, DNA damage, and death. These studies reveal a promising therapeutic strategy for KRAS-mutant NSCLCs, identify a predictive biomarker of response, and define a subset of NSCLCs with a targetable epigenetic vulnerability.
    Benjamin Cogné, Xenia Latypova, Lokuliyanage Dona Samudita Senaratne, Ludovic Martin, Daniel C Koboldt, Georgios Kellaris, Lorraine Fievet, Guylène Le Meur, Dominique Caldari, Dominique Debray, Mathilde Nizon, Eirik Frengen, Sara J Bowne, Lives 99 Consortium, Elizabeth L Cadena, Stephen P Daiger, Kinga M Bujakowska, Eric A Pierce, Michael Gorin, Nicholas Katsanis, Stéphane Bézieau, Simon M Petersen-Jones, Laurence M Occelli, Leslie A Lyons, Laurence Legeai-Mallet, Lori S Sullivan, Erica E Davis, and Bertrand Isidor. 2020. “Mutations in the Kinesin-2 Motor KIF3B Cause an Autosomal-Dominant Ciliopathy.” Am J Hum Genet, 106, 6, Pp. 893-904.Abstract
    Kinesin-2 enables ciliary assembly and maintenance as an anterograde intraflagellar transport (IFT) motor. Molecular motor activity is driven by a heterotrimeric complex comprised of KIF3A and KIF3B or KIF3C plus one non-motor subunit, KIFAP3. Using exome sequencing, we identified heterozygous KIF3B variants in two unrelated families with hallmark ciliopathy phenotypes. In the first family, the proband presents with hepatic fibrosis, retinitis pigmentosa, and postaxial polydactyly; he harbors a de novo c.748G>C (p.Glu250Gln) variant affecting the kinesin motor domain encoded by KIF3B. The second family is a six-generation pedigree affected predominantly by retinitis pigmentosa. Affected individuals carry a heterozygous c.1568T>C (p.Leu523Pro) KIF3B variant segregating in an autosomal-dominant pattern. We observed a significant increase in primary cilia length in vitro in the context of either of the two mutations while variant KIF3B proteins retained stability indistinguishable from wild type. Furthermore, we tested the effects of KIF3B mutant mRNA expression in the developing zebrafish retina. In the presence of either missense variant, rhodopsin was sequestered to the photoreceptor rod inner segment layer with a concomitant increase in photoreceptor cilia length. Notably, impaired rhodopsin trafficking is also characteristic of recessive KIF3B models as exemplified by an early-onset, autosomal-recessive, progressive retinal degeneration in Bengal cats; we identified a c.1000G>A (p.Ala334Thr) KIF3B variant by genome-wide association study and whole-genome sequencing. Together, our genetic, cell-based, and in vivo modeling data delineate an autosomal-dominant syndromic retinal ciliopathy in humans and suggest that multiple KIF3B pathomechanisms can impair kinesin-driven ciliary transport in the photoreceptor.
    Yanhui Yang, Xionggao Huang, Gaoen Ma, Jing Cui, Joanne Aiko Matsubara, Andrius Kazlauskas, Jun Zhao, Jiantao Wang, and Hetian Lei. 2020. “PDGFRβ plays an essential role in patient vitreous-stimulated contraction of retinal pigment epithelial cells from epiretinal membranes.” Exp Eye Res, 197, Pp. 108116.Abstract
    Platelet-derived growth factor (PDGF) is associated with clinical proliferative vitreoretinopathy (PVR), which is characterized by formation of sub- or epi-retinal membranes that consist of cells including retinal pigment epithelial (RPE) cells and extracellular matrix. RPE cells play an important role in PVR pathogenesis. Previous findings indicated that PDGF receptor (PDGFR)α was essential in experimental PVR induced by fibroblasts. In RPE cells derived from epiretinal membranes from patients with PVR (RPEMs), Akt was activated by PDGF-B but not PDGF-A, which suggested that PDGFRβ was the predominant PDGFR isoform expressed in RPEMs. Indeed, CRISPR/Cas9-mediated depletion of PDGFRβ in RPEMs attenuated patient vitreous-induced Akt activation and cellular responses intrinsic to PVR including cell proliferation, migration, and contraction. We conclude that PDGFRβ appears to be the PVR relevant PDGFR isoform in RPEMs.
    Kristy Hackett, Sarah Huber-Krum, Joel M. Francis, Leigh Senderowicz, Erin Pearson, Hellen Siril, Nzovu Ulenga, and Iqbal Shah. 2020. “Evaluating the Implementation of an Intervention to Improve Postpartum Contraception in Tanzania: A Qualitative Study of Provider and Client Perspectives.” Global Health: Science and Practice, 8, 2, Pp. 270-289. Publisher's VersionAbstract

    Background: This qualitative study assessed implementation of the Postpartum Intrauterine Device (PPIUD) Initiative in Tanzania, a country with high rates of unintended pregnancy and low contraceptive prevalence. The PPIUD Initiative was implemented to reduce unmet need for contraception among new mothers through postpartum family planning counseling delivered during antenatal care and offering PPIUD insertion immediately following birth.

    Methods: We used the implementation outcomes framework and an ecological framework to analyze in-depth interviews with providers (N=15) and women (N=47) participating in the initiative. We applied a multistage coding protocol and used thematic content analysis to identify the factors influencing implementation.

    Results: Both women and providers were enthusiastic and receptive to the PPIUD Initiative. Health system and resource constraints made adoption and fidelity to the intended intervention challenging. Many providers questioned the sustainability of the initiative, and most agreed that changes to the initiative’s design (e.g., additional training opportunities, improved staffing, and availability of PPIUD supplies) would strengthen future iterations of the initiative. According to women, interpersonal aspects of care varied, with some women reporting rushed or incomplete counseling or an emphasis on the PPIUD over other methods. The perception that some providers treat older married women more favorably suggests that fidelity to the intended PPIUD Initiative was not uniformly achieved.

    Conclusions: Study findings inform initiatives seeking to develop and adopt postpartum family planning programs and enhance program implementation. A comprehensive needs assessment to evaluate feasibility and identify potential adaptations for the local context is recommended. Training and supervision to improve interpersonal aspects of care, including an emphasis on patient-centered counseling, informed choice, and respectful and nondiscriminatory service delivery should be integrated into future postpartum family planning initiatives.

    Charlotte Heleniak and Katie A. McLaughlin. 2020. “Social-cognitive mechanisms in the cycle of violence: Cognitive and affective theory of mind, and externalizing psychopathology in children and adolescents.” Development and Psychopathology, 32, 2, Pp. 735-750. Publisher's VersionAbstract
    Children who are victims of interpersonal violence have a markedly elevated risk of engaging in aggressive behavior and perpetrating violence in adolescence and adulthood. Although alterations in social information processing have long been understood as a core mechanism underlying the link between violence exposure and externalizing behavior, scant research has examined more basic social cognition abilities that might underlie this association. To that end, this study examined the associations of interpersonal violence exposure with cognitive and affective theory of mind (ToM), core social-cognitive processes that underlie many aspects of social information processing. In addition, we evaluated whether difficulties with ToM were associated with externalizing psychopathology. Data were collected in a community-based sample of 246 children and adolescents aged 8–16 who had a high concentration of exposure to interpersonal violence. Violence exposure was associated with lower accuracy during cognitive and affective ToM, and the associations persisted after adjusting for co-occurring forms of adversity characterized by deprivation, including poverty and emotional neglect. Poor ToM performance, in turn, was associated with externalizing behaviors. These findings shed light on novel pathways that increase risk for aggression in children who have experienced violence.
    Harold Kiossou, Yannik Schenk, Frédéric Docquier, Ratheil Houndji, Siegfried Nijssen, and Pierre Schaus. 2020. “Using an interpretable Machine Learning approach to study the drivers of International Migration.” In AI for Social Good Workshop.Abstract

    Globally increasing migration pressures call for new modelling approaches in order to design effective policies. It is important to have not only efficient models to predict migration flows but also to understand how specific parameters influence these flows. In this paper, we propose an artificial neural network (ANN) to model international migration. Moreover, we use a technique for interpreting machine learning models, namely Partial Dependence Plots (PDP), to show that one can well study the effects of drivers behind international migration. We train and evaluate the model on a dataset containing annual international bilateral migration from 1960 to 2010 from 175 origin countries to 33 mainly OECD destinations, along with the main determinants as identified in the migration literature. The experiments carried out confirm that: 1) the ANN model is more efficient w.r.t. a traditional model, and 2) using PDP we are able to gain additional insights on the specific effects of the migration drivers. This approach provides much more information than only using the feature importance information used in previous works.

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    Yuan Luo, Alal Eran, Nathan Palmer, Paul Avillach, Ami Levy-Moonshine, Peter Szolovitis, and Isaac Kohane. 2020. “A multidimensional precision medicine approach identifies an autism subtype characterized by dyslipidemia.” Nat Med. Publisher's VersionAbstract

    Abstract

    The promise of precision medicine lies in data diversity. More than the sheer size of biomedical data, it is the layering of multiple data modalities, offering complementary perspectives, that is thought to enable the identification of patient subgroups with shared pathophysiology. In the present study, we use autism to test this notion. By combining healthcare claims, electronic health records, familial whole-exome sequences and neurodevelopmental gene expression patterns, we identified a subgroup of patients with dyslipidemia-associated autism.

    Siamak Yousefi, Tobias Elze, Louis R Pasquale, Osamah Saeedi, Mengyu Wang, Lucy Q Shen, Sarah R Wellik, Carlos G De Moraes, Jonathan S Myers, and Michael V Boland. 2020. “Monitoring Glaucomatous Functional Loss Using an Artificial Intelligence-Enabled Dashboard.” Ophthalmology, 127, 9, Pp. 1170-1178.Abstract
    PURPOSE: To develop an artificial intelligence (AI) dashboard for monitoring glaucomatous functional loss. DESIGN: Retrospective, cross-sectional, longitudinal cohort study. PARTICIPANTS: Of 31 591 visual fields (VFs) on 8077 subjects, 13 231 VFs from the most recent visit of each patient were included to develop the AI dashboard. Longitudinal VFs from 287 eyes with glaucoma were used to validate the models. METHOD: We entered VF data from the most recent visit of glaucomatous and nonglaucomatous patients into a "pipeline" that included principal component analysis (PCA), manifold learning, and unsupervised clustering to identify eyes with similar global, hemifield, and local patterns of VF loss. We visualized the results on a map, which we refer to as an "AI-enabled glaucoma dashboard." We used density-based clustering and the VF decomposition method called "archetypal analysis" to annotate the dashboard. Finally, we used 2 separate benchmark datasets-one representing "likely nonprogression" and the other representing "likely progression"-to validate the dashboard and assess its ability to portray functional change over time in glaucoma. MAIN OUTCOME MEASURES: The severity and extent of functional loss and characteristic patterns of VF loss in patients with glaucoma. RESULTS: After building the dashboard, we identified 32 nonoverlapping clusters. Each cluster on the dashboard corresponded to a particular global functional severity, an extent of VF loss into different hemifields, and characteristic local patterns of VF loss. By using 2 independent benchmark datasets and a definition of stability as trajectories not passing through over 2 clusters in a left or downward direction, the specificity for detecting "likely nonprogression" was 94% and the sensitivity for detecting "likely progression" was 77%. CONCLUSIONS: The AI-enabled glaucoma dashboard, developed using a large VF dataset containing a broad spectrum of visual deficit types, has the potential to provide clinicians with a user-friendly tool for determination of the severity of glaucomatous vision deficit, the spatial extent of the damage, and a means for monitoring the disease progression.
    P. Mattson, V. J. Reddi, C. Cheng, C. Coleman, G. Diamos, D. Kanter, P. Micikevicius, D. Patterson, G. Schmuelling, H. Tang, G. Wei, and C. Wu. 2020. “MLPerf: An Industry Standard Benchmark Suite for Machine Learning Performance.” IEEE Micro, 40, 2, Pp. 8-16.Abstract
    In this article, we describe the design choices behind MLPerf, a machine learning performance benchmark that has become an industry standard. The first two rounds of the MLPerf Training benchmark helped drive improvements to software-stack performance and scalability, showing a 1.3× speedup in the top 16-chip results despite higher quality targets and a 5.5× increase in system scale. The first round of MLPerf Inference received over 500 benchmark results from 14 different organizations, showing growing adoption.

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