A study of elective genome sequencing and pharmacogenetic testing in an unselected population.

Subjects provided written informed consent before participation. The study was approved by the Western Institutional Review Board (WIRB #20161118).

Fifty‐two patients were eligible for the study and elected to enroll. The average age of participants was 61. There was a roughly even split between males and females, with 27 males and 25 females. Ninety‐four percent ( n  = 49) of participants were primarily Caucasian, while four percent ( n  = 2) were Asian, and two percent ( n  = 1) were Latino. Forty‐nine participants (94%) had at least a bachelor's degree, while 30 (58%) had an advanced degree. Common professions included physicians, lawyers, and executives. An average of 76 minutes was spent on the pre‐test clinical evaluation and counseling (range 24–161, median 75). Participants had an average of four ICD10 codes (range 1–11). Patients in the 70 years group had five. Common diagnoses included hyperlipidemia, age‐related cataract, hypertension, and mild‐moderate hearing loss. Seventeen participants (33%) reported undergoing prior genetic testing; the majority of these participants had undergone direct‐to‐consumer ancestry or health testing. Ninety percent ( n  = 47) of participants elected to receive all possible secondary findings, while the remaining 10% elected to receive all possible secondary results except for untreatable adult‐onset conditions. At the time of post‐test counseling, all participants reported that they were satisfied with their current insurance coverage. None had changes in their preferences at the time of results disclosure. An average of 56 minutes was spent in post‐test counseling and results discussion (range 30–102). Twenty‐six primary results potentially related to clinical phenotype were identified in 18 of 52 participants (four individuals received multiple findings). This included 7 pathogenic variants, 2 likely pathogenic variants, 16 variants of uncertain significance, and 1 risk allele. No participants received secondary findings indicating an increased risk to develop an untreatable disease. Eight individuals (15%) received secondary findings related to treatable disease risk, three of these findings were in genes recommended for secondary disease analysis by the ACMG (Kalia et al., 2017 ) (two in APC (*611731) , and one in BRCA2 (*600185) ). Eighty‐five percent ( n  = 44) had a carrier status identified for at least one autosomal recessive or X‐linked disorder (range 1–7 variants, median 2 variants). As part of the limited pharmacogenetic assessment of the genome, 16 variants were reported in five individuals. None of these variants impacted a current medication (Table 1 ). Variants reported by elective clinical genome sequencing. Oth Disorders Of Plasma‐Protein Metabolism, Nec E88.09 Sleep Apnea, Unspecified G47.30 Restless Legs Syndrome G25.81 Dysthymic Disorder F34.1 Eosinophilic Esophagitis K20.0 Dysthymic Disorder F34.1 Parkinson's Disease G20 Abnormal Weight Loss R63.4 Unspecified Age‐Related Cataract H25.9 Unspecified Sensorineural Hearing Loss H90.5 Unspecified Dementia Without Behavioral Disturbance F03.90 Malignant Neoplasm Of Prostate C61 Low Back Pain M54.5 Unspecified Atrial Fibrillation I48.91 Dvrtclos Of Lg Int W/o Perforation Or Abscess W Bleeding K57.31 Unspecified Abdominal Hernia Without Obstruction Or Gangrene K46.9 Gilbert Syndrome E80.4 Polyp Of Colon K63.5 Cortical Age‐Related Cataract, Unspecified Eye H25.019 Endothelial Corneal Dystrophy H18.51 Exercise Induced Bronchospasm J45.990 Celiac Disease K90.0 Malignant Neoplasm Of Prostate C61 Unspecified Sensorineural Hearing Loss H90.5 Unspecified Cataract H26.9 Frequency Of Micturition R35.0 Age‐Related Cognitive Decline R41.81 Unspecified Age‐Related Cataract H25.9 Low Back Pain M54.5 Pain In Unspecified Hip M25.559 Other Chronic Sinusitis J32.8 Syncope And Collapse R55 Renal Agenesis, Unilateral Q60.0 Congenital Absence Of Ovary, Unilateral Q50.01 Old Myocardial Infarction I25.2 Tinea Unguium B35.1 Other Intervertebral Disc Displacement, Lumbar Region M51.26 Sleep Apnea, Unspecified G47.30 Hyperlipidemia, Unspecified E78.5 Essential (primary) Hypertension I10 Polyp Of Colon K63.5 Oth Types Of Non‐Hodg Lymph, Nodes Of Head, Face, And Neck C85.81 Hyperlipidemia, Unspecified E78.5 Hypothyroidism, Unspecified E03.9 Acute Embolism And Thrombosis Of Other Thoracic Veins I82.290 Chronic Ischemic Heart Disease, Unspecified I25.9 Essential (primary) Hypertension I10 Hyperlipidemia, Unspecified E78.5 Gastro‐Esophageal Reflux Disease Without Esophagitis K21.9 Anodontia K00.0 Acne Vulgaris L70.0 Mild Intermittent Asthma, Uncomplicated J45.20 Tension‐Type Headache, Unspecified, Not Intractable G44.209 Gastro‐Esophageal Reflux Disease Without Esophagitis K21.9 Essential (primary) Hypertension I10 Obstructive Sleep Apnea (adult) (pediatric) G47.33 Anxiety Disorder, Unspecified F41.9 Hypothyroidism, Unspecified E03.9 Attention‐Deficit Hyperactivity Disorder, Unspecified Type F90.9 Pure Hypercholesterolemia, Unspecified E78.00 Essential (primary) Hypertension I10 Disorder Of Bilirubin Metabolism, Unspecified E80.7 Allergy To Peanuts Z91.010 Eclampsia Complicating The Puerperium O15.2 Malignant Neoplasm Of Unsp Site Of Unspecified Female Breast C50.919 Supraventricular Tachycardia I47.1 Persistent Atrial Fibrillation I48.1 Noise Effects On Left Inner Ear H83.3X2 Rheumatoid arthritis M05.89 Onychomycosis B35.1 Gallstones K80.0 Kidney stones N20.0 Major Depressive Disorder F33.9 Interstitial Pulmonary Disease J84.9 Paroxysmal Atrial Fibrillation I48.0 Essential Hypertension I10 Behign Neoplasm of Cerebral Meninges D32.0 Benign prostatic hypertrophy N40.1 Age‐related cognitive decline R41.84 Other Specified Forms of Tremor G25.2 Abnormal Head Movements R25.0 Unspecified Voice and Resonance Disorder R49.9 Other Chorea G25.5 Hypothyroidism, Unspecified E03.9 Other Age‐Related Cataract H25.89 Other Muscle Spasm M628.38 Malignant Neoplasm of Breast C50.919 Family History of Epilepsy and Other Disease of the Nervous System Z82.0 Primary Osteoarthritis, Right Hand M19.041 Primary Osteoarthritis, Left Hand 19.042 Pure Hypercholesterolemia E78.00 Sensorineural HL, Ulilateral H90.42 Cyclical Vomiting, Not Intractable G43.A0 Pure Hypercholesterolemia, Unspecified E78.00 Essential (primary) Hypertension I10 Tic Disorder, Unspecified F95.9 Rosacea, Unspecified L71.9 Dry Eye Syndrome H04.129 Cerv Disc Disord M50.020 Raynaud's Syndrome I73.00 Hypothyroidism, Unspecified E03.9 Polyp of Colon K63.5 MIgraine G43.909 Hyperlipidemia, Unspecified E78.5 Circadial Rhythm Sleep Disord G47.20 Unspecified Hearing Loss H91.90 Hyperlipidemia, Unspecified E78.5 Episodic Cluster Headache G44.019 Essential (primary) Hypertension I10 Anxiety Disorder, Unspecified F41.9 Attention‐Deficit Hyperactivity Disorder, Other Type F90.8 Polyneuropathy, unspecified G62.9 Essential Tremor G25.0 Malignant Neoplasm of Prostate C61 Unspecified Sensorineural Hearing Loss H90.5 Other Seborrheic Keratosis L82.1 Malignant Neoplasm Of Unspecified Site Of Left Female Breast C50.912 Transient Cerebral Ischemic Attack, Unspecified G45.9 Supraventricular Tachycardia I47.1 Mild Persistent Asthma, Uncomplicated J45.30 Unspecified Osteoarthritis, Unspecified Site M19.90 Gastro‐Esophageal Reflux Disease Without Esophagitis K21.9 Essential (primary) Hypertension I10 Raynaud's Syndrome Without Gangrene I73.00 Rosacea, Unspecified L71.9 Acquired Absence Of Other Specified Parts Of Digestive Tract Z90.49 Dvrtclos Of Lg Int W/o Perforation Or Abscess W/o Bleeding K57.30 Headache R51 Hyperlipidemia, Unspecified E78.5 VentricularPrematureDepolarization!49.3 Other Specified Anxiety Disorders F41.8 GERD K21.0 Gout, Unspecified M10.9 Mycosis Fungoides, Unspecified Site C84.00 Obstructive Sleep Apnea G47.33 Type 2 DM without Complications E11.9 Osteoarthritis M19.90 Fibromyalgia M79.7 Primary Hypertension I10 Hyperlipidemia E78.5 Unspecified Osteoarthritis M19.90 GERD K21.0 Idiopathic Pulmonary Fibrosis J84.112 Hyperlipidemia E78.5 Unspecified Osteoarthritis M19.90 Age‐Related Cataract H25.9 Rhabdomyolysis M62.82 Hemochromatosis E83.119 Abnormal Levels of Other Serum Enzymes R74.8 Pure Hypercholesterolemia E78.00 Unspecified Hearing Loss H91.90 Angina Pectoris I20.9 Prediabetes R73.03 Macular Degeneration H35.30 Age‐Related Cataract H25.9 Unspecified Osteoarthritis M19.90 Family History of Carrier of Other Genetic Disease Z84.81 Parkinson's Disease G20 Persistant Atril Fibrillation I48.1 Other Age‐Related Cataract H25.89 Hyperlipidemia, Unspecified E78.5 Gout, Unspecified M10.9 Obstructive Sleep Apnea G47.33 Rheumatoid Arthritis, Unspecified M06.9 Calculus Of Kidney N20.0 Malignant Melanoma Of Skin, Unspecified C43.9 Unspecified Age‐Related Cataract H25.9 Acute Myocardial Infarction, Unspecified I21.9 Ulcerative (chronic) Proctitis Without Complications K51.20 Pure Hypercholesterolemia, Unspecified E78.00 Psoriasis, Unspecified L40.9 Other Specified Congenital Deformities Of Feet Q66.89 Endometriosis Of Pelvic Peritoneum N80.3 Crohn's Disease, Unspecified, Without Complications K50.90 Personal History Of Urinary Calculi Z87.442 Cervicalgia M54.2 Major Depressive Disorder, Recurrent, Mild F33.0 Gout, Unspecified M10.9 Athscl Heart Disease Of Native Coronary Artery W/o Ang Pctrs I25.10 Unspecified Atrial Flutter I48.92 Unspecified Age‐Related Cataract H25.9 Tinnitus, Bilateral H93.13 Breast cancer C50.919 Mixed hyperlipidemia E78.2 Cortical age‐related cataract H25.013 Other disturbance of skin sensation R20.8 Type 2 Diabetes E11.9 Cortical age‐related cataract H25.013 Mixed hyperlipidemia E78.2 Palmar fascial fibromatosis M72.0 Benign paroxysmal vertigo H81.10 Selective Deficiency Of Immunoglobulin A [iga] D80.2 Autoimmune Thyroiditis E06.3 Inflammatory Polyarthropathy M06.4 Variant classification in the table reflects the classification at the time of analysis and reporting. These classifications may have changed since the analysis and reporting of these genomes to participants. When compared to the variants found on the GSA (Illumina), 53% of all reported variants are represented on the array. This includes 43% of primary findings, 55% of secondary findings, and 60% of pharmacogenetic findings. Fifty‐one (98%) elective GS patients underwent a separate stand‐alone pharmacogenetics panel test. The pharmacogenetics panel test reported variants that alter drug metabolism and had the potential to impact a medication in all 51 (100%) patients. Twenty‐one individuals (40%) had pharmacogenetic variants identified by this panel with the potential to impact a current medication (Table 2 ). Selected pharmacogenetic variants reported by PGx Complete.

R.M. conceived and planned the elective genome sequencing program. M.C., K.E., V.G., W.K., and D.B. evaluated and counseled patients seen in this study. M.K., M.S., and D.B. performed genome analysis. T.M. designed and performed pharmacogenetic analysis. K.O. performed chart review and collected data. M.C. and D.B. designed the study, analyzed and interpreted results, and drafted and edited the manuscript. All authors reviewed and approved the final version of the manuscript.

Our study found nine pathogenic or likely pathogenic variants that may explain one or more aspects of the medical history in six individuals (11.5%) who underwent elective genome sequencing. This is comparable to the results from a recently published elective genome program that found 11.5% (137/1,190) of participants had a genotype–phenotype association (Hou et al., 2020 ). In four cases, primary findings included a single pathogenic or likely pathogenic variant in a gene associated with autosomal recessive disease that had some overlap with the patient's history. Case 13 had follicular lymphoma and was heterozygous for a c.1582delC frameshift variant in PRF1 (*170280) . Autosomal recessive PRF1 ‐associated hemophagocytic lymphohistiocytosis may present with lymphoma as the initial manifestation (Tesi et al., 2016 ). Interestingly, there is evidence that carriers of PRF1 variants are at risk for lymphomas (Chen et al., 2017 ; Ciambotti et al., 2014 ; Ding & Yang, 2013 ). Digenic inheritance has also been suggested (Clementi et al., 2004 ). Case 41 had an episode of severe rhabdomyolysis requiring an admission to the intensive care unit and was heterozygous for a c.191dupA frameshift variant in ANO5 (*608662) . While the second variant in trans was not identified, the patient's phenotype is consistent with the wide variability seen in ANO5  muscle disease (Jarmula et al., 2019 ; Penttilä et al., 2012 ; Savarese et al., 2016 ). Reports suggest that carriers of ANO5 variants may have a mild phenotype including cramps and increased CK (Jarmula et al., 2019 ; Savarese et al., 2016 ). Case 37 had episodic facial dystonia and was heterozygous for a c.8966‐1G>C canonical splice site variant in COL6A3 (*120250) . The patient's phenotype resembles cases of autosomal recessive dystonia‐27 (DYT‐27), which is characterized by a slowly progressive phenotype that starts in the hand or neck and spares the lower extremities with a median age at onset of 22 years with a range of 6–61 years (Panda & Sharawat, 2020 ). The variant reported in case 37 was seen in two DYT‐27 pedigrees (Jochim et al., 2016 ; Zech et al., 2015 ). Case 42 had age‐related macular degeneration (AMD) and an established pathogenic ABCA4 (*601691) variant c.3113C>T (p. Ala1038Val). ABCA4 ‐associated disease is a recessive disorder that ranges from early onset, rapidly progressing cone‐rod dystrophy and retinitis pigmentosa to a very late‐onset mild disease resembling AMD (Cremers et al., 2020 ; Zernant et al., 2017 ). In these cases, there are three potential explanations: (1) a second disease‐causing variant is actually present but was not detected; (2) a heterozygous state may be associated with a phenotype; and (3) these individuals have diseases that are phenocopies of the genetic disorder that they carry. These findings suggest that assessing GS in light of a patient's phenotype may prove useful, arguing that laboratories carrying out elective GS should obtain phenotypic information as we move to comprehensive elective testing(Lu et al., 2019 ). Individuals who do not have a standard indication for genetic testing may nevertheless have variants resulting in phenotypes related to their medical history. In 11 cases, 17 VUSs were identified (Table 1 ). In the case series by Hou et al. ( 2020 ), among 42 cases, 44 VUSs were identified. Additional counseling time is required to explain these findings, follow‐up testing may incur additional expense, and reassessment of VUSs in the future may be required. VUSs are common in genomic testing (Ziats et al., 2020 ) and functional assays to assign these variants to the pathogenic or benign category are just beginning to appear (Almeida et al., 2020 ; Boonen et al., 2019 ; Drost et al., 2020 ). As a result, resolution may not be possible currently for many VUSs. Nevertheless, some VUSs can be resolved and are worth pursuing. In case 36, for example, a VUS was found in SPTLC2 (*605713) , a gene associated with a treatable disorder (Fridman et al., 2019 ). Subsequent biochemical testing concluded that the patient did not have this condition, so the uncertainty about this result was resolved. While many VUSs are likely to be reclassified over time as benign, others will eventually prove to be disease‐causing, explaining the patient's phenotype. The opportunity to perform VUS resolution via biochemical testing, imaging, family testing, etc. requires the identification of a VUS in the first place. The identification of VUSs in elective GS relies on thorough phenotyping on the part of the ordering clinician. Importantly, careful phenotyping may identify an aspect of the individual's history or examination where an alternative diagnostic test may be superior to GS. Case 38 (age 63) and case 52 (age 77) showed evidence of clonal hematopoiesis of indeterminate potential (CHIP) based on likely pathogenic findings in TET2 (*612839) and ASXL1 (*612990) , respectively. In both cases, the pathogenic variant allele frequency (VAF) was greater than 10%. CHIP is found in approximately 7–10% of individuals over age 65 and is associated with increased cardiovascular disease due to accelerated atherogenesis and a 0.5% to 1% per year risk of developing a hematologic malignancy (Pinese et al., 2020 ). Most CHIP‐associated pathogenic variants occurred in three epigenetic regulators, DNMT3A *(602769) , TET2 , and ASXL1 . VAF >10% has a higher risk of cardiovascular disease, indicating that clone size may be correlated with risk (Evans et al., 2020 ; Fujino & Kitamura, 2020 ; Karner et al., 2019 ; Steensma, 2018 ). In case 38, the patient had a subsequent myocardial event and stent placement. Nine variants that may affect an individual's phenotype in the future were found in eight patients. As seen in Table A1 , the percentage of cases harboring an actionable secondary variant varies across studies. This reflects each study's inclusion criteria for this class of variants. In four studies, the authors include pathogenic and in some, likely pathogenic variants expected to be highly penetrant in restricted (Dewey et al., 2016 ; Natarajan et al., 2016 ; Van Hout et al., 2020 ) and unrestricted (Johnston et al., 2016 ) sets of genes. A more recent study reported secondary variants in 5.8% of cases (Hou et al., 2020 ). This study included pathogenic and likely pathogenic variants with a wider range of penetrance. Our study included the entire range of variant penetrance as outlined by the ClinGen Low Penetrance/Risk Allele Working Group by including low‐, moderate‐ and high‐penetrance variants. All but one of the secondary variants in our cohort would be classified as low or reduced penetrance ( ClinGen, xxxx ). Case 43 had the only highly penetrant variant, in BRCA2 . Cases 33 and 48 had the APC Ile1307Lys representing an example of a low‐penetrance variant. Importantly, certain low‐penetrance variants like APC Ile1307Lys have established care guidelines (Gupta et al., 2017 ). Other low‐ or moderate‐penetrance results included variants in NLRP3 (*606416) , WNT10A (*606268) , NOD2 (*605956) , APOC3 (*107720) , and LPL (*609708) . Until guidelines defining risk cutoffs (odds ratios) for low, moderate, and high penetrance are established, inconsistency in secondary variant reporting will remain. All cases requested carrier status for autosomal recessive or X‐linked disorders. Eighty‐five percent (44/52) were found to be carriers of disorders that were not related to their phenotype (secondary findings). These 44 individuals were carriers of between 1 and 7 variants (median 2 variants) in 89 genes. We examined a widely available microarray, the Illumina Global Screening Array, a platform that queries variants found in ClinVar. Only 53% of the carrier variants found by GS were represented on the array. As the cost of GS testing falls, couples planning a pregnancy will be able to take advantage of more inclusive screening. Efforts in this direction are underway (Kirk et al., 2019 ). GS also provides an opportunity for cascade testing of other family members. In our study, many of the participants had children of reproductive age. Laboratories often report both pathogenic and likely pathogenic variants when assessing GS for carrier status. It is unclear whether a likely pathogenic variant should be reported due to the problem of the positive predictive value of such variants in rare disorders (Hagenkord et al., 2020 ). We obtained pharmacogenetic data from both a stand‐alone panel of pharmacogenetic variants and from GS. Some pharmacogenetic variants identified by GS were not included in the pharmacogenetic test; these included variants in VKORC1 (*608547) , DPYD (*612779) , and NUDT15 (*615792) . Case 15 demonstrates the utility of obtaining pharmacogenetic information through GS; in this case, the patient was found to have heterozygous variants in TPMT (*187680) and NUDT15 that in combination would result in significant toxicity if treated with mercaptopurine or thioguanine. In 21 cases, pharmacogenetic testing was relevant to current medication, emphasizing the importance of obtaining patient history in the elective testing setting. At this time, pharmacogenetic testing via GS can be cost‐prohibitive due to the need for Sanger confirmation of variants. With the development of artificial intelligence tools that may make orthogonal confirmation unnecessary, this barrier may be removed in some cases (Holt et al., 2021 ). This study has several limitations. Our small cohort is composed of individuals who are well‐educated, generally older, and primarily Caucasian. Nevertheless, their health status was typical for individuals their age and included many common multifactorial diseases. Additionally, a reanalysis of the cases with updated clinical information would likely identify new primary and secondary variants and a reclassification of the pathogenicity of some of the VUSs (Lu et al., 2020 ). The inclusion of secondary finding variants that are not highly penetrant is also problematic. Assessing whether a variant has moderate penetrance, low penetrance, or should be designated a “risk allele” is not well established, and therefore complicates counseling for these individuals. Understanding how the participants and their physicians used the information from GS was not addressed. These limitations point to the need for longitudinal studies measuring health outcomes, benefits, and cost‐effectiveness to assess the value of elective GS. Establishing the usefulness of elective GS is challenging because of the different measures of utility by different stakeholders. A health insurance company might look for long‐term improvement in health outcomes as an essential measure of utility. An individual with a negative result from elective GS may feel reassured that they do not have a well‐recognized untreatable genetic disorder and consider this valuable information. A range of utility measures has been proposed reflecting this conundrum (Hayeems et al., 2020 ). This can be appreciated by examining whether a variant is used in patient care and when it is used. This approach to utility highlights the importance of obtaining the patient's phenotype in elective GS. It should also be noted that not all pathogenic variants are medically important. As the cost of sequencing falls and as other elective genetic tests become more widespread, we can expect the uptake of elective genetic testing, including GS, to grow dramatically. The clinical utility and personal utility of elective GS will improve with the addition of ancestry assessment, blood groups, human leukocyte antigen typing, and polygenic risk scores. Projects are underway to improve our understanding of variants with various levels of penetrance in the general population (Carlson et al., 2020 ; Cirulli et al., 2020 ; Pinese et al., 2020 ). Reports and online tools geared to the needs of patients and their providers will be required to make the information understandable and provide opportunities to engage with the data as the individuals’ medical needs evolve (Yu et al., 2013 ). With time we can expect to use elective GS across the lifespan (Ceyhan‐Birsoy et al., 2019 ). In addition, if the decreasing cost and increasing quality of sequencing lead to multiple rounds of GS throughout a person's lifetime, the ability to detect somatic variation such as CHIP could add additional value.

As the cost of GS falls, its uses in rare disease testing and now elective testing are increasing. A growing body of literature describes the value of elective testing using GS and ES. The case series described here emphasizes the importance of patient phenotype in the analysis of an elective genome, permitting the laboratory to help individuals understand medical conditions already present. The study supports the use of GS to uncover secondary findings including CHIP, disease risk, carrier status, and pharmacogenetics. As demonstrated here, elective genome sequencing allows individuals to realize the promise of personalized medicine.

Genome sequencing (GS) has entered clinical practice as an efficient approach to the diagnosis of rare genetic disorders (Bick et al., 2019 ). However, interest in this testing is not limited to patients with a medical indication for testing. Individuals without a medical indication request a variety of genetic tests, including GS. Such testing is referred to as “elective” genetic and genomic testing ( https://en.wikipedia.org/wiki/Elective_genetic_and_genomic_testing ; Lu et al., 2019 ). Elective testing uses GS or exome sequencing (ES) to evaluate an individual for both primary findings and secondary findings. Primary findings include variants that purport to explain an aspect of the patient's medical or family history. Secondary findings are variants that do not appear to be associated with medical or family history at the time of testing but are nevertheless clinically relevant. Examples of secondary findings include a pathogenic BRCA1 (*113705) variant in an individual with no known personal or family history of breast/ovarian cancer and carrier status for an autosomal recessive condition for which there is no known family history. The frequency and nature of the primary and secondary findings reported in elective genome studies have been quite variable for a number of reasons (Table A1 ). Patient recruitment criteria were not uniform across studies. For example, all study subjects were provided testing for free as part of a research project except those reported by Hou et al. ( 2020 ). In addition, the list of genes analyzed and criteria used for variant classification varied across studies. Since the first papers describing the use of elective genomic testing were published in 2012, the knowledge base concerning the association between genetic variants and human disease has grown significantly with the development of resources such as ClinVar, ClinGen, and gnomAD. As a result, recent elective testing produces more clinically relevant findings than did earlier testing. Further, while all elective GS and ES studies correlated variants with medical history, family history was not always considered. Some participants were likely motivated to undertake elective testing due to a suspected genetic disorder in the family. Considering these factors, it is unsurprising that studies examining patient perceptions and economic aspects of elective genomic testing yield a range of results and recommendations (Baptista et al., 2016 ; East et al., 2019 ; Fiala et al., 2019 ; Flemin et al., 2019 ; Lewis et al., 2016 ; Lupo et al., 2016 ; Price et al., 2017 ; Roberts et al., 2018 ; Sanderson et al., 2016 ; Zoltick et al., 2019 ). More research is needed to explore the clinical and personal impact of elective GS, across different clinical contexts and patient populations. In an effort to understand how elective GS can be integrated into routine clinical genetics practice, we evaluated a patient population that underwent elective GS on a self‐pay basis.

T.M. is the Chief Scientific Officer and R.M.M. is a co‐founder of Kailos Genetics. M.C.S. is consulted for PierianDx. No other authors have conflict(s) of interest to declare.

This study was approved by the Western Institutional Review Board (WIRB #20161118). Study recruitment occurred at the Smith Family Clinic for Genomic Medicine (SFC) located on the campus of HudsonAlpha Institute for Biotechnology in Huntsville, AL. Individuals became patients at the clinic either through consult requests from an outside provider or via self‐referral. All patients who sought a clinic appointment specifically for elective genomic testing and were 18 years or older were eligible for this study. Additionally, a single patient who came to SFC for a diagnostic purpose (neuropathy) and decided to pursue elective genome sequencing in addition to the recommended genetic testing strategy was also eligible. All participants provided informed consent and institutional review board approval was obtained from the Western Institutional Review Board. Prior to their in‐clinic evaluation, individuals were invited to access an online patient communication and education tool, Genome Gateway. This tool allows patients to complete preliminary questionnaires and a pedigree and to receive both general and targeted educational materials. Clinical evaluation of participants included a thorough gathering of medical and family history, review of previous medical records, and a physical exam. Participants received pre‐test genetic counseling regarding potential outcomes and result types, benefits, and limitations of testing, and considerations for testing, including the limits of current knowledge and familial and insurance implications of results. Individuals were counseled that their results would include primary findings related to a known personal or family history of disease and could include secondary findings unrelated to a known history but still medically significant if requested. The GS laboratory reports potential secondary findings in the following categories: untreatable childhood diseases (e.g., Tay‐Sachs), treatable adult‐onset diseases (e.g., Lynch syndrome), untreatable adult‐onset diseases (e.g., Autosomal Dominant Alzheimer's Disease), carrier status for a genetic disorder, and a limited number of pharmacogenetic variants. Individuals opted into the categories of secondary results that they wished to receive. As part of standard clinical practice, clinical whole‐genome sequencing was performed to 40X coverage by the HudsonAlpha Clinical Services Lab, LLC using the HiSeq (Illumina) or NovaSeq 6000 (Illumina) platform. Secondary analysis of FASTQ files to generate variant call file (VCF) files was performed using GATK ( https://gatk.broadinstitute.org/hc/en‐us ) or DRAGEN Bio‐IT platform (Illumina). The VCF file was loaded into a proprietary variant annotation software platform, Carpe Novo (Worthey, 2017 ) or Codicem ( https://hudsonalpha.org/codicem ). All primary variants were confirmed via Sanger sequencing. The majority of secondary variants and pharmacogenetic variants were confirmed via Sanger sequencing. A machine learning method developed by Holt et al. ( 2021 ) allowed confidence in the accuracy of GS data without orthogonal confirmation for certain variants. Variants were classified using the American College of Medical Genetics (ACMG) guidelines (Richards et al., 2016 ). Primary findings included pathogenic variants, likely pathogenic variants and variants of uncertain significance (VUSs). Secondary findings were limited to pathogenic and likely pathogenic variants in genes associated with Mendelian disorders. Selected pharmacogenetic variants were reported from the genome analysis. Pharmacogenetic panel testing was performed by Kailos Genetics, Inc. using the MiSeq System (Illumina), with paired end 78 bp reads, to sequence selected variants within 42 pharmacogenetic genes. Kailos Genetics’ PGxComplete™ panel was used to capture and enrich targeted regions of the genome, such that 98% of the resulting sequences were aligned to the target regions. Once sequenced, a proprietary cloud‐based analysis system performed sample demultiplexing, quality assessment, alignment to the genome, variant calling, and report generation. As this pharmacogenetic test was a clinical product and enrollment occurred over a span of >4 years, the specific genes tested and variants reported evolved over time. Patients received their clinical results and post‐test genetic counseling via in‐person appointment or conference call with a medical geneticist and genetic counselor. Prior to results disclosure, patients were queried about any changes to their results preferences, whether they had communicated with family members about their testing process, and whether they had any insurance concerns. A copy of the results was provided to patients as well as their referring physician, if requested by the patient.