Crowgey, Erin L.

Introduction: Sickle cell disease (SCD) is prevalent in sub-Saharan Africa. Phenotypic diversity in patients with similar SCD genotypes may result from genetic and environmental factors. Nigeria has the highest SCD prevalence, with homozygous SCD (HbSS) being the most severe form. Stroke affects about 11% of children under 20 years with SCD (Ohene-Frempong, Weiner, et al. 1998), primarily ischemic, involving medium to large intracranial arteries. Specific single nucleotide polymorphisms have been linked to ischemic stroke risk in some populations. (Earley, Kelly et al. 2023). This study aimed to identify genetic factors associated with early-age large-vessel stroke in SCD using whole-exome sequencing (WES) in a Nigerian cohort. Methods: The protocol was approved by the IRBs of TJU, Nemours, and 3 Nigerian sites. Subjects with SCD who experienced large vessel stroke early in life (16 years or less) were enrolled, along with controls (SCD patients without stroke). Subjects were recruited from 3SCD clinics in Kano Metropolis, Nigeria. Inclusion criteria were confirmed SCD diagnosis (SS and Sβ0 thalassemia genotypes), abnormal transcranial doppler (TCD) measurements, and clinical evidence of stroke confirmed by MRI by age 16. Controls included SCD patients (SS and Sβ0) aged 16-26 years without clinical stroke and at least one normal TCD. All cases underwent Magnetic Resonance Angiography (MRA) to establish arteriopathy. Immediate family members of subjects >16 years (siblings and parents) were used per best practice trio analysis to annotate variants with appropriate Mendelian inheritance patterns. WES was performed using SureSelect XT HS (Agilent) and Human All Exon V7 Rev B capture probes for library preparation on all samples. Libraries were sequenced on a NextSeq 550 to 50M paired-end 150bp reads. Variants were called using the GATK suite of algorithms following best practice guidelines and annotated using the VarSeq algorithm, including AlphaMissense annotations. Results: The control group had a median age of 21 years, and the stroke group had a median age of 9 years. The stroke group had a higher proportion of males (60%) compared to controls (30%) (p < 0.05). Fifty percent of the stroke group and 73% of the controls had a history of acute chest syndrome. History of avascular necrosis (7.5%), heart disease (2.5%), and splenic sequestration (1.3%) were present only in controls. Malaria (1.3%), sepsis (2.5%), and hand-foot syndrome (59%) affected the stroke group. History of priapism (6.3%) and leg ulcers (10%) had similar rates in both groups. Using AlphaMissense annotations, nine genes were identified to have more damaging mutations in the stroke cohort compared to the control cohort (odds ratio > 1 and p < 0.05). Pathway enrichment analysis utilizing genes prioritized with an odds ratio > 1 identified cadherin signaling, cellular junction/adhesion, and WNT signaling as significant (p < 0.05). The role of cellular adhesion has been previously described in SCD stroke subjects (Oni, Brito et al. 2024). The genes that we found that showed significance in our analysis include ADAMTSL2, ADCY9, OR3A1, OR3A2, XRRA1, ABTB2, CLDN18, CPNE7, EIF3A, SLC7A6, UBA7, PDE6A, GLOD5, and PCDHA1. Conclusion: Genes in the ADCY9 and ADAMSL2 families have been reported in previous studies to be associated with ischemic stroke. Though the small sample size limits this study, it offers preliminary insights into the genetic and clinical determinants of stroke in SCD patients in Northern Nigeria. The identified candidate genes potentially hold biological significance for the stroke phenotype; however, additional research with a larger sample size is required to validate these associations. These findings underscore the need for further whole-exome sequencing studies in Nigerian patients with the stroke/arteriopathy phenotype, which may augment our understanding of this severe complication. An in-depth examination of the genetic modifiers associated with stroke in SCD could lead to enhanced predictive models and targeted preventive interventions, reducing the burden of stroke in affected individuals. Our team has identified additional datasets in the United States to help validate molecular signatures of interest, inspiring us to continue our work in this important field.

Abstract Objective The Genomic Medicine Working Group of the National Advisory Council for Human Genome Research virtually hosted its 13th genomic medicine meeting titled “Developing a Clinical Genomic Informatics Research Agenda”. The meeting’s goal was to articulate a research strategy to develop Genomics-based Clinical Informatics Tools and Resources (GCIT) to improve the detection, treatment, and reporting of genetic disorders in clinical settings. Materials and Methods Experts from government agencies, the private sector, and academia in genomic medicine and clinical informatics were invited to address the meeting's goals. Invitees were also asked to complete a survey to assess important considerations needed to develop a genomic-based clinical informatics research strategy. Results Outcomes from the meeting included identifying short-term research needs, such as designing and implementing standards-based interfaces between laboratory information systems and electronic health records, as well as long-term projects, such as identifying and addressing barriers related to the establishment and implementation of genomic data exchange systems that, in turn, the research community could help address. Discussion Discussions centered on identifying gaps and barriers that impede the use of GCIT in genomic medicine. Emergent themes from the meeting included developing an implementation science framework, defining a value proposition for all stakeholders, fostering engagement with patients and partners to develop applications under patient control, promoting the use of relevant clinical workflows in research, and lowering related barriers to regulatory processes. Another key theme was recognizing pervasive biases in data and information systems, algorithms, access, value, and knowledge repositories and identifying ways to resolve them.

AbstractThe recent announcement of the Precision Medicine Initiative by President Obama has brought precision medicine (PM) to the forefront for healthcare providers, researchers, regulators, innovators, and funders alike. As technologies continue to evolve and datasets grow in magnitude, a strong computational infrastructure will be essential to realize PM’s vision of improved healthcare derived from personal data. In addition, informatics research and innovation affords a tremendous opportunity to drive the science underlying PM. The informatics community must lead the development of technologies and methodologies that will increase the discovery and application of biomedical knowledge through close collaboration between researchers, clinicians, and patients. This perspective highlights seven key areas that are in need of further informatics research and innovation to support the realization of PM.