Advances in Genomic Discovery and Implications for Personalized Prevention and Medicine: Estonia as Example

Genetical Signature-An Example of a Personalized Skin Aging Investigation with Possible Implementation in Clinical Practice

We conducted a research study to create the groundwork for personalized solutions within a skin aging segment. This test utilizes genetic and general laboratory data to predict individual susceptibility to weak skin characteristics, leveraging the research on genetic polymorphisms related to skin functional properties. A cross-sectional study was conducted in a collaboration between the Private Clinic Medicina Practica Laboratory (Vilnius, Lithuania) and the Public Institution Lithuanian University of Health Sciences (Kaunas, Lithuania). A total of 370 participants agreed to participate in the project. The median age of the respondents was 40, with a range of 19 to 74 years. After the literature search, we selected 15 polymorphisms of the genes related to skin aging, which were subsequently categorized in terms of different skin functions: SOD2 (rs4880), GPX1 (rs1050450), NQO1 (rs1800566), CAT (rs1001179), TYR (rs1126809), SLC45A2 (rs26722), SLC45A2 (rs16891982), MMP1 (rs1799750), ELN (rs7787362), COL1A1 (rs1800012), AHR (rs2066853), IL6 (rs1800795), IL1Beta (rs1143634), TNF-α (rs1800629), and AQP3 (rs17553719). RT genotyping, blood count, and immunochemistry results were analyzed using statistical methods. The obtained results show significant associations between genotyping models and routine blood screens. These findings demonstrate the personalized medicine approach for the aging segment and further add to the growing literature. Further investigation is warranted to fully understand the complex interplay between genetic factors, environmental influences, and skin aging.

Common clinical blood and urine biomarkers for ischemic stroke: an Estonian Electronic Health Records database study

BACKGROUND

Ischemic stroke (IS) is a major health risk without generally usable effective measures of primary prevention. Early warning signals that are easy to detect and widely available can save lives. Estonia has one nation-wide Electronic Health Record (EHR) database for the storage of medical information of patients from hospitals and primary care providers.

METHODS

We extracted structured and unstructured data from the EHRs of participants of the Estonian Biobank (EstBB) and evaluated different formats of input data to understand how this continuously growing dataset should be prepared for best prediction. The utility of the EHR database for finding blood- and urine-based biomarkers for IS was demonstrated by applying different analytical and machine learning (ML) methods.

RESULTS

Several early trends in common clinical laboratory parameter changes (set of red blood indices, lymphocyte/neutrophil ratio, etc.) were established for IS prediction. The developed ML models predicted the future occurrence of IS with very high accuracy and Random Forests was proved as the most applicable method to EHR data.

CONCLUSIONS

We conclude that the EHR database and the risk factors uncovered are valuable resources in screening the population for risk of IS as well as constructing disease risk scores and refining prediction models for IS by ML.

The implementation of large-scale genomic screening or diagnostic programmes: A rapid evidence review

Genomic healthcare programmes, both in a research and clinical context, have demonstrated a pivotal opportunity to prevent, diagnose, and treat rare diseases. However, implementation factors could increase overall costs and affect uptake. As well, uncertainties remain regarding effective training, guidelines and legislation. The purpose of this rapid evidence review was to draw together the available global evidence on the implementation of genomic testing programmes, particularly on population-based screening and diagnostic programmes implemented at the national level, to understand the range of factors influencing implementation. This review involved a search of terms related to genomics, implementation and health care. The search was limited to peer-reviewed articles published between 2017-2022 and found in five databases. The review included thirty articles drawing on sixteen countries. A wide range of factors was cited as critical to the successful implementation of genomics programmes. These included having policy frameworks, regulations, guidelines; clinical decision support tools; access to genetic counselling; and education and training for healthcare staff. The high costs of implementing and integrating genomics into healthcare were also often barriers to stakeholders. National genomics programmes are complex and require the generation of evidence and addressing implementation challenges. The findings from this review highlight that there is a strong emphasis on addressing genomic education and engagement among varied stakeholders, including the general public, policymakers, and governments. Articles also emphasised the development of appropriate policies and regulatory frameworks to govern genomic healthcare, with a focus on legislation that regulates the collection, storage, and sharing of personal genomic data.

Population Screening in Health Systems

Applications of genomics to population screening are expanding in the United States and internationally. Many of these programs are being implemented in the context of healthcare systems, mostly in a clinical research setting, but there are some emerging examples of clinical models. This review examines these genomic population screening programs to identify common features and differences in screened conditions, genomic technology employed, approach to results disclosure, health outcomes, financial models, and sustainability. The diversity of approaches provides opportunities to learn and better understand the optimal approach to implementation based on the contextual setting. Expected final online publication date for the Annual Review of Genomics and Human Genetics, Volume 23 is October 2022. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.