Kolb, Anders

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.

Background: Somatic mutations in the IDH genes are common in acute myeloid leukemia (AML). Mutations occur at active site arginine residues in IDH1 (R132) and IDH2 (R140, R172). IDH inhibitors, ivosidenib (IDH1) and enasidenib (IDH2), have shown improved clinical outcomes in patients with relapsed/refractory IDH-mutant AML and are approved for use in this setting, while investigations in combination with chemotherapy are underway in de novo AML. The prognostic significance of IDH mutations remains controversial. We hypothesize that refining our understanding of IDH-mutated AML will contribute to risk-adapted treatment strategies, including optimal use of IDH-targeted agents. The objective of our study was to identify characteristics that affect outcome in de novo IDH-mutated AML across the age spectrum utilizing a large cohort of patients enrolled on several pediatric and adult trials. Methods: The total cohort (N=3588) included patients age <1 month - 88 years. Pediatric and young adult (YA) patients were treated on recent CCG/COG AML trials (CCG2961, COG 03P1, 0531, 1031, N=2231) and YA/adult patients were treated on SWOG S0106 (N=396), ECOG E1900 AML trials (N=398), Beat AML (N=363), or included in the TCGA biology study (N=200; outcomes not evaluated for this group). Patients were analyzed according to three defined age groups: "younger" 0-29 years of age (N=2401), "intermediate" 30-59 years of age (N=819) and "older" 60 years of age and above (N=319). Data regarding clinical characteristics and treatment outcomes were collected and evaluated according to the standard practices of each cooperative or research groups for the respective studies. Mutational profiling was performed by targeted sequencing for patient samples from COG trials, Beat-AML, ECOG, and SWOG; whole-genome or whole-exome sequencing for the TCGA cohort. Prevalence of IDH mutations, co-occurring mutations, and outcomes (5-year event-free survival [EFS]) were analyzed across the defined age groups. Results: The prevalence of IDH mutations among the entire cohort was 8.6% (N=276). Analysis according to mutation type demonstrated that IDH2 mutations comprised 57% (N=158) and IDH1 mutations 43% (N=118). The prevalence of IDH mutations was strongly correlated with increased age (Fig 1A); according to the age-defined cohorts was 4.0% (N=82) in younger, 15.2% (N=126) in intermediate, and 20.3% (N=65) in older patients (p<0.001). The co-occurring mutational profile demonstrated that IDH mutations commonly co-occurred with NPM1,DNMT3A, and FLT3-ITD mutations (Fig 1B). Among IDH-mutant patients, 48% (N=132) harbored dual mutations (IDHmut/NPM1mut); 11.6% (N=32) triple mutations (IDHmut/NPM1mut/DNMT3Amut), the latter particularly prevalent in intermediate-aged adults (N=27/32, 85%). Analysis of the cohort with outcome data (N=2824) demonstrated that IDHmut and IDH-WT patients experienced similar EFS of 39% vs. 40%, respectively (p=0.723). Given the favorable prognostic significance of NPM1, we subsequently analyzed outcomes of this dual mutant group and found that NPM1 mutations retained favorable prognostic impact in the context of IDH mutant patients (Fig 2A). Notably, this effect was age-dependent, as those with IDHmut/NPM1mut had a favorable EFS compared to IDHmut/NPM1-WT for younger (76% vs. 24%, p<0.001) and intermediate patients (43% vs. 15%, p=0.001, Fig 2B) but this favorable effect was lost in older patients (29% vs. 34%, p=0.456, Fig 2C). Among intermediate age patients, outcome was further stratified by DNMT3A status, and IDHmut/NPM1mut/DNMT3Amut patients experienced an inferior EFS of 25% vs. 57% in IDHmut/NPMmut (p=0.003, Fig 2D). Conclusion: Analysis of this large patient cohort provides the most comprehensive description of IDH mutations in AML across the age spectrum. We confirm age-associated prevalence of IDH mutations and frequent co-occurrence with NPM1 mutation in all ages and in further combination with DNMT3A mutation in intermediate-aged adults. We definitively demonstrate that IDH mutation status is not an independent prognostic determinant of outcome in any age group. Co-occurrence of NPM1 and IDH mutations favorably impacts outcome in patients < 60 years of age with AML, particularly in the absence of DNMT3A mutation. Our data support that IDH inhibitors may be of particular interest in older adults and in patients <60 according to co-occurring NPM1 and DNMT3A mutations. Disclosures Othus: Marck: Consultancy; Daiichi Sankyo: Consultancy; Celgene: Membership on an entity's Board of Directors or advisory committees; Glycomimetics: Membership on an entity's Board of Directors or advisory committees. Radich:Jazz: Consultancy; Novartis Pharmaceuticals Corporation: Consultancy, Research Funding; Amgen: Consultancy; Bristol-Myers Squibb: Consultancy. Abdel-Wahab:Merck: Consultancy; Janssen: Consultancy; Envisagenics Inc.: Current equity holder in private company; H3 Biomedicine Inc.: Consultancy, Research Funding. Tallman:UpToDate: Patents & Royalties; ADC Therapeutics: Research Funding; BioSight: Membership on an entity's Board of Directors or advisory committees, Research Funding; Glycomimetics: Research Funding; Rafael: Research Funding; Amgen: Research Funding; Bioline rx: Membership on an entity's Board of Directors or advisory committees; Daiichi-Sankyo: Membership on an entity's Board of Directors or advisory committees; KAHR: Membership on an entity's Board of Directors or advisory committees; Rigel: Membership on an entity's Board of Directors or advisory committees; Delta Fly Pharma: Membership on an entity's Board of Directors or advisory committees; Oncolyze: Membership on an entity's Board of Directors or advisory committees; Jazz Pharma: Membership on an entity's Board of Directors or advisory committees; Roche: Membership on an entity's Board of Directors or advisory committees; Novartis: Membership on an entity's Board of Directors or advisory committees; Abbvie: Research Funding; Cellerant: Research Funding; Orsenix: Research Funding. Atallah:Jazz: Consultancy; Genentech: Consultancy; Abbvie: Consultancy; Takeda: Consultancy, Research Funding; Pfizer: Consultancy; Novartis Pharmaceutical Corporation: Consultancy. Luger:Daiichi-Sankyo: Honoraria; Pfizer: Honoraria; Bristol-Myers Squibb: Honoraria; Acceleron: Honoraria; Agios: Honoraria; Loxo Oncology: Honoraria; Onconova: Research Funding; Kura: Research Funding; Biosight: Research Funding; Ariad: Research Funding; Hoffman La Roche: Research Funding. Levine:Novartis: Consultancy; Loxo: Current equity holder in private company, Membership on an entity's Board of Directors or advisory committees; Morphosys: Consultancy; Astellas: Consultancy; Janssen: Consultancy; Prelude Therapeutics: Research Funding; Amgen: Honoraria; Gilead: Honoraria; Lilly: Consultancy, Honoraria; Qiagen: Current equity holder in publicly-traded company, Membership on an entity's Board of Directors or advisory committees; Imago: Current equity holder in private company, Membership on an entity's Board of Directors or advisory committees; C4 Therapeutics: Current equity holder in private company, Membership on an entity's Board of Directors or advisory committees; Isoplexis: Current equity holder in private company, Membership on an entity's Board of Directors or advisory committees; Celgene: Consultancy, Honoraria, Research Funding; Roche: Consultancy, Honoraria, Research Funding. Cooper:Celgene: Other: Spouse was an employee of Celgene (through August 2019).