CAP TODAY Pathology/Laboratory Medicine/Laboratory Management
Editors: Donna E. Hansel, MD, PhD, chair of pathology, Oregon Health and Science University, Portland; Richard D. Press, MD, PhD, professor and director of molecular pathology, OHSU; James Solomon, MD, PhD, assistant professor, Department of Pathology and Laboratory Medicine, Weill Cornell Medicine, New York; Sounak Gupta, MBBS, PhD, senior associate consultant, Mayo Clinic, Rochester, Minn.; Erica Reinig, MD, assistant professor and medical director of molecular diagnostics, University of Wisconsin-Madison; and Marcela Riveros Angel, MD, molecular genetic pathology fellow, Department of Pathology, OHSU.
Relationship between clone metrics and clinical outcome in clonal cytopenia
December 2021—Advances in sequencing technologies, such as next-generation sequencing, have yielded many insights into the genomic landscape and clinical import of molecular findings in myelodysplastic syndromes and other myeloid neoplasms with myelodysplasia (MN). Given the limitations often encountered with bone marrow assessment for dysplasia, there is value in demonstrating the clonal nature of hematopoiesis to provide insight into disorders that do not fulfill the diagnostic criteria for myeloid malignancy. However, additional evidence is needed to guide the use of molecular profiling in identifying clonal abnormalities and distinguishing between clonal hematopoiesis of indeterminate potential (CHIP), clonal cytopenia of uncertain significance (CCUS), and myelodysplastic syndrome or MN. Using a next-generation sequencing panel of 40 myeloid-associated genes, the authors conducted a study in which they examined the molecular profiles, hematologic phenotypes, and clinical outcomes of a prospective cohort of patients. This included 311 patients with idiopathic cytopenia of undetermined significance (ICUS); 532 community-dwelling individuals 60 years or older without hematologic phenotypes (n = 355) or with unexplained anemia (n = 177); and 592 patients with MN. Differences in mutation patterns, variant allele frequencies (clone metrics), and risk of progression were observed in the conditions studied. Ninety-two of the 311 (30 percent) patients with ICUS carried at least one somatic genetic lesion that signaled CCUS, and there was a significant association observed between mutation status, number of mutations per subject, and cumulative incidence of progression to MN. Patients harboring mutations in splicing factors, ASXL1, or TET2 showed a significantly increased risk of progression to MN, while patients with a DNMT3A mutation did not. No significant difference in risk of progression to MN was noted between patients without mutations and patients with mutations who had a variant allele frequency of less than 0.1. However, risk was significantly increased in those patients with mutations who had a variant allele frequency greater than 0.1. In the community-dwelling study population, those with anemia showed a higher prevalence of mutations in genes other than the DTA genes (DNMT3A, TET2, and ASXL1), including mutations in SF3B1 and other splicing factors, as well as a higher prevalence of co-mutations of DTA and other genes. Furthermore, SF3B1 mutations and co-mutation patterns involving SF3B1, U2AF1, and TP53 with other genes showed high specificity and positive predictive value for MN. Unsupervised clustering analysis based on mutation profiles identified two major clusters. The first was characterized by isolated DNMT3A mutations (CH-like cluster), and the second was characterized by a combination of mutations or isolated mutations in TET2, ASXL1, and other less frequent drivers (MN-like cluster). The two clusters differed significantly with regard to overall survival and, in patients with CCUS, with regard to risk of progression to MN. Within the MN-like cluster, clinical diagnosis did not have a significant effect on clinical outcome. However, it did have a significant effect within the CH-like cluster, with MN patients showing a shorter overall survival rate than CHIP and CCUS patients. This study supports the underlying genetic heterogeneity within CHIP, CCUS, and myelodysplastic syndrome and identifies mutation patterns and clonal metrics that may aid in classifying various hematopoietic clones based on the potential for disease and likely clinical behavior. The findings identified key variables predicted to effect outcomes, including the number of mutations, type/pattern of mutations, and variant allele frequency. Overall, the authors’ observations are concordant with previous studies, which have also shown distinct patterns of mutations and variant allele frequencies at differing stages of clonal hematopoiesis. The authors concluded that this study provides further insight into how molecular profiling may facilitate diagnosis and inform clinical management in patients with clonal cytopenia.
Gallì A, Todisco G, Catamo E, et al. Relationship between clone metrics and clinical outcome in clonal cytopenia. Blood. 2021;138(11):965–976. doi: 10.1182/blood.2021011323
Correspondence: Dr. Luca Malcovati at luca.malcovati@unipv.it
A genomewide association study to identify new risk loci for Alzheimer disease
Alzheimer disease is the most common form of dementia in European populations, representing 50 to 70 percent of all dementia cases. Nearly all patients are diagnosed after age 65 (late-onset AD), with only one percent of cases present before age 65 (early-onset AD). Twin studies have suggested that genetics drive a large proportion of individual risk for late-onset AD. Its heritability is believed to be spread across hundreds, or even thousands, of genetic variants, only a fraction of which have been identified. Genomewide association studies using larger sample sizes can improve the statistical power to identify causal variants. However, recruitment of patients with late-onset AD for such studies can be difficult due to advanced patient age at disease onset, which supports the case for including younger people as proxy cases by estimating their risk of late-onset AD using parental status. The authors performed a genomewide association study that involved a meta-analysis of data from 13 cohorts, including 90,338 (46,613 proxy) cases and 1,036,225 (318,246 proxy) controls to identify risk loci. The study used gene-set analysis, tissue and single-cell specificity analysis, colocalization, and fine-mapping to determine biologic mechanisms of genetic variants and late-onset AD pathology. The meta-analysis identified 38 independent loci with 3,915 significant variants. Seven of the 38 loci had not been associated with late-onset AD in prior genomewide association studies, and five of them had not previously been associated with any form of dementia. The latter included AGRN (role in formation and maintenance of neuromuscular junction, direction of polysynaptic differentiation, and depolarization of CNS synapses), TNIP1 (role in autoimmunity and hyperinflammation), HAVCR2 (role in immune modulation and mediation of apoptosis, implicated interaction with amyloid precursor protein), NTN5 (role in neurogenesis), and LILRB2 (role in mediation of immune activation, inhibition of axonal regeneration, and amyloid binding). The other two loci—TMEM106B and GRN—have been implicated in frontotemporal dementia. A combination of tissue-specificity and cell-type results identified microglia and immune tissues as potential experimental models for identifying the contribution of late-onset AD-associated genes to late-onset AD pathogenesis. Gene-set analysis identified biologic pathways that had independent late-onset AD association, highlighting the role of late-onset AD-associated genes in amyloid and tau plaque formation, protein catabolism of plaques, and immune cell recruitment and activation. Due to its large size, this study was able to identify previously unknown late-onset AD-associated loci, prioritize causal genes of interest, and provide support for the role of immune cells and microglia in the pathogenesis of late-onset AD. However, the study has limitations. Based on studies defining power curves for late-onset AD genomewide association studies, the authors estimated that the size of their meta-analysis is only powered to explain approximately six percent of genetic variance outside of chromosome 19 and 58.9 percent of genetic variance on chromosome 19. Of note, chromosome 19 contains the large APOE gene, which encodes for apolipoprotein E and is implicated in Alzheimer disease. Furthermore, the findings of this study have limited applicability in non-European populations. Larger sample size genomewide association studies, along with continued reporting of rare variants, copy number variants, and epigenetic studies in more diverse populations, would provide additional insight into late-onset AD pathogenesis and help identify risk loci.