Previde brings the next generation of risk analytics to your clinic to help identify a future child’s likelihood of inheriting over 1000 genetic diseases. Instead of reporting on the intermediate carrier status of prospective parents, we focus on the combined risk specific to ~5% of reproductive pairs. Our methodology expands the range of interpretable genetic variation, integrating sophisticated risk modeling and patient support seamlessly into your practice.
Our Virtual Progeny methodology digitally combines DNA information from two prospective parents to predict the genomes of a child they might conceive. We leverage this future child-based analysis to assist you and your clinical team in two important ways:
Our Genetic Counseling Team is ready to assist with results delivery and patient counseling. Our team is your team.
Carrier testing is the current paradigm for determining the preconception likelihood of transmitting heritable disease risk from prospective parents to future child. Carrier tests are unique among genetic tests in that a healthy adult is used as a proxy for a future child’s genetic disease risk. This disconnect between test subject and disease risk is problematic for several reasons:
We employ next generation sequencing to read the coding sequences of a targeted set of genes from two prospective genetic partners called “participants” in our process. Previde does not target a participant’s individual genetic information for interpretation. Instead, the sequence of each participant is digitally combined to enable a computational simulation of the genetics of reproduction. Thousands of virtual sperm or egg genomes, each with single copies of each gene sequence, are generated from each participant. Simulated male and female gametes are then joined together to produce novel “virtual progeny” genomes in proportions expected for the hypothetical offspring.
By focusing on the expected total amount of every functional gene product in each potential child, VPA provides a highly sensitive lens into potential disease-contributing genotypes. By integrating data across all virtual progeny, both disease and non-disease outcomes, we determine the likelihood and predicted frequency (if any) at which disease could be expressed. If disease risk is significantly higher than the background threshold level, the reproductive pair is flagged for further review.
To quantify the behavior of gene copies in VPA, our computational protocol assesses the impact of a variant – whether clinically classified or not – on the function of a single gene copy. We score each variant through a neural network analysis of multiple attributes, including clinical findings (when available), visibility in the clinical literature, population frequencies, protein structure and expression modeling, and observed evolutionary constraints. Confidence levels in each predictive attribute are calibrated on a variant and gene basis to generate a final dysfunction score along a continuum from fully functional (0.0) to fully dysfunctional (1.0).
The network is currently optimized for recessive disease analysis. Scores and data for over 2.4 million exome variants from diverse populations can be accessed through a public web browser. This research tool is designed for use by both healthcare professionals and genetics researchers.
Previde flags approximately 5% of reproductive pairs as at risk of transmitting one or more of the diseases on our panel. This relatively low number of positive outcomes reflects the reality that both chromosomes of a virtual progeny must contain potentially damaging variants in order to generate recessive disease risk.
This validated method allows us to calibrate our analysis to a very high level of sensitivity, while simultaneously reducing the number of intermediate positive results. To avoid false-positive computational calls, each flagged genotype is subjected to rigorous scientific and clinical review. The strength of the evidence of gene damage (VGD score) is considered in our final reproductive risk analysis.
Coverage of each gene on our panel includes coding regions and adjacent splice sites, which account for most, but not all identifiable disease mutations. Coding region deletions that exceed 50 bp and deletions with breakpoints outside coding region intervals are not expected to be detected faithfully, with the exception of specific deletions selected for detection by an alternate methodology.
Like other preconception screens, including carrier testing, Previde cannot predict either (1) de novo mutations that arise in the germinal cells of sequenced individuals or (2) genetic abnormalities that might occur in potential offspring during or after fertilization.
Previde identifies the risk for select inherited diseases associated with a specific set of genes and variants interrogated at the time of the analysis, using specific versions of our sequencing and analytic tools. There is no subsequent analysis beyond that date.
Some of the diseases and related disease symptoms screened by Previde may also be caused by genetic or non-genetic factors that are not covered by our panel. As a result, there will still be residual risk that a future child may develop one or more of the diseases included on our panel.
Previde was developed and validated by GenePeeks and is performed in our CLIA-certified laboratory. The performance characteristics and specifications of Previde were established pursuant to the requirements of the Clinical Laboratory Improvement Amendments (“CLIA”). As a prescriber-ordered, laboratory-developed test validated pursuant to CLIA, FDA submission is not required.