Emergence and rapid transmission of SARS-CoV-2 B.1.1.7 in the United States.

The highly transmissible B.1.1.7 variant of SARS-CoV-2, first identified in the United Kingdom, has gained a foothold across the world. Using S gene target failure (SGTF) and SARS-CoV-2 genomic sequencing, we investigated the prevalence and dynamics of this variant in the United States (US), tracking it back to its early emergence. We found that, while the fraction of B.1.1.7 varied by state, the variant increased at a logistic rate with a roughly weekly doubling rate and an increased transmission of 40%-50%. We revealed several independent introductions of B.1.1.7 into the US as early as late November 2020, with community transmission spreading it to most states within months. We show that the US is on a similar trajectory as other countries where B.1.1.7 became dominant, requiring immediate and decisive action to minimize COVID-19 morbidity and mortality.

Cardiomyopathy prevalence exceeds 30% in individuals with TTN variants and early atrial fibrillation.

PURPOSE: TTN truncating variants (TTNtvs) represent the largest known genetic cause of dilated cardiomyopathies (DCMs), however their penetrance for DCM in general populations is low. More broadly, patients with cardiomyopathies (CMs) often exhibit other cardiac conditions, such as atrial fibrillation (Afib), which has also been linked to TTNtvs. This retrospective analysis aims to characterize the relationship between different cardiac conditions in those with TTNtvs and identify individuals with the highest risk of DCM. METHODS: In this work we leverage longitudinal electronic health record and exome sequencing data from approximately 450,000 individuals in 2 health systems to statistically confirm and pinpoint the genetic footprint of TTNtv-related diagnoses aside from CM, such as Afib, and determine whether vetting additional significantly associated phenotypes better stratifies CM risk across those with TTNtvs. We focused on TTNtvs in exons with a percentage spliced in >90% (hiPSI TTNtvs), a representation of constitutive cardiac expression. RESULTS: When controlling for CM and Afib, other cardiac conditions retained only nominal association with TTNtvs. A sliding window analysis of TTNtvs across the locus confirms that the association is specific to hiPSI exons for both CM and Afib, with no meaningful associations in percent spliced in ≤90% exons (loPSI TTNtvs). The combination of hiPSI TTNtv status and early Afib diagnosis (before age 60) found a subset of TTNtv individuals at high risk for CM. The prevalence of CM in this subset was 33%, a rate that was 3.5 fold higher than that in individuals with hiPSI TTNtvs (9% prevalence), 5-fold higher than that in individuals without TTNtvs with early Afib (6% prevalence), and 80-fold higher than that in the general population. CONCLUSION: Our retrospective analyses revealed that those with hiPSI TTNtvs and early Afib (∼1/2900) have a high prevalence of CM (33%), far exceeding that in other individuals with TTNtvs and in those without TTNtvs with an early Afib diagnosis. These results show that combining phenotypic information along with genomic population screening can identify patients at higher risk for progressing to symptomatic heart failure.

Blacklisting variants common in private cohorts but not in public databases optimizes human exome analysis.

Computational analyses of human patient exomes aim to filter out as many nonpathogenic genetic variants (NPVs) as possible, without removing the true disease-causing mutations. This involves comparing the patient's exome with public databases to remove reported variants inconsistent with disease prevalence, mode of inheritance, or clinical penetrance. However, variants frequent in a given exome cohort, but absent or rare in public databases, have also been reported and treated as NPVs, without rigorous exploration. We report the generation of a blacklist of variants frequent within an in-house cohort of 3,104 exomes. This blacklist did not remove known pathogenic mutations from the exomes of 129 patients and decreased the number of NPVs remaining in the 3,104 individual exomes by a median of 62%. We validated this approach by testing three other independent cohorts of 400, 902, and 3,869 exomes. The blacklist generated from any given cohort removed a substantial proportion of NPVs (11-65%). We analyzed the blacklisted variants computationally and experimentally. Most of the blacklisted variants corresponded to false signals generated by incomplete reference genome assembly, location in low-complexity regions, bioinformatic misprocessing, or limitations inherent to cohort-specific private alleles (e.g., due to sequencing kits, and genetic ancestries). Finally, we provide our precalculated blacklists, together with ReFiNE, a program for generating customized blacklists from any medium-sized or large in-house cohort of exome (or other next-generation sequencing) data via a user-friendly public web server. This work demonstrates the power of extracting variant blacklists from private databases as a specific in-house but broadly applicable tool for optimizing exome analysis.

Positive predictive value highlights four novel candidates for actionable genetic screening from analysis of 220,000 clinicogenomic records.

PURPOSE: To identify conditions that are candidates for population genetic screening based on population prevalence, penetrance of rare variants, and actionability. METHODS: We analyzed exome and medical record data from >220,000 participants across two large population health cohorts with different demographics. We performed a gene-based collapsing analysis of rare variants to identify genes significantly associated with disease status. RESULTS: We identify 74 statistically significant gene-disease associations across 27 genes. Seven of these conditions have a positive predictive value (PPV) of at least 30% in both cohorts. Three are already used in population screening programs (BRCA1, BRCA2, LDLR), and we also identify four new candidates for population screening: GCK with diabetes mellitus, HBB with ß-thalassemia minor and intermedia, PKD1 with cystic kidney disease, and MIP with cataracts. Importantly, the associations are actionable in that early genetic screening of each of these conditions is expected to improve outcomes. CONCLUSION: We identify seven genetic conditions where rare variation appears appropriate to assess in population screening, four of which are not yet used in screening programs. The addition of GCK, HBB, PKD1, and MIP rare variants into genetic screening programs would reach an additional 0.21% of participants with actionable disease risk, depending on the population.

Incomplete penetrance for isolated congenital asplenia in humans with mutations in translated and untranslated RPSA exons.

Isolated congenital asplenia (ICA) is the only known human developmental defect exclusively affecting a lymphoid organ. In 2013, we showed that private deleterious mutations in the protein-coding region of RPSA, encoding ribosomal protein SA, caused ICA by haploinsufficiency with complete penetrance. We reported seven heterozygous protein-coding mutations in 8 of the 23 kindreds studied, including 6 of the 8 multiplex kindreds. We have since enrolled 33 new kindreds, 5 of which are multiplex. We describe here 11 new heterozygous ICA-causing RPSA protein-coding mutations, and the first two mutations in the 5'-UTR of this gene, which disrupt mRNA splicing. Overall, 40 of the 73 ICA patients (55%) and 23 of the 56 kindreds (41%) carry mutations located in translated or untranslated exons of RPSA. Eleven of the 43 kindreds affected by sporadic disease (26%) carry RPSA mutations, whereas 12 of the 13 multiplex kindreds (92%) carry RPSA mutations. We also report that 6 of 18 (33%) protein-coding mutations and the two (100%) 5'-UTR mutations display incomplete penetrance. Three mutations were identified in two independent kindreds, due to a hotspot or a founder effect. Finally, RPSA ICA-causing mutations were demonstrated to be de novo in 7 of the 23 probands. Mutations in RPSA exons can affect the translated or untranslated regions and can underlie ICA with complete or incomplete penetrance.

Whole-genome sequencing is more powerful than whole-exome sequencing for detecting exome variants.

We compared whole-exome sequencing (WES) and whole-genome sequencing (WGS) in six unrelated individuals. In the regions targeted by WES capture (81.5% of the consensus coding genome), the mean numbers of single-nucleotide variants (SNVs) and small insertions/deletions (indels) detected per sample were 84,192 and 13,325, respectively, for WES, and 84,968 and 12,702, respectively, for WGS. For both SNVs and indels, the distributions of coverage depth, genotype quality, and minor read ratio were more uniform for WGS than for WES. After filtering, a mean of 74,398 (95.3%) high-quality (HQ) SNVs and 9,033 (70.6%) HQ indels were called by both platforms. A mean of 105 coding HQ SNVs and 32 indels was identified exclusively by WES whereas 692 HQ SNVs and 105 indels were identified exclusively by WGS. We Sanger-sequenced a random selection of these exclusive variants. For SNVs, the proportion of false-positive variants was higher for WES (78%) than for WGS (17%). The estimated mean number of real coding SNVs (656 variants, ∼3% of all coding HQ SNVs) identified by WGS and missed by WES was greater than the number of SNVs identified by WES and missed by WGS (26 variants). For indels, the proportions of false-positive variants were similar for WES (44%) and WGS (46%). Finally, WES was not reliable for the detection of copy-number variations, almost all of which extended beyond the targeted regions. Although currently more expensive, WGS is more powerful than WES for detecting potential disease-causing mutations within WES regions, particularly those due to SNVs.

The human gene damage index as a gene-level approach to prioritizing exome variants.

The protein-coding exome of a patient with a monogenic disease contains about 20,000 variants, only one or two of which are disease causing. We found that 58% of rare variants in the protein-coding exome of the general population are located in only 2% of the genes. Prompted by this observation, we aimed to develop a gene-level approach for predicting whether a given human protein-coding gene is likely to harbor disease-causing mutations. To this end, we derived the gene damage index (GDI): a genome-wide, gene-level metric of the mutational damage that has accumulated in the general population. We found that the GDI was correlated with selective evolutionary pressure, protein complexity, coding sequence length, and the number of paralogs. We compared GDI with the leading gene-level approaches, genic intolerance, and de novo excess, and demonstrated that GDI performed best for the detection of false positives (i.e., removing exome variants in genes irrelevant to disease), whereas genic intolerance and de novo excess performed better for the detection of true positives (i.e., assessing de novo mutations in genes likely to be disease causing). The GDI server, data, and software are freely available to noncommercial users from lab.rockefeller.edu/casanova/GDI.

Exome and genome sequencing for inborn errors of immunity.

The advent of next-generation sequencing (NGS) in 2010 has transformed medicine, particularly the growing field of inborn errors of immunity. NGS has facilitated the discovery of novel disease-causing genes and the genetic diagnosis of patients with monogenic inborn errors of immunity. Whole-exome sequencing (WES) is presently the most cost-effective approach for research and diagnostics, although whole-genome sequencing offers several advantages. The scientific or diagnostic challenge consists in selecting 1 or 2 candidate variants among thousands of NGS calls. Variant- and gene-level computational methods, as well as immunologic hypotheses, can help narrow down this genome-wide search. The key to success is a well-informed genetic hypothesis on 3 key aspects: mode of inheritance, clinical penetrance, and genetic heterogeneity of the condition. This determines the search strategy and selection criteria for candidate alleles. Subsequent functional validation of the disease-causing effect of the candidate variant is critical. Even the most up-to-date dry lab cannot clinch this validation without a seasoned wet lab. The multifariousness of variations entails an experimental rigor even greater than traditional Sanger sequencing-based approaches in order not to assign a condition to an irrelevant variant. Finding the needle in the haystack takes patience, prudence, and discernment.

The Potential of Genetics in Identifying Women at Lower Risk of Breast Cancer.

Importance: Genetic information is not being used to identify women at lower risk of breast cancer or other diseases in clinical practice. With the new US Preventive Services Task Force guidelines lowering the age for mammogram screening for all, there is a potential benefit in identifying women at lower risk of disease who may defer the start of mammographic screening. This genetic risk-based approach would help mitigate overscreening, associated costs, and anxiety. Objective: To assess breast cancer incidence and age of onset among women at low genetic risk compared with women at average risk and evaluate the potential to delay mammography on the basis of genetic risk stratification. Design, Setting, and Participants: This retrospective case-control study included 25 591 women from the Healthy Nevada Project sequenced by Helix between 2018 and 2022. Data extracted from electronic health records at the end of 2022 (mean length of electronic health record available was 12 years) were used for the analysis in 2023. Main Outcomes and Measures: Breast cancer diagnosis was identified from electronic health records. Classification to the low-risk genetic group required (1) the absence of pathogenic variants or a variant of uncertain significance in BRCA1, BRCA2, PALB2, ATM, or CHEK2, and (2) a low polygenic risk score (bottom 10%) using a 313-single-nucleotide variant model. Results: Of 25 591 women in the study (mean [SD] age was 53.8 [16.9] years), 2338 women (9.1%) were classified as having low risk for breast cancer; 410 women (1.6%) were classified as high risk; and 22 843 women (89.3%) as average risk. There was a significant reduction in breast cancer diagnosis among the low-risk group (hazard ratio, 0.39; 95% CI, 0.29-0.52; P < .001). By 45 years of age, 0.69% of women in the average-risk group were diagnosed with breast cancer, whereas women in the low-risk group reached this rate at 51 years. By 50 years of age, 1.41% of those in the average-risk group were diagnosed with breast cancer, whereas those in the low-risk group reached this rate at age 58 years. These findings suggest that deferring mammogram screening by 5 to 10 years for women at low risk of breast cancer aligns with new draft recommendations. Conclusions and Relevance: The findings of this retrospective case-control study underscore the value of genetics in individualizing the onset of breast cancer screening. Improving breast cancer risk stratification by implementing both high-risk and low-risk strategies in screening can refine preventive measures and optimize health care resource allocation.

A power-based sliding window approach to evaluate the clinical impact of rare genetic variants in the nucleotide sequence or the spatial position of the folded protein.

Systematic determination of novel variant pathogenicity remains a major challenge, even when there is an established association between a gene and phenotype. Here we present Power Window (PW), a sliding window technique that identifies the impactful regions of a gene using population-scale clinico-genomic datasets. By sizing analysis windows on the number of variant carriers, rather than the number of variants or nucleotides, statistical power is held constant, enabling the localization of clinical phenotypes and removal of unassociated gene regions. The windows can be built by sliding across either the nucleotide sequence of the gene (through 1D space) or the positions of the amino acids in the folded protein (through 3D space). Using a training set of 350k exomes from the UK Biobank (UKB), we developed PW models for well-established gene-disease associations and tested their accuracy in two independent cohorts (117k UKB exomes and 65k exomes sequenced at Helix in the Healthy Nevada Project, myGenetics, or In Our DNA SC studies). The significant models retained a median of 49% of the qualifying variant carriers in each gene (range 2%-98%), with quantitative traits showing a median effect size improvement of 66% compared with aggregating variants across the entire gene, and binary traits' odds ratios improving by a median of 2.2-fold. PW showcases that electronic health record-based statistical analyses can accurately distinguish between novel coding variants in established genes that will have high phenotypic penetrance and those that will not, unlocking new potential for human genomics research, drug development, variant interpretation, and precision medicine.

Screening Familial Risk for Hereditary Breast and Ovarian Cancer.

Importance: Most patients with pathogenic or likely pathogenic (P/LP) variants for breast cancer have not undergone genetic testing. Objective: To identify patients meeting family history criteria for genetic testing in the electronic health record (EHR). Design, Setting, and Participants: This study included both cross-sectional (observation date, February 1, 2024) and retrospective cohort (observation period, January 1, 2018, to February 1, 2024) analyses. Participants included patients aged 18 to 79 years enrolled in Renown Health, a large health system in Northern Nevada. Genotype was known for 38 003 patients enrolled in Healthy Nevada Project (HNP), a population genomics study. Exposure: An EHR indicating that a patient is positive for criteria according to the Seven-Question Family History Questionnaire (hereafter, FHS7 positive) assessing familial risk for hereditary breast and ovarian cancer (HBOC). Main Outcomes and Measures: The primary outcomes were the presence of P/LP variants in the ATM, BRCA1, BRCA2, CHEK2, or PALB2 genes (cross-sectional analysis) or a diagnosis of cancer (cohort analysis). Age-adjusted cancer incidence rates per 100 000 patients per year were calculated using the 2020 US population as the standard. Hazard ratios (HRs) for cancer attributable to FHS7-positive status were estimated using cause-specific hazard models. Results: Among 835 727 patients, 423 393 (50.7%) were female and 29 913 (3.6%) were FHS7 positive. Among those who were FHS7 positive, 24 535 (82.0%) had no evidence of prior genetic testing for HBOC in their EHR. Being FHS7 positive was associated with increased prevalence of P/LP variants in BRCA1/BRCA2 (odds ratio [OR], 3.34; 95% CI, 2.48-4.47), CHEK2 (OR, 1.62; 95% CI, 1.05-2.43), and PALB2 (OR, 2.84; 95% CI, 1.23-6.16) among HNP female individuals, and in BRCA1/BRCA2 (OR, 3.35; 95% CI, 1.93-5.56) among HNP male individuals. Being FHS7 positive was also associated with significantly increased risk of cancer among 131 622 non-HNP female individuals (HR, 1.44; 95% CI, 1.22-1.70) but not among 114 982 non-HNP male individuals (HR, 1.11; 95% CI, 0.87-1.42). Among 1527 HNP survey respondents, 352 of 383 EHR-FHS7 positive patients (91.9%) were survey-FHS7 positive, but only 352 of 883 survey-FHS7 positive patients (39.9%) were EHR-FHS7 positive. Of the 29 913 FHS7-positive patients, 19 764 (66.1%) were identified only after parsing free-text family history comments. Socioeconomic differences were also observed between EHR-FHS7-negative and EHR-FHS7-positive patients, suggesting disparities in recording family history. Conclusions and Relevance: In this cross-sectional study, EHR-derived FHS7 identified thousands of patients with familial risk for breast cancer, indicating a substantial gap in genetic testing. However, limitations in EHR family history data suggested that other identification methods, such as direct-to-patient questionnaires, are required to fully address this gap.

Lack of association between classical HLA genes and asymptomatic SARS-CoV-2 infection.

Human genetic studies of critical COVID-19 pneumonia have revealed the essential role of type I interferon-dependent innate immunity to SARS-CoV-2 infection. Conversely, an association between the HLA-B∗15:01 allele and asymptomatic SARS-CoV-2 infection in unvaccinated individuals was recently reported, suggesting a contribution of pre-existing T cell-dependent adaptive immunity. We report a lack of association of classical HLA alleles, including HLA-B∗15:01, with pre-omicron asymptomatic SARS-CoV-2 infection in unvaccinated participants in a prospective population-based study in the United States (191 asymptomatic vs. 945 symptomatic COVID-19 cases). Moreover, we found no such association in the international COVID Human Genetic Effort cohort (206 asymptomatic vs. 574 mild or moderate COVID-19 cases and 1,625 severe or critical COVID-19 cases). Finally, in the Human Challenge Characterisation study, the three HLA-B∗15:01 individuals infected with SARS-CoV-2 developed symptoms. As with other acute primary infections studied, no classical HLA alleles favoring an asymptomatic course of SARS-CoV-2 infection were identified.

The immunopathological landscape of human pre-TCRα deficiency: From rare to common variants.

We describe humans with rare biallelic loss-of-function PTCRA variants impairing pre-α T cell receptor (pre-TCRα) expression. Low circulating naive αß T cell counts at birth persisted over time, with normal memory αß and high γδ T cell counts. Their TCRα repertoire was biased, which suggests that noncanonical thymic differentiation pathways can rescue αß T cell development. Only a minority of these individuals were sick, with infection, lymphoproliferation, and/or autoimmunity. We also report that 1 in 4000 individuals from the Middle East and South Asia are homozygous for a common hypomorphic PTCRA variant. They had normal circulating naive αß T cell counts but high γδ T cell counts. Although residual pre-TCRα expression drove the differentiation of more αß T cells, autoimmune conditions were more frequent in these patients compared with the general population.

Whole-exome-sequencing-based discovery of human FADD deficiency.

Germline mutations in FASL and FAS impair Fas-dependent apoptosis and cause recessively or dominantly inherited autoimmune lymphoproliferative syndrome (ALPS). Patients with ALPS typically present with no other clinical phenotype. We investigated a large, consanguineous, multiplex kindred in which biological features of ALPS were found in the context of severe bacterial and viral disease, recurrent hepatopathy and encephalopathy, and cardiac malformations. By a combination of genome-wide linkage and whole-exome sequencing, we identified a homozygous missense mutation in FADD, encoding the Fas-associated death domain protein (FADD), in the patients. This FADD mutation decreases steady-state protein levels and impairs Fas-dependent apoptosis in vitro, accounting for biological ALPS phenotypes in vivo. It also impairs Fas-independent signaling pathways. The observed bacterial infections result partly from functional hyposplenism, and viral infections result from impaired interferon immunity. We describe here a complex clinical disorder, its genetic basis, and some of the key mechanisms underlying its pathogenesis. Our findings highlight the key role of FADD in Fas-dependent and Fas-independent signaling pathways in humans.

Lack of association between HLA and asymptomatic SARS-CoV-2 infection.

Human genetic studies of critical COVID-19 pneumonia have revealed the essential role of type I interferon-dependent innate immunity to SARS-CoV-2 infection. Conversely, an association between the HLA-B*15:01 allele and asymptomatic SARS-CoV-2 infection in unvaccinated individuals was recently reported, suggesting a contribution of pre-existing T cell-dependent adaptive immunity. We report a lack of association of classical HLA alleles, including HLA-B*15:01, with pre-omicron asymptomatic SARS-CoV-2 infection in unvaccinated participants in a prospective population-based study in the US (191 asymptomatic vs. 945 symptomatic COVID-19 cases). Moreover, we found no such association in the international COVID Human Genetic Effort cohort (206 asymptomatic vs. 574 mild or moderate COVID-19 cases and 1,625 severe or critical COVID-19 cases). Finally, in the Human Challenge Characterisation study, the three HLA-B*15:01 individuals infected with SARS-CoV-2 developed symptoms. As with other acute primary infections, no classical HLA alleles favoring an asymptomatic course of SARS-CoV-2 infection were identified. These findings suggest that memory T-cell immunity to seasonal coronaviruses does not strongly influence the outcome of SARS-CoV-2 infection in unvaccinated individuals.

Rare predicted loss-of-function variants of type I IFN immunity genes are associated with life-threatening COVID-19.

BACKGROUND: We previously reported that impaired type I IFN activity, due to inborn errors of TLR3- and TLR7-dependent type I interferon (IFN) immunity or to autoantibodies against type I IFN, account for 15-20% of cases of life-threatening COVID-19 in unvaccinated patients. Therefore, the determinants of life-threatening COVID-19 remain to be identified in ~ 80% of cases. METHODS: We report here a genome-wide rare variant burden association analysis in 3269 unvaccinated patients with life-threatening COVID-19, and 1373 unvaccinated SARS-CoV-2-infected individuals without pneumonia. Among the 928 patients tested for autoantibodies against type I IFN, a quarter (234) were positive and were excluded. RESULTS: No gene reached genome-wide significance. Under a recessive model, the most significant gene with at-risk variants was TLR7, with an OR of 27.68 (95%CI 1.5-528.7, P = 1.1 × 10-4) for biochemically loss-of-function (bLOF) variants. We replicated the enrichment in rare predicted LOF (pLOF) variants at 13 influenza susceptibility loci involved in TLR3-dependent type I IFN immunity (OR = 3.70[95%CI 1.3-8.2], P = 2.1 × 10-4). This enrichment was further strengthened by (1) adding the recently reported TYK2 and TLR7 COVID-19 loci, particularly under a recessive model (OR = 19.65[95%CI 2.1-2635.4], P = 3.4 × 10-3), and (2) considering as pLOF branchpoint variants with potentially strong impacts on splicing among the 15 loci (OR = 4.40[9%CI 2.3-8.4], P = 7.7 × 10-8). Finally, the patients with pLOF/bLOF variants at these 15 loci were significantly younger (mean age [SD] = 43.3 [20.3] years) than the other patients (56.0 [17.3] years; P = 1.68 × 10-5). CONCLUSIONS: Rare variants of TLR3- and TLR7-dependent type I IFN immunity genes can underlie life-threatening COVID-19, particularly with recessive inheritance, in patients under 60 years old.

Incomplete Penetrance of Population-Based Genetic Screening Results in Electronic Health Record.

The clinical value of population-based genetic screening projects depends on the actions taken on the findings. The Healthy Nevada Project (HNP) is an all-comer genetic screening and research project based in northern Nevada. HNP participants with CDC Tier 1 findings of hereditary breast and ovarian cancer syndrome (HBOC), Lynch syndrome (LS), or familial hypercholesterolemia (FH) are notified and provided with genetic counseling. However, the HNP subsequently takes a "hands-off" approach: it is the responsibility of notified participants to share their findings with their healthcare providers, and providers are expected to implement the recommended action plans. Thus, the HNP presents an opportunity to evaluate the efficiency of participant and provider responses to notification of important genetic findings, using electronic health records (EHRs) at Renown Health (a large regional hospital in northern Nevada). Out of 520 HNP participants with findings, we identified 250 participants who were notified of their findings and who had an EHR. 107 of these participants responded to a survey, with 76 (71%) indicating that they had shared their findings with their healthcare providers. However, a sufficiently specific genetic diagnosis appeared in the EHRs and problem lists of only 22 and 10%, respectively, of participants without prior knowledge. Furthermore, review of participant EHRs provided evidence of possible relevant changes in clinical care for only a handful of participants. Up to 19% of participants would have benefited from earlier screening due to prior presentation of their condition. These results suggest that continuous support for both participants and their providers is necessary to maximize the benefit of population-based genetic screening. We recommend that genetic screening projects require participants' consent to directly document their genetic findings in their EHRs. Additionally, we recommend that they provide healthcare providers with ongoing training regarding documentation of findings and with clinical decision support regarding subsequent care.