15 research outputs found

    Can Machine Learning Models Predict Asparaginase-associated Pancreatitis in Childhood Acute Lymphoblastic Leukemia

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    Publisher Copyright: © 2021 Lippincott Williams and Wilkins. All rights reserved.Asparaginase-associated pancreatitis (AAP) frequently affects children treated for acute lymphoblastic leukemia (ALL) causing severe acute and persisting complications. Known risk factors such as asparaginase dosing, older age and single nucleotide polymorphisms (SNPs) have insufficient odds ratios to allow personalized asparaginase therapy. In this study, we explored machine learning strategies for prediction of individual AAP risk. We integrated information on age, sex, and SNPs based on Illumina Omni2.5exome-8 arrays of patients with childhood ALL (N=1564, 244 with AAP aged 1.0 to 17.9 y) from 10 international ALL consortia into machine learning models including regression, random forest, AdaBoost and artificial neural networks. A model with only age and sex had area under the receiver operating characteristic curve (ROC-AUC) of 0.62. Inclusion of 6 pancreatitis candidate gene SNPs or 4 validated pancreatitis SNPs boosted ROC-AUC somewhat (0.67) while 30 SNPs, identified through our AAP genome-wide association study cohort, boosted performance (0.80). Most predictive features included rs10273639 (PRSS1-PRSS2), rs10436957 (CTRC), rs13228878 (PRSS1/PRSS2), rs1505495 (GALNTL6), rs4655107 (EPHB2) and age (1 to 7 y). Second AAP following asparaginase re-exposure was predicted with ROC-AUC: 0.65. The machine learning models assist individual-level risk assessment of AAP for future prevention trials, and may legitimize asparaginase re-exposure when AAP risk is predicted to be low.Peer reviewe

    ProSAAS-Derived Peptides are Colocalized with Neuropeptide Y and Function as Neuropeptides in the Regulation of Food Intake

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    ProSAAS is the precursor of a number of peptides that have been proposed to function as neuropeptides. Because proSAAS mRNA is highly expressed in the arcuate nucleus of the hypothalamus, we examined the cellular localization of several proSAAS-derived peptides in the mouse hypothalamus and found that they generally colocalized with neuropeptide Y (NPY), but not α-melanocyte stimulating hormone. However, unlike proNPY mRNA, which is upregulated by food deprivation in the mediobasal hypothalamus, neither proSAAS mRNA nor proSAAS-derived peptides were significantly altered by 1–2 days of food deprivation in wild-type mice. Furthermore, while proSAAS mRNA levels in the mediobasal hypothalamus were significantly lower in Cpefat/fat mice as compared to wild-type littermates, proNPY mRNA levels in the mediobasal hypothalamus and in other subregions of the hypothalamus were not significantly different between wild-type and Cpefat/fat mice. Intracerebroventricular injections of antibodies to two proSAAS-derived peptides (big LEN and PEN) significantly reduced food intake in fasted mice, while injections of antibodies to two other proSAAS-derived peptides (little LEN and little SAAS) did not. Whole-cell patch clamp recordings of parvocellular neurons in the hypothalamic paraventricular nucleus, a target of arcuate NPY projections, showed that big LEN produced a rapid and reversible inhibition of synaptic glutamate release that was spike independent and abolished by blocking postsynaptic G protein activity, suggesting the involvement of a postsynaptic G protein-coupled receptor and the release of a retrograde synaptic messenger. Taken together with previous studies, these findings support a role for proSAAS-derived peptides such as big LEN as neuropeptides regulating food intake

    SEPTIN12 Genetic Variants Confer Susceptibility to Teratozoospermia

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    It is estimated that 10–15% of couples are infertile and male factors account for about half of these cases. With the advent of intracytoplasmic sperm injection (ICSI), many infertile men have been able to father offspring. However, teratozoospermia still remains a big challenge to tackle. Septins belong to a family of cytoskeletal proteins with GTPase activity and are involved in various biological processes e.g. morphogenesis, compartmentalization, apoptosis and cytokinesis. SEPTIN12, identified by c-DNA microarray analysis of infertile men, is exclusively expressed in the post meiotic male germ cells. Septin12+/+/Septin12+/− chimeric mice have multiple reproductive defects including the presence of immature sperm in the semen, and sperm with bent neck (defect of the annulus) and nuclear DNA damage. These facts make SEPTIN12 a potential sterile gene in humans. In this study, we sequenced the entire coding region of SEPTIN12 in infertile men (n = 160) and fertile controls (n = 200) and identified ten variants. Among them is the c.474 G>A variant within exon 5 that encodes part of the GTP binding domain. The variant creates a novel splice donor site that causes skipping of a portion of exon 5, resulting in a truncated protein lacking the C-terminal half of SEPTIN12. Most individuals homozygous for the c.474 A allele had teratozoospermia (abnormal sperm <14%) and their sperm showed bent tail and de-condensed nucleus with significant DNA damage. Ex vivo experiment showed truncated SEPT12 inhibits filament formation in a dose-dependent manner. This study provides the first causal link between SEPTIN12 genetic variant and male infertility with distinctive sperm pathology. Our finding also suggests vital roles of SEPT12 in sperm nuclear integrity and tail development

    Effects of Anacetrapib in Patients with Atherosclerotic Vascular Disease

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    BACKGROUND: Patients with atherosclerotic vascular disease remain at high risk for cardiovascular events despite effective statin-based treatment of low-density lipoprotein (LDL) cholesterol levels. The inhibition of cholesteryl ester transfer protein (CETP) by anacetrapib reduces LDL cholesterol levels and increases high-density lipoprotein (HDL) cholesterol levels. However, trials of other CETP inhibitors have shown neutral or adverse effects on cardiovascular outcomes. METHODS: We conducted a randomized, double-blind, placebo-controlled trial involving 30,449 adults with atherosclerotic vascular disease who were receiving intensive atorvastatin therapy and who had a mean LDL cholesterol level of 61 mg per deciliter (1.58 mmol per liter), a mean non-HDL cholesterol level of 92 mg per deciliter (2.38 mmol per liter), and a mean HDL cholesterol level of 40 mg per deciliter (1.03 mmol per liter). The patients were assigned to receive either 100 mg of anacetrapib once daily (15,225 patients) or matching placebo (15,224 patients). The primary outcome was the first major coronary event, a composite of coronary death, myocardial infarction, or coronary revascularization. RESULTS: During the median follow-up period of 4.1 years, the primary outcome occurred in significantly fewer patients in the anacetrapib group than in the placebo group (1640 of 15,225 patients [10.8%] vs. 1803 of 15,224 patients [11.8%]; rate ratio, 0.91; 95% confidence interval, 0.85 to 0.97; P=0.004). The relative difference in risk was similar across multiple prespecified subgroups. At the trial midpoint, the mean level of HDL cholesterol was higher by 43 mg per deciliter (1.12 mmol per liter) in the anacetrapib group than in the placebo group (a relative difference of 104%), and the mean level of non-HDL cholesterol was lower by 17 mg per deciliter (0.44 mmol per liter), a relative difference of -18%. There were no significant between-group differences in the risk of death, cancer, or other serious adverse events. CONCLUSIONS: Among patients with atherosclerotic vascular disease who were receiving intensive statin therapy, the use of anacetrapib resulted in a lower incidence of major coronary events than the use of placebo. (Funded by Merck and others; Current Controlled Trials number, ISRCTN48678192 ; ClinicalTrials.gov number, NCT01252953 ; and EudraCT number, 2010-023467-18 .)

    Can machine learning models predict asparaginase-associated pancreatitis in childhood acute lymphoblastic leukemia

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    Abstract Asparaginase-associated pancreatitis (AAP) frequently affects children treated for acute lymphoblastic leukemia (ALL) causing severe acute and persisting complications. Known risk factors such as asparaginase dosing, older age and single nucleotide polymorphisms (SNPs) have insufficient odds ratios to allow personalized asparaginase therapy. In this study, we explored machine learning strategies for prediction of individual AAP risk. We integrated information on age, sex, and SNPs based on Illumina Omni2.5exome-8 arrays of patients with childhood ALL (N=1564, 244 with AAP 1.0 to 17.9 yo) from 10 international ALL consortia into machine learning models including regression, random forest, AdaBoost and artificial neural networks. A model with only age and sex had area under the receiver operating characteristic curve (ROC-AUC) of 0.62. Inclusion of 6 pancreatitis candidate gene SNPs or 4 validated pancreatitis SNPs boosted ROC-AUC somewhat (0.67) while 30 SNPs, identified through our AAP genome-wide association study cohort, boosted performance (0.80). Most predictive features included rs10273639 (PRSS1-PRSS2), rs10436957 (CTRC), rs13228878 (PRSS1/PRSS2), rs1505495 (GALNTL6), rs4655107 (EPHB2) and age (1 to 7 y). Second AAP following asparaginase re-exposure was predicted with ROC-AUC: 0.65. The machine learning models assist individual-level risk assessment of AAP for future prevention trials, and may legitimize asparaginase re-exposure when AAP risk is predicted to be low
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