Faculty Opinions recommendation of Genetic risk factors for the development of osteonecrosis in children under age 10 treated for acute lymphoblastic leukemia.

2017 ◽  
Author(s):  
Kjeld Schmiegelow
Keyword(s):  
Risk Factors ◽  
Acute Lymphoblastic Leukemia ◽  
Genetic Risk ◽  
Lymphoblastic Leukemia ◽  
Genetic Risk Factors

scholarly journals Clinical and Genetic Risk Factors for Acute Pancreatitis in Patients With Acute Lymphoblastic Leukemia

2016 ◽  
Vol 34 (18) ◽  
pp. 2133-2140 ◽  
Author(s):  
Chengcheng Liu ◽  
Wenjian Yang ◽  
Meenakshi Devidas ◽  
Cheng Cheng ◽  
Deqing Pei ◽  
...  
Keyword(s):  
Risk Factors ◽  
Acute Pancreatitis ◽  
Native American ◽  
Acute Lymphoblastic Leukemia ◽  
Genetic Risk ◽  
Genome Wide Association Study ◽  
Lymphoblastic Leukemia ◽  
Genome Wide Association ◽  
Common Variants ◽  
Genome Wide

Purpose Acute pancreatitis is one of the common causes of asparaginase intolerance. The mechanism is unknown, and genetic predisposition to asparaginase-induced pancreatitis has not been previously identified. Methods To determine clinical risk factors for asparaginase-induced pancreatitis, we studied a cohort of 5,185 children and young adults with acute lymphoblastic leukemia, including 117 (2.3%) who were diagnosed with at least one episode of acute pancreatitis during therapy. A genome-wide association study was performed in the cohort and in an independent case-control group of 213 patients to identify genetic risk factors. Results Risk factors associated with pancreatitis included genetically defined Native American ancestry (P < .001), older age (P < .001), and higher cumulative dose of asparaginase (P < .001). No common variants reached genome-wide significance in the genome-wide association study, but a rare nonsense variant rs199695765 in CPA2, encoding carboxypeptidase A2, was highly associated with pancreatitis (hazard ratio, 587; 95% CI, 66.8 to 5166; P = 9.0 × 10−9). A gene-level analysis showed an excess of additional CPA2 variants in patients who did versus those who did not develop pancreatitis (P = .001). Sixteen CPA2 single-nucleotide polymorphisms were associated (P < .05) with pancreatitis, and 13 of 24 patients who carried at least one of these variants developed pancreatitis. Biologic functions that were overrepresented by common variants modestly associated with pancreatitis included purine metabolism and cytoskeleton regulation. Conclusion Older age, higher exposure to asparaginase, and higher Native American ancestry were independent risk factors for pancreatitis in patients with acute lymphoblastic leukemia. Those who inherit a nonsense rare variant in the CPA2 gene had a markedly increased risk of asparaginase-induced pancreatitis.

Genetic Risk Factors for the Development of Osteonecrosis in Children Under Age 10 Treated for Acute Lymphoblastic Leukemia

Blood ◽  
2015 ◽  
Vol 126 (23) ◽  
pp. 250-250
Author(s):  
Seth E. Karol ◽  
Wenjian Yang ◽  
Leonard A. Mattano ◽  
Kelly W. Maloney ◽  
Colton Smith ◽  
...  
Keyword(s):  
Risk Factors ◽  
Glutamate Receptor ◽  
Genetic Risk ◽  
Lymphoblastic Leukemia ◽  
Meta Analysis ◽  
Genetic Risk Factors ◽  
Discovery Cohort ◽  
Genome Wide ◽  
Whole Exome ◽  
Manhattan Plot

Abstract Background: Therapy induced osteonecrosis has become a limiting toxicity in the intensification of treatment for pediatric acute lymphoblastic leukemia (ALL), particularly among patients 10 to 20 years of age. Prior studies on the genetic determinants of osteonecrosis have focused primarily on patients older than 10 years, leaving the genetic risk factors for the larger group of children with ALL less than 10 years old incompletely understood. It is hypothesized that genetic risk factors may account for a greater proportion of risk of osteonecrosis or involve differing mechanisms in younger than in older patients. Methods: We performed the first evaluation of genetic risk factors for osteonecrosis in children less than 10 years old using a discovery cohort of 82 cases of osteonecrosis and 287 controls treated on Children's Oncology Group (COG) protocol AALL0331 (NCI standard risk ALL) and tested for replication in 817 children less than 10 treated on COG protocol AALL0232 (high risk ALL). Genotyping was performed using the Affymetrix Gene Chip Human Mapping Array 6.0 and the Illumina Human Exome BeadChip v1.1. A subset of 15 cases in the discovery cohort had coding variant calls verified by whole exome sequencing. Both discovery and replication genome-wide association studies (GWAS) adjusted for demographic and therapy variables known to modify the risk of osteonecrosis. Enhancer enrichment analysis using HaploReg identified tissues affected by the identified single nucleotide polymorphisms (SNPs). Genes associated with the identified SNPs were evaluated using Ingenuity Pathway Analysis for enrichment in biologically relevant pathways. Results: Within the discovery cohort, top ranked variants were rs76599360 and rs77556622 which were in full linkage disequilibrium [P=1.13x10-9, odds ratio (OR) 22.0, 95% confidence interval (95%CI) 8.15-59.6] located near bone morphogenic protein 7 (BMP7). The top replicated SNPs were located near BMP7 [rs75161997, P=5.34x10-8 (OR 15.0; 95%CI 5.64-39.7) and P =0.0498 (OR 8.44; 95%CI 1.002-71.1) in the discovery and replication cohorts, respectively] and PROX1-antisense RNA1 [PROX1-AS1:rs1891059, P=2.28x10-7 (OR 6.48; 95%CI 3.19-13.1) and P=0.0077 (OR 3.78; 95%CI 1.42-10.1) for the discovery and replication cohorts, respectively]. The top replicated non-synonymous SNP, rs34144324, was in a glutamate receptor gene [GRID2, P=8.65x10-6 (OR 3.46; 95%CI 2.00-5.98) and 0.0136 (OR 10.8; 95%CI 1.63-71.4) in the discovery and replication cohorts, respectively], and the genotyping of this variant was verified in the whole exome sequencing data. In a meta-analysis of both cohorts, the replicated BMP7 and PROX1-AS1 variants (rs75161997 and rs1891059, respectively) and a variant in NCRNA00251 (rs141059755) met the genome-wide significance threshold of <5x10-8 (Figure 1). In a meta-analysis of both cohorts, replicated SNPs with meta-analysis P<1 x10-5 showed enrichment in enhancers active in mesenchymal stem cells. Pathway analysis of genes linked to top SNPs (meta-analysis P <0.001) demonstrated enrichment in glutamate receptor signaling and adipogenesis pathways. Conclusions: Variants in genes important to bone and fat differentiation from mesenchymal stem cells were associated with osteonecrosis in children less than 10 years old. The importance of variants in glutamate receptor signaling in children less than 10 also confirms the findings of a recently completed GWAS of osteonecrosis in AALL0232 (Blood 2014 124:367; 2014) including patients of all ages and in which osteonecrosis occurred primarily in older children. These data provide new insights into osteonecrosis with implications for patients of all ages. Figure 1. Manhattan plot of meta-analysis for osteonecrosis risk in children <10 years old Figure 1. Manhattan plot of meta-analysis for osteonecrosis risk in children <10 years old Disclosures Hunger: Sigma Tau: Consultancy; Jazz Pharmaceuticals: Consultancy; Merck: Equity Ownership; Spectrum Pharmaceuticals: Consultancy.

Gene Expression Profiles Distinguish Children Who Develop Therapy-Related Myeloid Leukemia.

Blood ◽  
2004 ◽  
Vol 104 (11) ◽  
pp. 397-397
Author(s):  
Alessia Bogni ◽  
Cheng Cheng ◽  
Wei Liu ◽  
Wenjian Yang ◽  
Deborah French ◽  
...  
Keyword(s):  
Gene Expression ◽  
Risk Factors ◽  
Genetic Risk ◽  
Myeloid Leukemia ◽  
Permutation Test ◽  
Expression Profiles ◽  
Lymphoblastic Leukemia ◽  
Gene Expression Profiles ◽  
Genetic Risk Factors ◽  
Gene Probe

Abstract In children with acute lymphoblastic leukemia (ALL), failure due to therapy-related myeloid leukemia (t-ML) is a devastating complication. Using a target gene approach, only a few host genetic risk factors for t-ML have been defined. Microarray analysis of gene expression allows for a more genome-wide approach to identify possible genetic risk factors for t-ML. We assessed gene expression profiles (12625 gene probe sets) using oligonucleotide-based arrays in diagnostic ALL blasts from 228 children treated on St. Jude ALL protocols (Total XIII) that included etoposide; 13 of these children developed t-ML. A group of 83 probe sets were significantly related to the time-dependent risk of t-ML, with principal component analysis plot (right panel) separating patients who developed t-ML from the others. Hierarchical clustering of the 83 probe sets grouped patients into 3 clusters (n=163, n=52, n=13), with the cumulative incidence of t-ML being significantly higher in the last cluster (p < 0.0001, left panel) compared to those of the other gene-expression-defined clusters. Figure Figure A permutation test indicated that probe sets selected by chance are unlikely to obtain the observed distinct clusters (p=0.045). Distinguishing genes included transcription-related oncogenes (v-Myb, Pax-5), cyclins (CCNG1, CCNG2 and CCND1) and Histone H4. Common transcription factor recognition elements among similarly up- or down-regulated genes included several involved in hematopoietic differentiation or leukemogenesis (Maz, PU.1, FOXO4). This approach has identified several genes whose expression differentiates patients at risk of t-ML, and provides targets for assessing the germline predisposition to leukemogenesis.

scholarly journals Genetic risk factors for the development of osteonecrosis in children under age 10 treated for acute lymphoblastic leukemia

Blood ◽  
2016 ◽  
Vol 127 (5) ◽  
pp. 558-564 ◽  
Author(s):  
Seth E. Karol ◽  
Leonard A. Mattano ◽  
Wenjian Yang ◽  
Kelly W. Maloney ◽  
Colton Smith ◽  
...  
Keyword(s):  
Risk Factors ◽  
Stem Cell ◽  
Acute Lymphoblastic Leukemia ◽  
Mesenchymal Stem Cell ◽  
Genetic Risk ◽  
Lymphoblastic Leukemia ◽  
Stem Cell Differentiation ◽  
Glutamate Signaling ◽  
Mesenchymal Stem Cell Differentiation ◽  
Key Points

Key Points Variants in genes important for mesenchymal stem cell differentiation influence the risk of osteonecrosis in children with ALL under 10 years old. Variants in genes in the glutamate signaling pathway influence osteonecrosis in children with ALL regardless of age.

Genome Scan for Therapy-Related Leukemia.

Blood ◽  
2005 ◽  
Vol 106 (11) ◽  
pp. 3254-3254
Author(s):  
Christine M. Hartford ◽  
Wenjian Yang ◽  
Cheng Cheng ◽  
Stanley Pounds ◽  
Wei Liu ◽  
...  
Keyword(s):  
Risk Factors ◽  
Genetic Risk ◽  
Copy Number ◽  
Lymphoblastic Leukemia ◽  
Treatment Protocol ◽  
Genetic Risk Factors ◽  
Chromosome 9 ◽  
Chromosome 7 ◽  
Snp Analysis ◽  
Balanced Translocation

Abstract Therapy-related leukemia (t-ML) is a rare but devastating complication of anticancer treatment, including treatment of acute lymphoblastic leukemia (ALL). Although a number of treatment factors have been identified that contribute to the development of t-ML, little is known about the biology of the disease or the genetic risk factors. To identify possible genetic risk factors for and characteristics of t-ML among ALL patients, we used the Affymetrix GeneChip® Human Mapping 100K set to genotype over 100,000 single nucleotide polymorphisms (SNPs) in germline DNA from 13 cases with t-ML and from 13 matched controls, as well as DNA of the t-ML blast samples of the 13 cases. Controls were matched for treatment protocol, ALL risk classification, irradiation, prior use of G-CSF, and race. Germline allele frequencies differed (at the p &lt; 0.01 level) for 309 SNPs (203 genes) between t-ML cases and controls. Cytogenetically, most of the cases had translocations or inversions of 11q23; however, three cytogenetically-detected regions of chromosomal loss were also detected (on chromosome 5, 7, and 9, each found only once among the cases). These chromosomal deletions were all detected as regions of loss of heterozygosity (LOH) and decreased copy number by paired intra-patient germline vs t-ML blast analyses of SNP calls. However, the paired SNP data indicated 216 regions of LOH (FDR = 2.5%) corresponding to a total of 81 non-contiguous regions (Figure), most of which were not detected as losses cytogenetically, and 38 shared (among pairs) regions of LOH. As many as 45 noncontiguous and 12 contiguous LOH regions were found among those cases with no cytogenetically defined regions of loss, including patients with simple balanced translocations. In addition to cytogenetically-defined cases, using SNP analyses we detected additional t-ML cases with regions of LOH on 5q (n=1), on chromosome 7 (n=4), and on chromosome 9 (n=2). In fact, only one patient, whose cytogenetics showed a balanced translocation involving 11q23, had no extended regions of LOH detected by SNP analysis. Altogether, 5 of the 13 cases demonstrated LOH on chromosome 7. Using a change-point model, we detected 18 regions of copy number increase and 21 regions of copy number decrease in the blasts compared to paired germline DNA (p&lt;0.01). We conclude that dense genotyping of SNPs not only accurately detects cytogenetically defined regions of gain or loss, but also chromosome abnormalities not found by conventional techniques. Genes associated with SNPs whose frequencies differed between cases and controls, with LOH, or altered copy number, are involved in apoptosis, DNA damage repair, and novel pathways, thereby providing candidate genes that may contribute to the development of t-ML. Figure: 81 regions of inferred LOH in case t-ML blast DNA compared to germline DNA indicated losses involving multiple autosomes. Figure:. 81 regions of inferred LOH in case t-ML blast DNA compared to germline DNA indicated losses involving multiple autosomes.

1655-P: Genetic Risk Factors for Incident Cardiovascular Disease in Type 2 Diabetes Patients

Diabetes ◽  
2020 ◽  
Vol 69 (Supplement 1) ◽  
pp. 1655-P
Author(s):  
SOO HEON KWAK ◽  
JOSEP M. MERCADER ◽  
AARON LEONG ◽  
BIANCA PORNEALA ◽  
PEITAO WU ◽  
...  
Keyword(s):  
Risk Factors ◽  
Type 2 Diabetes ◽  
Cardiovascular Disease ◽  
Genetic Risk ◽  
Genetic Risk Factors ◽  
Incident Cardiovascular Disease ◽  
Diabetes Patients

107-OR: Novel Genetic Risk Factors Influence Islet Autoimmunity Progression

Diabetes ◽  
2020 ◽  
Vol 69 (Supplement 1) ◽  
pp. 107-OR
Author(s):  
SUNA ONENGUT-GUMUSCU ◽  
UMA DEVI PAILA ◽  
WEI-MIN CHEN ◽  
AAKROSH RATAN ◽  
ZHENNAN ZHU ◽  
...  
Keyword(s):  
Risk Factors ◽  
Genetic Risk ◽  
Genetic Risk Factors ◽  
Islet Autoimmunity
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