Return of Results and Clinical Follow-up
Participants are given the option to receive their report by standard mail or by secure file transfer over email. The report is accompanied by the consultation letter, which summarizes the primary research findings and, if applicable, plans for clinical follow-up. The study GC and clinical Geneticist meet to review pertinent cases and develop a structure for referrals and follow-up before meeting with the participant over Zoom or telephone conference. Genetic counseling for clinically significant findings, including risks for medically actionable and rare Mendelian conditions, is provided. During the results counseling session, the study GC collects a detailed medical and family history, delivers results, and discusses the plan for follow-up. The family physician is copied on the final report and any referrals made by the study team with the participant’s consent. Counseling and referrals for results related to carrier status, pharmacogenomics findings, PRS, and/or additional research findings (e.g. ancestry, HLA, blood group, etc.) are not initiated by the study team, however participants may request an appointment with the study GC to discuss their results if they wish.
DISCUSSION
We developed a genetic counseling and reporting framework for the return of comprehensive GS results to a large cohort of ostensibly healthy individuals. Although aspects of our report have been returned to participants before, never have they been presented collectively within a single, all-inclusive document and accompanied by a counseling and referral structure. Particularly novel is the return of a genetic ancestry estimate and HLA genotype within the research context. Individuals may seek ancestry testing to discover information about their ethnic background or genealogy. Determining genetic ancestry is important because there are often discrepancies between a patient’s self-reported ethnicity and genetic ancestry, which can impact risk calculations in the context of reproductive counseling (Shraga et al., 2017). Therefore, clinical applications of reporting genetic ancestry may include identifying founder populations with high carrier frequencies for autosomal recessive conditions to ensure accurate risk assessments (Kirkpatrick & Rashkin, 2017). HLA type has been reported specifically in the context of pharmacogenomic interactions to avoid adverse reactions to medications (e.g. HIV-positive patients with HLA*B57:01 are hypersensitive to Abacavir), but also has clinical use in the context of organ transplantation, blood product donations and transfusions (Fung & Benson, 2015). For instance, HLA-matching improves graft and host survival, as well as reduces alloimmunization rates in solid organ and hematopoietic stem cell transplantation (Fung & Benson, 2015). Universal reporting and registration of HLA and blood group genotype, alongside genetic ancestry, may increase the identification of unrelated organ and stem cell donors, especially for non-White/European individuals. HLA type has also been associated with increased risk for autoimmune conditions such as celiac disease (Schweiger et al., 2016). Reporting of HLA type may provide an at least partial underlying explanation for a patient’s chronic condition.
Counseling and educational materials were important given the novelty and complexity of the information being returned to participants. Due to limited time and resources it was not feasible to provide results counseling to all study participants. Patient-facing materials are helpful when it comes to increasing understanding of genomic information (Dwyer et al., 2021). To ensure appropriate understanding and interpretation of results, we developed appendices with additional information and resources on each section (i.e. ancestry, HLA, pharmacogenomics, blood type, etc.). For example, the PRS appendix contains sections titled “What is a polygenic risk score?” and “How can I reduce my risk?” as well as a list of external resources and websites with information on common health conditions like breast and prostate cancer. Likewise, we describe what HLA and genetic ancestry are in lay language, along with important limitations of the testing and results. We anticipate this will reduce the amount of time the study GC spends counseling participants who otherwise do not require clinical follow-up. In addition to detailed, patient-friendly appendices, the consultation letter is provided to all participants, regardless if they meet with the GC or not, which summarizes the primary SF (i.e. pharmacogenomics results, carrier status, monogenic disease risks). The consultation letter also suggests that participants contact their family physician should they have questions about their current medications in light of pharmacogenomics findings, or if they are actively family planning and wish to seek a referral to a local Genetics clinic for reproductive counseling. In the future, we aim to assess the understandability and overall acceptance of our reports and patient-facing materials through participant surveys and interviews. It will also be crucial to assess the uptake of clinical referrals and screening recommendations made through the GENCOV study. This type of longitudinal follow-up is essential in order to understand the impact of GS results on health outcomes and behaviors (e.g. disease diagnoses and smoking cessation). We may also adapt our reporting template, educational materials, and overall counseling framework to improve participants’ understanding and overall experiences post-return of GS results.
There are several limitations to our reporting. Repeat expansion disorders were not included in the report. We plan to use tools like ExpansionHunter (https://github.com/Illumina/ExpansionHunter/) for detecting repeat in order to report these types of results in the future. Currently, we do not have health outcome data on our cohort and are therefore unable to calculate specific risk percentiles or ORs for PRS for common health conditions. Therefore, it did not seem appropriate to model PRS using visuals reflective of continuous risk estimates (i.e. a bell curve with a threshold value), despite reports suggesting that these, along with percentiles and verbal explanations, may be better understood by research participants (Brockman et al., 2021). We may consider amending PRS results in the future after assessing health outcome data and calculating ORs for common conditions in our cohort. We chose to use HapMap3 over other commonly used datasets like 1000Genomes (https://www.internationalgenome.org) to generate an ancestry estimate due to reduced sample processing time. We recognize that 1000Genomes contains a larger number of reference populations and may increase the specificity of ancestry estimations. We plan to validate our genetic ancestry results against the 1000Genomes dataset in the future. Ancestry estimates and PRS are overall less accurate for individuals of non-White/European ethnicity given the lack of representation within publicly available datasets and genomic research studies. The GENCOV study population is recruited from within the Greater Toronto Area of Ontario, Canada, which represents a substantially diverse population. Correlations between self-reported and estimated genetic ancestry as well as contribution of GS data from non-White/European individuals to genomic datasets may help to identify discrepancies and potentially improve the accuracy of ancestry estimations and PRS calculations in the future. The traditional standard for HLA genotyping is PCR-based sequencing methodologies (Mimori et al., 2019). Compared to PCR-based methods, HLA-VBSeq is 66% and 52% accurate at determining approximate and exact HLA class I/II genotype to 4-digit resolution from GS data, respectively (Bauer et al., 2018). Therefore, clinical testing is recommended to confirm HLA genotype and phase at this time. Although, for applications like solid organ transplantation, complete matching of HLA loci is not necessarily required and lower resolution HLA genotyping may be sufficient alongside confirmation of ABO compatibility (Fung & Benson, 2015).
In summary, we developed an analysis and reporting structure for GS performed in healthy individuals. Our framework is in alignment with ideas about the future of genomic medicine, which involves the availability of information beyond what is currently considered clinically actionable to patients. Although more research is required to evaluate both the personal and medical implications of returning comprehensive GS data to healthy individuals, the integration of genomic data across multiple aspects of health, including knowledge of risks for hereditary diseases, pharmacogenomics interactions, PRS, as well as genetic ancestry and HLA/blood group genotyping is a step towards more personalized healthcare.
DATA AVAILABILITY
Raw, de-identified GS, viral, and clinical data will be submitted to and available for access through the databases listed in Table 3.
ACKNOWLEDGEMENTS
We thank Jo-Anne Hebrick and Miranda Lorenti of The Centre for Applied Genomics, The Hospital for Sick Children, Toronto, Canada for assistance with DNA extraction. We thank Karan Singh at William Osler Health System for recruitment support. We thank Andrew Wong at Sinai Health for IT support. We thank Paul Krzyzanowski at the Ontario Institute for Cancer Research (OICR), and Andrew McArthur at McMaster University for support generating viral sequence data. We thank the Canadian Institutes of Health Research (CIHR) for research funding.
AUTHOR CONTRIBUTIONS
Conceptualization: S.Ca., E.F., M.C., C.M., H.F., Y.B., J.T., J.L-E.; Data curation: E.F., M.C.; Methodology: S.Ca., E.F., M.C., L.S., T.J.P, J.S., E.G., M.L., L.H., W.L., A.N., J.T., J.L.E.; Project administration: G.M., S.Ch., J.T. J.L-E.; Software: E.F., M.C., T.J.P, J.S., M.L., L.H., W.L., J.L-E.; Visualization: S.Ca., E.F., M.C., G.M., H.F., M.L., L.H., W.L., A.N., J.L.E.; Writing-original draft: S.Ca.; Writing-review & editing: S.Ca., E.F., M.C., G.M., S.Ch., C.M., H.F., Y.B., L.S., T.J.P, J.S., E.G., M.L., L.H., W.L., A.N., J.T., J.L.E.; Supervision: J.T., J.L-E.; Funding acquisition: H.F., T.J.P., J.S., L.S., J.T., J.L-E.
ETHICS DECLARATION
This study is approved by the Mount Sinai Hospital research ethics board (Study ID: 424901). All institutions involved in recruitment of study participants received local ethics board approval. Informed consent was obtained from all participants in the study. Participant data was de-identified.
CONFLICTS OF INTEREST
The authors have no conflicts of interest to disclose.
FUNDING
This work was supported by the Canadian Institutes of Health Research (Funding Reference Number VR4-172753).
GENCOV STUDY WORKGROUP
Saranya Arnoldo1,2, Navneet Aujla1, Erin Bearss3, Alexandra Binnie2, Bjug Borgundvaag1,3, Howard Chertkow4, Marc Clausen5, Marc Dagher1,6, Luke Devine1,3, David Di Iorio1, Steven Marc Friedman3,7, Chun Yiu Jordan Fung3,8, Anne-Claude Gingras1,3,8, Lee W. Goneau9, Deepanjali Kaushik2, Zeeshan Khan10, Elisa Lapadula3,8, Tiffany Lu3, Tony Mazzulli1,3, Allison McGeer1,3,8, Shelley L McLeod1,3, Gregory Morgan1,3,8, David Richardson2, Harpreet Singh1, Seth Stern10, Ahmed Taher1,7,10, Iris Wong10, Natasha Zarei10
  1. University of Toronto
  2. William Osler Health System
  3. Mount Sinai Hospital, Sinai Health
  4. Baycrest Health Sciences
  5. Unity Health Toronto
  6. Women’s College Hospital
  7. University Health Network
  8. Lunenfeld-Tanenbaum Research Institute
  9. Dynacare Medical Laboratories
  10. Mackenzie Health
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FIGURE LEGENDS
Figure 1: Workflow for genetic counseling and return of GS results through the GENCOV study. 1) Study participants complete an online intake survey to collect information on medical history and COVID-19 symptoms, as well as an educational digital genomics platform wherein they are able to indicate initial preferences for return of SF from GS. The participant completes pre-test counseling with the study GC, either in group format by teleconference or by personal telephone and/or video appointment. The study GC confirms and records participants’ preferences for SF from GS. 2) GS data is filtered and analyzed based on participant preferences. A final GS report is compiled and reviewed by the study team. 3) The GC and Geneticist meet to review reports to determine which participants require results counseling and clinical follow-up. Individuals with clinically significant findings meet with the study GC (and Geneticist, where applicable) by teleconference to discuss their results and the plan for follow-up. The GC writes the consultation letter and initiates clinical referral(s). The family physician is forwarded a copy of the report, letter, and referrals with participants’ consent. Result counseling appointments and referrals are not initiated for other findings, however participants will receive a copy of their report along with a letter summarizing their results with the option to speak with the study GC if they have questions about their report. Clinically significant findings include monogenic disease risks for rare Mendelian conditions as well as medically actionable conditions. Other findings include carrier status results, PRS for common conditions, pharmacogenomics, ancestry, HLA, blood group, and viral lineage; GC: Genetic counselor; SF: Secondary findings; GS: Genome sequencing.
Figure 2: Summary of the elements of the comprehensive GS report: 1) Clinically significant findings related to the participant’s risk for hereditary conditions (monogenic disease risks, including medically actionable and rare Mendelian conditions); 2) Findings relevant to reproductive planning (carrier status); 3) Pharmacogenomic variants; 4) PRS for common conditions; 5) HLA genotype; 6) Genetic ancestry; 7) Blood group genotype; 8) COVID-19 viral lineage; 9) Testing methodologies and limitations; and, 10) Informational appendices. PRS: Polygenic risk score; Rh: Rhesus; GS: Genome sequencing; HLA: Human leukocyte antigen.
TABLES
Table 1: Summary of publically available data sources used in the GENCOV study.