The Application of Knowledge Engineering via the Use of a Biomimetic Digital Twin Ecosystem, Phenotype-Driven Variant Analysis, and Exome Sequencing to Understand the Molecular Mechanisms of Disease.

Applied artificial intelligence, particularly large language models, in biomedical research is accelerating, but effective discovery and validation requires a toolset without limitations or bias. On January 30, 2023, the National Academies of Sciences, Engineering, and Medicine (NAS) appointed an ad hoc committee to identify the needs and opportunities to advance the mathematical, statistical, and computational foundations of digital twins in applications across science, medicine, engineering, and society. On December 15, 2023, the NAS released a 164-page report, "Foundational Research Gaps and Future Directions for Digital Twins." This report described the importance of using digital twins in biomedical research. The current study was designed to develop an innovative method that incorporated phenotype-ranking algorithms with knowledge engineering via a biomimetic digital twin ecosystem. This ecosystem applied real-world reasoning principles to nonnormalized, raw data to identify hidden or "dark" data. Clinical exome sequencing study on patients with endometriosis indicated four variants of unknown clinical significance potentially associated with endometriosis-related disorders in nearly all patients analyzed. One variant of unknown clinical significance was identified in all patient samples and could be a biomarker for diagnostics. To the best of our knowledge, this is the first study to incorporate the recommendations of the NAS to biomedical research. This method can be used to understand the mechanisms of any disease, for virtual clinical trials, and to identify effective new therapies.

Blastocoel fluid from differentiated blastocysts harbors embryonic genomic material capable of a whole-genome deoxyribonucleic acid amplification and comprehensive chromosome microarray analysis.

OBJECTIVE: To obtain embryonic molecular karyotypes from genomic DNA (deoxyribonucleic acid) isolated from blastocoel fluid (BF) and to compare these karyotypes with the karyotypes from the remaining inner cell mass (ICM) and trophectoderm (TE) of the blastocyst. DESIGN: Prospective cohort study. SETTING: Academic center and preimplantation genetics laboratory. PATIENT(S): Ninety-six donated cryopreserved embryos. INTERVENTION(S): Embryo biopsy, BF aspiration, DNA analysis using a comparative genomic hybridization microarray (aCGH). MAIN OUTCOME MEASURE(S): The aCGH of a single blastomere, BF-DNA, and ICM-TE. RESULT(S): The BF-DNA samples resulted in a successful aCGH in 63% of cases. Discordance in karyotypes was found between the BF-DNA and the ICM-TE in 52% of cases. A total of 70% of aneusomic (mosaicism), cleavage-stage embryos differentiated into euploid blastocysts. Probabilities for diagnostic accuracy were calculated and demonstrated the following: sensitivity of 0.88 (95% confidence interval [CI]: 0.62-0.98); specificity of 0.55 (95% CI: 0.39-0.70); positive predictive value of 0.41 (95% CI: 0.25-0.60); negative predictive value of 0.92 (95% CI: 0.75-0.99). CONCLUSION(S): Genomic DNA from the BF can be amplified and characterized by comprehensive chromosome microarrays. The results demonstrated that aneusomic cleavage-stage embryos differentiated into euploid blastocysts, possibly using a mechanism that marginalizes aneuploid nuclei into the blastocoel cavity. In addition, owing to the high discordance between the karyotypes obtained from the BF-DNA and the ICM-TE, using BF-DNA for preimplantation genetic testing is not yet advised.

Two different microarray technologies for preimplantation genetic diagnosis and screening, due to reciprocal translocation imbalances, demonstrate equivalent euploidy and clinical pregnancy rates.

PURPOSE: To compare single nucleotide polymorphism (SNP) and comparative genomic hybridization (aCGH) microarray platforms to evaluate embryos for parental translocation imbalances and aneuploidy. METHODS: A retrospective review of preimplantation genetic diagnosis and screening (PGD/PGS) results of 498 embryos from 63 couples undergoing 75 in vitro fertilization cycles due to parental carriers of a reciprocal translocation. RESULTS: There was no significant difference between SNP and aCGH microarrays when comparing the prevalence of embryos that were euploid with no translocation imbalance, euploidy with a parental translocation imbalance or aneuploid with or without the parental chromosome imbalance. The clinical pregnancy rates were also equivalent for SNP (60 %) versus aCGH (65 %) microarrays. Of 498 diagnosed embryos, 45 % (226/498) were chromosomally normal without translocation errors or aneuploidy, 22 % (112/498) were euploid but had a parentally derived unbalanced chromosomal segregant, 8 % (42/498) harbored both a translocation imbalance and aneuploidy and 24 % (118/498) of embryos were genetically balanced for the parental reciprocal translocation but were aneuploid for other chromosomes. The overall clinical pregnancy rate per IVF cycle following SNP or aCGH microarray analysis was 61 % and was higher if the biopsy was done on blastocysts (65 %) versus cleavage stage embryos (59 %), although not statistically significant. CONCLUSIONS: SNP or aCGH microarray technologies demonstrate equivalent clinical findings that maximize the pregnancy potential in patients with known parental reciprocal chromosomal translocations.