A novel deep targeted sequencing method for minimal residual disease monitoring in acute myeloid leukemia

A high proportion of patients with acute myeloid leukemia who achieve minimal residual disease negative status ultimately relapse because a fraction of pathological clones remains undetected by standard methods. We designed and validated a high-throughput sequencing method for minimal residual disease assessment of cell clonotypes with mutations of NPM1, IDH1/2 and/or FLT3-single nucleotide variants. For clinical validation, 106 follow-up samples from 63 patients in complete remission were studied by sequencing, evaluating the level of mutations detected at diagnosis. The predictive value of minimal residual disease status by sequencing, multiparameter flow cytometry, or quantitative polymerase chain reaction analysis was determined by survival analysis. The sequencing method achieved a sensitivity of 10-4 for single nucleotide variants and 10-5 for insertions/deletions and could be used in acute myeloid leukemia patients who carry any mutation (86% in our diagnostic data set). Sequencing-determined minimal residual disease positive status was associated with lower disease-free survival (hazard ratio 3.4, P=0.005) and lower overall survival (hazard ratio 4.2, P<0.001). Multivariate analysis showed that minimal residual disease positive status determined by sequencing was an independent factor associated with risk of death (hazard ratio 4.54, P=0.005) and the only independent factor conferring risk of relapse (hazard ratio 3.76, P=0.012). This sequencing-based method simplifies and standardizes minimal residual disease evaluation, with high applicability in acute myeloid leukemia. It is also an improvement upon flow cytometry- and quantitative polymerase chain reaction-based prediction of outcomes of patients with acute myeloid leukemia and could be incorporated in clinical settings and clinical trials.This study was supported by the Subdirección General de Investigación Sanitaria (Instituto de Salud Carlos III, Spain) grants PI13/02387 and PI16/01530, and the CRIS against Cancer foundation grant 2014/0120. ML holds a postdoctoral fellowship of the Spanish Ministry of Economy and Competitiveness (FPDI-2013- 16409). PRP holds a postdoctoral fellowship of the Spanish Instituto de Salud Carlos III: Contrato Predoctoral de Formación en Investigación en Salud i-PFIS (IFI 14/00008).S

Novel deep targeted sequencing method for minimal residual disease monitoring in acute myeloid leukemia

A high proportion of patients with acute myeloid leukemia who achieve minimal residual disease (MRD) negative status ultimately relapse because a fraction of pathological clones remains undetected by standard methods. We designed and validated a high-throughput sequencing method for MRD assessment of cell clonotypes with mutations of NPM1, IDH1/2 and/or FLT3-SNVs. For clinical validation, 106 follow-up samples from 63 patients in complete remission were studied by NGS, evaluating the level of mutations detected at diagnosis. The predictive value of MRD status by NGS, multiparameter flow cytometry, or quantitative PCR was determined by survival analysis. The method achieved a sensitivity of 10-4 for SNV mutations and 10-5 for insertions/deletions and could be used in acute myeloid leukemia patients who carry any mutation (86% in our diagnosis data set). NGS-determined MRD positive status was associated with lower disease-free survival (hazard ratio [HR] 3.4, p=0.005) and lower overall survival (HR 4.2, p<0.001). Multivariate analysis showed that MRD positive status by NGS was an independent factor associated with risk of death (HR 4.54, p =0.005) and the only independent factor conferring risk of relapse (HR 3.76, p =0.012). This NGS based method simplifies and standardizes MRD evaluation, with high applicability in acute myeloid leukemia. It also improves upon flow cytometry and quantitative PCR to predict acute myeloid leukemia outcome and could be incorporated in clinical settings and clinical trials.This study was supported by the Subdirección General de Investigación Sanitaria (Instituto de Salud Carlos III, Spain) grants PI13/02387 and PI16/01530, and the CRIS against Cancer foundation grant 2014/0120. M.L. holds a postdoctoral fellowship of the Spanish Ministry of Economy and Competitiveness (FPDI-2013-16409). P.R.P. holds a postdoctoral fellowship of the Spanish of Instituto de Salud Carlos III: Contrato Predoctoral de Formación en Investigación en Salud i-PFIS (IFI 14/00008).S

Regulatory sites for splicing in human basal ganglia are enriched for disease-relevant information

Genome-wide association studies have generated an increasing number of common genetic variants associated with neurological and psychiatric disease risk. An improved understanding of the genetic control of gene expression in human brain is vital considering this is the likely modus operandum for many causal variants. However, human brain sampling complexities limit the explanatory power of brain-related expression quantitative trait loci (eQTL) and allele-specific expression (ASE) signals. We address this, using paired genomic and transcriptomic data from putamen and substantia nigra from 117 human brains, interrogating regulation at different RNA processing stages and uncovering novel transcripts. We identify disease-relevant regulatory loci, find that splicing eQTLs are enriched for regulatory information of neuron-specific genes, that ASEs provide cell-specific regulatory information with evidence for cellular specificity, and that incomplete annotation of the brain transcriptome limits interpretation of risk loci for neuropsychiatric disease. This resource of regulatory data is accessible through our web server, http://braineacv2.inf.um.es/

Identification of novel risk loci, causal insights, and heritable risk for Parkinson's disease: a meta-analysis of genome-wide association studies

Background Genome-wide association studies (GWAS) in Parkinson's disease have increased the scope of biological knowledge about the disease over the past decade. We aimed to use the largest aggregate of GWAS data to identify novel risk loci and gain further insight into the causes of Parkinson's disease. Methods We did a meta-analysis of 17 datasets from Parkinson's disease GWAS available from European ancestry samples to nominate novel loci for disease risk. These datasets incorporated all available data. We then used these data to estimate heritable risk and develop predictive models of this heritability. We also used large gene expression and methylation resources to examine possible functional consequences as well as tissue, cell type, and biological pathway enrichments for the identified risk factors. Additionally, we examined shared genetic risk between Parkinson's disease and other phenotypes of interest via genetic correlations followed by Mendelian randomisation. Findings Between Oct 1, 2017, and Aug 9, 2018, we analysed 7·8 million single nucleotide polymorphisms in 37 688 cases, 18 618 UK Biobank proxy-cases (ie, individuals who do not have Parkinson's disease but have a first degree relative that does), and 1·4 million controls. We identified 90 independent genome-wide significant risk signals across 78 genomic regions, including 38 novel independent risk signals in 37 loci. These 90 variants explained 16–36% of the heritable risk of Parkinson's disease depending on prevalence. Integrating methylation and expression data within a Mendelian randomisation framework identified putatively associated genes at 70 risk signals underlying GWAS loci for follow-up functional studies. Tissue-specific expression enrichment analyses suggested Parkinson's disease loci were heavily brain-enriched, with specific neuronal cell types being implicated from single cell data. We found significant genetic correlations with brain volumes (false discovery rate-adjusted p=0·0035 for intracranial volume, p=0·024 for putamen volume), smoking status (p=0·024), and educational attainment (p=0·038). Mendelian randomisation between cognitive performance and Parkinson's disease risk showed a robust association (p=8·00 × 10−7). Interpretation These data provide the most comprehensive survey of genetic risk within Parkinson's disease to date, to the best of our knowledge, by revealing many additional Parkinson's disease risk loci, providing a biological context for these risk factors, and showing that a considerable genetic component of this disease remains unidentified. These associations derived from European ancestry datasets will need to be followed-up with more diverse data. Funding The National Institute on Aging at the National Institutes of Health (USA), The Michael J Fox Foundation, and The Parkinson's Foundation (see appendix for full list of funding sources)

Identification of candidate Parkinson disease genes by integrating genome-wide association study, expression, and epigenetic data sets

Importance Substantial genome-wide association study (GWAS) work in Parkinson disease (PD) has led to the discovery of an increasing number of loci shown reliably to be associated with increased risk of disease. Improved understanding of the underlying genes and mechanisms at these loci will be key to understanding the pathogenesis of PD. Objective To investigate what genes and genomic processes underlie the risk of sporadic PD. Design and Setting This genetic association study used the bioinformatic tools Coloc and transcriptome-wide association study (TWAS) to integrate PD case-control GWAS data published in 2017 with expression data (from Braineac, the Genotype-Tissue Expression [GTEx], and CommonMind) and methylation data (derived from UK Parkinson brain samples) to uncover putative gene expression and splicing mechanisms associated with PD GWAS signals. Candidate genes were further characterized using cell-type specificity, weighted gene coexpression networks, and weighted protein-protein interaction networks. Main Outcomes and Measures It was hypothesized a priori that some genes underlying PD loci would alter PD risk through changes to expression, splicing, or methylation. Candidate genes are presented whose change in expression, splicing, or methylation are associated with risk of PD as well as the functional pathways and cell types in which these genes have an important role. Results Gene-level analysis of expression revealed 5 genes (WDR6 [OMIM 606031], CD38 [OMIM 107270], GPNMB [OMIM 604368], RAB29 [OMIM 603949], and TMEM163 [OMIM 618978]) that replicated using both Coloc and TWAS analyses in both the GTEx and Braineac expression data sets. A further 6 genes (ZRANB3 [OMIM 615655], PCGF3 [OMIM 617543], NEK1 [OMIM 604588], NUPL2 [NCBI 11097], GALC [OMIM 606890], and CTSB [OMIM 116810]) showed evidence of disease-associated splicing effects. Cell-type specificity analysis revealed that gene expression was overall more prevalent in glial cell types compared with neurons. The weighted gene coexpression performed on the GTEx data set showed that NUPL2 is a key gene in 3 modules implicated in catabolic processes associated with protein ubiquitination and in the ubiquitin-dependent protein catabolic process in the nucleus accumbens, caudate, and putamen. TMEM163 and ZRANB3 were both important in modules in the frontal cortex and caudate, respectively, indicating regulation of signaling and cell communication. Protein interactor analysis and simulations using random networks demonstrated that the candidate genes interact significantly more with known mendelian PD and parkinsonism proteins than would be expected by chance. Conclusions and Relevance Together, these results suggest that several candidate genes and pathways are associated with the findings observed in PD GWAS studies

Vascular endothelial growth factor A (VEGFA) gene polymorphisms have an impact on survival in a subgroup of indolent patients with chronic lymphocytic leukemia.

Vascular endothelial growth factor (VEGF)-mediated angiogenesis contributes to the pathogenesis of B-cell chronic lymphocytic leukaemia (CLL). We investigated the impact of VEGFA gene diversity on the clinical outcome of patients with this disease. A VEGFA haplotype conformed by positions rs699947 (-1540C>A), rs833061 (-460T>C) and rs2010963 (405C>G) and two additional single-nucleotide polymorphisms (SNPs), rs3025039 (936C>T) and rs25648 (1032C>T), were analysed in 239 patients at the time of their CLL diagnosis. Here, we showed that homozygosity for rs699947/rs833061/rs2010963 ACG haplotype (ACG+/+ genotype) correlated with a reduced survival in CLL patients (ACG+/+ vs other genotypes: HR = 2.3, p = 0.002; recessive model). In multivariate analysis, the ACG+/+ genotype was identified as a novel independent prognostic factor (HR = 2.1, p = 0.005). Moreover, ACG homozygosity subdivided patients with CLL with otherwise indolent parameters into prognostic subgroups with different outcomes. Specifically, patients carrying the ACG+/+ genotype with mutated IgVH, very low and low-risk cytogenetics, initial clinical stage, CD38 negative status or early age at diagnosis showed a shorter survival (ACG+/+ vs other genotypes: HR = 3.5, p = 0.035; HR = 3.4, p = 0.001; HR = 2.2, p = 0.035; HR = 3.4, p = 0.0001 and HR = 3.1, p = 0.009, respectively). In conclusion, VEGFA ACG+/+ genotype confers an adverse effect in overall survival in CLL patients with an indolent course of the disease. These observations support the biological and prognostic implications of VEGFA genetics in CLL

Minor allele frequencies (MAF) of the <i>VEGF</i> polymorphisms studied in CLL patients.

<p>Minor allele frequencies (MAF) of the <i>VEGF</i> polymorphisms studied in CLL patients.</p

Distribution of <i>VEGF</i> genotypes in B-CLL groups with different mutational status of the<i>IgV_H</i> genes.

<p>M: patients with mutated <i>IgV_H</i> genes, UM: patients with unmutated<i>IgV_H</i> genes.</p><p>OR: odds ratio; CI, confidence interval.</p>a<p>Haplotype rs699947/rs833061/rs2010963. X genotype corresponds to n haplotypes other than ACG (CTC or CTG).</p>b<p>The upper homozygous genotype of each variant is designated the reference with an arbitrary OR value of 1 upon which the OR of the other genotypes are based.</p><p>Significant risk factors are shown in bold.</p