grant

'Omics predictors of Sickle Cell Severity and Survival

Organization DUKE UNIVERSITYLocation DURHAM, UNITED STATESPosted 1 Aug 2024Deadline 31 Jul 2026
NIHUS FederalResearch GrantFY202421+ years oldActive Follow-upAddressAdultAdult HumanAffectAfrican American groupAfrican American individualAfrican American peopleAfrican American populationAfrican AmericansAgeAged, 80 and overAgingAnimal ModelAnimal Models and Related StudiesAttentionB-globinBiologicalBiological MarkersBlood PlasmaBlood leukocyteCNS Nervous SystemCardiovascular DiseasesCaringCause of DeathCentral Nervous SystemCessation of lifeCharacteristicsClinicalClinical DataCohort StudiesComplexConcurrent StudiesDNA copy numberDataDeathDeoxygenated Sickle HemoglobinDeoxyhemoglobin SDepositDepositionDeteriorationDiseaseDisease ProgressionDisorderDysfunctionEventFetal HbFetal HemoglobinFrequenciesFunctional disorderGenetic AlterationGenetic ChangeGenetic defectGlycopeptidesGoalsHaplogroupHb SS diseaseHbFHbSS diseaseHealthHeartHematopoiesisHematopoietic Cell TumorHematopoietic Cellular Control MechanismsHematopoietic MalignanciesHematopoietic NeoplasmsHematopoietic Neoplasms including LymphomasHematopoietic TumorHematopoietic and Lymphoid Cell NeoplasmHematopoietic and Lymphoid NeoplasmsHemoglobin FHemoglobin S DiseaseHemoglobin sickle cell diseaseHemoglobin sickle cell disorderHemolysisImmune GlobulinsImmunoglobulinsIndividualInflammation MediatorsInflammatoryKidneyKidney DiseasesKidney Urinary SystemLaboratoriesLengthLeukocytesLeukocytes Reticuloendothelial SystemLife ExpectancyLinkLiverLungLung Respiratory SystemMalignant Hematopoietic NeoplasmMarrow leukocyteMass Photometry/Spectrum AnalysisMass SpectrometryMass SpectroscopyMass SpectrumMass Spectrum AnalysesMass Spectrum AnalysisMeasuresMetabolicMetabolic GlycosylationMiceMice MammalsMitochondriaMitochondrial DNAModelingMolecularMurineMusMutationNHLBINational Heart, Lung, and Blood InstituteNatureNephropathyNeuraxisOldest OldOrganOrganism-Level ProcessOrganismal ProcessOutcomePatientsPeptidesPhenotypePhysical FunctionPhysiologicPhysiologic ProcessesPhysiologicalPhysiological ProcessesPhysiopathologyPlasmaPlasma ProteinsPlasma SerumPolymersPopulationPost-Translational Modification Protein/Amino Acid BiochemistryPost-Translational ModificationsPost-Translational Protein ModificationPost-Translational Protein ProcessingPosttranslational ModificationsPosttranslational Protein ProcessingPremature AgingPremature MortalityPremature aging syndromePrognosisProtein ModificationProteinsProteomicsRenal DiseaseReticuloendothelial System, Serum, PlasmaRiskRisk FactorsRoleSamplingSeveritiesSeverity of illnessSickle CellSickle Cell AnemiaSystemTOPMedTrans-Omics for Precision MedicineWhite Blood CellsWhite CellWorkaccelerated agingaccelerated biological ageaccelerated biological agingactive followupadulthoodage accelerationage clockagesaging biological markeraging biomarkeraging clocksaging markerbeta Globinbio-markersbiologicbiologic markerbiomarkerblood cancerblood cell formationcancer of bloodcancer of the bloodcardiovascular disorderclock measuring biological ageclock measuring biological agingclock of biological agingcohortcomputer based predictiondamage to kidneydeoxy-HbSdepositorydisease severityentire genomeerythrolysisfetal form of hemoglobinfetal globinfollow upfollow-upfollowed upfollowupfull genomegenome mutationgenome sequencingglycoproteomicsglycosylationhepatic body systemhepatic organ systemheteroplasmyimprovedinflammatory mediatorkidney damagekidney disorderlife spanlifespanmachine learning based methodmachine learning methodmachine learning methodologiesmitochondrialmodel of animalmolecular biomarkermolecular markermortalitymtDNAmultiomicsmultiple omicsnovelpace of agingpace of biological agingpanomicspathophysiologypatient subclasspatient subclusterpatient subgroupspatient subpopulationspatient subsetspatient subtypespersonalization of treatmentpersonalized medicinepersonalized therapypersonalized treatmentpolymerpolymericpolymerizationprecision medicineprecision-based medicinepredictive modelingprognostic profileprognostic signatureprogramspulmonaryrate of agingrate of biological agingrenalrenal damagerenal disorderrepositorysickle RBCsickle cell diseasesickle cell disordersickle deoxyhemoglobinsickle diseasesickle erythrocytesickle red blood cellsicklemiasocial rolespeed of agingspeed of the agingstudy populationtelomeretherapeutic targetwhite blood cellwhite blood corpusclewhole genomeβ-globin
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Full Description

ABSTRACT
Sickle cell disease (SCD) results in premature aging and early mortality. Although we (using >15 years follow up

[f/u]) and others have shown that life expectancy in SCD has improved, adults with SCD still have a life

expectancy of only 58 years. Early mortality is associated with SCD-related end-organ damage, especially to the

heart, lung, kidneys and central nervous system, as well as with vaso-occlusive event frequency and biomarkers

such as sVCAM-1. Most remarkable, however, is that adults with SCD >50 years (now 13% of adults with SCD)

have physical function similar to non-SCD adults over the age of 80. While frequency of death peaks in the 5th

decade, a subpopulation of patients live into their 70's. Yet little is currently known about how best to evaluate

and care for SCD patients over age 50 or predict which patients will achieve that milestone. We hypothesize that

multi-omics, by representing several SCD-related and unrelated physiologic processes, strongly determine-by

direct and indirect effects-both SCD organ severity and survival. Analysis of these relationships can inform our

understanding of the variability in survival and the pace of aging in SCD. Elucidating the multi-omic contributions

to SCD severity and mortality will also be critical for developing models of assessment and care for this

population. NHLBl's TOPMed program is an extraordinary opportunity to facilitate personalized medicine for

SCD, including improving our understanding of factors affecting severity and mortality. Our cohort (OMG-SCD),

together with other TOPMed SCD cohorts, total >4000 samples with whole genome sequence (WGS) results

and rich clinical data, including organ-function phenotypes and clinical laboratory data; several studies also have

survival data. The OMG-SCD cohort also has stored plasma samples, some of which have previously been used

to identify proteins associated with kidney damage. Plasma protein activity can be modulated by N-linked

glycosylation and thus contributes to health and aging. Yet the role of proteomics and N-linked glycosylation is

unexplored in the context of aging in SCD. Discovery of proteomic biomarkers could illuminate the underlying

biologic mechanisms of accelerated aging and mortality in SCD. Here, we propose to: (1) Identify novel clinical

and 'omic risk factors, including telomere length, mitochondrial copy number, and clonal hematopoiesis, for organ

dysfunction and early mortality and (2) Identify proteomic and glycoproteomic biomarkers for premature mortality.

Our work is poised to yield significant discoveries regarding the nature of aging and to identify 'omic risk factors

of poor prognosis in SCD, thus facilitating precision medicine-guided care models in SCD.

Grant Number: 1R21AG084916-01A1
NIH Institute/Center: NIH

Principal Investigator: ALLISON ASHLEY-KOCH

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