Using Electronic Health Records for Scientific Research: Promises and Perils

Professor Bhramar Mukherjee

Bhramar MukherjeeLink opens in a new window is the John D. Kalbfleisch Collegiate Professor and chair of the Department of Biostatistics at the University of Michigan School of Public Health. She is also a professor in the Department of Epidemiology and a professor of Global Public Health at the School of Public Health.

Mukherjee's research focuses on the development and application of statistical methods in epidemiology, environmental health, cancer research and disease risk assessment. She has authored more than 340 publications in statistics, biostatistics, epidemiology and medical journals and has led several impactful extramural grants as a principal investigator from both the NSF and the NIH.

Dedicated to diversifying the statistical and data science workforce, Mukherjee has been leading a flagship undergraduate summer program in Big Data since 2015. This program has trained nearly 300 undergraduates, more than 60% of whom go on to pursue graduate school in a quantitative field. She is a fellow of the American Statistical Association and the American Association for the Advancement of Science. She is recipient of many awards, including the Janet Norwood Award and the Sarah Goddard Power award in 2021. In 2022, she was elected to the National Academy of Medicine, one of the highest honors for researchers in health and medicine.

Using Electronic Health Records for Scientific Research: Promises and Perils

Electronic Health Records (EHR) linked with other auxiliary data sources hold tremendous potential for conducting real time actionable research. However, one has to answer two fundamental questions before conducting inference: "Who is in my study?" and "What is the target population of Inference?". Without accounting for selection bias, one can quickly produce rapid but inaccurate conclusions. In this talk, I will discuss a statistical framework for jointly considering selection bias and phenotype misclassification in analyzing EHR data. Examples will include genome and phenome-wide association studies of Cancer and COVID-19 outcomes using data from the Michigan Genomics initiative and the UK Biobank. This is joint work with Lars Fritsche, Lauren Beesley and Maxwell Salvatore at the University of Michigan School of Public Health.

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Abstract

Initial development of the embryo is exclusively under the control of maternally deposited proteins and RNAs. In externally developing metazoan embryos cycles of extremely fast and synchronous cell divisions precedes global zygotic genome activation (ZGA). The genome is activated when a threshold nucleo-cytoplasmic ratio is reached, which dilutes repressive maternal factors. This event coincides with the mid-blastula transition (MBT). However, the earliest expressed genes, which prepare the rest of the genome for activation escape global genome repression and are activated well before the MBT. How do these genes get transcribed during the short cell cycles, which are only 15 minutes and lack G phases, remains mostly unexplored. We have developed a native transcription imaging tool, which detected nascent transcripts accumulating in a transcription body during the minor wave of genome activation. We described the spatial and temporal dynamics of the first wave of genome activation and its cross-regulation by the cell cycle. We demonstrate that the transcription body forms at an excessively high copy number gene cluster, composed of the highest promoter density in the genome and which encodes miR430 microRNAs responsible for clearance of maternal mRNAs. While this transcription body represent the main sites of detectable transcription, we showed that minor wave genes can be independently transcribed due to their distinct promoter architecture and promoter features from that of the main wave of ZGA. These findings suggest distinct transcription mechanisms between the minor and major waves of genome activation.

To further explore mechanisms of zygotic genome activation and the contribution of parental information to this process we also focussed on the formation and specification of primordial germ cells, which are singled out by selective retention of maternal determinants. 4D imaging and epigenomic analysis of these cells have uncovered the role of cytoplasmic maternal determinants in distinct chromatin topology organisation for specific gene regulation of primordial germ cells during early development.

Selected references

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4. Hadzhiev, Y., Qureshi, H., Wheatley, L., Cooper, L. Jasiulewicz, A., Wragg, J., Nguyen, H., Poovathumkadavil, D., Conic, S., Bajan, S., Sik, A., Hutvagner, G., Tora, L., Gambus, A., Fossey J. and Müller F. (2019) A cell cycle-coordinated nuclear compartment for Polymerase II transcription encompasses the earliest gene expression before global genome activation Nature Communications 2019 Feb 11;10(1):691.

5. Haberle, V., Li, N., Hadzhiev, Y., Plessy, C., Previti, C., Nepal, C., Gehrig, J., Dong, X., Akalin, A., Suzuki, A-M., van IJcken, W., Armant, O., Ferg, M., Strähle, U., Carninci, P., Müller F.* and Lenhard B. Two independent transcription initiation codes overlap on vertebrate core promoters. Nature, 507(7492):381-5, *co-corresponding author.