Scoping Review of Factors Associated with Stem Cell Mobilization and Collection in Allogeneic Stem Cell Donors.

There is wide interindividual variation in the efficacy of CD34+ cell mobilization and collection in healthy allogenic hematopoietic stem cell donors. Donor characteristics, blood cell counts, and various factors related to mobilization and collection have been associated with blood CD34+ cell count and CD34+ cell yield after granulocyte colony-stimulating factor (G-CSF) mobilization and collection. Given the heterogenous nature of the literature reporting these associations, in this scoping review we clarify the determinants of CD34+ count and yield. Studies published between 2000 and 2023 reporting allogeneic donors undergoing G-CSF mobilization and peripheral blood stem cell (PBSC) collection were evaluated. Eligible studies were those that assessed blood CD34+ cell count or CD34+ cell yield in the first PBSC collection after mobilization with 4 or 5 days of G-CSF treatment. Associations were recorded between these outcomes and donor factors (age, sex, weight, ethnicity), mobilization factors (G-CSF scheduling or dose), collection factors (venous access, processed blood volume [PBV]) or laboratory factors (blood cell counts at baseline or after mobilization). The 52 studies evaluated between 15 and 20,884 donors. Forty-three studies were retrospective, 33 assessed blood CD34+ cell counts, and 39 assessed CD34+ cell yield from PBSCs. Blood CD34+ cell counts consistently predicted CD34+ cell yield. Younger donors usually had higher blood CD34+ cell counts and CD34+ cell yield. Most studies that investigated the effect of donor ancestry found that donors of non-European ancestry had higher blood CD34+ cell counts after mobilization and higher CD34+ cell yields from collection. The poor consensus about the best predictors of blood CD34+ cell count and yield necessitates further prospective studies, particularly of the role of donor ancestry. The current focus on donor sex as a major predictor requires re-evaluation.

Rare disease gene association discovery from burden analysis of the 100,000 Genomes Project data.

To discover rare disease-gene associations, we developed a gene burden analytical framework and applied it to rare, protein-coding variants from whole genome sequencing of 35,008 cases with rare diseases and their family members recruited to the 100,000 Genomes Project (100KGP). Following in silico triaging of the results, 88 novel associations were identified including 38 with existing experimental evidence. We have published the confirmation of one of these associations, hereditary ataxia with UCHL1 , and independent confirmatory evidence has recently been published for four more. We highlight a further seven compelling associations: hypertrophic cardiomyopathy with DYSF and SLC4A3 where both genes show high/specific heart expression and existing associations to skeletal dystrophies or short QT syndrome respectively; monogenic diabetes with UNC13A with a known role in the regulation of ß cells and a mouse model with impaired glucose tolerance; epilepsy with KCNQ1 where a mouse model shows seizures and the existing long QT syndrome association may be linked; early onset Parkinson's disease with RYR1 with existing links to tremor pathophysiology and a mouse model with neurological phenotypes; anterior segment ocular abnormalities associated with POMK showing expression in corneal cells and with a zebrafish model with developmental ocular abnormalities; and cystic kidney disease with COL4A3 showing high renal expression and prior evidence for a digenic or modifying role in renal disease. Confirmation of all 88 associations would lead to potential diagnoses in 456 molecularly undiagnosed cases within the 100KGP, as well as other rare disease patients worldwide, highlighting the clinical impact of a large-scale statistical approach to rare disease gene discovery.