Integrative multi-omics analyses to identify the genetic and functional mechanisms underlying ovarian cancer risk regions.

To identify credible causal risk variants (CCVs) associated with different histotypes of epithelial ovarian cancer (EOC), we performed genome-wide association analysis for 470,825 genotyped and 10,163,797 imputed SNPs in 25,981 EOC cases and 105,724 controls of European origin. We identified five histotype-specific EOC risk regions (p value <5 × 10-8) and confirmed previously reported associations for 27 risk regions. Conditional analyses identified an additional 11 signals independent of the primary signal at six risk regions (p value <10-5). Fine mapping identified 4,008 CCVs in these regions, of which 1,452 CCVs were located in ovarian cancer-related chromatin marks with significant enrichment in active enhancers, active promoters, and active regions for CCVs from each EOC histotype. Transcriptome-wide association and colocalization analyses across histotypes using tissue-specific and cross-tissue datasets identified 86 candidate susceptibility genes in known EOC risk regions and 32 genes in 23 additional genomic regions that may represent novel EOC risk loci (false discovery rate <0.05). Finally, by integrating genome-wide HiChIP interactome analysis with transcriptome-wide association study (TWAS), variant effect predictor, transcription factor ChIP-seq, and motifbreakR data, we identified candidate gene-CCV interactions at each locus. This included risk loci where TWAS identified one or more candidate susceptibility genes (e.g., HOXD-AS2, HOXD8, and HOXD3 at 2q31) and other loci where no candidate gene was identified (e.g., MYC and PVT1 at 8q24) by TWAS. In summary, this study describes a functional framework and provides a greater understanding of the biological significance of risk alleles and candidate gene targets at EOC susceptibility loci identified by a genome-wide association study.

Single-cell mutation analysis of clonal evolution in myeloid malignancies.

Myeloid malignancies, including acute myeloid leukaemia (AML), arise from the expansion of haematopoietic stem and progenitor cells that acquire somatic mutations. Bulk molecular profiling has suggested that mutations are acquired in a stepwise fashion: mutant genes with high variant allele frequencies appear early in leukaemogenesis, and mutations with lower variant allele frequencies are thought to be acquired later1-3. Although bulk sequencing can provide information about leukaemia biology and prognosis, it cannot distinguish which mutations occur in the same clone(s), accurately measure clonal complexity, or definitively elucidate the order of mutations. To delineate the clonal framework of myeloid malignancies, we performed single-cell mutational profiling on 146 samples from 123 patients. Here we show that AML is dominated by a small number of clones, which frequently harbour co-occurring mutations in epigenetic regulators. Conversely, mutations in signalling genes often occur more than once in distinct subclones, consistent with increasing clonal diversity. We mapped clonal trajectories for each sample and uncovered combinations of mutations that synergized to promote clonal expansion and dominance. Finally, we combined protein expression with mutational analysis to map somatic genotype and clonal architecture with immunophenotype. Our findings provide insights into the pathogenesis of myeloid transformation and how clonal complexity evolves with disease progression.

Estimation of intrafamilial DNA contamination in family trio genome sequencing using deviation from Mendelian inheritance.

With the increasing number of sequencing projects involving families, quality control tools optimized for family genome sequencing are needed. However, accurately quantifying contamination in a DNA mixture is particularly difficult when genetically related family members are the sources. We developed TrioMix, a maximum likelihood estimation (MLE) framework based on Mendel's law of inheritance, to quantify DNA mixture between family members in genome sequencing data of parent-offspring trios. TrioMix can accurately deconvolute any intrafamilial DNA contamination, including parent-offspring, sibling-sibling, parent-parent, and even multiple familial sources. In addition, TrioMix can be applied to detect genomic abnormalities that deviate from Mendelian inheritance patterns, such as uniparental disomy (UPD) and chimerism. A genome-wide depth and variant allele frequency plot generated by TrioMix facilitates tracing the origin of Mendelian inheritance deviations. We showed that TrioMix could accurately deconvolute genomes in both simulated and real data sets.

ArCH: improving the performance of clonal hematopoiesis variant calling and interpretation.

MOTIVATION: The acquisition of somatic mutations in hematopoietic stem and progenitor stem cells with resultant clonal expansion, termed clonal hematopoiesis (CH), is associated with increased risk of hematologic malignancies and other adverse outcomes. CH is generally present at low allelic fractions, but clonal expansion and acquisition of additional mutations leads to hematologic cancers in a small proportion of individuals. With high depth and high sensitivity sequencing, CH can be detected in most adults and its clonal trajectory mapped over time. However, accurate CH variant calling is challenging due to the difficulty in distinguishing low frequency CH mutations from sequencing artifacts. The lack of well-validated bioinformatic pipelines for CH calling may contribute to lack of reproducibility in studies of CH. RESULTS: Here, we developed ArCH, an Artifact filtering Clonal Hematopoiesis variant calling pipeline for detecting single nucleotide variants and short insertions/deletions by combining the output of four variant calling tools and filtering based on variant characteristics and sequencing error rate estimation. ArCH is an end-to-end cloud-based pipeline optimized to accept a variety of inputs with customizable parameters adaptable to multiple sequencing technologies, research questions, and datasets. Using deep targeted sequencing data generated from six acute myeloid leukemia patient tumor: normal dilutions, 31 blood samples with orthogonal validation, and 26 blood samples with technical replicates, we show that ArCH improves the sensitivity and positive predictive value of CH variant detection at low allele frequencies compared to standard application of commonly used variant calling approaches. AVAILABILITY AND IMPLEMENTATION: The code for this workflow is available at: https://github.com/kbolton-lab/ArCH.

Tracking the evolution of therapy-related myeloid neoplasms using chemotherapy signatures.

Patients treated with cytotoxic therapies, including autologous stem cell transplantation, are at risk for developing therapy-related myeloid neoplasms (tMN). Preleukemic clones (ie, clonal hematopoiesis [CH]) are detectable years before the development of these aggressive malignancies, although the genomic events leading to transformation and expansion are not well defined. Here, by leveraging distinctive chemotherapy-associated mutational signatures from whole-genome sequencing data and targeted sequencing of prechemotherapy samples, we reconstructed the evolutionary life-history of 39 therapy-related myeloid malignancies. A dichotomy was revealed, in which neoplasms with evidence of chemotherapy-induced mutagenesis from platinum and melphalan were hypermutated and enriched for complex structural variants (ie, chromothripsis), whereas neoplasms with nonmutagenic chemotherapy exposures were genomically similar to de novo acute myeloid leukemia. Using chemotherapy-associated mutational signatures as temporal barcodes linked to discrete clinical exposure in each patient's life, we estimated that several complex events and genomic drivers were acquired after chemotherapy was administered. For patients with prior multiple myeloma who were treated with high-dose melphalan and autologous stem cell transplantation, we demonstrate that tMN can develop from either a reinfused CH clone that escapes melphalan exposure and is selected after reinfusion, or from TP53-mutant CH that survives direct myeloablative conditioning and acquires melphalan-induced DNA damage. Overall, we revealed a novel mode of tMN progression that is not reliant on direct mutagenesis or even exposure to chemotherapy. Conversely, for tMN that evolve under the influence of chemotherapy-induced mutagenesis, distinct chemotherapies not only select preexisting CH but also promote the acquisition of recurrent genomic drivers.

Genomic profiling identifies somatic mutations predicting thromboembolic risk in patients with solid tumors.

Venous thromboembolism (VTE) associated with cancer (CAT) is a well-described complication of cancer and a leading cause of death in patients with cancer. The purpose of this study was to assess potential associations of molecular signatures with CAT, including tumor-specific mutations and the presence of clonal hematopoiesis. We analyzed deep-coverage targeted DNA-sequencing data of >14 000 solid tumor samples using the Memorial Sloan Kettering-Integrated Mutation Profiling of Actionable Cancer Targets platform to identify somatic alterations associated with VTE. End point was defined as the first instance of cancer-associated pulmonary embolism and/or proximal/distal lower extremity deep vein thrombosis. Cause-specific Cox proportional hazards regression was used, adjusting for pertinent clinical covariates. Of 11 695 evaluable individuals, 72% had metastatic disease at time of analysis. Tumor-specific mutations in KRAS (hazard ratio [HR], 1.34; 95% confidence interval (CI), 1.09-1.64; adjusted P = .08), STK11 (HR, 2.12; 95% CI, 1.55-2.89; adjusted P < .001), KEAP1 (HR, 1.84; 95% CI, 1.21-2.79; adjusted P = .07), CTNNB1 (HR, 1.73; 95% CI, 1.15-2.60; adjusted P = .09), CDKN2B (HR, 1.45; 95% CI, 1.13-1.85; adjusted P = .07), and MET (HR, 1.83; 95% CI, 1.15-2.92; adjusted P = .09) were associated with a significantly increased risk of CAT independent of tumor type. Mutations in SETD2 were associated with a decreased risk of CAT (HR, 0.35; 95% CI, 0.16-0.79; adjusted P = .09). The presence of clonal hematopoiesis was not associated with an increased VTE rate. This is the first large-scale analysis to elucidate tumor-specific genomic events associated with CAT. Somatic tumor mutations of STK11, KRAS, CTNNB1, KEAP1, CDKN2B, and MET were associated with an increased risk of VTE in patients with solid tumors. Further analysis is needed to validate these findings and identify additional molecular signatures unique to individual tumor types.

The proteome of clear cell ovarian carcinoma.

Clear cell ovarian carcinoma (CCOC) is the second most common subtype of epithelial ovarian carcinoma. Late-stage CCOC is not responsive to gold-standard chemotherapy and results in suboptimal outcomes for patients. In-depth molecular insight is urgently needed to stratify the disease and drive therapeutic development. We conducted global proteomics for 192 cases of CCOC and compared these with other epithelial ovarian carcinoma subtypes. Our results showed distinct proteomic differences in CCOC compared with other epithelial ovarian cancer subtypes including alterations in lipid and purine metabolism pathways. Furthermore, we report potential clinically significant proteomic subgroups within CCOC, suggesting the biologic plausibility of stratified treatment for this cancer. Taken together, our results provide a comprehensive understanding of the CCOC proteomic landscape to facilitate future understanding and research of this disease. © 2022 The Pathological Society of Great Britain and Ireland.

"All I was Thinking About was Shattered": Women's Experiences Transitioning Out of Anti-Trafficking Shelters During the COVID-19 Lockdown in Uganda.

Human trafficking is an egregious violation of fundamental human rights and a global challenge. The long-term harms to survivors' physical, psychological and social wellbeing are profound and well documented, and yet there are few studies exploring how to best promote resilience and holistic healing. This is especially true within shelter programs (where the majority of anti-trafficking services are provided) and during the transition out of residential shelter care, which is often a sensitive and challenging process. The current study begins to address this gap by centering the lived experiences of six women residing in a trafficking-specific shelter in Uganda as they unexpectedly transitioned back to their home communities due to the COVID-19 lockdown. We explore this pivotal moment in participants' post-trafficking journey, focusing on how these women described and interpreted their rapidly changing life circumstances-including leaving the shelter, adjusting back to the community setting, and simultaneously navigating the uncertainties of a global pandemic. Four core themes emerged from the analysis: economic insecurities as a cross-cutting hardship; intensification of emotional and physical symptoms; social disruptions; and sources of hope and resilience. By centering their personal stories of struggle and strength, we hope to elevate survivors' own accounts and draw on their insights to identify actionable considerations for future programming.

What to tell your patient with clonal hematopoiesis and why: insights from 2 specialized clinics.

Acquired genetic mutations in hematopoietic stem or progenitor cells can lead to clonal expansion and imbalanced blood cell production. Clonal hematopoiesis is exceptionally common with human aging, confers a risk of evolution to overt hematologic malignancy, and increases all-cause mortality and the risk of cardiovascular disease. The degree of risk depends on the specific mutant allele driving clonal expansion, number of mutations, mutant allele burden, and concomitant nongenetic risk factors (eg, hypertension or cigarette smoking). People with clonal hematopoiesis may come to clinical attention in a variety of ways, including during the evaluation of a possible hematologic malignancy, as an incidental discovery during molecular analysis of a nonhematologic neoplasm, after hematopoietic cell transplantation, or as a result of germline testing for inherited variants. Even though the risk of clonal progression or a cardiovascular event in an individual patient with clonal hematopoiesis may be low, the possibility of future clinical consequences may contribute to uncertainty and worry, because it is not yet known how to modify these risks. This review summarizes clinical considerations for patients with clonal hematopoiesis, including important points for hematologists to consider discussing with affected persons who may understandably be anxious about having a mutation in their blood that predisposes them to develop a malignancy, but which is significantly more likely to result in a myocardial infarction or stroke. The increasing frequency with which people with clonal hematopoiesis are discovered and the need for counseling these patients is driving many institutions to create specialized clinics. We describe our own experience with forming such clinics.

Association of clonal hematopoiesis mutations with clinical outcomes: A systematic review and meta-analysis.

Clonal hematopoiesis (CH) mutations are common among individuals without known hematologic disease. CH mutations have been associated with numerous adverse clinical outcomes across many different studies. We systematically reviewed the available literature for clinical outcomes associated with CH mutations in patients without hematologic disease. We searched PubMed, EMBASE, and Scopus for eligible studies. Three investigators independently extracted the data, and each study was verified by a second author. Risk of bias was assessed using the Newcastle-Ottawa Scale. We identified 32 studies with 56 cohorts that examine the association between CH mutations and clinical outcomes. We conducted meta-analyses comparing outcomes among individuals with and without detectable CH mutations. We conducted meta-analyses for cardiovascular diseases (nine studies; HR = 1.61, 95% CI = 1.26-2.07, p = .0002), hematologic malignancies (seven studies; HR = 5.59, 95% CI = 3.31-9.45, p < .0001), therapy-related myeloid neoplasms (four studies; HR = 7.55, 95% CI = 4.3-13.57, p < .001), and death (nine studies; HR = 1.34, 95% CI = 1.2-1.5, p < .0001). The cardiovascular disease analysis was further stratified by variant allele fraction (VAF) and gene, which showed a statistically significant association only with a VAF of ≥ 10% (HR = 1.42, 95% CI = 1.24-1.62, p < .0001), as well as statistically significant associations for each gene examined with the largest magnitude of effect found for CH mutations in JAK2 (HR = 3.5, 95% CI = 1.84-6.68, p < .0001). Analysis of the association of CH mutations with hematologic malignancy demonstrated a numeric stepwise increase in risk with increasing VAF thresholds. This analysis strongly supports the association of CH mutations with a clinically meaningful increased risk of adverse clinical outcomes among individuals without hematologic disease, particularly with increasing VAF thresholds.

Imputation and subset-based association analysis across different cancer types identifies multiple independent risk loci in the TERT-CLPTM1L region on chromosome 5p15.33.

Genome-wide association studies (GWAS) have mapped risk alleles for at least 10 distinct cancers to a small region of 63 000 bp on chromosome 5p15.33. This region harbors the TERT and CLPTM1L genes; the former encodes the catalytic subunit of telomerase reverse transcriptase and the latter may play a role in apoptosis. To investigate further the genetic architecture of common susceptibility alleles in this region, we conducted an agnostic subset-based meta-analysis (association analysis based on subsets) across six distinct cancers in 34 248 cases and 45 036 controls. Based on sequential conditional analysis, we identified as many as six independent risk loci marked by common single-nucleotide polymorphisms: five in the TERT gene (Region 1: rs7726159, P = 2.10 × 10(-39); Region 3: rs2853677, P = 3.30 × 10(-36) and PConditional = 2.36 × 10(-8); Region 4: rs2736098, P = 3.87 × 10(-12) and PConditional = 5.19 × 10(-6), Region 5: rs13172201, P = 0.041 and PConditional = 2.04 × 10(-6); and Region 6: rs10069690, P = 7.49 × 10(-15) and PConditional = 5.35 × 10(-7)) and one in the neighboring CLPTM1L gene (Region 2: rs451360; P = 1.90 × 10(-18) and PConditional = 7.06 × 10(-16)). Between three and five cancers mapped to each independent locus with both risk-enhancing and protective effects. Allele-specific effects on DNA methylation were seen for a subset of risk loci, indicating that methylation and subsequent effects on gene expression may contribute to the biology of risk variants on 5p15.33. Our results provide strong support for extensive pleiotropy across this region of 5p15.33, to an extent not previously observed in other cancer susceptibility loci.

Germline Predisposition in Hematologic Malignancies: Testing, Management, and Implications.

Although numerous barriers for clinical germline cancer predisposition testing exist, the increasing recognition of deleterious germline DNA variants contributing to myeloid malignancy risk is yielding steady improvements in referrals for testing and testing availability. Many germline predisposition alleles are common in populations, and the increasing number of recognized disorders makes inherited myeloid malignancy risk an entity worthy of consideration for all patients regardless of age at diagnosis. Germline testing is facilitated by obtaining DNA from cultured skin fibroblasts or hair bulbs, and cascade testing is easily performed via buccal swab, saliva, or blood. Increasingly as diagnostic criteria and clinical management guidelines include germline myeloid malignancy predisposition, insurance companies recognize the value of testing and provide coverage. Once an individual is recognized to have a deleterious germline variant that confers risk for myeloid malignancies, a personalized cancer surveillance plan can be developed that incorporates screening for other cancer risk outside of the hematopoietic system and/or other organ pathology. The future may also include monitoring the development of clonal hematopoiesis, which is common for many of these cancer risk disorders and/or inclusion of strategies to delay or prevent progression to overt myeloid malignancy. As research continues to identify new myeloid predisposition disorders, we may soon recommend testing for these conditions for all patients diagnosed with a myeloid predisposition condition.

A novel method for rapid estimation of active bone marrow dose for radiotherapy patients in epidemiological studies.

BACKGROUND: In a dedicated effort to improve the assessment of clonal hematopoiesis (CH) and study leukemia risk following radiotherapy, we are developing a large-scale cohort study among cancer patients who received radiation. To that end, it will be critical to analyze dosimetric parameters of red bone marrow (ABM) exposure in relation to CH and its progression to myeloid neoplasms, requiring reconstruction method for ABM doses of a large-scale patients rapidly and accurately. PURPOSE: To support a large-scale cohort study on the assessment of clonal hematopoiesis and leukemia risk following radiotherapy, we present a new method for the rapid reconstruction of ABM doses of radiotherapy among cancer patients. METHODS: The key idea of the presented method is to segment patient bones rapidly and automatically by matching a whole-body computational human phantom, in which the skeletal system is divided into 34 bone sites, to patient CT images via 3D skeletal registration. The automatic approach was used to segment site-specific bones for 40 radiotherapy patients. Also, we segmented the bones manually. The bones segmented both manually and automatically were then combined with the patient dose matrix calculated by the treatment planning system (TPS) to derive patient ABM dose. We evaluated the performance of the automatic method in geometric and dosimetric accuracy by comparison with the manual approach. RESULTS: The pelvis showed the best geometric performance [volume overlap fraction (VOF): 52% (mean) with 23% (σ) and average distance (AD): 0.8 cm (mean) with 0.5 cm (σ)]. The pelvis also showed the best dosimetry performance [absorbed dose difference (ADD): 0.7 Gy (mean) with 1.0 Gy (σ)]. Some bones showed unsatisfactory performances such as the cervical vertebrae [ADD: 5.2 Gy (mean) with 10.8 Gy (σ)]. This impact on the total ABM dose, however, was not significant. An excellent agreement for the total ABM dose was indeed observed [ADD: 0.4 Gy (mean) with 0.4 Gy (σ)]. The computation time required for dose calculation using our method was robust (about one minute per patient). CONCLUSIONS: We confirmed that our method estimates ABM doses across treatment sites accurately, while providing high computational efficiency. The method will be used to reconstruct patient-specific ABM doses for dose-response assessment in a large cohort study. The method can also be applied to prospective dose calculation within a clinical TPS to support clinical decision making at the point of care.

Predicting cytopenias, progression, and survival in patients with clonal cytopenia of undetermined significance: a prospective cohort study.

BACKGROUND: Somatic mutations are frequently reported in individuals with cytopenia but without a confirmed haematological diagnosis (clonal cytopenia of undetermined significance; CCUS). These patients have an increased risk of progression to a myeloid malignancy and worse overall survival than those with no such mutations. To date, studies have been limited by retrospective analysis or small patient numbers. We aimed to establish the natural history of CCUS by prospectively investigating outcome in a large, well defined patient cohort. METHODS: This prospective cohort study was conducted at the Haematological Malignancy Diagnostic Service, a diagnostic laboratory in Leeds, UK. Patients aged at least 18 years who were referred for investigation of cytopenia were eligible for inclusion; those with a history of myeloid malignancy were not eligible. Targeted sequencing was conducted alongside routine clinical testing. Baseline mutation analysis was then correlated with the main study outcomes: longitudinal blood counts, disease progression to a myeloid malignancy, and overall survival with a median follow-up of 4·54 years (IQR 4·03-5·04). Data were collected manually from hospital records or extracted from laboratory or clinical outcome databases. FINDINGS: Bone marrow samples from 2348 patients were received at the Haematological Malignancy Diagnostic Service between July 1, 2014, and July 31, 2016. Of these, 2083 patients (median age 72 years [IQR 63-80, range 18-99]; 854 [41·0%] female and 1229 [59·0%] male) met the inclusion criteria and had samples of sufficient quality for further analysis. 598 (28·7%) patients received a diagnosis on the basis of their biopsy sample, whereas 1485 (71·3%) samples were classified as non-diagnostic; of these, CCUS was confirmed in 400 (26·9%) patients (256 [64·0%] male and 144 [36·0%] female). TET2, SRSF2, and DNMT3A were the most frequently mutated genes in patients with CCUS, with 320 (80%) of 400 patients harbouring a mutation in at least one of these genes. Age (p<0·0001), sex (p=0·0027), and mutations in ASXL1 (p=0·0009), BCOR (p=0·0056), and TP53 (p=0·0055) correlated with a worse overall survival; however, the number of mutations was the strongest predictor for progression to a myeloid malignancy (two mutations, p=0·0024; three or more mutations, p=0·0004). Extended sequencing of samples from a subgroup of patients with sequential samples and no mutations in the initial myeloid gene panel showed recurrent mutations in both DDX41 and UBA1, suggesting that these genes should be included in clinical test panels. INTERPRETATION: Mutation analysis is advised in patients who have undergone bone marrow examination and have an otherwise-unexplained cytopenia. High-risk genetic mutations and increased numbers of mutations are predictive of both survival and progression within 5 years of presentation, warranting clinical surveillance and, when necessary, intervention. FUNDING: MDS Foundation.

Impact of Cancer Therapy on Clonal Hematopoiesis Mutations and Subsequent Clinical Outcomes.

Exposure to cancer therapies is associated with an increased risk of clonal hematopoiesis (CH). The objective of our study was to investigate the genesis and evolution of CH following cancer therapy. In this prospective study, we undertook error-corrected duplex DNA sequencing in blood samples collected prior to and at two timepoints following chemoradiation in patients with esophageal or lung cancer recruited from 2013-2018. We applied a customized workflow to identify the earliest changes in CH mutation count and clone size and determine their association with clinical outcomes. Our study included 29 patients (87 samples). Their median age was 67 years, 76% (n = 22) were male; the median follow-up period was 3.9 years. The most mutated genes were DNMT3A, TET2, TP53, and ASXL1. We observed a two-fold increase in the number of mutations from before to after treatment in TP53, which differed from all other genes examined (P < .001). Among mutations detected before and after treatment, we observed an increased clone size in 38% and a decreased clone size in 5% of TP53 mutations (odds ratio = 3.7; 95% CI = 1.75-7.84; P < .001). Changes in mutation count and clone size were not observed in other genes. Individuals with an increase in the number of TP53 mutations following chemoradiation experienced shorter overall survival (hazard ratio = 7.07; 95% CI = 1.50-33.46; P = .014). In summary, we found an increase in the number and size of TP53 CH clones following chemoradiation that were associated with clinical outcomes.

Donor-Derived Malignancy and Transplantation Morbidity: Risks of Patient and Donor Genetics in Allogeneic Hematopoietic Stem Cell Transplantation.

Allogeneic hematopoietic stem cell transplantation (allo-HSCT) remains a key treatment option for hematologic malignancies (HMs), although it carries significant risks. Up to 30% of patients relapse after allo-HSCT, of which up to 2% to 5% are donor-derived malignancies (DDMs). DDMs can arise from a germline genetic predisposition allele or clonal hematopoiesis (CH) in the donor. Increasingly, genetic testing reveals that patient and donor genetic factors contribute to the development of DDM and other allo-HSCT complications. Deleterious germline variants in CEBPA, DDX41, GATA2, and RUNX1 predispose to inferior allo-HSCT outcomes. DDM has been linked to donor-acquired somatic CH variants in DNMT3A, ASXL1, JAK2, and IDH2, often with additional new variants. We do not yet have evidence to standardize donor genetic sequencing prior to allo-HSCT. The presence of hereditary HM disorders should be considered in patients with myeloid malignancies and their related donors, and screening of unrelated donors should include family and personal history of cytopenia and HMs. Excellent multidisciplinary care is critical to ensure efficient timelines for screening and necessary discussions among medical oncologists, genetic counselors, recipients, and potential donors. After allo-HSCT, HM relapse monitoring with genetic testing effectively results in genetic sequencing of the donor, as the transplanted hematopoietic system is donor-derived, which presents ethical challenges for disclosure to patients and donors. We encourage consideration of the recent National Marrow Donor Program policy that allows donors to opt-in for notification about detection of their genetic variants after allo-HSCT, with appropriate genetic counseling when feasible. We look forward to prospective investigation of the impact of germline and acquired somatic genetic variants on hematopoietic stem cell mobilization/engraftment, graft-versus-host disease, and DDM to facilitate improved outcomes through knowledge of genetic risk.

Plasma Proteomic Signature Predicts Myeloid Neoplasm Risk.

PURPOSE: Clonal hematopoiesis (CH) is thought to be the origin of myeloid neoplasms (MN). Yet our understanding of the mechanisms driving CH progression to MN and clinical risk prediction of MN remains limited. The human proteome reflects complex interactions between genetic and epigenetic regulation of biological systems. We hypothesized that the plasma proteome might predict MN risk and inform our understanding of the mechanisms promoting MN development. EXPERIMENTAL DESIGN: We jointly characterized CH and plasma proteomic profiles of 46,237 individuals in the UK Biobank at baseline study entry. During 500,036 person-years of follow-up, 115 individuals developed MN. Cox proportional hazard regression was used to test for an association between plasma protein levels and MN risk. RESULTS: We identified 115 proteins associated with MN risk of which 30% (N=34) were also associated with CH. These were enriched for known regulators of the innate and adaptive immune system. Plasma proteomics improved the prediction of MN risk (AUC=0.85, p=5×10-9) beyond clinical factors and CH (AUC=0.80). In an independent group (N=381,485), we used inherited polygenic risk scores (PRS) for plasma protein levels to validate the relevance of these proteins to MN development. PRS analyses suggest that most MN-associated proteins we identified are not directly causally linked to MN risk, but rather represent downstream markers of pathways regulating the progression of CH to MN. CONCLUSIONS: These data highlight the role of immune cell regulation in the progression of CH to MN and the promise of leveraging multi-omic characterization of CH to improve MN risk stratification.

Genome and clonal hematopoiesis stability contrasts with immune, cfDNA, mitochondrial, and telomere length changes during short duration spaceflight.

Background: The Inspiration4 (I4) mission, the first all-civilian orbital flight mission, investigated the physiological effects of short-duration spaceflight through a multi-omic approach. Despite advances, there remains much to learn about human adaptation to spaceflight's unique challenges, including microgravity, immune system perturbations, and radiation exposure. Methods: To provide a detailed genetics analysis of the mission, we collected dried blood spots pre-, during, and post-flight for DNA extraction. Telomere length was measured by quantitative PCR, while whole genome and cfDNA sequencing provided insight into genomic stability and immune adaptations. A robust bioinformatic pipeline was used for data analysis, including variant calling to assess mutational burden. Result: Telomere elongation occurred during spaceflight and shortened after return to Earth. Cell-free DNA analysis revealed increased immune cell signatures post-flight. No significant clonal hematopoiesis of indeterminate potential (CHIP) or whole-genome instability was observed. The long-term gene expression changes across immune cells suggested cellular adaptations to the space environment persisting months post-flight. Conclusion: Our findings provide valuable insights into the physiological consequences of short-duration spaceflight, with telomere dynamics and immune cell gene expression adapting to spaceflight and persisting after return to Earth. CHIP sequencing data will serve as a reference point for studying the early development of CHIP in astronauts, an understudied phenomenon as previous studies have focused on career astronauts. This study will serve as a reference point for future commercial and non-commercial spaceflight, low Earth orbit (LEO) missions, and deep-space exploration.

How low can you go?: Methodologic considerations in clonal hematopoiesis variant calling.

Clonal hematopoiesis (CH) is defined by the presence of an expanded clonal hematopoietic cell population due to an acquired mutation conferring a selective growth advantage and is known to predispose to hematologic malignancy. In this review, we discuss sequencing methods for CH detection in bulk sequencing data and corresponding bioinformatic approaches for variant calling, filtering, and curation. We detail practical recommendations for CH calling. Finally, we discuss how improvements in CH sequencing and bioinformatic approaches will enable the characterization of CH trajectories, its impact on human health, and therapeutic approaches to mitigate its adverse effects.