The impact and future of artificial intelligence in medical genetics and molecular medicine: an ongoing revolution.

Artificial intelligence (AI) platforms have emerged as pivotal tools in genetics and molecular medicine, as in many other fields. The growth in patient data, identification of new diseases and phenotypes, discovery of new intracellular pathways, availability of greater sets of omics data, and the need to continuously analyse them have led to the development of new AI platforms. AI continues to weave its way into the fabric of genetics with the potential to unlock new discoveries and enhance patient care. This technology is setting the stage for breakthroughs across various domains, including dysmorphology, rare hereditary diseases, cancers, clinical microbiomics, the investigation of zoonotic diseases, omics studies in all medical disciplines. AI's role in facilitating a deeper understanding of these areas heralds a new era of personalised medicine, where treatments and diagnoses are tailored to the individual's molecular features, offering a more precise approach to combating genetic or acquired disorders. The significance of these AI platforms is growing as they assist healthcare professionals in the diagnostic and treatment processes, marking a pivotal shift towards more informed, efficient, and effective medical practice. In this review, we will explore the range of AI tools available and show how they have become vital in various sectors of genomic research supporting clinical decisions.

Homozygous missense variants in YKT6 result in loss of function and are associated with developmental delay, with or without severe infantile liver disease and risk for hepatocellular carcinoma.

PURPOSE: YKT6 plays important roles in multiple intracellular vesicle trafficking events but has not been associated with Mendelian diseases. METHODS: We report 3 unrelated individuals with rare homozygous missense variants in YKT6 who exhibited neurological disease with or without a progressive infantile liver disease. We modeled the variants in Drosophila. We generated wild-type and variant genomic rescue constructs of the fly ortholog dYkt6 and compared their ability in rescuing the loss-of-function phenotypes in mutant flies. We also generated a dYkt6KozakGAL4 allele to assess the expression pattern of dYkt6. RESULTS: Two individuals are homozygous for YKT6 [NM_006555.3:c.554A>G p.(Tyr185Cys)] and exhibited normal prenatal course followed by failure to thrive, developmental delay, and progressive liver disease. Haplotype analysis identified a shared homozygous region flanking the variant, suggesting a common ancestry. The third individual is homozygous for YKT6 [NM_006555.3:c.191A>G p.(Tyr64Cys)] and exhibited neurodevelopmental disorders and optic atrophy. Fly dYkt6 is essential and is expressed in the fat body (analogous to liver) and central nervous system. Wild-type genomic rescue constructs can rescue the lethality and autophagic flux defects, whereas the variants are less efficient in rescuing the phenotypes. CONCLUSION: The YKT6 variants are partial loss-of-function alleles, and the p.(Tyr185Cys) is more severe than p.(Tyr64Cys).

Genotype and Phenotype Correlation of Patients with Osteogenesis Imperfecta.

Osteogenesis imperfecta (OI) is the most common inherited connective tissue disease of the bone, characterized by recurrent fractures and deformities. In patients displaying the OI phenotype, genotype-phenotype correlation is used to screen multiple genes swiftly, identify new variants, and distinguish between differential diagnoses and mild subtypes. This study evaluated variants identified through next-generation sequencing in 58 patients with clinical characteristics indicative of OI. The cohort included 18 adults, 37 children, and 3 fetuses. Clinical classification revealed 25 patients as OI type I, three patients as OI type II, 18 as OI type III, and 10 as OI type IV. Fifteen variants in COL1A1 were detected in 19 patients, 9 variants in COL1A2 (n = 19), 5 variants in LEPRE1/P3H1 (n = 7), 3 variants in FKBP10 (n = 4), 3 variants in SERPINH1 (n = 2), 1 variant in IFITM5 (n = 1), and 1 variant in PLS3 (n = 1). In total, 37 variants (18 pathogenic, 14 likely pathogenic, and 5 variants of uncertain significance), including 16 novel variants, were identified in 43 (37 probands, 6 family members) of the 58 patients analyzed. This study highlights the efficacy of panel testing in the molecular diagnosis of OI, the significance of the next-generation sequencing technique, and the importance of genotype-phenotype correlation.

CC2D1A causes ciliopathy, intellectual disability, heterotaxy, renal dysplasia, and abnormal CSF flow.

Intellectual and developmental disabilities result from abnormal nervous system development. Over a 1,000 genes have been associated with intellectual and developmental disabilities, driving continued efforts toward dissecting variant functionality to enhance our understanding of the disease mechanism. This report identified two novel variants in CC2D1A in a cohort of four patients from two unrelated families. We used multiple model systems for functional analysis, including Xenopus, Drosophila, and patient-derived fibroblasts. Our experiments revealed that cc2d1a is expressed explicitly in a spectrum of ciliated tissues, including the left-right organizer, epidermis, pronephric duct, nephrostomes, and ventricular zone of the brain. In line with this expression pattern, loss of cc2d1a led to cardiac heterotaxy, cystic kidneys, and abnormal CSF circulation via defective ciliogenesis. Interestingly, when we analyzed brain development, mutant tadpoles showed abnormal CSF circulation only in the midbrain region, suggesting abnormal local CSF flow. Furthermore, our analysis of the patient-derived fibroblasts confirmed defective ciliogenesis, further supporting our observations. In summary, we revealed novel insight into the role of CC2D1A by establishing its new critical role in ciliogenesis and CSF circulation.