Anthony Gregg, MD, MBA, FACMG


Dear Study Participant:

Thank you for your participation in this Institutional Review Board (IRB)-approved research study. As part of this study, we have tested you, your partner and your relatives along with data derived from embryo samples that were obtained from your PGT/S-IVF process. We used Next-Generation Whole Genome Sequencing (WGS) and individualized analyses to identify genetic changes that are associated with specific types of diseases. Results are summarized on page 2. This summary includes risk information for each individual embryo with respect to:

  • Rare monogenic conditions: We looked for selected inherited variants in single genes (monogenic) that have a known association with disease. These include some hereditary cancer syndromes (e.g. Lynch syndrome), some cardiovascular conditions (e.g. hypertrophic cardiomyopathy, Marfan syndrome), and other medical disorders (e.g. Fabry disease). We also included 59 genes identified as medically actionable by the American College of Medical Genetics and Genomics (ACMG). Please visit for further details. The complete list of rare genetic disorders assessed in this study can be found in Addendum 2. Both the summaries for the embryos and the individual participant carrier results are included in this report.
  • Multifactorial conditions: Some diseases including certain autoimmune conditions (e.g. celiac disease, psoriasis) some cancers (e.g. breast cancer) and certain types of cardiovascular conditions (e.g. coronary artery disease) are associated with effects of multiple genes (polygenic) in combination with lifestyle and environmental factors. For these conditions, using your genome information, we generated a Polygenic Risk Score (PRS) to predict disease risk. While this approach has been previously used in research studies for a set of conditions we report (see References on Addendum 4), our risk estimates are experimental. We invite you to visit for further information)

A medical geneticist or board-certified genetic counselor will go over the summary with you and assist you in understanding the information within this report. Detailed information about the methodology and limitations of this study are available in the Addendum.


Akash Kumar, MD, PhD
Principal Investigator; Medical Director - MyOme, Inc.


If you have questions regarding this study, you can speak with the study's Principal Investigator (PI) and Medical Geneticist to discuss the study in detail and have your questions answered. If you have concerns, complaints or additional question regarding this study, contact the study PI Akash Kumar, MD, PhD, This research is being overseen by an Institutional Review Board (IRB). You may contact them at (800) 562-4789 or if:

  • You have questions, concerns, or complaints that are not being answered by the research team.
  • You are not getting answers from the research team.
  • You cannot reach the research team.
  • You want to talk to someone else about the research.
  • You have questions about your rights as a research subject.
Clinic: Acme Clinic
Physician: Dr. Pluto
Phone: (800) 347-6391
Fax: (800) 347-6392
Self-Reported Family History: Psoriasis (Paternal)

One embryo was predicted to carry a risk allele for colorectal cancer. Another embryo was predicted to be a carrier for the condition below. No embryos predicted to have positive findings.


One embryo was predicted to carry a risk allele for colorectal cancer. Another embryo was predicted to be a carrier for the condition below. No embryos predicted to have positive findings.

System Condition EMBRYO 1 EMBRYO 2 EMBRYO 3 EMBRYO 4
POSITIVE: indicates that the identified embryo carries a variant that may predispose the child towards the development of the specified genetic disorder. The finding of a pathogenic variant does not guarantee the individual will develop the disease associated with the gene
NEGATIVE: indicates that no pathogenic variant was identified in the gene associated with the specified genetic disorder in the embryo. This does not mean the child will not develop the disease. It means the child does not have a predisposition towards developing the disease.
NO CALL: indicates that we were unable to test this embryo for variants in the gene associated
with the specified genetic disorder.
CARRIER: indicates that a single pathogenic variant was identified in an autosomal recessive gene or in an X-linked gene in a female embryo. In most cases these variants would not affect an individual's health but can identify potential risk of passing a genetic disorder to their children.
RISK FACTOR: indicates that the embryo carries a variant that is associated with an increased risk of developing a condition, but does NOT cause that condition
IP: Inheritance Patterns: AD; Autosomal Dominant; AR: Autosomal Recessive; X: X-linked
RISK RATIO: Represents the fold-increase
in disease risk of the embryo (individual-specific estimate of lifetime risk divided by baseline lifetime risk of disease within the general population). A 1.0x risk ratio indicates the same risk as individuals of matched ethnicity
LIFETIME RISK: Calculated using a model based on a large repository of hundreds of thousands of genomes with associated clinical phenotypes to provide a lifetime risk of disease Highlighted regions indicate the embryo has either a two-fold higher lifetime risk of disease or PRS percentile of 95% or higher OR risk ratio 2x or higher. Generally, a lower risk (and a lower percentile) is preferable.

Note: This analysis assesses only inherited variants and does not analyze new (de novo) variants unique to the embryo.


Positive Findings for Monogenic Conditions


Carrier or Risk Alleles for Monogenic Conditions



Overview Psoriasis is a skin condition that causes redness and irritation. You can develop psoriasis at any age, but it is most commonly diagnosed between 15 and 35 years of age. A psoriasis attack may be triggered by too much sunlight, dry air or stress and may be worse in people with a compromised immune system.
Symptoms Symptoms of psoriasis can appear suddenly or slowly and often go away and then come back. The main symptom is red, flaky skin that is mostly commonly seen on elbows and knees. People with psoriasis may also experience joint pain or changes in their nails (thickening, discoloration).
Factors that
Increase Risk
PHaving a high genetic risk score does not mean you will necessarily develop psoriasis. There are other factors that influence your risk of developing this disease including the following:
1. Family history. Having parents with psoriasis increases your risk.
2. Smoking. Smoking increases your risk of developing this condition and may also increase severity
3. Obesity. Being overweight increases your risk of developing this condition
Next Steps We suggest you talk to your doctor about this finding in the context of your own and your family's health history.
Read More MedlinePlus Encyclopedia:
Mayo Clinic:

Type 1 Diabetes

Overview Type 1 diabetes is a disorder characterized by abnormally high blood sugar levels. In this form of diabetes, specialized cells in the pancreas called beta cells stop producing insulin. Insulin controls how much glucose (a type of sugar) is passed from the blood into cells for conversion to energy. Lack of insulin results in the inability to use glucose for energy or to control the amount of sugar in the blood. Type 1 diabetes can occur at any age; however, it usually develops by early adulthood, most often starting in adolescence. By age 18, approximately 1 in 300 people in the United States develop type 1 diabetes.
Symptoms The first signs and symptoms of the disorder are caused by high blood sugar and may include frequent urination (polyuria), excessive thirst (polydipsia), fatigue, blurred vision, tingling or loss of feeling in the hands and feet, and weight loss.
Factors that
Increase Risk
1. Family history: Having a parent or sibling with type 1 diabetes increases the risk of a person having the same type. If both parents have type 1 diabetes, the risk is even higher.
2. Age: Type 1 diabetes usually develops in younger adults and children. It is one of the most common chronic conditions that develop in childhood. Children are typically younger than 14 years old when they receive a diagnosis. Type 1 diabetes might occur at any age, although developing type 1 diabetes later in life is rare.
Having a high risk of type 1 diabetes based on this test does not mean you will definitely develop this condition. Other genetic and non-genetic factors such as age, sex, and ethnicity can impact your chances of developing the disease.
Next Steps We suggest you talk to your doctor about this finding in the context of your own and your family's health history.
Read More There are many resources with additional information about type 1 diabetes such as the following:
Genetics Home Reference:
MedlinePlus Encyclopedia:
Mayo Clinic:
Embryo 1
Lifetime Risk Pop. Risk Risk Ratio Percentile
0.0% 10% 20% 30% 40% 50%
Embryo 2
Lifetime Risk Pop. Risk Risk Ratio Percentile
0.0% 10% 20% 30% 40% 50%
Embryo 3
Lifetime Risk Pop. Risk Risk Ratio Percentile
0.0% 10% 20% 30% 40% 50%
Embryo 4
Lifetime Risk Pop. Risk Risk Ratio Percentile
0.0% 10% 20% 30% 40% 50%

Test Background

A genetic disorder is a disease caused in whole or in part by a change in the DNA sequence away from a typical sequence. Genetic disorders can be caused by a mutation in one gene (monogenic disorder), by mutations in multiple genes (polygenic disorders), by a combination of gene mutations and environmental factors (multifactorial disorders), or by chromosome abnormalities (changes in the number or structure of entire chromosomes, the structures that carry genes). For further information:

and Standard approaches for embryo testing investigate inherited conditions that run in families (PGT-M: Preimplantation Genetic Testing for Monogenic/single gene defects) as well as chromosome abnormalities (PGT-A: Preimplantation Genetic Testing for Aneuploidies). MyOme has developed a method that expands the range of genetic conditions available for testing to include multifactorial conditions and actionable rare monogenic disorders that may not have been identified in the family.

Test Method

Genomic DNA obtained from submitted samples was sequenced using either Illumina or BGI technology. Reads were aligned to a reference sequence (hg19) and sequence changes were identified. For some genes, only specific changes were analyzed. Deletions and duplications were not examined unless otherwise indicated above. In some scenarios, independent validation of HLA type may have been performed by an external lab. Selected variants were annotated and interpreted according to ACMG (American College of Medical Genetics) guidelines. Only pathogenic or likely pathogenic variants are reported.
Embryo and parent genotyping with subsequent "Parental Support" analysis was performed by Natera's CLIA laboratory. Embryo genomes were reconstructed using embryo genotypes and parental whole genome sequences using a proprietary

"Genome Reconstruction" algorithm. Only variants observed in the parents genomes that are predicted to have an impact on the embryo were examined in the reconstructed embryo genomes. Those are the only variants included in this report.
For a subset of conditions, a polygenic risk score was calculated as discussed in the publications below. Models for each condition were evaluated on the UK Biobank population. Some polygenic risk scores may be refined using HLA type. An individual's lifetime risk was calculated by adjusting the baseline risk (in the US population) according to their demographic information and polygenic risk score. Models for which the 95th percentile of polygenic risk was predicted to confer double the lifetime risk or 8% threshold baseline risk were included in the report.

Test Limitations

  1. The results of this study do not eliminate the need for routine prenatal screening and testing as recommended during pregnancy. Routine pregnancy care should still be practiced as directed by your physician.
  2. This test is designed to provide information only for the specific monogenic conditions listed in Addendum 2. Additional testing information for other monogenic diseases is NOT included in the analysis.
  3. This test does not examine structural variants, inclusive of deletions and duplications, which may be a cause of disease
  4. This analysis assesses only inherited variants and does not analyze new (de novo) variants unique to the embryo.
  5. PRS results are risk estimates only and are NOT diagnostic, nor do they guarantee the presence or absence of a disease. Irrespective of the results provided in this study, there is still a 3-5% chance in every pregnancy of genetic and/or non-genetic medical problems, including birth defects and intellectual disability.
  6. The PRS test is designed to provide risk estimates only for the specific conditions listed above. Additional PRS for other polygenic diseases are NOT included in the analysis.
  7. PRS is not reported in aneuploid embryos due to the known interference of chromosomal abnormalities with polygenic disease risk calculations.
  8. PRS calculations do not include additional non-genetic factors such as environmental exposure.
  1. Sensitivity of the test may be reduced when participant demographics differ from the training set which is currently a group of UK/British individuals.
  2. PRS prediction of disease risk may be reduced in certain families with rare, monogenic variants.
  3. A history of stem cell or bone marrow transplantation, or recent blood transfusion, in at least one of the biological parents may impact the accuracy of the results and must be reported to the PI of the study
  4. Like most tests, this test has a risk of false negative or false positive results. Chromosomal mosaicism is one possible cause for a false positive or false negative result. The overall chance of a false negative or a false positive result unrelated to mosaicism is 2% and includes, but is not limited to, sample contamination from biological or non-biological sources, specimen marking issues, rare genetic variants interfering with analysis, and other technical issues and limitations.
  5. Although rare, it is possible that results for one or more embryos are not available. Testing is unavailable for samples damaged by human error or lost/destroyed due to weather, transit issues or other problems beyond the control of this study and the testing laboratory.
  6. Test results should always be interpreted by a clinician in the context of clinical and familial data with the availability of genetic counseling when appropriate.

Disclaimers and Compliance Statements

The following information is provided under the IRB-approved study #1267554 under WIRB. Every reasonable care is taken to ensure that the information is accurate. Although portions of this testing were performed at Natera, Inc, a CLIA-certified clinical laboratory (CLIA ID#05D1082992), the summary and information is NOT provided as a clinical result. CLIA is a federal program overseen by the Centers for Medicare and Medicaid Services (CMS). This test is intended for research and informational purposes only. It has not been cleared or approved by the US Food and Drug Administration. The content is not intended to be a substitute for professional medical advice, diagnosis, or treatment. Always seek the advice of your physician or other qualified health provider with any questions you may have regarding a medical

condition or treatment. A medical geneticist is available for you under this study, at Consult your physician before taking action on any information provided in this report. The results are based upon polygenic risk scores (PRS) for each given disease trait. The results are risk estimates only and are NOT diagnostic, nor do they guarantee the presence or absence of a disease. This does not eliminate the need for prenatal screening and testing as recommended during pregnancy. Provided data may have implications for study participants' and their relatives' health. Consider further genetic testing to identify and confirm. This test does not substitute for carrier screening for recessive conditions. Additional carrier screening testing is recommended.


Test Background

  1. ABCA1 - Familial HDL deficiency; Familial alpha lipoprotein deficiency (aka Tangier disease)
  2. ABCC9 - Familial dilated cardiomyopathy; Familial atrial fibrillation
  3. ABCG5 - Sitosterolemia
  4. ABCG8 - Sitosterolemia
  5. ACADS - SCAD deficiency
  6. ACTA2 - Familial thoracic aortic aneurysms and dissections
  7. ACTC1 - Hypertrophic cardiomyopathy; Dilated cardiomyopathy; Left Ventricular Non-Compaction Cardiomyopathy
  8. ACTN2 - Hypertrophic cardiomyopathy, Dilated cardiomyopathy
  9. ACVRL1 - Hereditary hemorrhagic telangiectasia
  10. AKAP9 - Romano-Ward syndrome
  11. ALPK3 - Hypertrophic cardiomyopathy
  12. ANGPTL3 - Familial hypobetalipoproteinemia
  13. ANK2 - Ankyrin-B syndrome
  14. ANKRD1 - Familial dilated cardiomyopathy
  15. APC - Familial adenomatous polyposis
  16. APOA1 - Familial HDL deficiency
  17. APOA5 - Familial hypertriglyceridemia (predisposition), Familial type 5 hyperlipoproteinemia
  18. APOB - Familial hypercholesterolemia
  19. APOC2 - Apolipoprotein C2 deficiency; Hyperlipoproteinemia 1B (HLPP1B)
  20. ATM - Breast and pancreatic cancers
  21. ATP7B - Wilson disease
  22. BAG3 - Familial dilated cardiomyopathy
  23. BAP1 - Risk of melanoma
  24. BARD1 - Breast and ovarian cancers (evidence limited or conflicting)
  25. BLM - Bloom syndrome
  26. BMPR1A - Juvenile polyposis
  27. BRAF - Cardiofaciocutaneous syndrome; Noonan syndrome
  28. BRCA1 - Hereditary breast and ovarian cancer
  29. BRCA2 - Hereditary breast and ovarian cancer
  30. BRIP1 - Ovarian cancer
  31. CACNA1C - Brugada syndrome
  32. CACNA2D1 - Brugada syndrome
  33. CACNB2 - Brugada syndrome
  34. CALM1 - Romano-Ward syndrome
  35. CALM2 - Romano-Ward syndrome
  36. CALM3 - Romano-Ward syndrome
  37. CASQ2 - Catecholaminergic polymorphic ventricular tachycardia
  38. CDC73 - Hyperparathyroidism-jaw tumor syndrome
  39. CDH1 - Hereditary diffuse gastric cancer
  40. CDKN2A - Familial Atypical Multiple Mole Melanoma (FAMMM) syndrome
  41. CETP - Hyperalphalipoproteinemia 1
  42. CHEK2 - Breast and colorectal cancers
  43. CLCNKB - Bartter syndrome; Gitelman syndrome
  44. COL3A1 - Ehlers-Danlos syndrome, vascular type
  45. COQ2 - Coenzyme Q10 deficiency
  46. COQ9 - Coenzyme Q10 deficiency
  47. CSRP3 - Hypertrophic cardiomyopathy, dilated cardiomyopathy
  48. CUL3 - Pseudohypoaldosteronism type 2
  49. DES - Familial dilated cardiomyopathy; Arrhythmogenic right ventricular cardiomyopathy
  50. DMD - Familial dilated cardiomyopathy
  51. DSC2 - Arrhythmogenic right ventricular cardiomyopathy
  52. DSG2 - Arrhythmogenic right ventricular cardiomyopathy
  53. DSP - Arrhythmogenic right ventricular cardiomyopathy
  54. DTNA - Left Ventricular Non-Compaction
  55. ENG - Hereditary Hemorrhagic Telangiectasia
  56. EPCAM - Lynch syndrome
  57. F2 - Hereditary Thrombophilia
  58. FAM175A/ABRAXAS1 - Hereditary cancer-predisposing syndrome
  59. FBN1 - Marfan syndrome
  60. FH - Leiomyomatosis and renal cell cancer
  1. FHL1 - Emery-Dreifuss muscular dystrophy
  2. FKRP - Walker-Warburg syndrome; Limb-girdle muscular dystrophy
  3. FKTN - Fukuyama congenital muscular dystrophy; Walker-Warburg syndrome; Limb-girdle muscular dystrophy; Dilated cardiomyopathy type 1X (DCM1X)
  4. FLCN - Birt Hogg Dube syndrome
  5. FLG - Atopic dermatitis; Ichthyosis vulgaris
  6. FTH1 - Hemochromatosis
  7. GAA - Glycogen storage disease II
  8. GATA-4 - Critical congenital heart disease; Heterotaxy syndrome; NCBI gene - Tetralogy of Fallot
  9. GATAD1 - Familial dilated cardiomyopathy
  10. GCH1 - Dystonia,DOPA-responsive,with or without hyperphenylalaninemia
  11. GCKR - Hypertriglyceridemia; Triglycerides
  12. GLA - Fabry disease
  13. GPD1L - Brugada syndrome
  14. GREM1 - Hereditary mixed polyposis syndrome
  15. HAMP - Hemochromatosis,type 2B
  16. HCN4 - Brugada syndrome; left ventricular noncompaction
  17. HMBS - Porphyria,acute intermittent
  18. HRAS - Costello syndrome
  19. HSD11B2 - Apparent mineralocorticoid excess (AME)
  20. JUP - Arrhythmogenic right ventricular cardiomyopathy
  21. KCND3 - Brugada syndrome
  22. KCNE1 - Long QT syndrome
  23. KCNE1L/KCNE5 - Brugada syndrome
  24. KCNE2 - Long QT syndrome
  25. KCNE3 - Brugada syndrome
  26. KCNH2 - Romano-Ward syndrome; Brugada syndrome
  27. KCNJ1 - Bartter syndrome - type II
  28. KCNJ2 - Short QT syndrome
  29. KCNJ5 - Familial hyperaldosteronism type III
  30. KCNJ8 - Brugada syndrome
  31. KCNQ1 - Romano-Ward syndrome; Brugada syndrome
  32. KCNQ1 - Familial atrial fibrillation; Romano-Ward syndrome
  33. KIT - Gastrointestinal stromal tumor
  34. KLHL3 - Pseudohypoaldosteronism type 2 (PHA2)
  35. KRAS - Noonan syndrome
  36. LAMA4 - Familial dilated cardiomyopathy
  37. LAMP2 - Hypertrophic cardiomyopathy, dilated cardiomyopathy
  38. LCAT - Complete LCAT deficiency; Increased risk of atherosclerosis
  39. LDB3 - Dilated cardiomyopathy, Left Ventricular Non-Compaction Cardiomyopathy
  40. LDLR - Familial hypercholesterolemia; LDL cholesterol
  41. LDLRAP1/ARH - Familial hypercholesterolemia
  42. LIPC - Hepatic lipase deficiency; HDL cholesterol
  43. LMF1 - Combined lipase deficiency (CLD)
  44. LMNA - Hypertrophic cardiomyopathy; Dilated cardiomyopathy; Left Ventricular Non-Compaction Cardiomyopathy
  45. LPL - Familial lipoprotein lipase deficiency
  46. MAP2K1 - Cardiofaciocutaneous syndrome; Noonan syndrome; cancers
  47. MAP2K2 - Cardiofaciocutaneous syndrome
  48. MAX - Susceptibility to pheochromocytoma
  49. MEN1 - Multiple endocrine neoplasia type 1
  50. MET - Familial papillary renal cell carcinoma
  51. MIB1 - Left ventricular noncompaction
  52. MLH1 - Lynch syndrome
  53. MLH3 - Hereditary nonpolyposis colorectal cancer/Lynch syndrome
  54. MRE11 - Associated risk of breast and ovarian cancers
  55. MSH2 - Lynch syndrome
  56. MSH6 - Lynch syndrome
  57. MTTP - Abetalipoproteinemia
  58. MUTYH - MYH-associated polyposis; adenomas, multiple colorectal, FAP type 2; colorectal adenomatous polyposis, autosomal recessive, with pilomatricomas
  1. MYBPC3 - Hypertrophic cardiomyopathy; Dilated cardiomyopathy
  2. MYH11 - Familial thoracic aortic aneurysms and dissections
  3. MYH7 - Hypertrophic cardiomyopathy, dilated cardiomyopathy
  4. MYL2 - Hypertrophic cardiomyopathy, dilated cardiomyopathy
  5. MYL3 - Hypertrophic cardiomyopathy, dilated cardiomyopathy
  6. MYOZ2 - Hypertrophic cardiomyopathy
  7. NBN - Breast cancer
  8. NEXN - Hypertrophic cardiomyopathy; Dilated cardiomyopathy
  9. NF2 - Neurofibromatosis type 2
  10. NKX2-5 - Familial atrial fibrillation
  11. NOTCH1 - Bicuspid aortic valve
  12. NR3C2 - Pseudohypoaldosteronism type 1 (PHA1) (Autosomal dominant)
  13. NRAS - Noonan syndrome
  14. NT5E - Calcification of joints and arteries
  15. OTC - Ornithine transcarbamylase deficiency
  16. PALB2 - Risk of breast and pancreatic cancers
  17. PAH - Phenylketonuria
  18. PCBD1 - Hyperphenylalaninemia,BH4-deficient
  19. PCSK9 - Familial hypercholesterolemia
  20. PDGFRA - Gastrointestinal stromal tumor
  21. PKP2 - Arrhythmogenic right ventricular cardiomyopathy
  22. PLN - Familial dilated cardiomyopathy; Familial hypertrophic cardiomyopathy; Arrhythmogenic right ventricular cardiomyopathy
  23. PMS2 - Lynch syndrome
  24. PRKAG2 - Hypertrophic cardiomyopathy, dilated cardiomyopathy
  25. PRKAR1A - Carney complex,type 1
  26. PROC - Thrombophilia due to protein C deficiency
  27. PROS1 - Thrombophilia due to protein S deficiency
  28. PTCH1 - Basal cell nevus syndrome (aka Gorlin syndrome)
  29. PTEN - PTEN hamartoma tumor syndrome (Cowden syndrome)
  30. PTPN11 - Noonan syndrome
  31. PTS - Hyperphenylalaninemia,BH4-deficient
  32. QDPR - Hyperphenylalaninemia,BH4-deficient
  33. RAD50 - Risk of breast and ovarian cancers
  34. RAD51C - Risk of ovarian cancer
  35. RAD51D - Risk of ovarian cancer
  36. RAF1 - Noonan syndrome
  37. RANGED - Brugada syndrome
  38. RB1 - Retinoblastoma
  39. RBM20 - Familial dilated cardiomyopathy
  40. RET - Multiple endocrine neoplasia type 2; Familial medullary thyroid cancer
  41. RIT1 - Noonan syndrome
  42. RYR2 - Catecholaminergic polymorphic ventricular tachycardia
  43. SAR1B - Chylomicron retention disease
  44. SCN1B - Brugada syndrome; Progressive familial heart block; Familial atrial fibrillation
  45. SCN2B - Brugada syndrome
  46. SCN3B - Brugada syndrome
  47. SCN4B - Brugada syndrome; Familial atrial fibrillation
  48. SCN5A - Romano-Ward long-QT syndrome types 1, 2, and 3; Brugada syndrome
  49. SCNN1A - Pseudohypoaldosteronism type 1 (PHA1) (Autosomal recessive)
  50. SCNN1B - Pseudohypoaldosteronism type 1 (PHA1) (Autosomal recessive)
  51. SCNN1G - Pseudohypoaldosteronism type 1 (PHA1) (Autosomal recessive)
  52. SDHA - Hereditary paraganglioma-pheochromocytoma syndrome
  53. SDHAF2 - Hereditary paraganglioma-pheochromocytoma syndrome (PGL2)
  54. SDHB - Hereditary paraganglioma-pheochromocytoma syndrome (PGL4)
  55. SDHC - Hereditary paraganglioma-pheochromocytoma syndrome (PGL3)
  56. ADHD - Hereditary paraganglioma-pheochromocytoma syndrome (PGL1)
  57. SERPINA1 - Alpha-1-Antitrypsin Deficiency
  58. SERPINC1 - Thrombophilia due to antithrombin III deficiency
  59. SGCD - Familial dilated cardiomyopathy
  60. SLC12A1 - Bartter syndrome
  1. SLC25A13 - Citrullinemia,adult onset type II
  2. SLC37A4 - Glycogen storage disease Ib; Glycogen storage disease
  3. SLC3A1 - Cystinuria
  4. SLC40A1 - Hemochromatosis
  5. SLC7A9 - Cystinuria
  6. SMAD3 - Loeys-Dietz syndromes
  7. SMAD4 - Juvenile polyposis
  8. SMAD4 - Hereditary hemorrhagic telangiectasia/Juvenile polyposis
  9. SMARCB1 - Schwannomatosis
  10. SNTA1 - Romano-Ward syndrome
  11. SOS1 - Noonan syndrome
  12. STK11 - Peutz-Jeghers syndrome
  13. TAZ - Barth syndrome
  14. TBX5 - Holt-Oram syndrome
  15. TCAP - Limb-girdle muscular dystrophy type 2G
  16. TGFB2 - Loeys Dietz syndrome
  17. TGFB3 - Arrhythmogenic right ventricular dysplasia (aka Arrhythmogenic right ventricular cardiomyopathy type 5 - ARVC5)
  18. TGFBR1 - Loeys-Dietz syndromes
  19. TGFBR2 - Loeys-Dietz syndromes
  20. TMEM127 - Susceptibility to pheochromocytoma
  21. TMEM43 - Arrhythmogenic right ventricular cardiomyopathy
  22. TNNC1 - Hypertrophic cardiomyopathy; dilated cardiomyopathy
  23. TNNI3 - Hypertrophic cardiomyopathy; dilated cardiomyopathy
  24. TNNT2 - Hypertrophic cardiomyopathy; dilated cardiomyopathy
  25. TP53 - Li-Fraumeni syndrome; hereditary cancer
  26. TPM1 - Hypertrophic cardiomyopathy; dilated cardiomyopathy
  27. TRDN - Catecholaminergic polymorphic ventricular tachycardia
  28. TRPM4 - Brugada syndrome
  29. TSC1 - Tuberous sclerosis complex
  30. TSC2 - Tuberous sclerosis complex
  31. TTN - Familial dilated cardiomyopathy
  32. TTR - Transthyretin amyloidosis
  33. VCL - Dilated cardiomyopathy; Left Ventricular Non-Compaction Cardiomyopathy
  34. VHL - Von Hippel–Lindau syndrome
  35. WNK1 - Pseudohypoaldosteronism type 2 (PHA2)
  36. WNK4 - Pseudohypoaldosteronism type 2 (PHA2)
  37. WT1 - WT1-related Wilms tumor
  38. XRCC2 - Hereditary cancer
  39. HBA - Alpha Thalassemia
  40. CLN3 - Juvenile CLN3 Disease
  41. HBB - Beta Thalassemia, Methemoglobinemia, Beta-globin Type, Sickle cell disease
  42. BLM - Bloom syndrome
  43. ASPA - Canavan disease
  44. ASS1 - Type I Citrullinemia
  45. CFTR - Cystic Fibrosis
  46. DMD - Duchenne & Becker Muscular Dystrophy, Familial Dilated Cardiomyopathy
  47. IKBKAP - Familial Dysautonomia
  48. FANCC - Fanconi anemia
  49. GALT - Galactosemia
  50. GBA - Gaucher disease/Parkinson disease, Dementia with Lewy bodies
  51. G6PC - Glycogen Storage Disease,
  52. IVD - Isovaleric Acidemia
  53. ACADM - Medium-Chain Acyl-CoA Dehydrogenase (MCAD) Deficiency
  54. MMACHC - Methylmalonic Acidemia with Homocystinuria, cblC type
  55. MCOLN1 - Mucolipidosis Type IV.
  56. IDUA - Mucopolysaccharidosis Type I (MPS I)
  57. SMPD1 - Niemann-Pick Disease types A and B
  58. PKHD1 - Polycystic Kidney Disease
  59. PEX7 - Refsum Disease, rhizomelic chondrodysplasia punctata type 1 (RCDP1)
  60. DHCR7 - Smith-Lemli-Opitz Syndrome
  61. HEXA - Tay-Sachs Disease
  62. FAH - Tyrosinemia Type I
  63. PEX1 - Zellweger Spectrum Disorder

Multifactorial Conditions Details: Experimental Results

The diseases and traits listed in the experimental section of this report are not meant to be used in any way for decision-making purposes by you or your physician. These diseases and traits have not met our threshold for being statistically relevant and are included here for informational purposes only because explicitly requested by parents. The following limitations apply:

  1. The analytical models related to these diseases and traits have been validated by MyOme but may have statistical significance comparable with random chance or close to it.
  2. The likelihood of the disease or trait manifesting itself may not be any greater than it happening by chance without using the information below.


Lifetime risk %
(Percentile of PRS)
System/Category Disease Embryo 1 Embryo 2 EMBRYO 3 EMBRYO 4


These experimental trait predictions have been included at the request of the study participant. The accuracy of a prediction of a behavioral trait may be low because of unaccounted for environmental factors that can be far more significant than genetic factors, rare genetic variants not included in the model, interactions between variants not included in the model, inability to project from a model based on one ethnicity to another, various other genetic factors not captured in the model, the inability to precisely measure the underlying trait, unmodeled population biases and a host of other factors that can make the models inaccurate. The majority of the risk alleles in behavioral models do not have a known causal relationship connecting the variant to the trait. The definition of behavioral traits often varies and is debated in the scientific community. If you would like further information on our definitions, please contact

the study PI. All caveats and limitations from Addendum 1 additionally apply below.
Education Attainment - Probability the born child will complete a Bachelor's degree. Highly dependent on a baseline percentage. In 2018, the baseline national average was 35%.
Household Income - Probability the born child will be in the top quartile of household income. Highly dependent on the baseline percentage, defined as 25%.
Cognitive Ability - Probability the born child will be in the greater than 90th percentile of a standardized IQ scale.
Subjective Well-being - Probability the born child would respond "Very Satisfied" on a life satisfaction survey.

Lifetime probability %
(Percentile of PRS)
Disease Embryo 1 Embryo 2 Embryo 3 Embryo 4

References to Publications

  1. Goldstein BA, Knowles JW, Salfati E, Ioannidis JP, Assimes TL. Simple, standardized incorporation of genetic risk into non-genetic risk prediction tools for complex traits: coronary heart disease as an example. Front Genet. 2014;5:254.
  2. Mavaddat N, Pharoah PD, Michailidou K, et al. Prediction of breast cancer risk based on profiling with common genetic variants. J Natl Cancer Inst. 2015;107(5)
  3. "Liu CC, Liu CC, Kanekiyo T, Xu H, Bu G. Apolipoprotein E and Alzheimer disease: risk, mechanisms and therapy. Nat Rev Neurol. 2013;9(2):106-18.
  4. Corder EH, Saunders AM, Strittmatter WJ, et al. Gene dose of apolipoprotein E type 4 allele and the risk of Alzheimer's disease in late onset families. Science. 1993;261(5123):921-3.
  5. Rebeck GW, Reiter JS, Strickland DK, Hyman BT. Apolipoprotein E in sporadic Alzheimer's disease: allelic variation and receptor interactions. Neuron. 1993;11(4):575-80.
  6. Farrer LA, Cupples LA, Haines JL, et al. Effects of age, sex, and ethnicity on the association between apolipoprotein E genotype and Alzheimer disease. A meta-analysis. APOE and Alzheimer Disease Meta Analysis Consortium. JAMA. 1997;278(16):1349-56.
  7. Genin E, Hannequin D, Wallon D, et al. APOE and Alzheimer disease: a major gene with semi-dominant inheritance. Mol Psychiatry. 2011;16(9):903-7.
  8. Chubb D, Broderick P, Frampton M, et al. Genetic diagnosis of high-penetrance susceptibility for colorectal cancer (CRC) is achievable for a high proportion of familial CRC by exome sequencing. J Clin Oncol. 2015;33(5):426-32.
  9. "Gan EK, Powell LW, Olynyk JK. Natural history and management of HFE-hemochromatosis. Semin Liver Dis. 2011;31(3):293-301.
  10. Allen KJ, Bertalli NA, Osborne NJ, et al. HFE Cys282Tyr homozygotes with serum ferritin concentrations below 1000 microg/L are at low risk of hemochromatosis. Hepatology. 2010;52(3):925-33.
  11. EASL clinical practice guidelines for HFE hemochromatosis. J Hepatol. 2010;53(1):3-22."
  12. Fritsche LG, Gruber SB, Wu Z, et al. Association of Polygenic Risk Scores for Multiple Cancers in a Phenome-wide Study: Results from The Michigan Genomics Initiative. Am J Hum Genet. 2018;102(6):1048-1061.
  13. Abraham G, Tye-din JA, Bhalala OG, Kowalczyk A, Zobel J, Inouye M. Accurate and robust genomic prediction of celiac disease using statistical learning. PLoS Genet. 2014;10(2):e1004137.
  14. Meigs JB, Shrader P, Sullivan LM, et al. Genotype score in addition to common risk factors for prediction of type 2 diabetes. N Engl J Med. 2008;359(21):2208-19.
  15. Fritsche LG, Chen W, Schu M, et al. Seven new loci associated with age-related macular degeneration. Nat Genet. 2013;45(4):433-9, 439e1-2.
  16. Chen H, Poon A, Yeung C, et al. A genetic risk score combining ten psoriasis risk loci improves disease prediction. PLoS ONE. 2011;6(4):e19454.
  17. Jiang X, Askling J, Saevarsdottir S, et al. A genetic risk score composed of rheumatoid arthritis risk alleles, HLA-DRB1 haplotypes, and response to TNFi therapy - results from a Swedish cohort study. Arthritis Res Ther. 2016;18(1):288.
  1. "Liu JZ, Van Sommeren S, Huang H, et al. Association analyses identify 38 susceptibility loci for inflammatory bowel disease and highlight shared genetic risk across populations. Nat Genet. 2015;47(9):979-986.
  2. Huang C, De ravin SS, Paul AR, et al. Genetic Risk for Inflammatory Bowel Disease Is a Determinant of Crohn's Disease Development in Chronic Granulomatous Disease. Inflamm Bowel Dis. 2016;22(12):2794-2801."
  3. Gao XR, Huang H, Kim H. Polygenic Risk Score Is Associated With Intraocular Pressure and Improves Glaucoma Prediction in the UK Biobank Cohort. Transl Vis Sci Technol. 2019;8(2):10.
  4. "Olds LC, Sibley E. Lactase persistence DNA variant enhances lactase promoter activity in vitro: functional role as a cis regulatory element. Hum Mol Genet. 2003;12(18):2333-40.
  5. Enattah NS, Sahi T, Savilahti E, Terwilliger JD, Peltonen L, Järvelä I. Identification of a variant associated with adult-type hypolactasia. Nat Genet. 2002;30(2):233-7."
  6. "Potrony M, Puig-butille JA, Aguilera P, et al. Prevalence of MITF p.E318K in Patients With Melanoma Independent of the Presence of CDKN2A Causative Mutations. JAMA Dermatol. 2016;152(4):405-12.
  7. Ghiorzo P, Pastorino L, Queirolo P, et al. Prevalence of the E318K MITF germline mutation in Italian melanoma patients: associations with histological subtypes and family cancer history. Pigment Cell Melanoma Res. 2013;26(2):259-62.
  8. Yokoyama S, Woods SL, Boyle GM, et al. A novel recurrent mutation in MITF predisposes to familial and sporadic melanoma. Nature. 2011;480(7375):99-103.
  9. Bertolotto C, Lesueur F, Giuliano S, et al. A SUMOylation-defective MITF germline mutation predisposes to melanoma and renal carcinoma. Nature. 2011;480(7375):94-8.
  10. Berwick M, Macarthur J, Orlow I, et al. MITF E318K's effect on melanoma risk independent of, but modified by, other risk factors. Pigment Cell Melanoma Res. 2014;27(3):485-8."
  11. "Meier Y, Zodan T, Lang C, et al. Increased susceptibility for intrahepatic cholestasis of pregnancy and contraceptive-induced cholestasis in carriers of the 1331T>C polymorphism in the bile salt export pump. World J Gastroenterol. 2008;14(1):38-45.
  12. Dixon PH, Van mil SW, Chambers J, et al. Contribution of variant alleles of ABCB11 to susceptibility to intrahepatic cholestasis of pregnancy. Gut. 2009;58(4):537-44."
  13. "Kobashi G, Yamada H, Ohta K, Kato E, Ebina Y, Fujimoto S. Endothelial nitric oxide synthase gene (NOS3) variant and hypertension in pregnancy. Am J Med Genet. 2001;103(3):241-4.
  14. Yoshimura T, Yoshimura M, Tabata A, et al. Association of the missense Glu298Asp variant of the endothelial nitric oxide synthase gene with severe preeclampsia. J Soc Gynecol Investig. 2000;7(4):238-41.
  15. Hillermann R, Carelse K, Gebhardt GS. The Glu298Asp variant of the endothelial nitric oxide synthase gene is associated with an increased risk for abruptio placentae in pre-eclampsia. J Hum Genet. 2005;50(8):415-419."
  16. "Lee AJ, Marder K, Alcalay RN, et al. Estimation of genetic risk function with covariates in the presence of missing genotypes. Stat Med. 2017;36(22):3533-3546.
  1. Lee AJ, Wang Y, Alcalay RN, et al. Penetrance estimate of LRRK2 p.G2019S mutation in individuals of non-Ashkenazi Jewish ancestry. Mov Disord. 2017;32(10):1432-1438.
  2. Licher S, Darweesh SKL, Wolters FJ, et al. Lifetime risk of common neurological diseases in the elderly population. J Neurol Neurosurg Psychiatry. 2019;90(2):148-156."
  3. "Zhu QQ, Zhang XL, Zhang SM, et al. Association Between the MUC5B Promoter Polymorphism rs35705950 and Idiopathic Pulmonary Fibrosis: A Meta-analysis and Trial Sequential Analysis in Caucasian and Asian Populations. Medicine (Baltimore). 2015;94(43):e1901.
  4. Helling BA, Gerber AN, Kadiyala V, et al. Regulation of MUC5B Expression in Idiopathic Pulmonary Fibrosis. Am J Respir Cell Mol Biol. 2017;57(1):91-99.
  5. Seibold MA, Wise AL, Speer MC, et al. A common MUC5B promoter polymorphism and pulmonary fibrosis. N Engl J Med. 2011;364(16):1503-12.
  6. Horimatsu Y, Ohshima S, Bonella F, et al. MUC5B promoter polymorphism in Japanese patients with idiopathic pulmonary fibrosis. Respirology. 2015;20(3):439-44.
  7. Noth I, Zhang Y, Ma SF, et al. Genetic variants associated with idiopathic pulmonary fibrosis susceptibility and mortality: a genome-wide association study. Lancet Respir Med. 2013;1(4):309-317."
  8. "Stanescu HC, Arcos-burgos M, Medlar A, et al. Risk HLA-DQA1 and PLA(2)R1 alleles in idiopathic membranous nephropathy. N Engl J Med. 2011;364(7):616-26.
  9. Ramachandran R, Kumar V, Kumar A, et al. PLA2R antibodies, glomerular PLA2R deposits and variations in PLA2R1 and HLA-DQA1 genes in primary membranous nephropathy in South Asians. Nephrol Dial Transplant. 2016;31(9):1486-93.
  10. Kaga H, Komatsuda A, Omokawa A, et al. Analysis of PLA2R1 and HLA-DQA1 sequence variants in Japanese patients with idiopathic and secondary membranous nephropathy. Clin Exp Nephrol. 2018;22(2):275-282.
  11. Wang W, Fan S, Li G, et al. Interaction between PLA2R1 and HLA-DQA1 variants contributes to the increased genetic susceptibility to membranous nephropathy in Western China. Nephrology (Carlton). 2019;24(9):919-925.
  12. Lv J, Hou W, Zhou X, et al. Interaction between PLA2R1 and HLA-DQA1 variants associated with anti-PLA2R antibodies and membranous nephropathy. J Am Soc Nephrol. 2013;24(8):1323-9.
  13. Stanescu HC, Arcos-burgos M, Medlar A, et al. Risk HLA-DQA1 and PLA(2)R1 alleles in idiopathic membranous nephropathy. N Engl J Med. 2011;364(7):616-26.
  14. Xu X, Wang G, Chen N, et al. Long-Term Exposure to Air Pollution and Increased Risk of Membranous Nephropathy in China. J Am Soc Nephrol. 2016;27(12):3739-3746.
  15. Wang JH, Pappas D, De jager PL, et al. Modeling the cumulative genetic risk for multiple sclerosis from genome-wide association data. Genome Med. 2011;3(1):3.
  16. Pisanu C, Preisig M, Castelao E, et al. A genetic risk score is differentially associated with migraine with and without aura. Hum Genet. 2017;136(8):999-1008.
  1. Leo PJ, Madeleine MM, Wang S, et al. Defining the genetic susceptibility to cervical neoplasia-A genome-wide association study. PLoS Genet. 2017;13(8):e1006866.
  2. Kleinstern G, Camp NJ, Goldin LR, et al. Association of polygenic risk score with the risk of chronic lymphocytic leukemia and monoclonal B-cell lymphocytosis. Blood. 2018;131(23):2541-2551.
  3. Sharp SA, Rich SS, Wood AR, et al. Development and Standardization of an Improved Type 1 Diabetes Genetic Risk Score for Use in Newborn Screening and Incident Diagnosis. Diabetes Care. 2019;42(2):200-207.
  4. De haan HG, Bezemer ID, Doggen CJ, et al. Multiple SNP testing improves risk prediction of first venous thrombosis. Blood. 2012;120(3):656-63.
  5. Muse ED, Wineinger NE, Spencer EG, et al. Validation of a genetic risk score for atrial fibrillation: A prospective multicenter cohort study. PLoS Med. 2018;15(3):e1002525.
  6. Stahl EA, Breen G, Forstner AJ, et al. Genome-wide association study identifies 30 loci associated with bipolar disorder. Nat Genet. 2019;51(5):793-803.
  7. Howard DM, Adams MJ, Clarke TK, et al. Genome-wide meta-analysis of depression identifies 102 independent variants and highlights the importance of the prefrontal brain regions. Nat Neurosci. 2019;22(3):343-352.
  8. Revealing the complex genetic architecture of obsessive-compulsive disorder using meta-analysis. Mol Psychiatry. 2018;23(5):1181-1188.
  9. Biological insights from 108 schizophrenia-associated genetic loci. Nature. 2014;511(7510):421-7.
  10. Purves KL, Coleman JRI, Meier SM, et al. A major role for common genetic variation in anxiety disorders. Mol Psychiatry. 2019;
  11. Lee JJ, Wedow R, Okbay A, et al. Gene discovery and polygenic prediction from a genome-wide association study of educational attainment in 1.1 million individuals. Nat Genet. 2018;50(8):1112-1121.
  12. Roberts GHL, Paul S, Yorgov D, Santorico SA, Spritz RA. Family Clustering of Autoimmune Vitiligo Results Principally from Polygenic Inheritance of Common Risk Alleles. Am J Hum Genet. 2019;105(2):364-372.
  13. Hill WD, Davies NM, Ritchie SJ, et al. Genome-wide analysis identifies molecular systems and 149 genetic loci associated with income. Nat Commun. 2019;10(1):5741.
  14. Khera AV, Chaffin M, Wade KH, et al. Polygenic Prediction of Weight and Obesity Trajectories from Birth to Adulthood. Cell. 2019;177(3):587-596.e9.
  15. Baselmans, B.M.L., Jansen, R., Ip, H.F. et al. Multivariate genome-wide analyses of the well-being spectrum. Nat Genet 51, 445–451 (2019).
  16. Hill, W.D., Davies, N.M., Ritchie, S.J. et al. Genome-wide analysis identifies molecular systems and 149 genetic loci associated with income. Nat Commun 10, 5741 (2019).
  17. Hill, W.D., Marioni, R.E., Maghzian, O. et al. A combined analysis of genetically correlated traits identifies 187 loci and a role for neurogenesis and myelination in intelligence. Mol Psychiatry 24, 169–181 (2019).

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