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.

Evaluation of chromosomal abnormalities in the postnatal cohort: A single-center study on 14,242 patients.

BACKGROUND AND AIM: Chromosomal analysis is a laboratory technique used to examine the chromosomes of an individual, offering insights into chromosome numbers, structures, and arrangements to diagnose and comprehend genetic diseases. This retrospective study provides a comprehensive understanding of the distribution by indications in a large cohort of 14,242 patients and the frequency of chromosomal abnormalities in different clinical populations. METHOD: The study examined various indications for karyotype evaluation, with recurrent pregnancy loss being the most common indication, followed by intellectual disability, dysmorphic features, congenital anomalies, and developmental delay. RESULTS: The overall chromosomal abnormality rate was found to be 5.4%, with numerical abnormalities accounting for the majority of cases (61.7%). Trisomies, particularly trisomy 21, were the most frequent numerical abnormalities. In terms of structural abnormalities, inversions and translocations were the most commonly identified. The rates of chromosomal anomalies varied in specific indications such as amenorrhea, disorders of sex development, and Turner syndrome. The study also highlighted significant differences between males and females in the presence of chromosomal abnormalities across certain indications. Males exhibited a higher incidence of chromosomal abnormalities in cases of Down syndrome and infertility, whereas females showed higher abnormalities in terms of recurrent pregnancy loss. CONCLUSION: While this study provides valuable insights into the frequency and distribution of chromosomal abnormalities, it has limitations, including its retrospective design and reliance on data from a single medical genetics department. Nevertheless, the findings emphasize the importance of karyotype analysis in diagnosing chromosomal disorders and providing appropriate management, while also pointing to potential gender-related variations in chromosomal abnormalities that warrant further investigation.

A Case Series of Three Patients with Cleidocranial Dysplasia: Clinical Presentation and Diagnostic Considerations.

Cleidocranial dysplasia (CCD) is a rare genetic condition that affects the bones and teeth. In our study, we presented three cases of CCD, including one with a new mutation and two with a family history. Case 1 had a unique heterozygous frameshift mutation (NM_001015051,c.762del, p.(Ser256Valfs*2)), while Case 2 and her brother (Case 3) had a common pathogenic missense mutation (NM_001015051,c.674G, p.Arg225Gln), which was also found in their father. The mutation in Case 1 was not reported before. Interestingly, the symptoms in Case 1, with the new mutation, were less severe than the other cases and the previous reports.

Diagnosing Alström syndrome in a patient followed up with syndromic obesity for years.

Alström syndrome (AS) is a rare autosomal recessive monogenic disorder caused by mutations of the Alström syndrome 1 (ALMS1) gene, located on chromosome 2p13. It is a progressive multisystemic disease characterized mostly by obesity, sensorineural hearing loss, visual impairments, cardiomyopathy, insulin resistance and/or type 2 diabetes mellitus (T2DM), metabolic dysfunctions, non-alcoholic fatty liver disease, and chronic progressive kidney disease. Generally, the first clinical symptoms of the disease appear in the first years of life with a major variation of onset age. In this study, we aimed to examine the molecular diagnosis of a 6-year-old patient with suspected AS clinical symptoms. After applying clinical exome sequencing (CES) in the patient we found a homozygous deletion in exon 8 at the ALMS1 gene (c.2311_2312del). We identified a homozygous frameshift mutation. The reported variant was pathogenic according to the criteria of the American College of Medical Genetics and Genomics (ACMG). Thus, the patient was diagnosed with AS as a result of the combined clinical phenotype and genetic tests results. We hope the variant we found can expand the spectrum of ALMS1 variants in AS.