Snyder Lab


All Publications (755)

Featured Publications (82)

Journal Articles (738)

Conference Proceedings (17)

Stanford W. Ascherman Professor of Genetics


  • Precision environmental health monitoring by longitudinal exposome and multi-omics profiling. Genome research Gao, P., Shen, X., Zhang, X., Jiang, C., Zhang, S., Zhou, X., Schüssler-Fiorenza Rose, S. M., Snyder, M. 2022


    Conventional environmental health studies have primarily focused on limited environmental stressors at the population level, which lacks the power to dissect the complexity and heterogeneity of individualized environmental exposures. Here, as a pilot case study, we integrated deep-profiled longitudinal personal exposome and internal multi-omics to systematically investigate how the exposome shapes a single individual's phenome. We annotated thousands of chemical and biological components in the personal exposome cloud and found they were significantly correlated with thousands of internal biomolecules, which was further cross-validated using corresponding clinical data. Our results showed that agrochemicals and fungi predominated in the highly diverse and dynamic personal exposome, and the biomolecules and pathways related to the individual's immune system, kidney, and liver were highly associated with the personal external exposome. Overall, this data-driven longitudinal monitoring study shows the potential dynamic interactions between the personal exposome and internal multi-omics, as well as the impact of the exposome on precision health by producing abundant testable hypotheses.

    View details for DOI 10.1101/gr.276521.121

    View details for PubMedID 35667843

  • Multiomic analysis reveals cell-type-specific molecular determinants of COVID-19 severity. Cell systems Zhang, S., Cooper-Knock, J., Weimer, A. K., Shi, M., Kozhaya, L., Unutmaz, D., Harvey, C., Julian, T. H., Furini, S., Frullanti, E., Fava, F., Renieri, A., Gao, P., Shen, X., Timpanaro, I. S., Kenna, K. P., Baillie, J. K., Davis, M. M., Tsao, P. S., Snyder, M. P. 2022


    The determinants of severe COVID-19 in healthy adults are poorly understood, which limits the opportunity for early intervention. We present a multiomic analysis using machine learning to characterize the genomic basis of COVID-19 severity. We use single-cell multiome profiling of human lungs to link genetic signals to cell-type-specific functions. We discover >1,000 risk genes across 19 cell types, which account for 77% of the SNP-based heritability for severe disease. Genetic risk is particularly focused within natural killer (NK) cells and T cells, placing the dysfunction of these cells upstream of severe disease. Mendelian randomization and single-cell profiling of human NK cells support the role of NK cells and further localize genetic risk to CD56bright NK cells, which are key cytokine producers during the innate immune response. Rare variant analysis confirms the enrichment of severe-disease-associated genetic variation within NK-cell risk genes. Our study provides insights into the pathogenesis of severe COVID-19 with potential therapeutic targets.

    View details for DOI 10.1016/j.cels.2022.05.007

    View details for PubMedID 35690068

  • Global, distinctive, and personal changes in molecular and microbial profiles by specific fibers in humans. Cell host & microbe Lancaster, S. M., Lee-McMullen, B., Abbott, C. W., Quijada, J. V., Hornburg, D., Park, H., Perelman, D., Peterson, D. J., Tang, M., Robinson, A., Ahadi, S., Contrepois, K., Hung, C., Ashland, M., McLaughlin, T., Boonyanit, A., Horning, A., Sonnenburg, J. L., Snyder, M. P. 2022


    Dietary fibers act through the microbiome to improve cardiovascular health and prevent metabolic disorders and cancer. To understand the health benefits of dietary fiber supplementation, we investigated two popular purified fibers, arabinoxylan (AX) and long-chain inulin (LCI), and a mixture of five fibers. We present multiomic signatures of metabolomics, lipidomics, proteomics, metagenomics, a cytokine panel, and clinical measurements on healthy and insulin-resistant participants. Each fiber is associated with fiber-dependent biochemical and microbial responses. AX consumption associates with a significant reduction in LDL and an increase in bile acids, contributing to its observed cholesterol reduction. LCI is associated with an increase in Bifidobacterium. However, at the highest LCI dose, there is increased inflammation and elevation in the liver enzyme alanine aminotransferase. This study yields insights into the effects of fiber supplementation and the mechanisms behind fiber-induced cholesterol reduction, and it shows effects of individual, purified fibers on the microbiome.

    View details for DOI 10.1016/j.chom.2022.03.036

    View details for PubMedID 35483363

  • Adverse childhood experiences, diabetes and associated conditions, preventive care practices and healthcare access: A population-based study. Preventive medicine Rose, S. M., Slavich, G. M., Snyder, M. P. 2022: 107044


    Our objective was to examine associations between Adverse Childhood Experiences (ACEs) and diabetes mellitus, including related conditions and preventive care practices. We used data from the Behavioral Risk Factor Surveillance System (BRFSS) 2009-2012, a cross-sectional, population-based survey, to assess ACEs, diabetes, and healthcare access in 179,375 adults. In those with diabetes (n = 21,007), we assessed the association of ACEs with myocardial infarction, stroke, and five Healthy People 2020 (HP2020) diabetes-related preventive-care objectives (n = 13,152). Healthcare access indicators included lack of a regular healthcare provider, insurance, and difficulty affording healthcare. Regression analyses adjusted for age, sex, and race. The adjusted odds ratio (AOR) of diabetes increased in a stepwise fashion by ACE exposure, ranging from 1.2 (95% CI 1.1-1.3) for 1 ACE to 1.7 (95% CI 1.6-1.9) for ≥4 ACEs, versus having no ACEs. In persons with diabetes, those with ≥4 ACEs had an elevated adjusted odds of myocardial infarction (AOR = 1.6, 95% CI 1.2-2.0) and stroke (AOR = 1.8, 95% CI 1.3-2.4), versus having no ACEs. ACEs were also associated with a reduction in the adjusted percent of HP2020 diabetes objectives met: 72.9% (95% CI 71.3-74.5) for those with no ACEs versus only 66.5% (95% CI 63.8-69.3%) for those with ≥4 ACEs (p = 0.0002). Finally, ACEs predicted worse healthcare access in a stepwise fashion for all indicators. In conclusion, ACEs are associated with greater prevalence of diabetes and associated conditions, and with meeting fewer HP2020 prevention goals. ACEs screening and trauma-informed care practices are thus recommended.

    View details for DOI 10.1016/j.ypmed.2022.107044

    View details for PubMedID 35398366

  • Genome-wide identification of the genetic basis of amyotrophic lateral sclerosis. Neuron Zhang, S., Cooper-Knock, J., Weimer, A. K., Shi, M., Moll, T., Marshall, J. N., Harvey, C., Nezhad, H. G., Franklin, J., Souza, C. D., Ning, K., Wang, C., Li, J., Dilliott, A. A., Farhan, S., Elhaik, E., Pasniceanu, I., Livesey, M. R., Eitan, C., Hornstein, E., Kenna, K. P., Project MinE ALS Sequencing Consortium, Veldink, J. H., Ferraiuolo, L., Shaw, P. J., Snyder, M. P., Blair, I., Wray, N. R., Kiernan, M., Mitne Neto, M., Chio, A., Cauchi, R., Robberecht, W., van Damme, P., Corcia, P., Couratier, P., Hardiman, O., McLaughin, R., Gotkine, M., Drory, V., Ticozzi, N., Silani, V., Veldink, J. H., van den Berg, L. H., de Carvalho, M., Mora Pardina, J. S., Povedano, M., Andersen, P., Weber, M., Basak, N. A., Al-Chalabi, A., Shaw, C., Shaw, P. J., Morrison, K. E., Landers, J. E., Glass, J. D. 1800


    Amyotrophic lateral sclerosis (ALS) is a complex disease that leads to motor neuron death. Despite heritability estimates of 52%, genome-wide association studies (GWASs) have discovered relatively few loci. We developed a machine learning approach called RefMap, which integrates functional genomics with GWAS summary statistics for gene discovery. With transcriptomic and epigenetic profiling of motor neurons derived from induced pluripotent stem cells (iPSCs), RefMap identified 690 ALS-associated genes that represent a 5-fold increase in recovered heritability. Extensive conservation, transcriptome, network, and rare variant analyses demonstrated the functional significance of candidate genes in healthy and diseased motor neurons and brain tissues. Genetic convergence between common and rare variation highlighted KANK1 as a new ALS gene. Reproducing KANK1 patient mutations in human neurons led to neurotoxicity and demonstrated that TDP-43 mislocalization, a hallmark pathology of ALS, is downstream of axonal dysfunction. RefMap can be readily applied to other complex diseases.

    View details for DOI 10.1016/j.neuron.2021.12.019

    View details for PubMedID 35045337

  • Real-time alerting system for COVID-19 and other stress events using wearable data. Nature medicine Alavi, A., Bogu, G. K., Wang, M., Rangan, E. S., Brooks, A. W., Wang, Q., Higgs, E., Celli, A., Mishra, T., Metwally, A. A., Cha, K., Knowles, P., Alavi, A. A., Bhasin, R., Panchamukhi, S., Celis, D., Aditya, T., Honkala, A., Rolnik, B., Hunting, E., Dagan-Rosenfeld, O., Chauhan, A., Li, J. W., Bejikian, C., Krishnan, V., McGuire, L., Li, X., Bahmani, A., Snyder, M. P. 2021


    Early detection of infectious diseases is crucial for reducing transmission and facilitating early intervention. In this study, we built a real-time smartwatch-based alerting system that detects aberrant physiological and activity signals (heart rates and steps) associated with the onset of early infection and implemented this system in a prospective study. In a cohort of 3,318 participants, of whom 84 were infected with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), this system generated alerts for pre-symptomatic and asymptomatic SARS-CoV-2 infection in 67 (80%) of the infected individuals. Pre-symptomatic signals were observed at a median of 3 days before symptom onset. Examination of detailed survey responses provided by the participants revealed that other respiratory infections as well as events not associated with infection, such as stress, alcohol consumption and travel, could also trigger alerts, albeit at a much lower mean frequency (1.15 alert days per person compared to 3.42 alert days per person for coronavirus disease 2019 cases). Thus, analysis of smartwatch signals by an online detection algorithm provides advance warning of SARS-CoV-2 infection in a high percentage of cases. This study shows that a real-time alerting system can be used for early detection of infection and other stressors and employed on an open-source platform that is scalable to millions of users.

    View details for DOI 10.1038/s41591-021-01593-2

    View details for PubMedID 34845389

  • A scalable, secure, and interoperable platform for deep data-driven health management. Nature communications Bahmani, A., Alavi, A., Buergel, T., Upadhyayula, S., Wang, Q., Ananthakrishnan, S. K., Alavi, A., Celis, D., Gillespie, D., Young, G., Xing, Z., Nguyen, M. H., Haque, A., Mathur, A., Payne, J., Mazaheri, G., Li, J. K., Kotipalli, P., Liao, L., Bhasin, R., Cha, K., Rolnik, B., Celli, A., Dagan-Rosenfeld, O., Higgs, E., Zhou, W., Berry, C. L., Van Winkle, K. G., Contrepois, K., Ray, U., Bettinger, K., Datta, S., Li, X., Snyder, M. P. 2021; 12 (1): 5757


    The large amount of biomedical data derived from wearable sensors, electronic health records, and molecular profiling (e.g., genomics data) is rapidly transforming our healthcare systems. The increasing scale and scope of biomedical data not only is generating enormous opportunities for improving health outcomes but also raises new challenges ranging from data acquisition and storage to data analysis and utilization. To meet these challenges, we developed the Personal Health Dashboard (PHD), which utilizes state-of-the-art security and scalability technologies to provide an end-to-end solution for big biomedical data analytics. The PHD platform is an open-source software framework that can be easily configured and deployed to any big data health project to store, organize, and process complex biomedical data sets, support real-time data analysis at both the individual level and the cohort level, and ensure participant privacy at every step. In addition to presenting the system, we illustrate the use of the PHD framework for large-scale applications in emerging multi-omics disease studies, such as collecting and visualization of diverse data types (wearable, clinical, omics) at a personal level, investigation of insulin resistance, and an infrastructure for the detection of presymptomatic COVID-19.

    View details for DOI 10.1038/s41467-021-26040-1

    View details for PubMedID 34599181

  • Chromatin accessibility associates with protein-RNA correlation in human cancer. Nature communications Sanghi, A., Gruber, J. J., Metwally, A., Jiang, L., Reynolds, W., Sunwoo, J., Orloff, L., Chang, H. Y., Kasowski, M., Snyder, M. P. 2021; 12 (1): 5732


    Although alterations in chromatin structure are known to exist in tumors, how these alterations relate to molecular phenotypes in cancer remains to be demonstrated. Multi-omics profiling of human tumors can provide insight into how alterations in chromatin structure are propagated through the pathway of gene expression to result in malignant protein expression. We applied multi-omics profiling of chromatin accessibility, RNA abundance, and protein abundance to 36 human thyroid cancer primary tumors, metastases, and patient-match normal tissue. Through quantification of chromatin accessibility associated with active transcription units and global protein expression, we identify a local chromatin structure that is highly correlated with coordinated RNA and protein expression. In particular, we identify enhancers located within gene-bodies as predictive of correlated RNA and protein expression, that is independent of overall transcriptional activity. To demonstrate the generalizability of these findings we also identify similar results in an independent cohort of human breast cancers. Taken together, these analyses suggest that local enhancers, rather than distal enhancers, are likely most predictive of cancer gene expression phenotypes. This allows for identification of potential targets for cancer therapeutic approaches and reinforces the utility of multi-omics profiling as a methodology to understand human disease.

    View details for DOI 10.1038/s41467-021-25872-1

    View details for PubMedID 34593797

  • metID: a R package for automatable compound annotation for LC-MS-based data. Bioinformatics (Oxford, England) Shen, X., Wu, S., Liang, L., Chen, S., Contrepois, K., Zhu, Z., Snyder, M. 2021


    SUMMARY: Accurate and efficient compound annotation is a long-standing challenge for LC-MS-based data (e.g., untargeted metabolomics and exposomics). Substantial efforts have been devoted to overcoming this obstacle, whereas current tools are limited by the sources of spectral information used (in-house and public databases) and are not automated and streamlined. Therefore, we developed metID, an R package that combines information from all major databases for comprehensive and streamlined compound annotation. metID is a flexible, simple, and powerful tool that can be installed on all platforms, allowing the compound annotation process to be fully automatic and reproducible. A detailed tutorial and a case study are provided in Supplementary Materials.AVAILABILITY AND IMPLEMENTATION: INFORMATION: Supplementary data are available at Bioinformatics online.

    View details for DOI 10.1093/bioinformatics/btab583

    View details for PubMedID 34432001

  • Five-year pediatric use of a digital wearable fitness device: lessons from a pilot case study. JAMIA open Butte, K. D., Bahmani, A., Butte, A. J., Li, X., Snyder, M. P. 2021; 4 (3): ooab054


    Objectives: Wearable fitness devices are increasingly being used by the general population, with many new applications being proposed for healthy adults as well as for adults with chronic diseases. Fewer, if any, studies of these devices have been conducted in healthy adolescents and teenagers, especially over a long period of time. The goal of this work was to document the successes and challenges involved in 5 years of a wearable fitness device use in a pediatric case study.Materials and methods: Comparison of 5 years of step counts and minutes asleep from a teenaged girl and her father.Results: At 60 months, this may be the longest reported pediatric study involving a wearable fitness device, and the first simultaneously involving a parent and a child. We find step counts to be significantly higher for both the adult and teen on school/work days, along with less sleep. The teen walked significantly less towards the end of the 5-year study. Surprisingly, many of the adult's and teen's sleeping and step counts were correlated, possibly due to coordinated behaviors.Discussion: We end with several recommendations for pediatricians and device manufacturers, including the need for constant adjustments of stride length and calorie counts as teens are growing.Conclusion: With periodic adjustments for growth, this pilot study shows these devices can be used for more accurate and consistent measurements in adolescents and teenagers over longer periods of time, to potentially promote healthy behaviors.

    View details for DOI 10.1093/jamiaopen/ooab054

    View details for PubMedID 34350390

  • Wearable sensors enable personalized predictions of clinical laboratory measurements. Nature medicine Dunn, J., Kidzinski, L., Runge, R., Witt, D., Hicks, J. L., Schussler-Fiorenza Rose, S. M., Li, X., Bahmani, A., Delp, S. L., Hastie, T., Snyder, M. P. 2021


    Vital signs, including heart rate and body temperature, are useful in detecting or monitoring medical conditions, but are typically measured in the clinic and require follow-up laboratory testing for more definitive diagnoses. Here we examined whether vital signs as measured by consumer wearable devices (that is, continuously monitored heart rate, body temperature, electrodermal activity and movement) can predict clinical laboratory test results using machine learning models, including random forest and Lasso models. Our results demonstrate that vital sign data collected from wearables give a more consistent and precise depiction of resting heart rate than do measurements taken in the clinic. Vital sign data collected from wearables can also predict several clinical laboratory measurements with lower prediction error than predictions made using clinically obtained vital sign measurements. The length of time over which vital signs are monitored and the proximity of the monitoring period to the date of prediction play a critical role in the performance of the machine learning models. These results demonstrate the value of commercial wearable devices for continuous and longitudinal assessment of physiological measurements that today can be measured only with clinical laboratory tests.

    View details for DOI 10.1038/s41591-021-01339-0

    View details for PubMedID 34031607

  • Pre-symptomatic detection of COVID-19 from smartwatch data. Nature biomedical engineering Mishra, T., Wang, M., Metwally, A. A., Bogu, G. K., Brooks, A. W., Bahmani, A., Alavi, A., Celli, A., Higgs, E., Dagan-Rosenfeld, O., Fay, B., Kirkpatrick, S., Kellogg, R., Gibson, M., Wang, T., Hunting, E. M., Mamic, P., Ganz, A. B., Rolnik, B., Li, X., Snyder, M. P. 2020


    Consumer wearable devices that continuously measure vital signs have been used to monitor the onset of infectious disease. Here, we show that data from consumer smartwatches can be used for the pre-symptomatic detection of coronavirus disease 2019 (COVID-19). We analysed physiological and activity data from 32 individuals infected with COVID-19, identified from a cohort of nearly 5,300 participants, and found that 26 of them (81%) had alterations in their heart rate, number of daily steps or time asleep. Of the 25 cases of COVID-19 with detected physiological alterations for which we had symptom information, 22 were detected before (or at) symptom onset, with four cases detected at least nine days earlier. Using retrospective smartwatch data, we show that 63% of the COVID-19 cases could have been detected before symptom onset in real time via a two-tiered warning system based on the occurrence of extreme elevations in resting heart rate relative to the individual baseline. Our findings suggest that activity tracking and health monitoring via consumer wearable devices may be used for the large-scale, real-time detection of respiratory infections, often pre-symptomatically.

    View details for DOI 10.1038/s41551-020-00640-6

    View details for PubMedID 33208926

  • An integrative ENCODE resource for cancer genomics. Nature communications Zhang, J., Lee, D., Dhiman, V., Jiang, P., Xu, J., McGillivray, P., Yang, H., Liu, J., Meyerson, W., Clarke, D., Gu, M., Li, S., Lou, S., Xu, J., Lochovsky, L., Ung, M., Ma, L., Yu, S., Cao, Q., Harmanci, A., Yan, K., Sethi, A., Gursoy, G., Schoenberg, M. R., Rozowsky, J., Warrell, J., Emani, P., Yang, Y. T., Galeev, T., Kong, X., Liu, S., Li, X., Krishnan, J., Feng, Y., Rivera-Mulia, J. C., Adrian, J., Broach, J. R., Bolt, M., Moran, J., Fitzgerald, D., Dileep, V., Liu, T., Mei, S., Sasaki, T., Trevilla-Garcia, C., Wang, S., Wang, Y., Zang, C., Wang, D., Klein, R. J., Snyder, M., Gilbert, D. M., Yip, K., Cheng, C., Yue, F., Liu, X. S., White, K. P., Gerstein, M. 2020; 11 (1): 3696


    ENCODE comprises thousands of functional genomics datasets, and the encyclopedia covers hundreds of cell types, providing a universal annotation for genome interpretation. However, for particular applications, it may be advantageous to use a customized annotation. Here, we develop such a custom annotation by leveraging advanced assays, such as eCLIP, Hi-C, and whole-genome STARR-seq on a number of data-rich ENCODE cell types. A key aspect of this annotation is comprehensive and experimentally derived networks of both transcription factors and RNA-binding proteins (TFs and RBPs). Cancer, a disease of system-wide dysregulation, is an ideal application for such a network-based annotation. Specifically, for cancer-associated cell types, we put regulators into hierarchies and measure their network change (rewiring) during oncogenesis. We also extensively survey TF-RBP crosstalk, highlighting how SUB1, a previously uncharacterized RBP, drives aberrant tumor expression and amplifies the effect of MYC, a well-known oncogenic TF. Furthermore, we show how our annotation allows us to place oncogenic transformations in the context of a broad cell space; here, many normal-to-tumor transitions move towards a stem-like state, while oncogene knockdowns show an opposing trend. Finally, we organize the resource into a coherent workflow to prioritize key elements and variants, in addition to regulators. We showcase the application of this prioritization to somatic burdening, cancer differential expression and GWAS. Targeted validations of the prioritized regulators, elements and variants using siRNA knockdowns, CRISPR-based editing, and luciferase assays demonstrate the value of the ENCODE resource.

    View details for DOI 10.1038/s41467-020-14743-w

    View details for PubMedID 32728046

  • Perspectives on ENCODE. Nature ENCODE Project Consortium, Snyder, M. P., Gingeras, T. R., Moore, J. E., Weng, Z., Gerstein, M. B., Ren, B., Hardison, R. C., Stamatoyannopoulos, J. A., Graveley, B. R., Feingold, E. A., Pazin, M. J., Pagan, M., Gilchrist, D. A., Hitz, B. C., Cherry, J. M., Bernstein, B. E., Mendenhall, E. M., Zerbino, D. R., Frankish, A., Flicek, P., Myers, R. M., Abascal, F., Acosta, R., Addleman, N. J., Adrian, J., Afzal, V., Aken, B., Akiyama, J. A., Jammal, O. A., Amrhein, H., Anderson, S. M., Andrews, G. R., Antoshechkin, I., Ardlie, K. G., Armstrong, J., Astley, M., Banerjee, B., Barkal, A. A., Barnes, I. H., Barozzi, I., Barrell, D., Barson, G., Bates, D., Baymuradov, U. K., Bazile, C., Beer, M. A., Beik, S., Bender, M. A., Bennett, R., Bouvrette, L. P., Bernstein, B. E., Berry, A., Bhaskar, A., Bignell, A., Blue, S. M., Bodine, D. M., Boix, C., Boley, N., Borrman, T., Borsari, B., Boyle, A. P., Brandsmeier, L. A., Breschi, A., Bresnick, E. H., Brooks, J. A., Buckley, M., Burge, C. B., Byron, R., Cahill, E., Cai, L., Cao, L., Carty, M., Castanon, R. G., Castillo, A., Chaib, H., Chan, E. T., Chee, D. R., Chee, S., Chen, H., Chen, H., Chen, J., Chen, S., Cherry, J. M., Chhetri, S. B., Choudhary, J. S., Chrast, J., Chung, D., Clarke, D., Cody, N. A., Coppola, C. J., Coursen, J., D'Ippolito, A. M., Dalton, S., Danyko, C., Davidson, C., Davila-Velderrain, J., Davis, C. A., Dekker, J., Deran, A., DeSalvo, G., Despacio-Reyes, G., Dewey, C. N., Dickel, D. E., Diegel, M., Diekhans, M., Dileep, V., Ding, B., Djebali, S., Dobin, A., Dominguez, D., Donaldson, S., Drenkow, J., Dreszer, T. R., Drier, Y., Duff, M. O., Dunn, D., Eastman, C., Ecker, J. R., Edwards, M. D., El-Ali, N., Elhajjajy, S. I., Elkins, K., Emili, A., Epstein, C. B., Evans, R. C., Ezkurdia, I., Fan, K., Farnham, P. J., Farrell, N., Feingold, E. A., Ferreira, A., Fisher-Aylor, K., Fitzgerald, S., Flicek, P., Foo, C. S., Fortier, K., Frankish, A., Freese, P., Fu, S., Fu, X., Fu, Y., Fukuda-Yuzawa, Y., Fulciniti, M., Funnell, A. P., Gabdank, I., Galeev, T., Gao, M., Giron, C. G., Garvin, T. H., Gelboin-Burkhart, C. A., Georgolopoulos, G., Gerstein, M. B., Giardine, B. M., Gifford, D. K., Gilbert, D. M., Gilchrist, D. A., Gillespie, S., Gingeras, T. R., Gong, P., Gonzalez, A., Gonzalez, J. M., Good, P., Goren, A., Gorkin, D. U., Graveley, B. R., Gray, M., Greenblatt, J. F., Griffiths, E., Groudine, M. T., Grubert, F., Gu, M., Guigo, R., Guo, H., Guo, Y., Guo, Y., Gursoy, G., Gutierrez-Arcelus, M., Halow, J., Hardison, R. C., Hardy, M., Hariharan, M., Harmanci, A., Harrington, A., Harrow, J. L., Hashimoto, T. B., Hasz, R. D., Hatan, M., Haugen, E., Hayes, J. E., He, P., He, Y., Heidari, N., Hendrickson, D., Heuston, E. F., Hilton, J. A., Hitz, B. C., Hochman, A., Holgren, C., Hou, L., Hou, S., Hsiao, Y. E., Hsu, S., Huang, H., Hubbard, T. J., Huey, J., Hughes, T. R., Hunt, T., Ibarrientos, S., Issner, R., Iwata, M., Izuogu, O., Jaakkola, T., Jameel, N., Jansen, C., Jiang, L., Jiang, P., Johnson, A., Johnson, R., Jungreis, I., Kadaba, M., Kasowski, M., Kasparian, M., Kato, M., Kaul, R., Kawli, T., Kay, M., Keen, J. C., Keles, S., Keller, C. A., Kelley, D., Kellis, M., Kheradpour, P., Kim, D. S., Kirilusha, A., Klein, R. J., Knoechel, B., Kuan, S., Kulik, M. J., Kumar, S., Kundaje, A., Kutyavin, T., Lagarde, J., Lajoie, B. R., Lambert, N. J., Lazar, J., Lee, A. Y., Lee, D., Lee, E., Lee, J. W., Lee, K., Leslie, C. S., Levy, S., Li, B., Li, H., Li, N., Li, X., Li, Y. I., Li, Y., Li, Y., Li, Y., Lian, J., Libbrecht, M. W., Lin, S., Lin, Y., Liu, D., Liu, J., Liu, P., Liu, T., Liu, X. S., Liu, Y., Liu, Y., Long, M., Lou, S., Loveland, J., Lu, A., Lu, Y., Lecuyer, E., Ma, L., Mackiewicz, M., Mannion, B. J., Mannstadt, M., Manthravadi, D., Marinov, G. K., Martin, F. J., Mattei, E., McCue, K., McEown, M., McVicker, G., Meadows, S. K., Meissner, A., Mendenhall, E. M., Messer, C. L., Meuleman, W., Meyer, C., Miller, S., Milton, M. G., Mishra, T., Moore, D. E., Moore, H. M., Moore, J. E., Moore, S. H., Moran, J., Mortazavi, A., Mudge, J. M., Munshi, N., Murad, R., Myers, R. M., Nandakumar, V., Nandi, P., Narasimha, A. M., Narayanan, A. K., Naughton, H., Navarro, F. C., Navas, P., Nazarovs, J., Nelson, J., Neph, S., Neri, F. J., Nery, J. R., Nesmith, A. R., Newberry, J. S., Newberry, K. M., Ngo, V., Nguyen, R., Nguyen, T. B., Nguyen, T., Nishida, A., Noble, W. S., Novak, C. S., Novoa, E. M., Nunez, B., O'Donnell, C. W., Olson, S., Onate, K. C., Otterman, E., Ozadam, H., Pagan, M., Palden, T., Pan, X., Park, Y., Partridge, E. C., Paten, B., Pauli-Behn, F., Pazin, M. J., Pei, B., Pennacchio, L. A., Perez, A. R., Perry, E. H., Pervouchine, D. D., Phalke, N. N., Pham, Q., Phanstiel, D. H., Plajzer-Frick, I., Pratt, G. A., Pratt, H. E., Preissl, S., Pritchard, J. K., Pritykin, Y., Purcaro, M. J., Qin, Q., Quinones-Valdez, G., Rabano, I., Radovani, E., Raj, A., Rajagopal, N., Ram, O., Ramirez, L., Ramirez, R. N., Rausch, D., Raychaudhuri, S., Raymond, J., Razavi, R., Reddy, T. E., Reimonn, T. M., Ren, B., Reymond, A., Reynolds, A., Rhie, S. K., Rinn, J., Rivera, M., Rivera-Mulia, J. C., Roberts, B., Rodriguez, J. M., Rozowsky, J., Ryan, R., Rynes, E., Salins, D. N., Sandstrom, R., Sasaki, T., Sathe, S., Savic, D., Scavelli, A., Scheiman, J., Schlaffner, C., Schloss, J. A., Schmitges, F. W., See, L. H., Sethi, A., Setty, M., Shafer, A., Shan, S., Sharon, E., Shen, Q., Shen, Y., Sherwood, R. I., Shi, M., Shin, S., Shoresh, N., Siebenthall, K., Sisu, C., Slifer, T., Sloan, C. A., Smith, A., Snetkova, V., Snyder, M. P., Spacek, D. V., Srinivasan, S., Srivas, R., Stamatoyannopoulos, G., Stamatoyannopoulos, J. A., Stanton, R., Steffan, D., Stehling-Sun, S., Strattan, J. S., Su, A., Sundararaman, B., Suner, M., Syed, T., Szynkarek, M., Tanaka, F. Y., Tenen, D., Teng, M., Thomas, J. A., Toffey, D., Tress, M. L., Trout, D. E., Trynka, G., Tsuji, J., Upchurch, S. A., Ursu, O., Uszczynska-Ratajczak, B., Uziel, M. C., Valencia, A., Biber, B. V., van der Velde, A. G., Van Nostrand, E. L., Vaydylevich, Y., Vazquez, J., Victorsen, A., Vielmetter, J., Vierstra, J., Visel, A., Vlasova, A., Vockley, C. M., Volpi, S., Vong, S., Wang, H., Wang, M., Wang, Q., Wang, R., Wang, T., Wang, W., Wang, X., Wang, Y., Watson, N. K., Wei, X., Wei, Z., Weisser, H., Weissman, S. M., Welch, R., Welikson, R. E., Weng, Z., Westra, H., Whitaker, J. W., White, C., White, K. P., Wildberg, A., Williams, B. A., Wine, D., Witt, H. N., Wold, B., Wolf, M., Wright, J., Xiao, R., Xiao, X., Xu, J., Xu, J., Yan, K., Yan, Y., Yang, H., Yang, X., Yang, Y., Yardimci, G. G., Yee, B. A., Yeo, G. W., Young, T., Yu, T., Yue, F., Zaleski, C., Zang, C., Zeng, H., Zeng, W., Zerbino, D. R., Zhai, J., Zhan, L., Zhan, Y., Zhang, B., Zhang, J., Zhang, J., Zhang, K., Zhang, L., Zhang, P., Zhang, Q., Zhang, X., Zhang, Y., Zhang, Z., Zhao, Y., Zheng, Y., Zhong, G., Zhou, X., Zhu, Y., Zimmerman, J. 2020; 583 (7818): 693–98


    The Encylopedia of DNA Elements (ENCODE) Project launched in 2003 with the long-term goal of developing a comprehensive map of functional elements in the human genome. These included genes, biochemical regions associated with gene regulation (for example, transcription factor binding sites, open chromatin, and histone marks) and transcript isoforms. The marks serve as sites for candidate cis-regulatory elements (cCREs) that may serve functional roles in regulating gene expression1. The project has been extended to model organisms, particularly the mouse. In the third phase of ENCODE, nearly a million and more than 300,000 cCRE annotations have been generated for human and mouse, respectively, and these have provided a valuable resource for the scientific community.

    View details for DOI 10.1038/s41586-020-2449-8

    View details for PubMedID 32728248

  • Metabolic Dynamics and Prediction of Gestational Age and Time to Delivery in Pregnant Women. Cell Liang, L., Rasmussen, M. H., Piening, B., Shen, X., Chen, S., Rost, H., Snyder, J. K., Tibshirani, R., Skotte, L., Lee, N. C., Contrepois, K., Feenstra, B., Zackriah, H., Snyder, M., Melbye, M. 2020; 181 (7): 1680


    Metabolism during pregnancy is a dynamic and precisely programmed process, the failure of which can bring devastating consequences to the mother and fetus. To define a high-resolution temporal profile of metabolites during healthy pregnancy, we analyzed the untargeted metabolome of 784weekly blood samples from 30 pregnant women. Broad changes and a highly choreographed profile were revealed: 4,995 metabolic features (of 9,651 total), 460 annotated compounds (of 687 total), and 34 human metabolic pathways (of 48 total) were significantly changed during pregnancy. Using linear models, we built a metabolic clock with five metabolites that time gestational age in high accordance with ultrasound (R= 0.92). Furthermore, two to three metabolites can identify when labor occurs (time to delivery within two, four, and eight weeks, AUROC ≥ 0.85). Our study represents a weekly characterization of the human pregnancy metabolome, providing a high-resolution landscape for understanding pregnancy with potential clinical utilities.

    View details for DOI 10.1016/j.cell.2020.05.002

    View details for PubMedID 32589958

  • Systematic identification of silencers in human cells. Nature genetics Pang, B., Snyder, M. P. 2020


    The majority of the human genome does not encode proteins. Many of these noncoding regions contain important regulatory sequences that control gene expression. To date, most studies have focused on activators such as enhancers, but regions that repress gene expression-silencers-have not been systematically studied. We have developed a system that identifies silencer regions in a genome-wide fashion on the basis of silencer-mediated transcriptional repression of caspase9. We found that silencers are widely distributed and may function in a tissue-specific fashion. These silencers harbor unique epigenetic signatures and are associated with specific transcription factors. Silencers also act at multiple genes, and at the level of chromosomal domains and long-range interactions. Deletion of silencer regions linked to the drug transporter genes ABCC2 and ABCG2 caused chemo-resistance. Overall, our study demonstrates that tissue-specific silencing is widespread throughout the human genome and probably contributes substantially to the regulation of gene expression and human biology.

    View details for DOI 10.1038/s41588-020-0578-5

    View details for PubMedID 32094911

  • Deep Characterization of the Human Antibody Response to Natural Infection Using Longitudinal Immune Repertoire Sequencing. Molecular & cellular proteomics : MCP Mitsunaga, E. M., Snyder, M. P. 2020; 19 (2): 278-293


    Human antibody response studies are largely restricted to periods of high immune activity (e.g. vaccination). To comprehensively understand the healthy B cell immune repertoire and how this changes over time and through natural infection, we conducted immune repertoire RNA sequencing on flow cytometry-sorted B cell subsets to profile a single individual's antibodies over 11 months through two periods of natural viral infection. We found that 1) a baseline of healthy variable (V) gene usage in antibodies exists and is stable over time, but antibodies in memory cells consistently have a different usage profile relative to earlier B cell stages; 2) a single complementarity-determining region 3 (CDR3) is potentially generated from more than one VJ gene combination; and 3) IgG and IgA antibody transcripts are found at low levels in early human B cell development, suggesting that class switching may occur earlier than previously realized. These findings provide insight into immune repertoire stability, response to natural infections, and human B cell development.

    View details for DOI 10.1074/mcp.RA119.001633

    View details for PubMedID 33451388

  • Molecular Choreography of Acute Exercise. Cell Contrepois, K. n., Wu, S. n., Moneghetti, K. J., Hornburg, D. n., Ahadi, S. n., Tsai, M. S., Metwally, A. A., Wei, E. n., Lee-McMullen, B. n., Quijada, J. V., Chen, S. n., Christle, J. W., Ellenberger, M. n., Balliu, B. n., Taylor, S. n., Durrant, M. G., Knowles, D. A., Choudhry, H. n., Ashland, M. n., Bahmani, A. n., Enslen, B. n., Amsallem, M. n., Kobayashi, Y. n., Avina, M. n., Perelman, D. n., Schüssler-Fiorenza Rose, S. M., Zhou, W. n., Ashley, E. A., Montgomery, S. B., Chaib, H. n., Haddad, F. n., Snyder, M. P. 2020; 181 (5): 1112–30.e16


    Acute physical activity leads to several changes in metabolic, cardiovascular, and immune pathways. Although studies have examined selected changes in these pathways, the system-wide molecular response to an acute bout of exercise has not been fully characterized. We performed longitudinal multi-omic profiling of plasma and peripheral blood mononuclear cells including metabolome, lipidome, immunome, proteome, and transcriptome from 36 well-characterized volunteers, before and after a controlled bout of symptom-limited exercise. Time-series analysis revealed thousands of molecular changes and an orchestrated choreography of biological processes involving energy metabolism, oxidative stress, inflammation, tissue repair, and growth factor response, as well as regulatory pathways. Most of these processes were dampened and some were reversed in insulin-resistant participants. Finally, we discovered biological pathways involved in cardiopulmonary exercise response and developed prediction models revealing potential resting blood-based biomarkers of peak oxygen consumption.

    View details for DOI 10.1016/j.cell.2020.04.043

    View details for PubMedID 32470399

  • Personal aging markers and ageotypes revealed by deep longitudinal profiling. Nature medicine Ahadi, S., Zhou, W., Schussler-Fiorenza Rose, S. M., Sailani, M. R., Contrepois, K., Avina, M., Ashland, M., Brunet, A., Snyder, M. 2020; 26 (1): 83–90


    The molecular changes that occur with aging are not well understood1-4. Here, we performed longitudinal and deep multiomics profiling of 106 healthy individuals from 29 to 75 years of age and examined how different types of 'omic' measurements, including transcripts, proteins, metabolites, cytokines, microbes and clinical laboratory values, correlate with age. We identified both known and new markers that associated with age, as well as distinct molecular patterns of aging in insulin-resistant as compared to insulin-sensitive individuals. In a longitudinal setting, we identified personal aging markers whose levels changed over a short time frame of 2-3 years. Further, we defined different types of aging patterns in different individuals, termed 'ageotypes', on the basis of the types of molecular pathways that changed over time in a given individual. Ageotypes may provide a molecular assessment of personal aging, reflective of personal lifestyle and medical history, that may ultimately be useful in monitoring and intervening in the aging process.

    View details for DOI 10.1038/s41591-019-0719-5

    View details for PubMedID 31932806

  • A Quantitative Proteome Map of the Human Body. Cell Jiang, L. n., Wang, M. n., Lin, S. n., Jian, R. n., Li, X. n., Chan, J. n., Dong, G. n., Fang, H. n., Robinson, A. E., Snyder, M. P. 2020


    Determining protein levels in each tissue and how they compare with RNA levels is important for understanding human biology and disease as well as regulatory processes that control protein levels. We quantified the relative protein levels from over 12,000 genes across 32 normal human tissues. Tissue-specific or tissue-enriched proteins were identified and compared to transcriptome data. Many ubiquitous transcripts are found to encode tissue-specific proteins. Discordance of RNA and protein enrichment revealed potential sites of synthesis and action of secreted proteins. The tissue-specific distribution of proteins also provides an in-depth view of complex biological events that require the interplay of multiple tissues. Most importantly, our study demonstrated that protein tissue-enrichment information can explain phenotypes of genetic diseases, which cannot be obtained by transcript information alone. Overall, our results demonstrate how understanding protein levels can provide insights into regulation, secretome, metabolism, and human diseases.

    View details for DOI 10.1016/j.cell.2020.08.036

    View details for PubMedID 32916130

  • Candidate variants in TUB are associated with familial tremor. PLoS genetics Sailani, M. R., Jahanbani, F. n., Abbott, C. W., Lee, H. n., Zia, A. n., Rego, S. n., Winkelmann, J. n., Hopfner, F. n., Khan, T. N., Katsanis, N. n., Müller, S. H., Berg, D. n., Lyman, K. M., Mychajliw, C. n., Deuschl, G. n., Bernstein, J. A., Kuhlenbäumer, G. n., Snyder, M. P. 2020; 16 (9): e1009010


    Essential tremor (ET) is the most common adult-onset movement disorder. In the present study, we performed whole exome sequencing of a large ET-affected family (10 affected and 6 un-affected family members) and identified a TUB p.V431I variant (rs75594955) segregating in a manner consistent with autosomal-dominant inheritance. Subsequent targeted re-sequencing of TUB in 820 unrelated individuals with sporadic ET and 630 controls revealed significant enrichment of rare nonsynonymous TUB variants (e.g. rs75594955: p.V431I, rs1241709665: p.Ile20Phe, rs55648406: p.Arg49Gln) in the ET cohort (SKAT-O test p-value = 6.20e-08). TUB encodes a transcription factor predominantly expressed in neuronal cells and has been previously implicated in obesity. ChIP-seq analyses of the TUB transcription factor across different regions of the mouse brain revealed that TUB regulates the pathways responsible for neurotransmitter production as well thyroid hormone signaling. Together, these results support the association of rare variants in TUB with ET.

    View details for DOI 10.1371/journal.pgen.1009010

    View details for PubMedID 32956375

  • Landscape of cohesin-mediated chromatin loops in the human genome. Nature Grubert, F. n., Srivas, R. n., Spacek, D. V., Kasowski, M. n., Ruiz-Velasco, M. n., Sinnott-Armstrong, N. n., Greenside, P. n., Narasimha, A. n., Liu, Q. n., Geller, B. n., Sanghi, A. n., Kulik, M. n., Sa, S. n., Rabinovitch, M. n., Kundaje, A. n., Dalton, S. n., Zaugg, J. B., Snyder, M. n. 2020; 583 (7818): 737–43


    Physical interactions between distal regulatory elements have a key role in regulating gene expression, but the extent to which these interactions vary between cell types and contribute to cell-type-specific gene expression remains unclear. Here, to address these questions as part of phase III of the Encyclopedia of DNA Elements (ENCODE), we mapped cohesin-mediated chromatin loops, using chromatin interaction analysis by paired-end tag sequencing (ChIA-PET), and analysed gene expression in 24 diverse human cell types, including core ENCODE cell lines. Twenty-eight per cent of all chromatin loops vary across cell types; these variations modestly correlate with changes in gene expression and are effective at grouping cell types according to their tissue of origin. The connectivity of genes corresponds to different functional classes, with housekeeping genes having few contacts, and dosage-sensitive genes being more connected to enhancer elements. This atlas of chromatin loops complements the diverse maps of regulatory architecture that comprise the ENCODE Encyclopedia, and will help to support emerging analyses of genome structure and function.

    View details for DOI 10.1038/s41586-020-2151-x

    View details for PubMedID 32728247

  • Expanded encyclopaedias of DNA elements in the human and mouse genomes. Nature Moore, J. E., Purcaro, M. J., Pratt, H. E., Epstein, C. B., Shoresh, N. n., Adrian, J. n., Kawli, T. n., Davis, C. A., Dobin, A. n., Kaul, R. n., Halow, J. n., Van Nostrand, E. L., Freese, P. n., Gorkin, D. U., Shen, Y. n., He, Y. n., Mackiewicz, M. n., Pauli-Behn, F. n., Williams, B. A., Mortazavi, A. n., Keller, C. A., Zhang, X. O., Elhajjajy, S. I., Huey, J. n., Dickel, D. E., Snetkova, V. n., Wei, X. n., Wang, X. n., Rivera-Mulia, J. C., Rozowsky, J. n., Zhang, J. n., Chhetri, S. B., Zhang, J. n., Victorsen, A. n., White, K. P., Visel, A. n., Yeo, G. W., Burge, C. B., Lécuyer, E. n., Gilbert, D. M., Dekker, J. n., Rinn, J. n., Mendenhall, E. M., Ecker, J. R., Kellis, M. n., Klein, R. J., Noble, W. S., Kundaje, A. n., Guigó, R. n., Farnham, P. J., Cherry, J. M., Myers, R. M., Ren, B. n., Graveley, B. R., Gerstein, M. B., Pennacchio, L. A., Snyder, M. P., Bernstein, B. E., Wold, B. n., Hardison, R. C., Gingeras, T. R., Stamatoyannopoulos, J. A., Weng, Z. n. 2020; 583 (7818): 699–710


    The human and mouse genomes contain instructions that specify RNAs and proteins and govern the timing, magnitude, and cellular context of their production. To better delineate these elements, phase III of the Encyclopedia of DNA Elements (ENCODE) Project has expanded analysis of the cell and tissue repertoires of RNA transcription, chromatin structure and modification, DNA methylation, chromatin looping, and occupancy by transcription factors and RNA-binding proteins. Here we summarize these efforts, which have produced 5,992 new experimental datasets, including systematic determinations across mouse fetal development. All data are available through the ENCODE data portal (, including phase II ENCODE1 and Roadmap Epigenomics2 data. We have developed a registry of 926,535 human and 339,815 mouse candidate cis-regulatory elements, covering 7.9 and 3.4% of their respective genomes, by integrating selected datatypes associated with gene regulation, and constructed a web-based server (SCREEN; to provide flexible, user-defined access to this resource. Collectively, the ENCODE data and registry provide an expansive resource for the scientific community to build a better understanding of the organization and function of the human and mouse genomes.

    View details for DOI 10.1038/s41586-020-2493-4

    View details for PubMedID 32728249

  • Deep longitudinal multiomics profiling reveals two biological seasonal patterns in California. Nature communications Sailani, M. R., Metwally, A. A., Zhou, W. n., Rose, S. M., Ahadi, S. n., Contrepois, K. n., Mishra, T. n., Zhang, M. J., Kidziński, Ł. n., Chu, T. J., Snyder, M. P. 2020; 11 (1): 4933


    The influence of seasons on biological processes is poorly understood. In order to identify biological seasonal patterns based on diverse molecular data, rather than calendar dates, we performed a deep longitudinal multiomics profiling of 105 individuals over 4 years. Here, we report more than 1000 seasonal variations in omics analytes and clinical measures. The different molecules group into two major seasonal patterns which correlate with peaks in late spring and late fall/early winter in California. The two patterns are enriched for molecules involved in human biological processes such as inflammation, immunity, cardiovascular health, as well as neurological and psychiatric conditions. Lastly, we identify molecules and microbes that demonstrate different seasonal patterns in insulin sensitive and insulin resistant individuals. The results of our study have important implications in healthcare and highlight the value of considering seasonality when assessing population wide health risk and management.

    View details for DOI 10.1038/s41467-020-18758-1

    View details for PubMedID 33004787

  • The human body at cellular resolution: the NIH Human Biomolecular Atlas Program NATURE Snyder, M. P., Lin, S., Posgai, A., Atkinson, M., Regev, A., Rood, J., Rozenblatt-Rosen, O., Gaffney, L., Hupalowska, A., Satija, R., Gehlenborg, N., Shendure, J., Laskin, J., Harbury, P., Nystrom, N. A., Silverstein, J. C., Bar-Joseph, Z., Zhang, K., Borner, K., Lin, Y., Conroy, R., Procaccini, D., Roy, A. L., Pillai, A., Brown, M., Galis, Z. S., Cai, L., Shendure, J., Trapnell, C., Lin, S., Jackson, D., Snyder, M. P., Nolan, G., Greenleaf, W., Lin, Y., Plevritis, S., Ahadi, S., Nevins, S. A., Lee, H., Schuerch, C., Black, S., Venkataraaman, V., Esplin, E., Horning, A., Bahmani, A., Zhang, K., Sun, X., Jain, S., Hagood, J., Pryhuber, G., Kharchenko, P., Atkinson, M., Bodenmiller, B., Brusko, T., Clare-Salzler, M., Nick, H., Otto, K., Posgai, A., Wasserfall, C., Jorgensen, M., Brusko, M., Maffioletti, S., Caprioli, R. M., Spraggins, J. M., Gutierrez, D., Patterson, N., Neumann, E. K., Harris, R., deCaestecker, M., Fogo, A. B., van de Plas, R., Lau, K., Cai, L., Yuan, G., Zhu, Q., Dries, R., Yin, P., Saka, S. K., Kishi, J. Y., Wang, Y., Goldaracena, I., Laskin, J., Ye, D., Burnum-Johnson, K. E., Piehowski, P. D., Ansong, C., Zhu, Y., Harbury, P., Desai, T., Mulye, J., Chou, P., Nagendran, M., Bar-Joseph, Z., Teichmann, S. A., Paten, B., Murphy, R. F., Ma, J., Kiselev, V., Kingsford, C., Ricarte, A., Keays, M., Akoju, S. A., Ruffalo, M., Gehlenborg, N., Kharchenko, P., Vella, M., McCallum, C., Borner, K., Cross, L. E., Friedman, S. H., Heiland, R., Herr, B., Macklin, P., Quardokus, E. M., Record, L., Sluka, J. P., Weber, G. M., Nystrom, N. A., Silverstein, J. C., Blood, P. D., Ropelewski, A. J., Shirey, W. E., Scibek, R. M., Mabee, P., Lenhardt, W., Robasky, K., Michailidis, S., Satija, R., Marioni, J., Regev, A., Butler, A., Stuart, T., Fisher, E., Ghazanfar, S., Rood, J., Gaffney, L., Eraslan, G., Biancalani, T., Vaishnav, E. D., Conroy, R., Procaccini, D., Roy, A., Pillai, A., Brown, M., Galis, Z., Srinivas, P., Pawlyk, A., Sechi, S., Wilder, E., Anderson, J., HuBMAP Consortium 2019; 574 (7777): 187–92


    Transformative technologies are enabling the construction of three-dimensional maps of tissues with unprecedented spatial and molecular resolution. Over the next seven years, the NIH Common Fund Human Biomolecular Atlas Program (HuBMAP) intends to develop a widely accessible framework for comprehensively mapping the human body at single-cell resolution by supporting technology development, data acquisition, and detailed spatial mapping. HuBMAP will integrate its efforts with other funding agencies, programs, consortia, and the biomedical research community at large towards the shared vision of a comprehensive, accessible three-dimensional molecular and cellular atlas of the human body, in health and under various disease conditions.

    View details for DOI 10.1038/s41586-019-1629-x

    View details for Web of Science ID 000489784200035

    View details for PubMedID 31597973

    View details for PubMedCentralID PMC6800388

  • Big data and health. The Lancet. Digital health Snyder, M., Zhou, W. 2019; 1 (6): e252-e254

    View details for DOI 10.1016/S2589-7500(19)30109-8

    View details for PubMedID 33323249

  • HAT1 Coordinates Histone Production and Acetylation via H4 Promoter Binding. Molecular cell Gruber, J. J., Geller, B., Lipchik, A. M., Chen, J., Salahudeen, A. A., Ram, A. N., Ford, J. M., Kuo, C. J., Snyder, M. P. 2019


    The energetic costs of duplicating chromatin are large and therefore likely depend on nutrient sensing checkpoints and metabolic inputs. By studying chromatin modifiers regulated by epithelial growth factor, we identified histone acetyltransferase 1 (HAT1) as an induced gene that enhances proliferation through coordinating histone production, acetylation, and glucose metabolism. In addition to its canonical role as a cytoplasmic histone H4 acetyltransferase, we isolated a HAT1-containing complex bound specifically at promoters of H4 genes. HAT1-dependent transcription of H4 genes required an acetate-sensitive promoter element. HAT1 expression was critical for S-phase progression and maintenance of H3 lysine 9 acetylation at proliferation-associated genes, including histone genes. Therefore, these data describe a feedforward circuit whereby HAT1 captures acetyl groups on nascent histones and drives H4 production by chromatin binding to support chromatin replication and acetylation. These findings have important implications for human disease, since high HAT1 levels associate with poor outcomes across multiple cancer types.

    View details for DOI 10.1016/j.molcel.2019.05.034

    View details for PubMedID 31278053

  • The Integrative Human Microbiome Project NATURE Proctor, L. M., Creasy, H. H., Fettweis, J. M., Lloyd-Price, J., Mahurkar, A., Zhou, W., Buck, G. A., Snyder, M. P., Strauss, J. F., Weinstock, G. M., White, O., Huttenhower, C., Integrative HMP iHMP Res Network 2019; 569 (7758): 641–48


    The NIH Human Microbiome Project (HMP) has been carried out over ten years and two phases to provide resources, methods, and discoveries that link interactions between humans and their microbiomes to health-related outcomes. The recently completed second phase, the Integrative Human Microbiome Project, comprised studies of dynamic changes in the microbiome and host under three conditions: pregnancy and preterm birth; inflammatory bowel diseases; and stressors that affect individuals with prediabetes. The associated research begins to elucidate mechanisms of host-microbiome interactions under these conditions, provides unique data resources (at the HMP Data Coordination Center), and represents a paradigm for future multi-omic studies of the human microbiome.

    View details for DOI 10.1038/s41586-019-1238-8

    View details for Web of Science ID 000470144100031

    View details for PubMedID 31142853

  • A longitudinal big data approach for precision health NATURE MEDICINE Rose, S., Contrepois, K., Moneghetti, K. J., Zhou, W., Mishra, T., Mataraso, S., Dagan-Rosenfeld, O., Ganz, A. B., Dunn, J., Hornburg, D., Rego, S., Perelman, D., Ahadi, S., Sailani, M., Zhou, Y., Leopold, S. R., Chen, J., Ashland, M., Christle, J. W., Avina, M., Limcaoco, P., Ruiz, C., Tan, M., Butte, A. J., Weinstock, G. M., Slavich, G. M., Sodergren, E., McLaughlin, T. L., Haddad, F., Snyder, M. P. 2019; 25 (5): 792-+
  • Longitudinal multi-omics of host-microbe dynamics in prediabetes. Nature Zhou, W., Sailani, M. R., Contrepois, K., Zhou, Y., Ahadi, S., Leopold, S. R., Zhang, M. J., Rao, V., Avina, M., Mishra, T., Johnson, J., Lee-McMullen, B., Chen, S., Metwally, A. A., Tran, T. D., Nguyen, H., Zhou, X., Albright, B., Hong, B., Petersen, L., Bautista, E., Hanson, B., Chen, L., Spakowicz, D., Bahmani, A., Salins, D., Leopold, B., Ashland, M., Dagan-Rosenfeld, O., Rego, S., Limcaoco, P., Colbert, E., Allister, C., Perelman, D., Craig, C., Wei, E., Chaib, H., Hornburg, D., Dunn, J., Liang, L., Rose, S. M., Kukurba, K., Piening, B., Rost, H., Tse, D., McLaughlin, T., Sodergren, E., Weinstock, G. M., Snyder, M. 2019; 569 (7758): 663–71


    Type 2 diabetes mellitus (T2D) is a growing health problem, but little is known about its early disease stages, its effects on biological processes or the transition to clinical T2D. To understand the earliest stages of T2Dbetter, we obtained samples from 106 healthy individuals and individuals with prediabetes over approximately four years and performed deep profiling of transcriptomes, metabolomes, cytokines, and proteomes, as well as changes in the microbiome. This rich longitudinal data set revealed many insights: first, healthy profiles are distinct among individuals while displaying diverse patterns of intra- and/or inter-personal variability. Second, extensive host and microbial changes occur during respiratory viral infections and immunization, and immunization triggers potentially protective responses that are distinct from responses to respiratory viral infections. Moreover, during respiratory viral infections, insulin-resistant participants respond differently than insulin-sensitive participants. Third, global co-association analyses among the thousands of profiled molecules reveal specific host-microbe interactions that differ between insulin-resistant and insulin-sensitive individuals. Last, we identified early personal molecular signatures in one individual that preceded the onset of T2D, including the inflammation markers interleukin-1 receptor agonist (IL-1RA) and high-sensitivity C-reactive protein (CRP) paired with xenobiotic-induced immune signalling. Our study reveals insights into pathways and responses that differ between glucose-dysregulated and healthy individuals during health and disease and provides an open-access data resource to enable further research into healthy, prediabetic and T2D states.

    View details for DOI 10.1038/s41586-019-1236-x

    View details for PubMedID 31142858

  • The NASA Twins Study: A multidimensional analysis of a year-long human spaceflight SCIENCE Garrett-Bakelman, F. E., Darshi, M., Green, S. J., Gur, R. C., Lin, L., Macias, B. R., McKenna, M. J., Meydan, C., Mishra, T., Nasrini, J., Piening, B. D., Rizzardi, L. F., Sharma, K., Siamwala, J. H., Taylor, L., Vitaterna, M., Afkarian, M., Afshinnekoo, E., Ahadi, S., Ambati, A., Arya, M., Bezdan, D., Callahan, C. M., Chen, S., Choi, A. K., Chlipala, G. E., Contrepois, K., Covington, M., Crucian, B. E., De Vivo, I., Dinges, D. F., Ebert, D. J., Feinberg, J. I., Gandara, J. A., George, K. A., Goutsias, J., Grills, G. S., Hargens, A. R., Heer, M., Hillary, R. P., Hoofnagle, A. N., Hook, V. H., Jenkinson, G., Jiang, P., Keshavarzian, A., Laurie, S. S., Lee-McMullen, B., Lumpkins, S. B., MacKay, M., Maienschein-Cline, M. G., Melnick, A. M., Moore, T. M., Nakahira, K., Patel, H. H., Pietrzyk, R., Rao, V., Saito, R., Salins, D. N., Schilling, J. M., Sears, D. D., Sheridan, C. K., Stenger, M. B., Tryggvadottir, R., Urban, A. E., Vaisar, T., Van Espen, B., Zhang, J., Ziegler, M. G., Zwart, S. R., Charles, J. B., Kundrot, C. E., Scott, G. I., Bailey, S. M., Basner, M., Feinberg, A. P., Lee, S. C., Mason, C. E., Mignot, E., Rana, B. K., Smith, S. M., Snyder, M. P., Turek, F. W. 2019; 364 (6436): 144-+
  • Gene-Environment Interaction in the Era of Precision Medicine CELL Li, J., Li, X., Zhang, S., Snyder, M. 2019; 177 (1): 38–44
  • A longitudinal big data approach for precision health. Nature medicine Schüssler-Fiorenza Rose, S. M., Contrepois, K. n., Moneghetti, K. J., Zhou, W. n., Mishra, T. n., Mataraso, S. n., Dagan-Rosenfeld, O. n., Ganz, A. B., Dunn, J. n., Hornburg, D. n., Rego, S. n., Perelman, D. n., Ahadi, S. n., Sailani, M. R., Zhou, Y. n., Leopold, S. R., Chen, J. n., Ashland, M. n., Christle, J. W., Avina, M. n., Limcaoco, P. n., Ruiz, C. n., Tan, M. n., Butte, A. J., Weinstock, G. M., Slavich, G. M., Sodergren, E. n., McLaughlin, T. L., Haddad, F. n., Snyder, M. P. 2019; 25 (5): 792–804


    Precision health relies on the ability to assess disease risk at an individual level, detect early preclinical conditions and initiate preventive strategies. Recent technological advances in omics and wearable monitoring enable deep molecular and physiological profiling and may provide important tools for precision health. We explored the ability of deep longitudinal profiling to make health-related discoveries, identify clinically relevant molecular pathways and affect behavior in a prospective longitudinal cohort (n = 109) enriched for risk of type 2 diabetes mellitus. The cohort underwent integrative personalized omics profiling from samples collected quarterly for up to 8 years (median, 2.8 years) using clinical measures and emerging technologies including genome, immunome, transcriptome, proteome, metabolome, microbiome and wearable monitoring. We discovered more than 67 clinically actionable health discoveries and identified multiple molecular pathways associated with metabolic, cardiovascular and oncologic pathophysiology. We developed prediction models for insulin resistance by using omics measurements, illustrating their potential to replace burdensome tests. Finally, study participation led the majority of participants to implement diet and exercise changes. Altogether, we conclude that deep longitudinal profiling can lead to actionable health discoveries and provide relevant information for precision health.

    View details for PubMedID 31068711

  • Chromatin Remodeling in Response to BRCA2-Crisis. Cell reports Gruber, J. J., Chen, J. n., Geller, B. n., Jäger, N. n., Lipchik, A. M., Wang, G. n., Kurian, A. W., Ford, J. M., Snyder, M. P. 2019; 28 (8): 2182–93.e6


    Individuals with a single functional copy of the BRCA2 tumor suppressor have elevated risks for breast, ovarian, and other solid tumor malignancies. The exact mechanisms of carcinogenesis due to BRCA2 haploinsufficiency remain unclear, but one possibility is that at-risk cells are subject to acute periods of decreased BRCA2 availability and function ("BRCA2-crisis"), which may contribute to disease. Here, we establish an in vitro model for BRCA2-crisis that demonstrates chromatin remodeling and activation of an NF-κB survival pathway in response to transient BRCA2 depletion. Mechanistically, we identify BRCA2 chromatin binding, histone acetylation, and associated transcriptional activity as critical determinants of the epigenetic response to BRCA2-crisis. These chromatin alterations are reflected in transcriptional profiles of pre-malignant tissues from BRCA2 carriers and, therefore, may reflect natural steps in human disease. By modeling BRCA2-crisis in vitro, we have derived insights into pre-neoplastic molecular alterations that may enhance the development of preventative therapies.

    View details for DOI 10.1016/j.celrep.2019.07.057

    View details for PubMedID 31433991

  • The NASA Twins Study: A multidimensional analysis of a year-long human spaceflight. Science (New York, N.Y.) Garrett-Bakelman, F. E., Darshi, M. n., Green, S. J., Gur, R. C., Lin, L. n., Macias, B. R., McKenna, M. J., Meydan, C. n., Mishra, T. n., Nasrini, J. n., Piening, B. D., Rizzardi, L. F., Sharma, K. n., Siamwala, J. H., Taylor, L. n., Vitaterna, M. H., Afkarian, M. n., Afshinnekoo, E. n., Ahadi, S. n., Ambati, A. n., Arya, M. n., Bezdan, D. n., Callahan, C. M., Chen, S. n., Choi, A. M., Chlipala, G. E., Contrepois, K. n., Covington, M. n., Crucian, B. E., De Vivo, I. n., Dinges, D. F., Ebert, D. J., Feinberg, J. I., Gandara, J. A., George, K. A., Goutsias, J. n., Grills, G. S., Hargens, A. R., Heer, M. n., Hillary, R. P., Hoofnagle, A. N., Hook, V. Y., Jenkinson, G. n., Jiang, P. n., Keshavarzian, A. n., Laurie, S. S., Lee-McMullen, B. n., Lumpkins, S. B., MacKay, M. n., Maienschein-Cline, M. G., Melnick, A. M., Moore, T. M., Nakahira, K. n., Patel, H. H., Pietrzyk, R. n., Rao, V. n., Saito, R. n., Salins, D. N., Schilling, J. M., Sears, D. D., Sheridan, C. K., Stenger, M. B., Tryggvadottir, R. n., Urban, A. E., Vaisar, T. n., Van Espen, B. n., Zhang, J. n., Ziegler, M. G., Zwart, S. R., Charles, J. B., Kundrot, C. E., Scott, G. B., Bailey, S. M., Basner, M. n., Feinberg, A. P., Lee, S. M., Mason, C. E., Mignot, E. n., Rana, B. K., Smith, S. M., Snyder, M. P., Turek, F. W. 2019; 364 (6436)


    To understand the health impact of long-duration spaceflight, one identical twin astronaut was monitored before, during, and after a 1-year mission onboard the International Space Station; his twin served as a genetically matched ground control. Longitudinal assessments identified spaceflight-specific changes, including decreased body mass, telomere elongation, genome instability, carotid artery distension and increased intima-media thickness, altered ocular structure, transcriptional and metabolic changes, DNA methylation changes in immune and oxidative stress-related pathways, gastrointestinal microbiota alterations, and some cognitive decline postflight. Although average telomere length, global gene expression, and microbiome changes returned to near preflight levels within 6 months after return to Earth, increased numbers of short telomeres were observed and expression of some genes was still disrupted. These multiomic, molecular, physiological, and behavioral datasets provide a valuable roadmap of the putative health risks for future human spaceflight.

    View details for PubMedID 30975860

  • High-Resolution Bisulfite-Sequencing of Peripheral Blood DNA Methylation in Early-Onset and Familial Risk Breast Cancer Patients. Clinical cancer research : an official journal of the American Association for Cancer Research Chen, J. n., Haanpää, M. K., Gruber, J. J., Jäger, N. n., Ford, J. M., Snyder, M. P. 2019


    Understanding and explaining hereditary predisposition to cancer has focused on the genetic etiology of the disease. However, mutations in known genes associated with breast cancer, such as BRCA1 and BRCA2, account for less than 25% of familial cases of breast cancer. Recently, specific epigenetic modifications at BRCA1 have been shown to promote hereditary breast cancer, but the broader potential for epigenetic contribution to hereditary breast cancer is not yet well understood.We examined DNA methylation through deep bisulfite sequencing of CpG islands and known promoter or regulatory regions in peripheral blood DNA from 99 familial or early-onset breast or ovarian cancer patients, 6 unaffected BRCA-mutation carriers, and 49 unaffected controls.In 9% of patients, we observed altered methylation in the promoter regions of genes known to be involved in cancer including hypermethylation at the tumor suppressor PTEN and hypomethylation at the proto-oncogene TEX14 These alterations occur in the form of allelic methylation that span up to hundreds of base-pairs in length.Our observations suggest a broader role for DNA methylation in early-onset, familial risk breast cancer. Further studies are warranted to clarify these mechanisms and the benefits of DNA methylation screening for early risk prediction of familial cancers.

    View details for DOI 10.1158/1078-0432.CCR-18-2423

    View details for PubMedID 31175093

  • Metformin Affects Heme Function as a Possible Mechanism of Action. G3 (Bethesda, Md.) Li, X., Wang, X., Snyder, M. P. 2018


    Metformin elicits pleiotropic effects that are beneficial for treating diabetes, and as well as particular cancers and aging. In spite of its importance, a convincing and unifying mechanism to explain how metformin operates is lacking. Here we describe investigations into the mechanism of metformin action through heme and hemoprotein(s). Metformin suppresses heme production by 50% in yeast, and this suppression requires mitochondria function, which is necessary for heme synthesis. At high concentrations comparable to those in the clinic, metformin also suppresses heme production in human erythrocytes, erythropoietic cells and hepatocytes by 30-50%; the heme-targeting drug artemisinin operates at a greater potency. Significantly, metformin prevents oxidation of heme in three protein scaffolds, cytochrome c, myoglobin and hemoglobin, with Kd values < 3 mM suggesting a dual oxidation and reduction role in the regulation of heme redox transition. Since heme- and porphyrin-like groups operate in diverse enzymes that control important metabolic processes, we suggest that metformin acts, at least in part, through stabilizing appropriate redox states in heme and other porphyrin-containing groups to control cellular metabolism.

    View details for PubMedID 30554148

  • High Frequency Actionable Pathogenic Exome Variants in an Average-Risk Cohort. Cold Spring Harbor molecular case studies Rego, S., Dagan-Rosenfeld, O., Zhou, W., Sailani, M. R., Limcaoco, P., Colbert, E., Avina, M., Wheeler, J., Craig, C., Salins, D., Rost, H. L., Dunn, J., McLaughlin, T., Steinmetz, L. M., Bernstein, J. A., Snyder, M. P. 2018


    Exome sequencing is increasingly utilized in both clinical and non-clinical settings, but little is known about its utility in healthy individuals. Most previous studies on this topic have examined a small subset of genes known to be implicated in human disease and/or have used automated pipelines to assess pathogenicity of known variants. In order to determine the frequency of both medically actionable and non-actionable but medically relevant exome findings in the general population we assessed the exomes of 70 participants who have been extensively characterized over the past several years as part of a longitudinal integrated multi-omics profiling study. We analyzed exomes by identifying rare likely pathogenic and pathogenic variants in genes associated with Mendelian disease in the Online Mendelian Inheritance in Man (OMIM) database. We then used American College of Medical Genetics (ACMG) guidelines for the classification of rare sequence variants. Additionally, we assessed pharmacogenetic variants. Twelve out of 70 (17%) participants had medically actionable findings in Mendelian disease genes. Five had phenotypes or family histories associated with their genetic variants. The frequency of actionable variants is higher than that reported in most previous studies and suggests added benefit from utilizing expanded gene lists and manual curation to assess actionable findings. A total of 63 participants (90%) had additional non-actionable findings, including 60 who were found to be carriers for recessive diseases and 21 who have increased Alzheimer's disease risk due to heterozygous or homozygous APOE e4 alleles (18 participants had both). Our results suggest that exome sequencing may have considerable more utility for health management in the general population than previously thought.

    View details for PubMedID 30487145

  • Longitudinal personal DNA methylome dynamics in a human with a chronic condition. Nature medicine Chen, R., Xia, L., Tu, K., Duan, M., Kukurba, K., Li-Pook-Than, J., Xie, D., Snyder, M. 2018


    Epigenomics regulates gene expression and is as important as genomics in precision personal health, as it is heavily influenced by environment and lifestyle. We profiled whole-genome DNA methylation and the corresponding transcriptome of peripheral blood mononuclear cells collected from a human volunteer over a period of 36 months, generating 28 methylome and 57 transcriptome datasets. We found that DNA methylomic changes are associated with infrequent glucose level alteration, whereas the transcriptome underwent dynamic changes during events such as viral infections. Most DNA meta-methylome changes occurred 80-90days before clinically detectable glucose elevation. Analysis of the deep personal methylome dataset revealed an unprecedented number of allelic differentially methylated regions that remain stable longitudinally and are preferentially associated with allele-specific gene regulation. Our results revealed that changes in different types of 'omics' data associate with different physiological aspects of this individual: DNA methylation with chronic conditions and transcriptome with acute events.

    View details for PubMedID 30397358

  • Dynamic Human Environmental Exposome Revealed by Longitudinal Personal Monitoring. Cell Jiang, C., Wang, X., Li, X., Inlora, J., Wang, T., Liu, Q., Snyder, M. 2018; 175 (1): 277


    Human health is dependent upon environmental exposures, yet the diversity and variation in exposures are poorly understood. We developed a sensitive method to monitor personal airborne biological and chemical exposures and followed the personal exposomes of 15 individuals for up to 890days and over 66 distinct geographical locations. We found that individuals are potentially exposed to thousands of pan-domain species and chemical compounds, including insecticides and carcinogens. Personal biological and chemical exposomes are highly dynamic and vary spatiotemporally, even for individuals located in the same general geographical region.Integrated analysis of biological and chemical exposomes revealed strong location-dependent relationships. Finally, construction of an exposome interaction network demonstrated the presence of distinct yet interconnected human- and environment-centric clouds, comprised of interacting ecosystems such as human, flora, pets, and arthropods. Overall, we demonstrate that human exposomes are diverse, dynamic, spatiotemporally-driven interaction networks with the potential to impact human health.

    View details for PubMedID 30241608

  • Decoding the Genomics of Abdominal Aortic Aneurysm. Cell Li, J., Pan, C., Zhang, S., Spin, J. M., Deng, A., Leung, L. L., Dalman, R. L., Tsao, P. S., Snyder, M. 2018; 174 (6): 1361


    A key aspect of genomic medicine is to make individualized clinical decisions from personal genomes. We developed a machine-learning framework to integrate personal genomes and electronic health record (EHR) data and used this framework to study abdominal aortic aneurysm (AAA), a prevalent irreversible cardiovascular disease with unclear etiology. Performing whole-genome sequencing on AAA patients and controls, we demonstrated its predictive precision solely from personal genomes. By modeling personal genomes with EHRs, this framework quantitatively assessed the effectiveness of adjusting personal lifestyles given personal genome baselines, demonstrating its utility as a personal health management tool. We showed that this new framework agnostically identified genetic components involved in AAA, which were subsequently validated in human aortic tissues and in murine models. Our study presents a new framework for disease genome analysis, which can be used for both health management and understanding the biological architecture of complex diseases. VIDEO ABSTRACT.

    View details for PubMedID 30193110

  • Glucotypes reveal new patterns of glucose dysregulation. PLoS biology Hall, H., Perelman, D., Breschi, A., Limcaoco, P., Kellogg, R., McLaughlin, T., Snyder, M. 2018; 16 (7): e2005143


    Diabetes is an increasing problem worldwide; almost 30 million people, nearly 10% of the population, in the United States are diagnosed with diabetes. Another 84 million are prediabetic, and without intervention, up to 70% of these individuals may progress to type 2 diabetes. Current methods for quantifying blood glucose dysregulation in diabetes and prediabetes are limited by reliance on single-time-point measurements or on average measures of overall glycemia and neglect glucose dynamics. We have used continuous glucose monitoring (CGM) to evaluate the frequency with which individuals demonstrate elevations in postprandial glucose, the types of patterns, and how patterns vary between individuals given an identical nutrient challenge. Measurement of insulin resistance and secretion highlights the fact that the physiology underlying dysglycemia is highly variable between individuals. We developed an analytical framework that can group individuals according to specific patterns of glycemic responses called "glucotypes" that reveal heterogeneity, or subphenotypes, within traditional diagnostic categories of glucose regulation. Importantly, we found that even individuals considered normoglycemic by standard measures exhibit high glucose variability using CGM, with glucose levels reaching prediabetic and diabetic ranges 15% and 2% of the time, respectively. We thus show that glucose dysregulation, as characterized by CGM, is more prevalent and heterogeneous than previously thought and can affect individuals considered normoglycemic by standard measures, and specific patterns of glycemic responses reflect variable underlying physiology. The interindividual variability in glycemic responses to standardized meals also highlights the personal nature of glucose regulation. Through extensive phenotyping, we developed a model for identifying potential mechanisms of personal glucose dysregulation and built a webtool for visualizing a user-uploaded CGM profile and classifying individualized glucose patterns into glucotypes.

    View details for PubMedID 30040822

  • Natural Selection Has Differentiated the Progesterone Receptor among Human Populations. American journal of human genetics Li, J., Hong, X., Mesiano, S., Muglia, L. J., Wang, X., Snyder, M., Stevenson, D. K., Shaw, G. M. 2018


    The progesterone receptor (PGR) plays a central role in maintaining pregnancy and is significantly associated with medical conditions such as preterm birth that affects 12.6% of all the births in U.S. PGR has been evolving rapidly since the common ancestor of human and chimpanzee, and we herein investigated evolutionary dynamics of PGR during recent human migration and population differentiation. Our study revealed substantial population differentiation at the PGR locus driven by natural selection, where very recent positive selection in East Asians has substantially decreased its genetic diversity by nearly fixing evolutionarily novel alleles. On the contrary, in European populations, the PGR locus has been promoted to a highly polymorphic state likely due to balancing selection. Integrating transcriptome data across multiple tissue types together with large-scale genome-wide association data for preterm birth, our study demonstrated the consequence of the selection event in East Asians on remodeling PGR expression specifically in the ovary and determined a significant association of early spontaneous preterm birth with the evolutionarily selected variants. To reconstruct its evolutionary trajectory on the human lineage, we observed substantial differentiation between modern and archaic humans at the PGR locus, including fixation of a deleterious missense allele in the Neanderthal genome that was later introgressed in modern human populations. Taken together, our study revealed substantial evolutionary innovation in PGR even during very recent human evolution, and its different forms among human populations likely result in differential susceptibility to progesterone-associated disease conditions including preterm birth.

    View details for PubMedID 29937092

  • Systematic Protein Prioritization for Targeted Proteomics Studies through Literature Mining JOURNAL OF PROTEOME RESEARCH Yu, K., Lee, T., Wan, C., Chen, Y., Re, C., Kou, S. C., Chiang, J., Kohane, I. S., Snyder, M. 2018; 17 (4): 1383–96


    There are more than 3.7 million published articles on the biological functions or disease implications of proteins, constituting an important resource of proteomics knowledge. However, it is difficult to summarize the millions of proteomics findings in the literature manually and quantify their relevance to the biology and diseases of interest. We developed a fully automated bioinformatics framework to identify and prioritize proteins associated with any biological entity. We used the 22 targeted areas of the Biology/Disease-driven (B/D)-Human Proteome Project (HPP) as examples, prioritized the relevant proteins through their Protein Universal Reference Publication-Originated Search Engine (PURPOSE) scores, validated the relevance of the score by comparing the protein prioritization results with a curated database, computed the scores of proteins across the topics of B/D-HPP, and characterized the top proteins in the common model organisms. We further extended the bioinformatics workflow to identify the relevant proteins in all organ systems and human diseases and deployed a cloud-based tool to prioritize proteins related to any custom search terms in real time. Our tool can facilitate the prioritization of proteins for any organ system or disease of interest and can contribute to the development of targeted proteomic studies for precision medicine.

    View details for PubMedID 29505266

  • Microfluidic isoform sequencing shows widespread splicing coordination in the human transcriptome GENOME RESEARCH Tilgner, H., Jahanbani, F., Gupta, I., Collier, P., Wei, E., Rasmussen, M., Snyder, M. 2018; 28 (2): 231–42


    Understanding transcriptome complexity is crucial for understanding human biology and disease. Technologies such as Synthetic long-read RNA sequencing (SLR-RNA-seq) delivered 5 million isoforms and allowed assessing splicing coordination. Pacific Biosciences and Oxford Nanopore increase throughput also but require high input amounts or amplification. Our new droplet-based method, sparse isoform sequencing (spISO-seq), sequences 100k-200k partitions of 10-200 molecules at a time, enabling analysis of 10-100 million RNA molecules. SpISO-seq requires less than 1 ng of input cDNA, limiting or removing the need for prior amplification with its associated biases. Adjusting the number of reads devoted to each molecule reduces sequencing lanes and cost, with little loss in detection power. The increased number of molecules expands our understanding of isoform complexity. In addition to confirming our previously published cases of splicing coordination (e.g., BIN1), the greater depth reveals many new cases, such as MAPT Coordination of internal exons is found to be extensive among protein coding genes: 23.5%-59.3% (95% confidence interval) of highly expressed genes with distant alternative exons exhibit coordination, showcasing the need for long-read transcriptomics. However, coordination is less frequent for noncoding sequences, suggesting a larger role of splicing coordination in shaping proteins. Groups of genes with coordination are involved in protein-protein interactions with each other, raising the possibility that coordination facilitates complex formation and/or function. We also find new splicing coordination types, involving initial and terminal exons. Our results provide a more comprehensive understanding of the human transcriptome and a general, cost-effective method to analyze it.

    View details for PubMedID 29196558

    View details for PubMedCentralID PMC5793787

  • A genome-wide association study identifies only two ancestry specific variants associated with spontaneous preterm birth SCIENTIFIC REPORTS Rappoport, N., Toung, J., Hadley, D., Wong, R. J., Fujioka, K., Reuter, J., Abbott, C. W., Oh, S., Hu, D., Eng, C., Huntsman, S., Bodian, D. L., Niederhuber, J. E., Hong, X., Zhang, G., Sikora-Wohfeld, W., Gignoux, C. R., Wang, H., Oehlert, J., Jelliffe-Pawlowski, L. L., Gould, J. B., Darmstadt, G. L., Wang, X., Bustamante, C. D., Snyder, M. P., Ziv, E., Patsopoulos, N. A., Muglia, L. J., Burchard, E., Shaw, G. M., O'Brodovich, H. M., Stevenson, D. K., Butte, A. J., Sirota, M. 2018; 8: 226


    Preterm birth (PTB), or the delivery prior to 37 weeks of gestation, is a significant cause of infant morbidity and mortality. Although twin studies estimate that maternal genetic contributions account for approximately 30% of the incidence of PTB, and other studies reported fetal gene polymorphism association, to date no consistent associations have been identified. In this study, we performed the largest reported genome-wide association study analysis on 1,349 cases of PTB and 12,595 ancestry-matched controls from the focusing on genomic fetal signals. We tested over 2 million single nucleotide polymorphisms (SNPs) for associations with PTB across five subpopulations: African (AFR), the Americas (AMR), European, South Asian, and East Asian. We identified only two intergenic loci associated with PTB at a genome-wide level of significance: rs17591250 (P = 4.55E-09) on chromosome 1 in the AFR population and rs1979081 (P = 3.72E-08) on chromosome 8 in the AMR group. We have queried several existing replication cohorts and found no support of these associations. We conclude that the fetal genetic contribution to PTB is unlikely due to single common genetic variant, but could be explained by interactions of multiple common variants, or of rare variants affected by environmental influences, all not detectable using a GWAS alone.

    View details for PubMedID 29317701

  • Integrative Personal Omics Profiles during Periods of Weight Gain and Loss. Cell systems Piening, B. D., Zhou, W. n., Contrepois, K. n., Röst, H. n., Gu Urban, G. J., Mishra, T. n., Hanson, B. M., Bautista, E. J., Leopold, S. n., Yeh, C. Y., Spakowicz, D. n., Banerjee, I. n., Chen, C. n., Kukurba, K. n., Perelman, D. n., Craig, C. n., Colbert, E. n., Salins, D. n., Rego, S. n., Lee, S. n., Zhang, C. n., Wheeler, J. n., Sailani, M. R., Liang, L. n., Abbott, C. n., Gerstein, M. n., Mardinoglu, A. n., Smith, U. n., Rubin, D. L., Pitteri, S. n., Sodergren, E. n., McLaughlin, T. L., Weinstock, G. M., Snyder, M. P. 2018


    Advances in omics technologies now allow an unprecedented level of phenotyping for human diseases, including obesity, in which individual responses to excess weight are heterogeneous and unpredictable. To aid the development of better understanding of these phenotypes, we performed a controlled longitudinal weight perturbation study combining multiple omics strategies (genomics, transcriptomics, multiple proteomics assays, metabolomics, and microbiomics) during periods of weight gain and loss in humans. Results demonstrated that: (1) weight gain is associated with the activation of strong inflammatory and hypertrophic cardiomyopathy signatures in blood; (2) although weight loss reverses some changes, a number of signatures persist, indicative of long-term physiologic changes; (3) we observed omics signatures associated with insulin resistance that may serve as novel diagnostics; (4) specific biomolecules were highly individualized and stable in response to perturbations, potentially representing stable personalized markers. Most data are available open access and serve as a valuable resource for the community.

    View details for PubMedID 29361466

  • Association of Omics Features with Histopathology Patterns in Lung Adenocarcinoma CELL SYSTEMS Yu, K., Berry, G. J., Rubin, D. L., Re, C., Altman, R. B., Snyder, M. 2017; 5 (6): 620-+


    Adenocarcinoma accounts for more than 40% of lung malignancy, and microscopic pathology evaluation is indispensable for its diagnosis. However, how histopathology findings relate to molecular abnormalities remains largely unknown. Here, we obtained H&E-stained whole-slide histopathology images, pathology reports, RNA sequencing, and proteomics data of 538 lung adenocarcinoma patients from The Cancer Genome Atlas and used these to identify molecular pathways associated with histopathology patterns. We report cell-cycle regulation and nucleotide binding pathways underpinning tumor cell dedifferentiation, and we predicted histology grade using transcriptomics and proteomics signatures (area under curve >0.80). We built an integrative histopathology-transcriptomics model to generate better prognostic predictions for stage I patients (p = 0.0182 ± 0.0021) compared with gene expression or histopathology studies alone, and the results were replicated in an independent cohort (p = 0.0220 ± 0.0070). These results motivate the integration of histopathology and omics data to investigate molecular mechanisms of pathology findings and enhance clinical prognostic prediction.

    View details for PubMedID 29153840

    View details for PubMedCentralID PMC5746468

  • Plasma sterols and depressive symptom severity in a population-based cohort PLOS ONE Cenik, B., Cenik, C., Snyder, M. P., Brown, E. 2017; 12 (9): e0184382


    Convergent evidence strongly suggests major depressive disorder is heterogeneous in its etiology and clinical characteristics. Depression biomarkers hold potential for identifying etiological subtypes, improving diagnostic accuracy, predicting treatment response, and personalization of treatment. Human plasma contains numerous sterols that have not been systematically studied. Changes in cholesterol concentrations have been implicated in suicide and depression, suggesting plasma sterols may be depression biomarkers. Here, we investigated associations between plasma levels of 34 sterols (measured by mass spectrometry) and scores on the Quick Inventory of Depressive Symptomatology-Self Report (QIDS-SR16) scale in 3117 adult participants in the Dallas Heart Study, an ethnically diverse, population-based cohort. We built a random forest model using feature selection from a pool of 43 variables including demographics, general health indicators, and sterol concentrations. This model comprised 19 variables, 13 of which were sterol concentrations, and explained 15.5% of the variation in depressive symptoms. Desmosterol concentrations below the fifth percentile (1.9 ng/mL, OR 1.9, 95% CI 1.2-2.9) were significantly associated with depressive symptoms of at least moderate severity (QIDS-SR16 score ≥10.5). This is the first study reporting a novel association between plasma concentrations cholesterol precursors and depressive symptom severity.

    View details for PubMedID 28886149

  • Fetal de novo mutations and preterm birth. PLoS genetics Li, J., Oehlert, J., Snyder, M., Stevenson, D. K., Shaw, G. M. 2017; 13 (4)


    Preterm birth (PTB) affects ~12% of pregnancies in the US. Despite its high mortality and morbidity, the molecular etiology underlying PTB has been unclear. Numerous studies have been devoted to identifying genetic factors in maternal and fetal genomes, but so far few genomic loci have been associated with PTB. By analyzing whole-genome sequencing data from 816 trio families, for the first time, we observed the role of fetal de novo mutations in PTB. We observed a significant increase in de novo mutation burden in PTB fetal genomes. Our genomic analyses further revealed that affected genes by PTB de novo mutations were dosage sensitive, intolerant to genomic deletions, and their mouse orthologs were likely developmentally essential. These genes were significantly involved in early fetal brain development, which was further supported by our analysis of copy number variants identified from an independent PTB cohort. Our study indicates a new mechanism in PTB occurrence independently contributed from fetal genomes, and thus opens a new avenue for future PTB research.

    View details for DOI 10.1371/journal.pgen.1006689

    View details for PubMedID 28388617

Our Publications

Michael P. Snyder is the 12th most cited Molecular Biology & Genetics researcher in the world with a global h index of 395 and an i10 index of 1163  (as of June 2022).