Our Bodies, Our Choice

Our Bodies, Our Choice

The moral and technical case for enabling people to view their own genomes for reproductive decision-making.

Orchid is led by women. We’ve seen the impact of genetic disease strike our own families, so our mission is personal: to expand reproductive choice by providing the information people need to have healthy families.

Specifically, we believe in a constitutionally protected right to choose. We believe that people have the right to information about their own bodies. We believe that reproductive decision-making is a personal affair, and — for good historical reasons — we believe that it should be outside of state control. And we believe that genomics has recently improved to the point that parents can now quantifiably reduce a future child’s risk of both rare Mendelian disorders and more prevalent multifactorial inherited diseases like heart disease, type I diabetes, and breast cancer.

Today, rather than freezing the status quo in amber — which artificially limits the availability of pre-pregnancy genetic testing to testing for mostly rare single-gene diseases — we can use polygenic risk score (PRS) testing before pregnancy to help parents protect their children from inheriting an elevated genetic predisposition to multifactorial inherited diseases with no cure. 

In short, we believe in the moral necessity and technical feasibility of expanding access to reproductive genetic testing in all senses of the term - we need to reduce stigma, lower costs, increase the diversity of tested populations, expand the number of test recipients, and broaden the set of conditions to the chronic diseases that strike us all.

The Moral Necessity

The moral case for broadening pre-pregnancy genetic testing is simple: opposing it means opposing reproductive choice.

Over the last few generations, reproductive rights became legally protected in the United States and large swaths of the world. Women can now freely choose to use birth control, to freeze their eggs, to opt for in vitro fertilization (IVF), and in general to choose when and whether they want to have children.

The enabling technologies weren’t initially welcomed. Birth control was fought for decades, artificial insemination was denounced as a form of adultery, and in-vitro fertilization (IVF) was strongly opposed for creating “test-tube” babies. Eventually, of course, these practices all became mainstream, and the scientists who pushed through the controversy to expand choice ended up winning Nobel Prizes.

At every step, clinical genomics has likewise been fought. Some opposed the sequencing of the human genome in the first place. Some said genomics hadn’t produced any clinical value. And some said that expanded carrier testing for Mendelian conditions was too radical, before it became the standard of care just a few years later.

When you put together reproductive choice and clinical genomics, you get pre-pregnancy genetic testing. Just like people have the right to look in a mirror, the right to choose a partner, and the right to view their own medical records, they have the right to see their own genome — and to make reproductive decisions on the basis of that information, including which embryo to transfer, as already happens many times per day in the privacy of clinics around the world. 

And in an age of personal genomics, it’s impractical to prevent people from viewing their own genomes.  There are now more than 30 million sequenced genomes out there. The responsible approach is to provide clinical reports and professional guidance to clearly articulate the risks, benefits, and limitations for patients to make informed reproductive decisions about their own bodies and their future children.

These decisions are evolving to consider information beyond just rare genetic variants for single-gene disorders. The reason is that large new genomic datasets have led to the development of polygenic risk scores, which statistically approximate the chance that an individual can develop a complex polygenic disease, one that is affected by variation across many genes. This means prospective parents can potentially reduce their risk of having children affected by rare monogenic disorders and more common polygenic diseases like heart disease, diabetes, and breast cancer.

There are several ways for them to reduce their risk. Prospective parents can get tested prior to marriage (as Dor Yeshorim does), after pairing up but before conception (preconception testing), over the course of IVF treatment (via PGT), or during pregnancy (prenatal testing). The earlier prospective parents get tested, the more choices they can make.

But the ultimate choice is theirs alone. A woman, in concert with her chosen partner and clinical team, has the right to information to identify which embryo she would like to implant into her body. We resist the idea that others should be preventing women from accessing information about their own bodies or stigmatizing the use of clinical genetics research to reduce risk of diseases. Informed families allow for more equality in health outcomes. Families most susceptible stand to receive the greatest benefit from screening.

This is the start of the conversation for why we should enable parents to make informed reproductive decisions, in the absence of state coercion, in the presence of a genetic counselor or physician should they see fit, using all available data — including their own genetic makeup. It is the next step in using technology to expand reproductive choice.

Now for the technical feasibility: why we can now enable parents to make informed decisions about a wider array of conditions beyond the monogenic disorders that are already a staple of practice in reproductive genomics.

Common Questions

We’ve heard some questions, here are some answers. We're excited to engage with the broader community around the most thoughtful and transparent way to communicate genetic risk.


Pre-pregnancy genetic testing is not new. For many years, parents have used preimplantation genetic testing (PGT) to reduce the risk of having children with monogenic disorders like Tay Sachs, where the disease is caused by mutations in a single gene.

Orchid’s goal is to help families and their care team begin to judiciously use polygenic risk scores as part of preconception planning. We review the literature to develop tests for:

  • Chronic, debilitating diseases only
  • With reproducible results, in 3 or more peer reviewed publications 
  • With large study sizes, with 10,000 or more individuals 
  • Where the top percentiles of the distribution are at least 2.5 times the baseline risk of developing the disease. 

This curation is not a static process. We revisit it regularly, to update our panels as new information becomes available. Because the number of studies with polygenic risk scores is growing exponentially, we expect these scores to become even better over time.

What are polygenic risk scores?

Short answer: A way to estimate risk for a disease like type I diabetes based on the combined effect of many genetic variants. 

Long answer: Over the last decades, genomic datasets have exploded in size. Our understanding of genomics has taken a step forward with the development of polygenic risk scores. These prediction algorithms give us the ability to identify individuals at elevated risk of developing complex diseases like heart disease, breast cancer, and diabetes from genome sequences.

Larger genome-wide association studies lead to more accurate risk scores. Martin et al.

Polygenic risk scores are useful today because the genome-wide association studies from which they derive are no longer underpowered, as they were a decade ago. These genetic risk predictions depend upon aggregating many variants of small effect, and are often contrasted with the traditional clinical practice of testing for a few genetic variants of large effect, as is the case with high-penetrance Mendelian conditions. 

Can polygenic risk scores detect an increased genetic susceptibility to disease?

Short answer: Yes. Individuals with higher genetic risk scores develop disease at higher rates than individuals with average genetic risk. For example, individuals in the 90th percentile of polygenic risk for type I diabetes are at 8 times the average risk compared to the general population, and individuals in the 99th percentile of risk are at 30 times the average risk (Sharp).

Long answer: Genetic risk scores are the subject of extensive academic and clinical research. In the past year alone, hundreds of peer-reviewed research articles have evaluated genetic risk assessment for polygenic diseases. Today, for a number of diseases, polygenic risk scores are able to identify a substantially larger fraction of the population with comparable or greater disease risk than can be found using rare monogenic mutations (Khera, Wunnemann), are already in clinical use, and are improving every year (Mahajan, Zhang). 

For coronary artery disease, the PRS identified 8 percent of the population at greater than threefold increased risk, this prevalence is 20-fold higher than the carrier frequency of rare monogenic mutations conferring comparable risk (familial hypercholesterolemia, present in 0.4% of the population conferring up to a threefold increased risk). Khera et al. Nature Genetics
Genome-wide polygenic scores for common diseases identify individuals with risk equivalent to monogenic mutations. Khera et al.

Are polygenic risk scores already used in clinical settings?

Short answer: Yes. 

Long answer: Polygenic risk score based genetic testing has been rolled out by several commercial genetic testing laboratories as well as large academic medical centers like Stanford and the Broad Institute for coronary artery disease, breast cancer, and diabetes. Clinicians use results in conjunction with personal risk factors and family history, when establishing a patient’s risk management plan (medication changes, screening recommendations).

Are physicians already screening embryos for genes which predispose to adult onset conditions?

Short Answer: Yes.

Long Answer: Prospective parents already use carrier testing to prevent fully penetrant monogenic conditions like Tay-Sachs. They also screen embryos (use PGD) to select against lower penetrance adult-onset conditions like hereditary breast cancers.

Screening embryos, even for adult-onset disease and genes conferring an elevated predisposition, has been part of clinical practice since 2002. Today, during IVF, over 20% of embryo testing for single gene disorders (called “PGT-M”) screens for adult-onset disorders (Rechitsky). Couples elect to screen their embryos for adult-onset disorders because doing so can give their child a better life. A number of these disorders are cancer susceptibility syndromes — such as CHEK2, a gene variant which confers a 2-3 fold increased risk for breast cancer (Cybulski). This elevated risk is comparable to what is conferred by a polygenic risk score above the 97th percentile for breast cancer (Khera). 

Aren’t monogenic conditions much easier to predict from genetics, so shouldn’t we stick to those?

Short Answer: Monogenic testing alone misses the majority of individuals at elevated genetic risk. 

Long Answer: While identifying monogenic risk factors can be relevant to carriers, the vast majority of disease occurs without these rare mutations. Most common diseases have a genetic component and are polygenic in nature. The distinction between Mendelian conditions and polygenic traits is somewhat artificial, as genetic architecture is best thought of as a continuum. 

“Genetic architecture is often categorized as monogenic versus polygenic, meaning that one or many gene perturbations contribute to the occurrence of disease in an individual, respectively. For common adult-onset diseases, this dichotomous classification is a historical artefact derived from the available technology and study designs most suited to detect rare high-risk (monogenic; via family-based linkage analysis) versus common low-risk (polygenic; via GWAS) genetic risk loci. In reality, the genetic architecture of common adult-onset diseases is likely a continuum of common low-risk to rare high-risk genetic variants that can act cumulatively to drive overall risk in any single individual.” (Torkamani)

As an example, certain variants in the BRCA1 and BRCA2 genes have been found to significantly elevate Breast Cancer risk (Nelson, Amir), but these mutations are rare and only affect a few women per thousand in the general population (Offit, Ford, Whittemore). A polygenic risk score for breast cancer uses thousands of variants, and can identify ten times as many women at high-risk (Khera, Kuchenbaecker, Mavaddat) and is a useful addition to risk prediction.

Do embryos from the same set of prospective parents have different genetic risks?

Short answer: Yes. For instance, a couple could have one embryo in the 80th percentile (1.3% risk) and another in the 99th percentile (9.1% risk) for Type I Diabetes (Sharp 2019).

Long answer: Using data on thousands of siblings, where at least one sibling developed a disease, a polygenic risk score was able to identify the affected sibling 70-90% of the time across a variety of diseases, including breast cancer, heart attack and type I diabetes (Lello). 

Statistical analysis demonstrates that substantial—20-80%—relative risk reductions are attainable through polygenic embryo screening under certain conditions (which included an examination of the relative contributions of the variance explained by the score, the selection strategy, the number of embryos, the disease prevalence, and parental scores and disease status on the utility of screening) (Lencz). 

The relative risk reduction when the polygenic risk scores of the parents are known (Lencz)

The variance between siblings is smaller than the total variance observed across the entire population. However, there can still be substantial differences in genetic risk between sibling embryos. For some couples, and for some diseases, the difference in genetic susceptibility to disease will be significant enough for these couples to consider prioritization. 

The achievable risk reduction varies depending on the genetic architecture (the number and location of the variants) included in the genetic risk score in the disease of interest, the genomes of the parents, the number of embryos available, and the selection strategy employed. We share this genetic data with couples and their doctors so that they can make an informed decision. 

Do genetic tests in general, and polygenic risk scores in particular, work for people of non-European ancestry?

Short answer: Yes. That said, PRS is currently less sensitive in non-European ancestries due to a lack of data. But this is not a permanent barrier to equity. The portability of risk scores is an important limitation to overcome with more data — which Orchid, a minority-founded organization, intends to help collect.

Long answer: Statistical geneticists, both in industry and academia, are studying ways to improve polygenic score portability (Atkinson, Sirugo). The results to date offer concrete solutions: better genetic sampling of diverse populations and validation of genetic risk scores before applying them to new ancestries or geographic regions. Even accounting for the data and model limitations, some polygenic risk scores, such as type I diabetes and breast cancer remain useful across ancestries (Harrison, Shieh). It is an ongoing priority for us to generalize these scores and make them perform better among all ancestries. We’re excited to support and work with population geneticists on expanding these research models to diverse genetic datasets. PRS predictive abilities will continue to improve across all ancestries as genetic testing continues to become less expensive and more widely available.

The issue of biased genetic datasets is personal to members of our team - many of us are not European. Every area of medicine is affected by the issue of oversampling of Europeans relative to their share of world population. That doesn’t mean we stop using reference ranges, new drugs, or procedures entirely. It does mean that we seek to expand our tested populations. It is also worth acknowledging that the issue of ancestry has not been worked out entirely for monogenic disorders.

Does pleiotropy mean that reducing risk for disease A necessarily comes at the cost of increasing risk for disease B?

Short Answer: It’s unlikely. Embryos that are screened for diseases and subsequently selected for transfer all represent genetic makeups that could have resulted from a natural conception. If a woman prefers to implant a chromosomally normal embryo with a lower genetic predisposition to cancer, or any other disease, that is her choice and reproductive right.

Long Answer: It is possible for there to be no trade-off required between different disease risks, i.e an individual can be at low-risk for all conditions simultaneously. All embryos created from the same egg and sperm source are genetic siblings.  In an analysis of the variants included in polygenic risk scores, they have been found to be largely disjoint (with a few exceptions), which suggests that well-known examples of inverse correlation, such as malaria-risk and sickle-cell disease, are the exception (Yong).

Some situations do arise where mitigating risk for one disease trades off increased susceptibility towards another. In these cases, couples may prefer to weigh the two options and make their own informed decision in concert with their clinical team, as opposed to the choice being made for them by random chance.

How does Orchid curate conditions for inclusion in its test?

Short answer: We look for incurable, highly heritable diseases where the high end of the distribution has at least 2.5 times the baseline rate of developing a disease.

Long answer: Most diseases have a genetic component. For every disease, it is necessary to assess what percentage of a disease outcome can be explained by PRS. Some conditions are less heritable, so the ceiling for utility is lower. Other conditions have moderate to high heritability, and a polygenic risk score is able to capture a meaningful portion of the genetic component of risk. Recognizing this, we carefully curate genetic risk predictors for chronic diseases with high heritability and a PRS risk distribution in which the highest percentiles of risk are at least 2.5 times the baseline rate of developing the disease. We filter for reproducible results, with multiple peer-reviewed publications confirming the same result. We filter for studies with large cohort sizes, we don’t consider studies with fewer than 10,000 individuals.

What about lifestyle changes like nutrition and exercise instead of mitigating genetic risk?

Making lifestyle changes is not mutually exclusive with mitigating genetic risk. For some families, lifestyle changes may have a dominating effect on the health of their future child. For other families, a genetic predisposition may be the dominating factor. We support all spectrum of choices prospective parents select to protect their family's health.

The Future is Here: Get Access

Orchid’s Couple Report is available now.

You can join the waitlist here.

Orchid’s Couple Report is designed for all couples looking to go into their pregnancy prepared and informed about how to optimize health for their family. It’s a simple at-home saliva test that comes with three reports – one detailing a future child’s risk and one outlining each partner’s individual risk. You’re not alone – every report is reviewed by a board certified genetic counselor before delivery to you.  

Here’s to a future where every couple that wants to conceive, gets to do so with confidence.

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