Precision Medicine: What Challenges are We Facing?

Meng

Genomics, Proteomics &Amp; Bioinformatics

et al. 2018

The isolated type of orofacial cleft, termed non-syndromic cleft lip with or without cleft palate (NSCL/P), is the second most common birth defect in China, with Asians having the highest incidence in the world. NSCL/P involves multiple genes and complex interactions between genetic and environmental factors, imposing difficulty for the genetic assessment of the unborn fetus carrying multiple NSCL/P-susceptible variants. Although genome-wide association studies (GWAS) have uncovered dozens of single nucleotide polymorphism (SNP) loci in different ethnic populations, the genetic diagnostic effectiveness of these SNPs requires further experimental validation in Chinese populations before a diagnostic panel or a predictive model covering multiple SNPs can be built. In this study, we collected blood samples from control and NSCL/P infants in Han and Uyghur Chinese populations to validate the diagnostic effectiveness of 43 candidate SNPs previously detected using GWAS. We then built predictive models with the validated SNPs using different machine learning algorithms and evaluated their prediction performance. Our results showed that logistic regression had the best performance for risk assessment according to the area under curve. Notably, defective variants in MTHFR and RBP4, two genes involved in folic acid and vitamin A biosynthesis, were found to have high contributions to NSCL/P incidence based on feature importance evaluation with logistic regression. This is consistent with the notion that folic acid and vitamin A are both essential nutritional supplements for pregnant women to reduce the risk of conceiving an NSCL/P baby. Moreover, we observed a lower predictive power in Uyghur than in Han cases, likely due to differences in genetic background between these two ethnic populations. Thus, our study highlights the urgency to generate the HapMap for Uyghur population and perform resequencing-based screening of Uyghur-specific NSCL/P markers.

Section: Discussionmentioning

confidence: 99%

Machine Learning Models for Genetic Risk Assessment of Infants with Non-Syndromic Orofacial Cleft

Meng

Genomics, Proteomics &Amp; Bioinformatics

et al. 2018

“…As the field of precision medicine expands, researchers will be collecting, organizing and analyzing burgeoning quantities of data; more efficient database and analytical techniques will be required to utilize all of this information [ 16 , 33 , 34 , 35 ]. As this knowledge base is used to develop individual diagnostics, we must be able to properly align individuals and subgroups with the proper tests.…”

Section: Challenges Facing Precision Medicinementioning

confidence: 99%

Precision Medicine: Steps along the Road to Combat Human Cancer

Nassar

Raddassi

Ubhi³

et al. 2020

Cells

The diagnosis and treatment of diseases such as cancer is becoming more accurate and specialized with the advent of precision medicine techniques, research and treatments. Reaching down to the cellular and even sub-cellular level, diagnostic tests can pinpoint specific, individual information from each patient, and guide providers to a more accurate plan of treatment. With this advanced knowledge, researchers and providers can better gauge the effectiveness of drugs, radiation, and other therapies, which is bound to lead to a more accurate, if not more positive, prognosis. As precision medicine becomes more established, new techniques, equipment, materials and testing methods will be required. Herein, we will examine the recent innovations in assays, devices and software, along with next generation sequencing in genomics diagnostics which are in use or are being developed for personalized medicine. So as to avoid duplication and produce the fullest possible benefit, all involved must be strongly encouraged to collaborate, across national borders, public and private sectors, science, medicine and academia alike. In this paper we will offer recommendations for tools, research and development, along with ideas for implementation. We plan to begin with discussion of the lessons learned to date, and the current research on pharmacogenomics. Given the steady stream of advances in imaging mass spectrometry and nanoLC-MS/MS, and use of genomic, proteomic and metabolomics biomarkers to distinguish healthy tissue from diseased cells, there is great potential to utilize pharmacogenomics to tailor a drug or drugs to a particular cohort of patients. Such efforts very well may bring increased hope for small groups of non-responders and those who have demonstrated adverse reactions to current treatments.

“… 13 These improvements led to the advent of a new field in diagnosing and treating diseases as well as reducing healthcare costs. 14 – 16 This new field is called precision medicine ( Figure 1 ). A simple definition for precision medicine is a treatment designed for diseases that, unlike the conventional procedures, do not prescribe a common treatment for all people with the same disease.…”

Section: Introductionmentioning

confidence: 99%

<p>Genomics and Transcriptomics: The Powerful Technologies in Precision Medicine</p>

Khodadadian¹,

Darzi²,

Haghi-Daredeh³

et al. 2020

IJGM

In a clinical trial, people with the same disease can show different responses after treatment with the same drug and exactly under the same conditions. Some of them may improve, some may not show any response, and occasionally side effects may be observed. In other words, people with the same disease process under the same therapeutic conditions may have different responses. Today, some diseases are resistant to conventional (standard) treatment procedures. Why do people with the same disease show different responses to the treatment with the same drug? This is primarily due to differences in molecular pathways (especially genetic variations) associated with the disease. On the other hand, designing and delivery of a new drug is a time-consuming and costly process, so any mistake in any stage of this process can have irreparable consequences for pharmaceutical companies and consumer patients. Therefore, we can achieve more accurate and reliable treatments by acquiring precise insight into different aspects of precision medicine including genomics and transcriptomics. The aim of this paper is to address the role of genomics and transcriptomics in precision medicine.