The rise of the genome and personalised medicine

Role of high-dose amoxicillin dual therapy for Helicobacter pylori eradication in an Irish cohort: A prospective study

Helicobacter pylori (H. pylori) infections may cause chronic gastritis, peptic ulcer disease, gastric cancers, and other conditions outside of the gastrointestinal tract. Hence, it is important to diagnose and treat it early. H. pylori is resistant to certain drugs in traditional eradication therapy, so alternative therapy protocols are needed, such as high-dose amoxicillin dual therapy (HDADT). This article aims to comment on a recent paper by Costigan et al in the World Journal of Clinical Cases. In this study, the authors recruited 139 patients diagnosed with H. pylori, all treated with HDADT. Of these, 93 were treatment-naïve and 46 had received at least one alternative treatment in the past. Four weeks after the end of the treatment, the urea breath test was administered to estimate the eradication rate. The total eradication rate was 56% (78/139), 62% for the treatment-naïve arm and 43% for the previous treatment arm, thus indicating a lower success rate for the arm that had previously received a different treatment regimen. In conclusion, a therapeutic approach with first-line HDADT may potentially be a better treatment, but the results are not sufficient to recommend the use of this regimen in a country with high levels of dual resistance.

The Journey to Improve the College of American Pathologists Cancer Biomarker Reporting Protocols

CONTEXT.—

Biomarker reporting has increasingly become a key component of pathology reporting, providing diagnostic, prognostic, and actionable therapeutic data for patient care.

OBJECTIVE.—

To expand and improve the College of American Pathologists (CAP) biomarker protocols.

DESIGN.—

We surveyed CAP members to better understand the limitations they experienced when reporting cancer biomarker results. A Biomarker Workgroup reviewed the survey results and developed a strategy to improve and standardize biomarker reporting. Drafts of new and revised biomarker protocols were reviewed in both print and electronic template formats during interactive webinars presented to the CAP House of Delegates. Feedback was collected, and appropriate revisions were made to finalize the protocols.

RESULTS.—

The first phase of the CAP Biomarker Workgroup saw the development of (1) a new stand-alone general Immunohistochemistry Biomarker Protocol that includes reporting for ER (estrogen receptor), PR (progesterone receptor), Ki-67, HER2 (human epidermal growth factor receptor 2), PD-L1 (programmed death ligand-1), and mismatch repair; (2) a new Head and Neck Biomarker Protocol that updates the prior 2017 paper-only version into an electronic template, adding new diagnostic and theranostic markers; (3) a major revision to the Lung Biomarker Protocol to streamline it and add in pan-cancer markers; and (4) a revision to the Colon and Rectum Biomarker Protocol to add HER2 reporting.

CONCLUSIONS.—

We have taken a multipronged approach to improving biomarker reporting in the CAP cancer protocols. We continue to review current biomarker reporting protocols to reduce and eliminate unnecessary methodologic details and update with new markers as needed. The biomarker templates will serve as standardized modular units that can be inserted into cancer-reporting protocols.

Impact of prenatal genomics on clinical genetics practice

Genetic testing for prenatal diagnosis in the pre-genomic era primarily focused on detecting common fetal aneuploidies, using methods that combine maternal factors and imaging findings. The genomic era, ushered in by the emergence of new technologies like chromosomal microarray analysis and next-generation sequencing, has transformed prenatal diagnosis. These new tools enable screening and testing for a broad spectrum of genetic conditions, from chromosomal to monogenic disorders, and significantly enhance diagnostic precision and efficacy. This chapter reviews the transition from traditional karyotyping to comprehensive sequencing-based genomic analyses. We discuss both the clinical utility and the challenges of integrating prenatal exome and genome sequencing into prenatal care and underscore the need for ethical frameworks, improved prenatal phenotypic characterization, and global collaboration to further advance the field.

Genetic investigations in cerebral palsy

The original description of cerebral palsy (CP) contained case histories suggesting that perinatal environmental stressors resulted in brain injury and neurodevelopmental disability. While there are clear associations between environmental impact on brain development and CP, recent studies indicate an 11% to 40% incidence of monogenic conditions in patients given a diagnosis of CP. A genetic diagnosis supports the delivery of personalized medicine. In this review, we describe how the Wnt pathway exemplifies our understanding of pathophysiology related to a gene variant (CTNNB1) found in some children diagnosed with CP. We cover studies undertaken to establish the baseline prevalence of monogenic conditions in populations attending CP clinics. We list factors indicating increased likelihood of a genomic diagnosis; and we highlight the need for a comprehensive, accurate, genotype-phenotype reference data set to aid variant interpretation in CP cohorts. We also consider the wider societal implications of genomic management of CP including significance of the diagnostic label, benefits and pitfalls of a genetic diagnosis, logistics, and cost.

Resolving unsolved whole-genome sequencing data in paediatric neurological disorders: a cohort study

OBJECTIVE

To resolve unsolved whole-genome sequencing (WGS) data in individuals with paediatric neurological disorders.

DESIGN

A cohort study method using updated bioinformatic tools, new analysis targets, clinical information and literature databases was employed to reanalyse existing unsolved genome data.

PARTICIPANTS

From January 2016 to September 2023, a total of 615 individuals who aged under 18 years old, exhibited neurological disorders and received singleton WGS were recruited. 364 cases were unsolved during initial WGS analysis, in which 102 consented to reanalyse existing singleton WGS data.

RESULTS

Median duration for reanalysis after initial negative WGS results was 2 years and 4 months. The diagnostic yield was 29 of 102 individuals (28.4%) through reanalysis. New disease gene discovery and new target acquisitions contributed to 13 of 29 solved cases (44.8%). The reasons of non-detected causative variants during initial WGS analysis were variant reclassification in 9 individuals (31%), analytical issue in 9 (31%), new emerging disease-gene association in 8 (27.6%) and clinical update in 3 (10.3%). The 29 new diagnoses increased the cumulative diagnostic yield of clinical WGS in the entire study cohort to 45.5% after reanalysis.

CONCLUSIONS

Unsolved paediatric WGS individuals with neurological disorders could obtain molecular diagnoses through reanalysis within a timeframe of 2-2.5 years. New disease gene, structural variations and deep intronic splice variants make a significant contribution to diagnostic yield. This approach can provide precise genetic counselling to positive reanalysis results and end a diagnostic odyssey.

Benefit-Sharing by Design: A Call to Action for Human Genomics Research

The ethical standards for the responsible conduct of human research have come a long way; however, concerns surrounding equity remain in human genetics and genomics research. Addressing these concerns will help society realize the full potential of human genomics research. One outstanding concern is the fair and equitable sharing of benefits from research on human participants. Several international bodies have recognized that benefit-sharing can be an effective tool for ethical research conduct, but international laws, including the Convention on Biological Diversity and its Nagoya Protocol on Access and Benefit-Sharing, explicitly exclude human genetic and genomic resources. These agreements face significant challenges that must be considered and anticipated if similar principles are applied in human genomics research. We propose that benefit-sharing from human genomics research can be a bottom-up effort and embedded into the existing research process. We propose the development of a "benefit-sharing by design" framework to address concerns of fairness and equity in the use of human genomic resources and samples and to learn from the aspirations and decade of implementation of the Nagoya Protocol.

A panel sequencing dataset of peripheral blood gene variations in pan-cancer

Circulating cell-free DNA (cfDNA) in the peripheral blood is a promising biomarker for cancer diagnosis and prognosis. Somatic mutations identified in cancers have been used to detect therapeutic targets for clinical transformation and individualize drug selection, while germline variants can predict a patient's risk of developing cancer and drug sensitivity. However, no platform has been developed to analyze, calculate, integrate, and friendly visualize these pan-cancer cfDNA mutations deeply. In this work, we performed panel sequencing encompassing 1,115 cancer-related genes across 16,659 cancer patients, spanning 27 cancer types. We detected 496 germline variants in leukocytes and 11,232 somatic mutations in the cfDNA of all patients. CPGV (Cancer Peripheral blood Gene Variations), a database constructed from this dataset, is the first pan-cancer cfDNA database that encompasses somatic mutations, germline variants, and further comparative analyses of mutations across different cancer types. It bears great promise to serve as a valuable resource for cancer research.

Advancing Precision Medicine: Algebraic Topology and Differential Geometry in Radiology and Computational Pathology

Precision medicine aims to provide personalized care based on individual patient characteristics, rather than guideline-directed therapies for groups of diseases or patient demographics. Images-both radiology- and pathology-derived-are a major source of information on presence, type, and status of disease. Exploring the mathematical relationship of pixels in medical imaging ("radiomics") and cellular-scale structures in digital pathology slides ("pathomics") offers powerful tools for extracting both qualitative and, increasingly, quantitative data. These analytical approaches, however, may be significantly enhanced by applying additional methods arising from fields of mathematics such as differential geometry and algebraic topology that remain underexplored in this context. Geometry's strength lies in its ability to provide precise local measurements, such as curvature, that can be crucial for identifying abnormalities at multiple spatial levels. These measurements can augment the quantitative features extracted in conventional radiomics, leading to more nuanced diagnostics. By contrast, topology serves as a robust shape descriptor, capturing essential features such as connected components and holes. The field of topological data analysis was initially founded to explore the shape of data, with functional network connectivity in the brain being a prominent example. Increasingly, its tools are now being used to explore organizational patterns of physical structures in medical images and digitized pathology slides. By leveraging tools from both differential geometry and algebraic topology, researchers and clinicians may be able to obtain a more comprehensive, multi-layered understanding of medical images and contribute to precision medicine's armamentarium.

The synergy of artificial intelligence and personalized medicine for the enhanced diagnosis, treatment, and prevention of disease

INTRODUCTION

The completion of the Human Genome Project in 2003 marked the beginning of a transformative era in medicine. This milestone laid the foundation for personalized medicine, an innovative approach that customizes healthcare treatments.

CONTENT

Central to the advancement of personalized medicine is the understanding of genetic variations and their impact on drug responses. The integration of artificial intelligence (AI) into drug response trials has been pivotal in this domain. These technologies excel in handling large-scale genomic datasets and patient histories, significantly improving diagnostic accuracy, disease prediction and drug discovery. They are particularly effective in addressing complex diseases such as cancer and genetic disorders. Furthermore, the advent of wearable technology, when combined with AI, propels personalized medicine forward by offering real-time health monitoring, which is crucial for early disease detection and management.

SUMMARY

The integration of AI into personalized medicine represents a significant advancement in healthcare, promising more accurate diagnoses, effective treatment plans and innovative drug discoveries.

OUTLOOK

As technology continues to evolve, the role of AI in enhancing personalized medicine and transforming the healthcare landscape is expected to grow exponentially. This synergy between AI and healthcare holds great promise for the future, potentially revolutionizing the way healthcare is delivered and experienced.

Optimized whole-genome sequencing workflow for tumor diagnostics in routine pathology practice

Two decades after the genomics revolution, oncology is rapidly transforming into a genome-driven discipline, yet routine cancer diagnostics is still mainly microscopy based, except for tumor type-specific predictive molecular tests. Pathology laboratories struggle to quickly validate and adopt biomarkers identified by genomics studies of new targeted therapies. Consequently, clinical implementation of newly approved biomarkers suffers substantial delays, leading to unequal patient access to these therapies. Whole-genome sequencing (WGS) can successfully address these challenges by providing a stable molecular diagnostic platform that allows detection of a multitude of genomic alterations in a single cost-efficient assay and facilitating rapid implementation, as well as by the development of new genomic biomarkers. Recently, the Whole-genome sequencing Implementation in standard Diagnostics for Every cancer patient (WIDE) study demonstrated that WGS is a feasible and clinically valid technique in routine clinical practice with a turnaround time of 11 workdays. As a result, WGS was successfully implemented at the Netherlands Cancer Institute as part of routine diagnostics in January 2021. The success of implementing WGS has relied on adhering to a comprehensive protocol including recording patient information, sample collection, shipment and storage logistics, sequencing data interpretation and reporting, integration into clinical decision-making and data usage. This protocol describes the use of fresh-frozen samples that are necessary for WGS but can be challenging to implement in pathology laboratories accustomed to using formalin-fixed paraffin-embedded samples. In addition, the protocol outlines key considerations to guide uptake of WGS in routine clinical care in hospitals worldwide.

Precision Anesthesia in 2050

Over the last few decades, the field of anesthesia has advanced far beyond its humble beginnings. Today's anesthetics are better and safer than ever, thanks to innovations in drugs, monitors, equipment, and patient safety.1-4 At the same time, we remain limited by our herd approach to medicine. Each of our patients is unique, but health care today is based on a one-size-fits-all approach, while our patients grow older and more medically complex every year. By 2050, we believe that precision medicine will play a central role across all medical specialties, including anesthesia. In addition, we expect that health care and consumer technology will continually evolve to improve and simplify the interactions between patients, providers, and the health care system. As demonstrated by 2 hypothetical patient experiences, these advancements will enable more efficient and safe care, earlier and more accurate diagnoses, and truly personalized treatment plans.

Toward robust clinical genome interpretation: Developing a consistent terminology to characterize Mendelian disease-gene relationships-allelic requirement, inheritance modes, and disease mechanisms

PURPOSE

The terminology used for gene-disease curation and variant annotation to describe inheritance, allelic requirement, and both sequence and functional consequences of a variant is currently not standardized. There is considerable discrepancy in the literature and across clinical variant reporting in the derivation and application of terms. Here, we standardize the terminology for the characterization of disease-gene relationships to facilitate harmonized global curation and to support variant classification within the ACMG/AMP framework.

METHODS

Terminology for inheritance, allelic requirement, and both structural and functional consequences of a variant used by Gene Curation Coalition members and partner organizations was collated and reviewed. Harmonized terminology with definitions and use examples was created, reviewed, and validated.

RESULTS

We present a standardized terminology to describe gene-disease relationships, and to support variant annotation. We demonstrate application of the terminology for classification of variation in the ACMG SF 2.0 genes recommended for reporting of secondary findings. Consensus terms were agreed and formalized in both Sequence Ontology (SO) and Human Phenotype Ontology (HPO) ontologies. Gene Curation Coalition member groups intend to use or map to these terms in their respective resources.

CONCLUSION

The terminology standardization presented here will improve harmonization, facilitate the pooling of curation datasets across international curation efforts and, in turn, improve consistency in variant classification and genetic test interpretation.

Genomics-informed nursing strategies and health equity: A scoping review protocol

OBJECTIVE

The objective of this scoping review is to map the available evidence on strategies that nurses can use to facilitate genomics-informed healthcare to address health disparities.

INTRODUCTION

Advancements in genomics over the last two decades have led to an increase in the delivery of genomics-informed health care. Although the integration of genomics into health care services continues to enhance patient outcomes, access to genomic technologies is not equitable, exacerbating existing health disparities amongst certain populations. As the largest portion of the health workforce, nurses play a critical role in the delivery of equitable genomics-informed care. However, little is known about how nurses can help address health disparities within the context of genomics-informed health care. A review of the literature will provide the necessary foundation to identify promising practices, policy, and knowledge gaps for further areas of inquiry.

INCLUSION CRITERIA

We will include papers that explore strategies that nurses can undertake to facilitate genomics-informed care to address health disparities.

METHODS

This review will be conducted using JBI methodology for scoping reviews. We will search electronic databases including MEDLINE (OVID), EMBASE, Cochrane Library, PsychInfo, and CINAHL for quantitative and qualitative studies, systematic reviews and grey literature. Theses, books, and unavailable full-text papers will be excluded. The search will be limited to papers from 2013 and beyond. Two reviewers will screen titles and abstracts followed by full-text and disagreements will be resolved by a third reviewer. We will use a data extraction tool using Microsoft Excel and analyse data using descriptive statistics and conventional content analysis. Findings will be presented in the form of evidence tables and a narrative summary. We will report findings using the Preferred Reporting Items for Systematic reviews and Meta-Analyses extension for Scoping Reviews (PRISMA-ScR).

DISCUSSION

Genomics will continue to transform all aspects of health care across the wellness continuum from prevention, assessment, diagnosis, management, treatment, and palliative care. The identification of nursing strategies to address health disparities will build the foundation for policy and practice to ensure that the integration of genomic technologies benefits everyone.

Physician Perception of the Importance of Medical Genetics and Genomics in Medical Education and Clinical Practice

PURPOSE

The objective of this study was to determine physician perceptions regarding the importance of and comfort with the use of medical genetics and genomics in medical education and practice, as well as physician expectations for medical trainees.

METHODS

A retrospective survey was sent to physicians employed by a health system associated with a public medical school to assess their perceived training in medical genetics and genomics and their comfort level with ordering genetic testing.

METHODS

Despite reporting formal genetics training in medical schools, clinicians' comfort with and knowledge in this content area does not meet personal expectations of competency. Though physicians report some discomfort with the use of medical genetics and genomics, the majority also believe that its impact on practice will increase in the next five years. Survey recipients were also asked about their expectations for preparation in the same domains for medical students and incoming residents. The surveyed physicians expect a high level of competency for medical students and incoming residents.

METHODS

Our study revealed that practicing physicians feel current medical curricula do not produce physicians with the necessary competency in medical genetics and genomics. This is despite physicians' perceived importance of this domain in medical practice. Our findings suggest a need for re-evaluation of medical genetics and genomics education at all levels of training.

Revisiting Genetic Influence on Mercury Exposure and Intoxication in Humans: A Scoping Review

Human intoxication to mercury is a worldwide health problem. In addition to the type and length of exposure, the genetic background plays an important role in mercury poisoning. However, reviews on the genetic influence in mercury toxicity are scarce and not systematic. Therefore, this review aimed to systematically overview the most recent evidence on the genetic influence (using single nucleotide polymorphisms, SNPs) on human mercury poisoning. Three different databases (PubMed/Medline, Web of Science and Scopus) were searched, and 380 studies were found that were published from 2015 to 2022. After applying inclusion/exclusion criteria, 29 studies were selected and data on characteristics (year, country, profile of participants) and results (mercury biomarkers and quantitation, SNPs, main findings) were extracted and analyzed. The largest number of studies was performed in Brazil, mainly involving traditional populations of the Tapajós River basin. Most studies evaluated the influence of the SNPs related to genes of the glutathione system (GST, GPx, etc.), the ATP-binding cassette transporters and the metallothionein proteins. The recent findings regarding other SNPs, such as those of apolipoprotein E and brain-derived neurotrophic factor genes, are also highlighted. The importance of the exposure level is discussed considering the possible biphasic behavior of the genetic modulation phenomena that could explain some SNP associations. Overall, recommendations are provided for future studies based on the analysis obtained in this scoping review.

Structural and non-coding variants increase the diagnostic yield of clinical whole genome sequencing for rare diseases

BACKGROUND

Whole genome sequencing is increasingly being used for the diagnosis of patients with rare diseases. However, the diagnostic yields of many studies, particularly those conducted in a healthcare setting, are often disappointingly low, at 25-30%. This is in part because although entire genomes are sequenced, analysis is often confined to in silico gene panels or coding regions of the genome.

METHODS

We undertook WGS on a cohort of 122 unrelated rare disease patients and their relatives (300 genomes) who had been pre-screened by gene panels or arrays. Patients were recruited from a broad spectrum of clinical specialties. We applied a bioinformatics pipeline that would allow comprehensive analysis of all variant types. We combined established bioinformatics tools for phenotypic and genomic analysis with our novel algorithms (SVRare, ALTSPLICE and GREEN-DB) to detect and annotate structural, splice site and non-coding variants.

RESULTS

Our diagnostic yield was 43/122 cases (35%), although 47/122 cases (39%) were considered solved when considering novel candidate genes with supporting functional data into account. Structural, splice site and deep intronic variants contributed to 20/47 (43%) of our solved cases. Five genes that are novel, or were novel at the time of discovery, were identified, whilst a further three genes are putative novel disease genes with evidence of causality. We identified variants of uncertain significance in a further fourteen candidate genes. The phenotypic spectrum associated with RMND1 was expanded to include polymicrogyria. Two patients with secondary findings in FBN1 and KCNQ1 were confirmed to have previously unidentified Marfan and long QT syndromes, respectively, and were referred for further clinical interventions. Clinical diagnoses were changed in six patients and treatment adjustments made for eight individuals, which for five patients was considered life-saving.

CONCLUSIONS

Genome sequencing is increasingly being considered as a first-line genetic test in routine clinical settings and can make a substantial contribution to rapidly identifying a causal aetiology for many patients, shortening their diagnostic odyssey. We have demonstrated that structural, splice site and intronic variants make a significant contribution to diagnostic yield and that comprehensive analysis of the entire genome is essential to maximise the value of clinical genome sequencing.

Lessons from complex trait genetics may help us overcome the neuroimaging replication crisis

The research fields of Complex Trait (or Statistical) Genetics and Neuroimaging face similar challenges in identifying reliable biological correlates of common traits and diseases. This Viewpoint focuses on five major lessons that allowed population-level genetics research to overcome many of its issues of replicability and may be directly applicable to inter-individual neuroimaging research. First, the failure of candidate gene studies inspires abandoning overly simplistic studies mapping individual brain regions onto traits and diseases. Second, developments in genetics research demonstrate that robust study results can be achieved by increasing sample sizes. Third and fourth, the success of genome-wide association studies motivates the use of mass-univariate testing and sharing summary-level association data to boost large-scale collaboration and meta-analysis. Finally, applying genetics methods dealing with complex data structures to vertex-wise (or voxel-wise) neuroimaging data promises more robust discoveries without the need to develop novel neuroimaging-specific methods. Those practices - that are firmly established in genetics research - should either be further endorsed, or newly adopted by the neuroimaging community, promising to accelerate the evolution of Neuroimaging through robust discovery.

Most people share genetic test results with relatives even if the findings are normal: Family communication in a diverse population

PURPOSE

With increasing utilization of genetic testing, sharing genetic information can become part of general family health communication while providing biological relatives with important information about their own genetic risk. Importantly, little is known about motivations for and barriers to family communication of genetic information in historically underserved populations.

METHODS

Using mixed methods, we explored patient experiences with family communication in a study population of English- and Spanish-speaking adults aged 18 to 49 years, enriched for participants from historically underserved backgrounds. Risk screening for hereditary cancer guided genetic testing for cancer risk genes and other medically actionable findings.

RESULTS

Most participants overall (91%), including most with normal findings (89%), shared or planned to share their results with relatives. Common motivations for sharing results were to give relatives information about their genetic risk and because the participant thought the results were interesting. Reasons for not sharing were limited contact with relatives, perceptions of limited clinical utility for relatives, and concern that discussion of genetic information was stigmatized or taboo.

CONCLUSION

Results demonstrate high rates of sharing genetic information, indicate motivations for sharing go beyond facilitating genetic testing for relatives, and suggest general willingness to share genetic information as part of family health communication.

Physicians' Perspectives on AI in Clinical Decision Support Systems: Interview Study of the CURATE.AI Personalized Dose Optimization Platform

BACKGROUND

Physicians play a key role in integrating new clinical technology into care practices through user feedback and growth propositions to developers of the technology. As physicians are stakeholders involved through the technology iteration process, understanding their roles as users can provide nuanced insights into the workings of these technologies that are being explored. Therefore, understanding physicians' perceptions can be critical toward clinical validation, implementation, and downstream adoption. Given the increasing prevalence of clinical decision support systems (CDSSs), there remains a need to gain an in-depth understanding of physicians' perceptions and expectations toward their downstream implementation. This paper explores physicians' perceptions of integrating CURATE.AI, a novel artificial intelligence (AI)-based and clinical stage personalized dosing CDSSs, into clinical practice.

OBJECTIVE

This study aims to understand physicians' perspectives of integrating CURATE.AI for clinical work and to gather insights on considerations of the implementation of AI-based CDSS tools.

METHODS

A total of 12 participants completed semistructured interviews examining their knowledge, experience, attitudes, risks, and future course of the personalized combination therapy dosing platform, CURATE.AI. Interviews were audio recorded, transcribed verbatim, and coded manually. The data were thematically analyzed.

RESULTS

Overall, 3 broad themes and 9 subthemes were identified through thematic analysis. The themes covered considerations that physicians perceived as significant across various stages of new technology development, including trial, clinical implementation, and mass adoption.

CONCLUSIONS

The study laid out the various ways physicians interpreted an AI-based personalized dosing CDSS, CURATE.AI, for their clinical practice. The research pointed out that physicians' expectations during the different stages of technology exploration can be nuanced and layered with expectations of implementation that are relevant for technology developers and researchers.

PhenoScore quantifies phenotypic variation for rare genetic diseases by combining facial analysis with other clinical features using a machine-learning framework

Several molecular and phenotypic algorithms exist that establish genotype-phenotype correlations, including facial recognition tools. However, no unified framework that investigates both facial data and other phenotypic data directly from individuals exists. We developed PhenoScore: an open-source, artificial intelligence-based phenomics framework, combining facial recognition technology with Human Phenotype Ontology data analysis to quantify phenotypic similarity. Here we show PhenoScore's ability to recognize distinct phenotypic entities by establishing recognizable phenotypes for 37 of 40 investigated syndromes against clinical features observed in individuals with other neurodevelopmental disorders and show it is an improvement on existing approaches. PhenoScore provides predictions for individuals with variants of unknown significance and enables sophisticated genotype-phenotype studies by testing hypotheses on possible phenotypic (sub)groups. PhenoScore confirmed previously known phenotypic subgroups caused by variants in the same gene for SATB1, SETBP1 and DEAF1 and provides objective clinical evidence for two distinct ADNP-related phenotypes, already established functionally.

Decision trees to evaluate the risk of developing multiple sclerosis

Introduction

Multiple sclerosis (MS) is a persistent neurological condition impacting the central nervous system (CNS). The precise cause of multiple sclerosis is still uncertain; however, it is thought to arise from a blend of genetic and environmental factors. MS diagnosis includes assessing medical history, conducting neurological exams, performing magnetic resonance imaging (MRI) scans, and analyzing cerebrospinal fluid. While there is currently no cure for MS, numerous treatments exist to address symptoms, decelerate disease progression, and enhance the quality of life for individuals with MS.

Methods

This paper introduces a novel machine learning (ML) algorithm utilizing decision trees to address a key objective: creating a predictive tool for assessing the likelihood of MS development. It achieves this by combining prevalent demographic risk factors, specifically gender, with crucial immunogenetic risk markers, such as the alleles responsible for human leukocyte antigen (HLA) class I molecules and the killer immunoglobulin-like receptors (KIR) genes responsible for natural killer lymphocyte receptors.

Results

The study included 619 healthy controls and 299 patients affected by MS, all of whom originated from Sardinia. The gender feature has been disregarded due to its substantial bias in influencing the classification outcomes. By solely considering immunogenetic risk markers, the algorithm demonstrates an ability to accurately identify 73.24% of MS patients and 66.07% of individuals without the disease.

Discussion

Given its notable performance, this system has the potential to support clinicians in monitoring the relatives of MS patients and identifying individuals who are at an increased risk of developing the disease.

Prognostic value of genotyping in hepatocellular carcinoma: A systematic review

Primary liver cancer is the sixth most commonly diagnosed cancer and the third leading cause of cancer death. Advances in sequencing technology are opening genomics to widespread application for diagnosis and research. The poor prognosis of advanced HCC warrants a personalized approach. The objective was to assess the value of genotyping for risk stratification and prognostication of HCC. We performed a systematic review of manuscripts published on MEDLINE from 1 January 2009 to 1 January 2022, addressing the value of genotyping for HCC risk stratification and prognostication. Publication information for each has been collected using a standardized data extraction form. Twenty-five articles were analysed. This study showed that various genomics approaches (i.e., NGS, SNP, CASP or polymorphisms in circadian genes' association) provided predictive and prognostic information, such as disease control rate, median progression-free survival, and shorter median overall survival. Genotyping, which advances in understanding the molecular origin, could be a solution to predict prognosis or treatment response in patients with HCC.

Understanding the Clinical Utility of Genome Sequencing in Critically Ill Newborns

Diagnostic genome sequencing (GS) in newborns may have many benefits. More accurate diagnosis could spur the development of innovative genomic therapies. A precise diagnosis could help doctors and parents anticipate clinical problems and inform a family's future reproductive choices. However, the integration of GS into neonatal care remains associated with a variety of ethical controversies, including concerns about informed consent, about interpreting uncertain results, about resource allocation and whether access to genomic services could exacerbate health disparities, and about the effect of genome diagnostics on people with disabilities. There also remains significant uncertainty about which babies should be tested and when and how the potential benefits of GS ought to be measured. Probably related to these challenges, some payors have been reluctant to cover the cost of GS for critically ill newborns. Much of the reluctance appears to turn on questions about the clinical benefit associated with GS and whether and for whom GS will be cost-effective. These situations point to the urgent need for careful assessments of the clinical utility of GS in critically ill infants. In this paper, we critically examine the ways in which the clinical utility of GS has been evaluated in this patient population. We focus on "change of management" (COM), a widely used measure of clinical utility for diagnostic GS. We suggest that this measure is often ambiguous because not all COMs can be attributed to genomic results and because not all COMs lead to patient benefit. Finally, we suggest ways that measurement of clinical utility could be improved.

Towards robust clinical genome interpretation: developing a consistent terminology to characterize disease-gene relationships - allelic requirement, inheritance modes and disease mechanisms

PURPOSE

The terminology used for gene-disease curation and variant annotation to describe inheritance, allelic requirement, and both sequence and functional consequences of a variant is currently not standardized. There is considerable discrepancy in the literature and across clinical variant reporting in the derivation and application of terms. Here we standardize the terminology for the characterization of disease-gene relationships to facilitate harmonized global curation, and to support variant classification within the ACMG/AMP framework.

METHODS

Terminology for inheritance, allelic requirement, and both structural and functional consequences of a variant used by Gene Curation Coalition (GenCC) members and partner organizations was collated and reviewed. Harmonized terminology with definitions and use examples was created, reviewed, and validated.

RESULTS

We present a standardized terminology to describe gene-disease relationships, and to support variant annotation. We demonstrate application of the terminology for classification of variation in the ACMG SF 2.0 genes recommended for reporting of secondary findings. Consensus terms were agreed and formalized in both sequence ontology (SO) and human phenotype ontology (HPO) ontologies. GenCC member groups intend to use or map to these terms in their respective resources.

CONCLUSION

The terminology standardization presented here will improve harmonization, facilitate the pooling of curation datasets across international curation efforts and, in turn, improve consistency in variant classification and genetic test interpretation.

Breast Cancer Risk Assessment Tools for Stratifying Women into Risk Groups: A Systematic Review

BACKGROUND

The benefits and harms of breast screening may be better balanced through a risk-stratified approach. We conducted a systematic review assessing the accuracy of questionnaire-based risk assessment tools for this purpose.

METHODS

Population: asymptomatic women aged ≥40 years; Intervention: questionnaire-based risk assessment tool (incorporating breast density and polygenic risk where available); Comparison: different tool applied to the same population; Primary outcome: breast cancer incidence; Scope: external validation studies identified from databases including Medline and Embase (period 1 January 2008-20 July 2021). We assessed calibration (goodness-of-fit) between expected and observed cancers and compared observed cancer rates by risk group. Risk of bias was assessed with PROBAST.

RESULTS

Of 5124 records, 13 were included examining 11 tools across 15 cohorts. The Gail tool was most represented (n = 11), followed by Tyrer-Cuzick (n = 5), BRCAPRO and iCARE-Lit (n = 3). No tool was consistently well-calibrated across multiple studies and breast density or polygenic risk scores did not improve calibration. Most tools identified a risk group with higher rates of observed cancers, but few tools identified lower-risk groups across different settings. All tools demonstrated a high risk of bias.

CONCLUSION

Some risk tools can identify groups of women at higher or lower breast cancer risk, but this is highly dependent on the setting and population.

Transforming Diagnosis and Therapeutics Using Cancer Genomics

In past quarter of the century, much has been understood about the genetic variation and abnormal genes that activate cancer in humans. All the cancers somehow possess alterations in the DNA sequence of cancer cell's genome. In present, we are heading toward the era where it is possible to obtain complete genome of the cancer cells for their better diagnosis, categorization and to explore treatment options.

Factors Associated with the Uptake of Genetic Testing for Cancer Risks: A Pathway Analysis Using the Health Information National Trends Survey Data

Our study aimed to identify pathways from the source of information to the uptake of cancer genetic testing, with consideration of intermediate variables including perceptional, attitudinal and psychosocial factors. We used the Health Information National Trends Survey (2020 database) and constructed a structural equation model for pathway analysis (using SPSS version 24). Variables for socio-demographic, lifestyle and health information were also collected and used for confounding adjustment. A total of 2941 participants were analyzed (68.5%, non-Hispanic white; 59.7%, females; 58 years, median age; and 142 (4.8%) had undertaken genetic testing for cancer risk previously). Our pathway analysis found that only information from particular sources (i.e., healthcare providers and genetic counsellors) had positive and significant effects on people’s perceptions of cancer regarding its prevention, detection and treatment (standardized β range, 0.15−0.31, all p-values < 0.01). Following the paths, these perceptional variables (cancer prevention, detection and treatment) showed considerable positive impacts on the uptake of genetic testing (standardized β (95% CIs): 0.25 (0.20, 0.30), 0.28 (0.23, 0.33) and 0.12 (0.06, 0.17), respectively). Pathways involving attitudinal and psychosocial factors showed much smaller or insignificant effects on the uptake of genetic testing. Our study brings several novel perspectives to the behavior model and may underpin certain issues regarding cancer risk genetic testing.

Genetically personalised organ-specific metabolic models in health and disease

Understanding how genetic variants influence disease risk and complex traits (variant-to-function) is one of the major challenges in human genetics. Here we present a model-driven framework to leverage human genome-scale metabolic networks to define how genetic variants affect biochemical reaction fluxes across major human tissues, including skeletal muscle, adipose, liver, brain and heart. As proof of concept, we build personalised organ-specific metabolic flux models for 524,615 individuals of the INTERVAL and UK Biobank cohorts and perform a fluxome-wide association study (FWAS) to identify 4312 associations between personalised flux values and the concentration of metabolites in blood. Furthermore, we apply FWAS to identify 92 metabolic fluxes associated with the risk of developing coronary artery disease, many of which are linked to processes previously described to play in role in the disease. Our work demonstrates that genetically personalised metabolic models can elucidate the downstream effects of genetic variants on biochemical reactions involved in common human diseases.

Attitudes of Australian dermatologists on the use of genetic testing: A cross-sectional survey with a focus on melanoma

Background: Melanoma genetic testing reportedly increases preventative behaviour without causing psychological harm. Genetic testing for familial melanoma risk is now available, yet little is known about dermatologists' perceptions regarding the utility of testing and genetic testing ordering behaviours. Objectives: To survey Australasian Dermatologists on the perceived utility of genetic testing, current use in practice, as well as their confidence and preferences for the delivery of genomics education. Methods: A 37-item survey, based on previously validated instruments, was sent to accredited members of the Australasian College of Dermatologists in March 2021. Quantitative items were analysed statistically, with one open-ended question analysed qualitatively. Results: The response rate was 56% (256/461), with 60% (153/253) of respondents between 11 and 30 years post-graduation. While 44% (112/252) of respondents agreed, or strongly agreed, that genetic testing was relevant to their practice today, relevance to future practice was reported significantly higher at 84% (212/251) (t = -9.82, p < 0.001). Ninety three percent (235/254) of respondents reported rarely or never ordering genetic testing. Dermatologists who viewed genetic testing as relevant to current practice were more likely to have discussed (p < 0.001) and/or offered testing (p < 0.001). Respondents indicated high confidence in discussing family history of melanoma, but lower confidence in ordering genetic tests and interpreting results. Eighty four percent (207/247) believed that genetic testing could negatively impact life insurance, while only 26% (63/244) were aware of the moratorium on using genetic test results in underwriting in Australia. A minority (22%, 55/254) reported prior continuing education in genetics. Face-to-face courses were the preferred learning modality for upskilling. Conclusion: Australian Dermatologists widely recognise the relevance of genetic testing to future practice, yet few currently order genetic tests. Future educational interventions could focus on how to order appropriate genetic tests and interpret results, as well as potential implications on insurance.

A practical guide to genetic testing in endocrinology

Rapid advances in sequencing technology have led to significant improvements in genomic analysis, resulting in increased understanding of the molecular basis of many endocrine conditions. Genomic testing for rare disease is being integrated into everyday clinical practice, as the importance of confirming a genetic diagnosis earlier in a patient's pathway helps direct their clinical care and specialized management. In England, the new nationally commissioned Genomic Medicine Service has started to deliver testing for rare and inherited disease and cancer somatic tissue via seven Genomic Laboratory Hubs. The range of genetic tests, technology employed and eligibility criteria for patient testing are all defined in the National Genomic Test Directory. This review provides practical guidance on how to access genomic testing for endocrine disease, how to interpret and relay results, and details how genetic counselling can help integrate results into ongoing care of the individual and their family. This article discusses general principles as well as specifics related to the process of genomic testing in England. We illustrate mainstream genetic testing with a clinical scenario involving an individual with inherited endocrine neoplasia, followed by a generic description of the different steps involved, including informed consent to proceed to diagnostic testing. Most genetic tests analyse multiple genes simultaneously by next-generation sequencing, and variant interpretation may yield not only pathogenic explanatory results, but also ambiguous outcomes, with variants of unknown significance or incidental findings. Delivery of results and posttest genetic counselling are therefore key components of integrating genetic testing into routine endocrine care.

Cost-Effectiveness of Polygenic Risk Scores to Guide Statin Therapy for Cardiovascular Disease Prevention

BACKGROUND

Atherosclerotic cardiovascular diseases (CVDs) are leading causes of death despite effective therapies and result in unnecessary morbidity and mortality throughout the world. We aimed to investigate the cost-effectiveness of polygenic risk scores (PRS) to guide statin therapy for Canadians with intermediate CVD risk and model its economic outlook.

METHODS

This cost-utility analysis was conducted using UK Biobank prospective cohort study participants, with recruitment from 2006 to 2010, and at least 10 years of follow-up. We included nonrelated white British-descent participants (n=96 116) at intermediate CVD risk with no prior lipid lowering medication or statin-indicated conditions. A coronary artery disease PRS was used to inform decision to use statins. The effects of statin therapy with and without PRS, as well as CVD events were modelled to determine the incremental cost-effectiveness ratio from a Canadian public health care perspective. We discounted future costs and quality-adjusted life-years by 1.5% annually.

RESULTS

The optimal economic strategy was when intermediate risk individuals with a PRS in the top 70% are eligible for statins while the lowest 1% are excluded. Base-case analysis at a genotyping cost of $70 produced an incremental cost-effectiveness ratio of $172 906 (143 685 USD) per quality-adjusted life-year. In the probabilistic sensitivity analysis, the intervention has approximately a 50% probability of being cost-effective at $179 100 (148 749 USD) per quality-adjusted life-year. At a $0 genotyping cost, representing individuals with existing genotyping information, PRS-guided strategies dominated standard care when 12% of the lowest PRS individuals were withheld from statins. With improved PRS predictive performance and lower genotyping costs, the incremental cost-effectiveness ratio demonstrates possible cost-effectiveness under thresholds of $150 000 and possibly $50 000 per quality-adjusted life-year.

CONCLUSIONS

This study suggests that using PRS alongside existing guidelines might be cost-effective for CVD. Stronger predictiveness combined with decreased cost of PRS could further improve cost-effectiveness, providing an economic basis for its inclusion into clinical care.

The value of genotype-specific reference for transcriptome analyses in barley

It is increasingly apparent that although different genotypes within a species share "core" genes, they also contain variable numbers of "specific" genes and different structures of "core" genes that are only present in a subset of individuals. Using a common reference genome may thus lead to a loss of genotype-specific information in the assembled Reference Transcript Dataset (RTD) and the generation of erroneous, incomplete or misleading transcriptomics analysis results. In this study, we assembled genotype-specific RTD (sRTD) and common reference-based RTD (cRTD) from RNA-seq data of cultivated Barke and Morex barley, respectively. Our quantitative evaluation showed that the sRTD has a significantly higher diversity of transcripts and alternative splicing events, whereas the cRTD missed 40% of transcripts present in the sRTD and it only has ∼70% accurate transcript assemblies. We found that the sRTD is more accurate for transcript quantification as well as differential expression analysis. However, gene-level quantification is less affected, which may be a reasonable compromise when a high-quality genotype-specific reference is not available.

Zebrafish Is a Powerful Tool for Precision Medicine Approaches to Neurological Disorders

Personalized medicine is currently one of the most promising tools which give hope to patients with no suitable or no available treatment. Patient-specific approaches are particularly needed for common diseases with a broad phenotypic spectrum as well as for rare and yet-undiagnosed disorders. In both cases, there is a need to understand the underlying mechanisms and how to counteract them. Even though, during recent years, we have been observing the blossom of novel therapeutic techniques, there is still a gap to fill between bench and bedside in a patient-specific fashion. In particular, the complexity of genotype-to-phenotype correlations in the context of neurological disorders has dampened the development of successful disease-modifying therapeutics. Animal modeling of human diseases is instrumental in the development of therapies. Currently, zebrafish has emerged as a powerful and convenient model organism for modeling and investigating various neurological disorders. This model has been broadly described as a valuable tool for understanding developmental processes and disease mechanisms, behavioral studies, toxicity, and drug screening. The translatability of findings obtained from zebrafish studies and the broad prospect of human disease modeling paves the way for developing tailored therapeutic strategies. In this review, we will discuss the predictive power of zebrafish in the discovery of novel, precise therapeutic approaches in neurosciences. We will shed light on the advantages and abilities of this in vivo model to develop tailored medicinal strategies. We will also investigate the newest accomplishments and current challenges in the field and future perspectives.

COL4A4 variant recently identified: lessons learned in variant interpretation-a case report

Background

Alport syndrome is a hereditary kidney disease characterized by hematuria and proteinuria. Although there have been reports of autosomal dominant COL4A4 variants, this is likely an underdiagnosed condition. Improved access to affordable genetic testing has increased the diagnosis of Alport syndrome. As genetic testing becomes ubiquitous, it is imperative that clinical nephrologists understand the benefits and challenges associated with clinical genetic testing.

Case Presentation

We present a family of Mexican descent with a heterozygous COL4A4 variant (c.5007delC, ClinVar accession numbers: SCV001580980.2, SCV001993731.1) not previously discussed in detail in the literature. The proband received a biopsy diagnosis suggestive of Fabry disease 18 years after she first developed hematuria and progressed to chronic kidney disease stage III. One year later, the proband was provisionally diagnosed with Alport syndrome after a variant of uncertain significance in the COL4A4 gene was identified following targeted family variant testing of her daughter. Upon review of the medical histories of the proband’s children and niece, all but one had the same variant. Of the four with the variant, three display clinical symptoms of hematuria, and/or proteinuria. The youngest of the four, only months old, has yet to exhibit clinical symptoms. Despite these findings there was a considerable delay in synthesizing this data, as patients were tested in different commercial genetic testing laboratories. Subsequently, understanding this family’s inheritance pattern, family history, and clinical symptoms, as well as the location of the COL4A4 variant resulted in the upgrade of the variant’s classification. Although the classification of this variant varied among different clinical genetic testing laboratories, the consensus was that this variant is likely pathogenic.

Conclusions

This COL4A4 variant (c.5007delC) not yet discussed in detail in the literature is associated with Alport syndrome. The inheritance pattern is suggestive of autosomal dominant inheritance. This report highlights the intricacies of variant interpretation and classification, the siloed nature of commercial genetic testing laboratories, and the importance of a thorough family history for proper variant interpretation. Additionally, the cases demonstrate the varied clinical presentations of Alport syndrome and suggest the utility of early screening, diagnosis, monitoring, and treatment.

Neurofibromatosis: New Clinical Challenges in the Era of COVID-19

Rare diseases constitute a wide range of disorders thus defined for their low prevalence. However, taken together, rare diseases impact a considerable percentage of the world population, thus representing a public healthcare problem. In particular, neurofibromatoses are autosomal-dominant genetic disorders that include type 1 neurofibromatosis (NF1), type 2 neurofibromatosis (NF2) and schwannomatosis. Each of the three types is a genetically distinct disease with an unpredictable clinical course and for which there is still no resolutive cure. Therefore, a personalized therapeutic approach directed at improving the symptomatology as well as the search for new pharmacological strategies for the management of neurofibromatosis represents a priority for positive outcomes for affected patients. The coronavirus disease 2019 (COVID-19) pandemic has severely affected health systems around the world, impacting the provision of medical care and modifying clinical surveillance along with scientific research procedures. COVID-19 significantly worsened exchanges between healthcare personnel and neurofibromatosis patients, precluding continuous clinical monitoring in specialized clinic centers. In this new scenario, our article presents, for the first time, a comprehensive literature review on the clinical challenges for neurofibromatosis clinical care and research during the COVID-19 pandemic health emergency. The review was performed through PubMed (Medline) and Google Scholar databases until December 2021.

The angiotensin-converting enzyme gene insertion/deletion polymorphism interacts with fear of falling in relation to stepping speed in community-dwelling older adults

BACKGROUND

Despite the association of genetic factors with falls, balance, and lower extremity functioning, interaction of the angiotensin-converting enzyme (ACE) gene insertion/deletion (I/D) polymorphism with fear of falling (FOF) in relation to stepping performance has, to the best of our knowledge, not been investigated in older adults.

OBJECTIVE

The purpose of this study was to examine the interaction effects of the ACE I/D polymorphism with FOF in relation to stepping performance in older adults.

METHODS

Eighty-eight community-dwelling adults 60 years or older participated in a cross-sectional observational study. Participants completed tests of rapid and distance stepping, and self-reported FOF (yes/no). Participants provided saliva for ACE genotyping. General linear models evaluated ACE genotype × FOF interaction effects in relation to stepping performance. The α level was set at 0.05.

RESULTS

The ACE I/D polymorphism exhibited significant interaction effects (p for interactions 0.002 ≤ p ≤ .04) with FOF in relation to stepping speed. Relationships between FOF and stepping speed varied among ACE genotypes. The insertion/insertion (II) genotype was significantly associated (p = .01) with slow stepping in individuals with, but not without FOF (p > .05).

CONCLUSION

Variation in relationships between FOF and stepping speed among ACE genotypes suggests a role for the ACE I/D polymorphism in modifying relationships between FOF and stepping speed in older adults. The association of the ACE II genotype with slow stepping performance in individuals with, but not without FOF, suggests that older adults with the ACE II genotype and FOF may be at increased risk for poor stepping performance and associated functional declines.

Multi-omics strategies for personalized and predictive medicine: past, current, and future translational opportunities

Precision medicine is driven by the paradigm shift of empowering clinicians to predict the most appropriate course of action for patients with complex diseases and improve routine medical and public health practice. It promotes integrating collective and individualized clinical data with patient specific multi-omics data to develop therapeutic strategies, and knowledgebase for predictive and personalized medicine in diverse populations. This study is based on the hypothesis that understanding patient's metabolomics and genetic make-up in conjunction with clinical data will significantly lead to determining predisposition, diagnostic, prognostic and predictive biomarkers and optimal paths providing personalized care for diverse and targeted chronic, acute, and infectious diseases. This study briefs emerging significant, and recently reported multi-omics and translational approaches aimed to facilitate implementation of precision medicine. Furthermore, it discusses current grand challenges, and the future need of Findable, Accessible, Intelligent, and Reproducible (FAIR) approach to accelerate diagnostic and preventive care delivery strategies beyond traditional symptom-driven, disease-causal medical practice.

Can we know if donor trust expires? About trust relationships and time in the context of open consent for future data use

As donor trust legitimises research, trust is vital for research in the fields of biomedicine, genetics, translational medicine and personalised medicine. For parts of the donor community, the consent signature is a sign of trust in research. Many consent processes in biomedical research ask donors to provide their data for an unspecified future use, which introduces uncertainty of the unknown. This uncertainty can jeopardise donor trust or demand blind trust. But which donor wants to trust blindly? To reduce this uncertainty, we explore first, which future-proof actors donors could trust when signing a consent form. Second, we discuss the question Can we know if donor trust expires? and what prevents donor trust from expiring. Finally, we present possible measures that can help to nurture trust in the far future. In this article, we draw on our previous research on trust in biomedical research, on trust in the broader healthcare system and Niklas Luhmann's and Anthony Giddens' trust theories. Our findings suggest that, in the far future, researchers will need to consider donor autonomy, as well as societal norms and values of the time period in which the data were donated. They will need to find mechanisms where possible to publicly announce the use of old data sets. However, foremost researchers will need to treat the data respectfully. It remains vital that professionals and the society continue to elaborate on the norms and values that shape the common understanding of what is morally right and wrong when researching data.

A Web Screening on Training Initiatives in Cancer Genomics for Healthcare Professionals

The disruptive advances in genomics contributed to achieve higher levels of precision in the diagnosis and treatment of cancer. This scientific advance entails the need for greater literacy for all healthcare professionals. Our study summarizes the training initiatives conducted worldwide in cancer genomics field for healthcare professionals. We conducted a web search of the training initiatives aimed at improving healthcare professionals’ literacy in cancer genomics undertaken worldwide by using two search engines (Google and Bing) in English language and conducted from 2003 to 2021. A total of 85,649 initiatives were identified. After the screening process, 36 items were included. The majority of training programs were organized in the United States (47%) and in the United Kingdom (28%). Most of the initiatives were conducted in the last five years (83%) by universities (30%) and as web-based modalities (80%). In front of the technological advances in genomics, education in cancer genomics remains fundamental. Our results may contribute to provide an update on the development of educational programs to build a skilled and appropriately trained genomics health workforce in the future.

Educational Interventions to Improve Nurses' Competency in Genetics and Genomics: A Scoping Review

BACKGROUND

Regardless of profession and area of practice, every health care provider must possess basic knowledge and skills to integrate genetics and genomics into practice. Nurses play a pivotal role in providing health care, and they should be well equipped to apply genetics and genomics to health care settings. This scoping review explored the existing literature of educational interventions to improve nurses' competencies, including knowledge, attitudes, and skills in genetics and genomics.

METHOD

A scoping review was conducted with the Joanna Briggs Institute method for scoping reviews. We searched PubMed, Web of Science, CINAHL, and ERIC in March 2021. We included original research studies published in English in peer-reviewed journals that reported findings on the effectiveness of an educational intervention to improve nurses' competencies in genetics or genomics.

RESULTS

A total of 17 studies were included in the scoping review. Registered nurses, advanced practice nurses, and nursing faculty were targeted with different types of interventions, including face-to-face education, online/remote education, and written materials.

CONCLUSION

Limited research shows that various educational interventions improved the competencies in genetics and genomics among nurses with different degrees and areas of practice. Research is needed to evaluate the long-term effects of educational interventions by reliable assessment methods for nurses with appropriate sample sizes. [J Contin Educ Nurs. 2022;53(1):13-20.].

Guidelines for Genetic Testing and Management of Alport Syndrome

Genetic testing for pathogenic COL4A3-5 variants is usually undertaken to investigate the cause of persistent hematuria, especially with a family history of hematuria or kidney function impairment. Alport syndrome experts now advocate genetic testing for persistent hematuria, even when a heterozygous pathogenic COL4A3 or COL4A4 is suspected, and cascade testing of their first-degree family members because of their risk of impaired kidney function. The experts recommend too that COL4A3 or COL4A4 heterozygotes do not act as kidney donors. Testing for variants in the COL4A3-COL4A5 genes should also be performed for persistent proteinuria and steroid-resistant nephrotic syndrome due to suspected inherited FSGS and for familial IgA glomerulonephritis and kidney failure of unknown cause.

The correctness of large scale analysis of genomic data

Implementing a large genomic project is a demanding task, also from the computer science point of view. Besides collecting many genome samples and sequencing them, there is processing of a huge amount of data at every stage of their production and analysis. Efficient transfer and storage of the data is also an important issue. During the execution of such a project, there is a need to maintain work standards and control quality of the results, which can be difficult if a part of the work is carried out externally. Here, we describe our experience with such data quality analysis on a number of levels - from an obvious check of the quality of the results obtained, to examining consistency of the data at various stages of their processing, to verifying, as far as possible, their compatibility with the data describing the sample.

Current Status of Genetic Counselling for Rare Diseases in Spain

Genetic Counselling is essential for providing personalised information and support to patients with Rare Diseases (RD). Unlike most other developed countries, Spain does not recognize geneticists or genetic counsellors as healthcare professionals Thus, patients with RD face not only challenges associated with their own disease but also deal with lack of knowledge, uncertainty, and other psychosocial issues arising as a consequence of diagnostic delay. In this review, we highlight the importance of genetic counsellors in the field of RD as well as evaluate the current situation in which rare disease patients receive genetic services in Spain. We describe the main units and strategies at the national level assisting patients with RD and we conclude with a series of future perspectives and unmet needs that Spain should overcome to improve the management of patients with RD.