What are new technologies for genetic diagnosis?

The significant advance in technological development has brought with it an essential and profound knowledge of the genetic and molecular bases of a human being. For example, the grounds on which knowledge about clinical genetics and the relationships between genetic causes and the development of hereditary diseases were based have been modified in a transcendental way. In this area, discoveries in clinical genetics have been oriented towards concepts of genetic and phenotypic heterogeneity so that the same hereditary pathology is currently known to be caused by alterations in different genes and, simultaneously, variants in the same gene could trigger highly diverse phenotypes.

This same deepening of genetic knowledge has identified new areas of study that were previously unknown. the individual’s genetic profiles influence the final pharmacological response regarding safety and effectiveness. 

Additionally, the biological substrate of genetic studies has evolved along with scientific progress. 

In terms of cost-effectiveness, our efforts should be directed towards the early diagnosis of diseases with high genetic heterogeneity and the rapid detection of recurrences in neoplastic diseases. Both situations increase the chances of success of pharmacological treatment for the patient and her family and therefore contribute to increasing the patient’s survival and improving her quality of life.

Technological development

the significant progress of technological development has allowed profound knowledge about the genetic and molecular human beings.

This deepening in genetic knowledge has identified new fields of study previously unknown. 

In terms of cost-effectiveness, we must direct our efforts toward precocious high heterogeneity genetic disease diagnosis and the quickest ability to detect tumoural recurrences. Both situations increase the chances of the patient’s or his family’s treatment effectiveness, contributing to patient survival and improving their quality of life.


 The knowledge of the human genome has made it possible to determine the genetic and molecular bases of many diseases. Genetics is one of the scientific disciplines that has contributed the most to understanding the aetiology of conditions, thereby opening the door to finding the means for their prevention, diagnosis and treatment. For this reason, it is now an essential tool for the correct management of the patient in any of the medical disciplines, and the work of the clinical geneticist and bioinformatician has become definitive in differential diagnoses for the right prescription of treatment.


Clinical genetics started from the study of monogenic diseases, where a cause-effect relationship is established between altering a particular gene and a specific disease. For example, about 8,000 genetic diseases are listed in OMIM ( Online Mendelian inheritance of Man ), which have an inheritance pattern compatible with transmission according to Mendelian or mitochondrial laws. Of more than half (about 4,500 diseases), the molecular basis and the description of the phenotype are already known, but there remains approximately 50% of diseases where this relationship is still unknown. 

In this sense, the vision of the classical genetic study has also been modified because the number of candidate genes to be analysed for the same phenotype has been considerably increased. This new approach to genetic studies entails an economic impact on the cost and time invested in them. 

For this reason, this genetic and clinical heterogeneity, traditionally and until the appearance of technologies that allow the multiple studies of genes, such as massive sequencing technologies, has been and is one of the main problems when making a genetic diagnosis.

Advances in technological knowledge have led to the improvement, simplification and lowering of prices of critical technologies, allowing this type of disease to no longer be an intractable challenge in actual clinical practice and to move from the side of research to the side of routine clinical practice. 

The problem that arose after having the unlimited capacity to analyse genes was the problem of the cost of storing the generated data and especially the analysis and interpretation of the enormous flow of genomic sequence data, which is constantly increasing at a dizzying rate. And requires complex and highly specialised computer processing. This new situation means that geneticists are not only part of the diagnostic teams but also a new type of professional: clinical bioinformaticians. These new professionals require an exhaustive knowledge of the operation of the new sequencing platforms, as well as of what we today call “Systems Biology” 2, to advance understanding of the human genome and progress towards more precise diagnosis, earlier prognosis, and personalised treatment. The development of algorithms using bioinformatic tools makes it possible to process substantial genomic databases generated with massive sequencing platforms and integrate data from other media or other diagnostic disciplines such as biochemistry, immunology, imaging, etc.; 

Due to all the previous evolution, we find that, increasingly, the choice of the ideal pharmacological treatment, as well as the most appropriate dose, takes into account the genetic profile of each patient. 

If we talk about cancer, early tumour detection, diagnosis confirmation, prognosis and prediction of therapeutic response, as well as disease and recurrence monitoring, are based on technological advances such as massive sequencing and digital droplet PCR ( ddPCR) in both tumour and liquid biopsy, which provide new benefits such as precision, efficacy, safety and speed. This can allow us to intervene even before the symptoms develop and act on the general health of the patient, reaching the so-called Precision Medicine 3understood as the design and application of prevention, diagnosis and treatment interventions more adapted to the genetic substrate of each patient and the molecular profile of each disease.

However, the question of efficiently safeguarding data remains again. Currently, we have variants of unknown significance, which have been reclassified as pathogenic when published clinical evidence, so although a diagnosis made today is correct, it would be necessary to incorporate analysis and re-analysis mechanisms at the time of diagnosis—report variants. 

The new way of discovering drugs is based on directing the use of drugs to specific subgroups of patients in which it is possible to predict both the efficacy of the treatment and its safety. Since it is known that not all patients respond to or tolerate the same treatment, in the same way, not the same pathological entity presents or progresses in the same way in all patients.

Shailendra Kumar

DA50+Guest Post sites

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