Nurturing diversity and inclusion in AI in Biomedicine through a virtual summer program for high school students.

Artificial Intelligence (AI) has the power to improve our lives through a wide variety of applications, many of which fall into the healthcare space; however, a lack of diversity is contributing to limitations in how broadly AI can help people. The UCSF AI4ALL program was established in 2019 to address this issue by targeting high school students from underrepresented backgrounds in AI, giving them a chance to learn about AI with a focus on biomedicine, and promoting diversity and inclusion. In 2020, the UCSF AI4ALL three-week program was held entirely online due to the COVID-19 pandemic. Thus, students participated virtually to gain experience with AI, interact with diverse role models in AI, and learn about advancing health through AI. Specifically, they attended lectures in coding and AI, received an in-depth research experience through hands-on projects exploring COVID-19, and engaged in mentoring and personal development sessions with faculty, researchers, industry professionals, and undergraduate and graduate students, many of whom were women and from underrepresented racial and ethnic backgrounds. At the conclusion of the program, the students presented the results of their research projects at the final symposium. Comparison of pre- and post-program survey responses from students demonstrated that after the program, significantly more students were familiar with how to work with data and to evaluate and apply machine learning algorithms. There were also nominally significant increases in the students' knowing people in AI from historically underrepresented groups, feeling confident in discussing AI, and being aware of careers in AI. We found that we were able to engage young students in AI via our online training program and nurture greater diversity in AI. This work can guide AI training programs aspiring to engage and educate students entirely online, and motivate people in AI to strive towards increasing diversity and inclusion in this field.

Genome-Wide Association Study of Ustekinumab Response in Psoriasis.

Heterogeneous genetic and environmental factors contribute to the psoriasis phenotype, resulting in a wide range of patient response to targeted therapies. Here, we investigate genetic factors associated with response to the IL-12/23 inhibitor ustekinumab in psoriasis. To date, only HLA-C*06:02 has been consistently reported to associate with ustekinumab response in psoriasis. Genome-wide association testing was performed on the continuous outcome of percent change in Psoriasis Area Severity Index (PASI) at 12 weeks of ustekinumab therapy relative to baseline. A total of 439 European ancestry individuals with psoriasis were included [mean age, 46.6 years; 277 men (63.1%)]. 310 (70.6%) of the participants comprised the discovery cohort and the remaining 129 (29.4%) individuals comprised the validation cohort. Chromosome 4 variant rs35569429 was significantly associated with ustekinumab response at 12 weeks at a genome-wide significant level in the discovery cohort and replicated in the validation cohort. Of psoriasis subjects with at least one copy of the deletion allele of rs35569429, 44% achieved PASI75 (75% improvement in PASI from baseline) at week 12 of ustekinumab treatment, while for subjects without the deletion allele, 75% achieved PASI75 at week 12. We found that differences in treatment response increased when rs35569429 was considered alongside HLA-C*06:02. Psoriasis patients with the deletion allele of rs35569429 who were HLA-C*06:02 negative had a PASI75 response rate of 35% at week 12, while those without the deletion allele who were HLA-C*06:02 positive had a PASI75 response rate of 82% at week 12. Through GWAS, we identified a novel SNP that is potentially associated with response to ustekinumab in psoriasis.