Using a chat-based informed consent tool in large-scale genomic research.

OBJECTIVE: We implemented a chatbot consent tool to shift the time burden from study staff in support of a national genomics research study. MATERIALS AND METHODS: We created an Institutional Review Board-approved script for automated chat-based consent. We compared data from prospective participants who used the tool or had traditional consent conversations with study staff. RESULTS: Chat-based consent, completed on a user's schedule, was shorter than the traditional conversation. This did not lead to a significant change in affirmative consents. Within affirmative consents and declines, more prospective participants completed the chat-based process. A quiz to assess chat-based consent user understanding had a high pass rate with no reported negative experiences. CONCLUSION: Our report shows that a structured script can convey important information while realizing the benefits of automation and burden shifting. Analysis suggests that it may be advantageous to use chatbots to scale this rate-limiting step in large research projects.

Increased diagnostic yield from negative whole genome-slice panels using automated reanalysis.

We evaluated the diagnostic yield using genome-slice panel reanalysis in the clinical setting using an automated phenotype/gene ranking system. We analyzed whole genome sequencing (WGS) data produced from clinically ordered panels built as bioinformatic slices for 16 clinically diverse, undiagnosed cases referred to the Pediatric Mendelian Genomics Research Center, an NHGRI-funded GREGoR Consortium site. Genome-wide reanalysis was performed using Moon™, a machine-learning-based tool for variant prioritization. In five out of 16 cases, we discovered a potentially clinically significant variant. In four of these cases, the variant was found in a gene not included in the original panel due to phenotypic expansion of a disorder or incomplete initial phenotyping of the patient. In the fifth case, the gene containing the variant was included in the original panel, but being a complex structural rearrangement with intronic breakpoints outside the clinically analyzed regions, it was not initially identified. Automated genome-wide reanalysis of clinical WGS data generated during targeted panels testing yielded a 25% increase in diagnostic findings and a possibly clinically relevant finding in one additional case, underscoring the added value of analyses versus those routinely performed in the clinical setting.

"Development and Implementation of Novel Chatbot-based Genomic Research Consent".

Objective: To conduct a retrospective analysis comparing traditional human-based consenting to an automated chat-based consenting process. Materials and Methods: We developed a new chat-based consent using our IRB-approved consent forms. We leveraged a previously developed platform (GiaⓇ, or "Genetic Information Assistant") to deliver the chat content to candidate participants. The content included information about the study, educational information, and a quiz to assess understanding. We analyzed 144 families referred to our study during a 6-month time period. A total of 37 families completed consent using the traditional process, while 35 families completed consent using Gia. Results: Engagement rates were similar between both consenting methods. The median length of the consent conversation was shorter for Gia users compared to traditional (44 vs. 76 minutes). Additionally, the total time from referral to consent completion was faster with Gia (5 vs. 16 days). Within Gia, understanding was assessed with a 10-question quiz that most participants (96%) passed. Feedback about the chat consent indicated that 86% of participants had a positive experience. Discussion: Using Gia resulted in time savings for both the participant and study staff. The chatbot enables studies to reach more potential candidates. We identified five key features related to human-centered design for developing a consent chat. Conclusion: This analysis suggests that it is feasible to use an automated chatbot to scale obtaining informed consent for a genomics research study. We further identify a number of advantages when using a chatbot.

Pediatric medical genetics house call: Telemedicine for the next generation of patients and providers.

In an era of increasing technology and interaction with the patient bedside, we explore the role of relocating the bedside from the hospital to the home using telemedicine. The COVID-19 pandemic pushed telemedicine from small and pilot programs to widespread practice at an unprecedented rate. With the rapid implementation of telemedicine, it is important to consider how to create a telehealth system that provides both good care for patients and families while maintaining an excellent education environment for trainees of all levels. To this end, we developed telemedicine educational milestones to describe novel skills required to provide high quality telemedicine care, and allow trainees and clinical educators a metric by which to assess trainee progress. We also created methods and tools to help trainees learn and families feel comfortable in their new role as virtual collaborators. We envision a time when safety does not set the venue; instead the needs of the patient will dictate whether a virtual or in-person visit is the right choice for a family. We expect that pediatric medical genetics and metabolism groups across the country will continue to set a standard of a hybrid care system to meet the unique needs of each individual patient, using telemedicine technology.

Hotspots of aberrant enhancer activity punctuate the colorectal cancer epigenome.

In addition to mutations in genes, aberrant enhancer element activity at non-coding regions of the genome is a key driver of tumorigenesis. Here, we perform epigenomic enhancer profiling of a cohort of more than forty genetically diverse human colorectal cancer (CRC) specimens. Using normal colonic crypt epithelium as a comparator, we identify enhancers with recurrently gained or lost activity across CRC specimens. Of the enhancers highly recurrently activated in CRC, most are constituents of super enhancers, are occupied by AP-1 and cohesin complex members, and originate from primed chromatin. Many activate known oncogenes, and CRC growth can be mitigated through pharmacologic inhibition or genome editing of these loci. Nearly half of all GWAS CRC risk loci co-localize to recurrently activated enhancers. These findings indicate that the CRC epigenome is defined by highly recurrent epigenetic alterations at enhancers which activate a common, aberrant transcriptional programme critical for CRC growth and survival.

Modeling disease risk through analysis of physical interactions between genetic variants within chromatin regulatory circuitry.

SNPs associated with disease susceptibility often reside in enhancer clusters, or super-enhancers. Constituents of these enhancer clusters cooperate to regulate target genes and often extend beyond the linkage disequilibrium (LD) blocks containing risk SNPs identified in genome-wide association studies (GWAS). We identified 'outside variants', defined as SNPs in weak LD with GWAS risk SNPs that physically interact with risk SNPs as part of a target gene's regulatory circuitry. These outside variants further explain variation in target gene expression beyond that explained by GWAS-associated SNPs. Additionally, the clinical risk associated with GWAS SNPs is considerably modified by the genotype of outside variants. Collectively, these findings suggest a potential model in which outside variants and GWAS SNPs that physically interact in 3D chromatin collude to influence target transcript levels as well as clinical risk. This model offers an additional hypothesis for the source of missing heritability for complex traits.

Acupuncture: role in comprehensive cancer care--a primer for the oncologist and review of the literature.

In recent studies, patients have reported an increased use of complementary and alternative medicine (CAM). Acupuncture is a popular complementary therapy for patients with cancer. This article will provide current cancer treatment providers with information on acupuncture as well as the research conducted on cancer symptoms and side effects of cancer treatments. Antiemetic studies are the most prevalent and contain the most promising results. Several studies have found that acupuncture significantly reduces the number of emesis (vomiting) episodes for patients receiving chemotherapy. While studies on pain control vary due to the heterogeneity of pain, there are few studies investigating pain caused from cancer and the removal of cancerous tumors. These studies, while promising, provide basic results that need further investigation for more definitive results. Although relatively few studies have been done on anxiety and depression, several researchers have found acupuncture to be just as effective as or more effective than antidepressants for patients without cancer. Studies on breathlessness, while small, have shown acupuncture to have a significant positive effect on chronic obstructive pulmonary disease, breathlessness associated with end-stage cancer, and asthma. Researchers studying xerostomic individuals who have received salivary gland irradiation found significant positive results in salivary flow rates compared to baseline. Patients with hot flashes due to hormonal imbalance may benefit from the use of acupuncture. A recent pilot study showed improvement of chronic postchemotherapy fatigue following acupuncture treatments. Many individuals with cancer have turned to acupuncture because their symptoms persisted with conventional treatments or as an alternative or complement to their ongoing treatments. Despite the immense popularity in the community, few large randomized trials have been conducted to determine the effects acupuncture has on cancer symptoms and side effects of treatments. A majority of the current studies have shown beneficial effects that warrant further investigation with large trial sizes.