Stanford Advisors

2022-23 Courses

All Publications

  • Increasing equity in science requires better ethics training: A course by trainees, for trainees. Cell genomics Patel, R. A., Ungar, R. A., Pyke, A. L., Adimoelja, A., Chakraborty, M., Cotter, D. J., Freund, M., Goddard, P., Gomez-Stafford, J., Greenwald, E., Higgs, E., Hunter, N., MacKenzie, T. M., Narain, A., Gjorgjieva, T., Martschenko, D. O. 2024: 100554


    Despite the profound impacts of scientific research, few scientists have received the necessary training to productively discuss the ethical and societal implications of their work. To address this critical gap, we-a group of predominantly human genetics trainees-developed a course on genetics, ethics, and society. We intend for this course to serve as a template for other institutions and scientific disciplines. Our curriculum positions human genetics within its historical and societal context and encourages students to evaluate how societal norms and structures impact the conduct of scientific research. We demonstrate the utility of this course via surveys of enrolled students and provide resources and strategies for others hoping to teach a similar course. We conclude by arguing that if we are to work toward rectifying the inequities and injustices produced by our field, we must first learn to view our own research as impacting and being impacted by society.

    View details for DOI 10.1016/j.xgen.2024.100554

    View details for PubMedID 38697124

  • Genetic interactions drive heterogeneity in causal variant effect sizes for gene expression and complex traits. American journal of human genetics Patel, R. A., Musharoff, S. A., Spence, J. P., Pimentel, H., Tcheandjieu, C., Mostafavi, H., Sinnott-Armstrong, N., Clarke, S. L., Smith, C. J., V.A. Million Veteran Program,,, Durda, P. P., Taylor, K. D., Tracy, R., Liu, Y., Johnson, W. C., Aguet, F., Ardlie, K. G., Gabriel, S., Smith, J., Nickerson, D. A., Rich, S. S., Rotter, J. I., Tsao, P. S., Assimes, T. L., Pritchard, J. K. 2022


    Despite the growing number of genome-wide association studies (GWASs), it remains unclear to what extent gene-by-gene and gene-by-environment interactions influence complex traits in humans. The magnitude of genetic interactions in complex traits has been difficult to quantify because GWASs are generally underpowered to detect individual interactions of small effect. Here, we develop a method to test for genetic interactions that aggregates information across all trait-associated loci. Specifically, we test whether SNPs in regions of European ancestry shared between European American and admixed African American individuals have the same causal effect sizes. We hypothesize that in African Americans, the presence of genetic interactions will drive the causal effect sizes of SNPs in regions of European ancestry to be more similar to those of SNPs in regions of African ancestry. We apply our method to two traits: gene expression in 296 African Americans and 482 European Americans in the Multi-Ethnic Study of Atherosclerosis (MESA) and low-density lipoprotein cholesterol (LDL-C) in 74K African Americans and 296K European Americans in the Million Veteran Program (MVP). We find significant evidence for genetic interactions in our analysis of gene expression; for LDL-C, we observe a similar point estimate, although this is not significant, most likely due to lower statistical power. These results suggest that gene-by-gene or gene-by-environment interactions modify the effect sizes of causal variants in human complex traits.

    View details for DOI 10.1016/j.ajhg.2022.05.014

    View details for PubMedID 35716666