Puberty Status Modifies the Effects of Genetic Variants, Lifestyle Factors and Their Interactions on Adiponectin: The BCAMS Study

BackgroundHypoadiponectinemia has been associated with various cardiometabolic disease states. Previous studies in adults have shown that adiponectin levels were regulated by specific genetic and behavioral or lifestyle factors. However, little is known about the influence of these factors on adiponectin levels in children, particularly as mitigated by pubertal development.MethodsWe performed a cross-sectional analysis of data from 3,402 children aged 6-18 years from the Beijing Child and Adolescent Metabolic Syndrome (BCAMS) study. Pubertal progress was classified as prepubertal, midpuberty, and postpuberty. Six relevant single nucleotide polymorphisms (SNPs) were selected from previous genome-wide association studies of adiponectin in East Asians. Individual SNPs and two weighted genetic predisposition scores, as well as their interactions with 14 lifestyle factors, were analyzed to investigate their influence on adiponectin levels across puberty. The effect of these factors on adiponectin was analyzed using general linear models adjusted for age, sex, and BMI.ResultsAfter adjustment for age, sex, and BMI, the associations between adiponectin levels and diet items, and diet score were significant at prepuberty or postpuberty, while the effect of exercise on adiponectin levels was more prominent at mid- and postpuberty. Walking to school was found to be associated with increased adiponectin levels throughout puberty. Meanwhile, the effect of WDR11-FGFR2-rs3943077 was stronger at midpuberty (P = 0.002), and ADIPOQ-rs6773957 was more effective at postpuberty (P = 0.005), while CDH13-rs4783244 showed the strongest association with adiponectin levels at all pubertal stages (all P < 3.24 × 10-15). We further found that effects of diet score (Pinteraction = 0.022) and exercise (Pinteraction = 0.049) were stronger in children with higher genetic risk of hypoadiponectinemia, while higher diet score and exercise frequency attenuated the differences in adiponectin levels among children with different genetic risks.ConclusionsOur study confirmed puberty modulates the associations between adiponectin, and genetic variants, lifestyle factors, and gene-by-lifestyle interactions. These findings provide new insight into puberty-specific lifestyle suggestions, especially in genetically susceptible individuals.

Influence of Genetic Factors on Immunopathogenesis and Clinical Phenotypes of ANCA-associated Vasculitis

The review presents the recent data on assumed risk factors for the development of ANCA-associated vasculitis (AAV), among which environmental factors, such as climatic, chemical, etc., are of particular interest of researchers. Controversial opinions of various authors on the role of individual causative agents of infectious diseases in the development of AAV are analyzed. The review pays special attention to scientific data on the influence of variants of the structure of genes encoding various components of the immune system on the development of the pathogenetic process of AAV. Up-to-date information on the association of single-nucleotide polymorphisms (SNPs) with the course, risk of development and the likelihood of AAV recurrence is indicated, the most associated of which are genes encoding proteins of the main histocompatibility complex (HLA), a toll-like receptors (TLR`s), as well as an inhibitor of serine proteinases-alpha-antitrypsin (AAT). The analysis of scientific publications describing the molecular mechanism of the development of a pathological focus that forms the conditions for the synthesis of PR3ANCA and MPOANCA complexes characteristic of AAV has been carried out. The data of a number of foreign studies on the relationship of individual SNPs associated with the features of the course of granulomatosis with polyangiitis, microscopic polyangiitis, as well as eosinophilic granulomatosis with polyangiitis are presented and summarized. The review presents current AAV treatment regimens and promising directions for the development of medical care for patients.

Identification of ATP2B4 regulatory element containing functional genetic variants associated with severe malaria

Genome-wide association studies (GWAS) for severe malaria have identified 30 genetic variants that are mostly located in non-coding regions, with only a few associations replicated in independent populations. In this study, we aimed at identifying potential causal genetic variants located in these loci and demonstrate their functional activity. We systematically investigated the regulatory effect of the SNPs in linkage disequilibrium with the tagSNPs associated with severe malaria in several populations. Annotating and prioritizing genetic variants led to the identification of a regulatory region containing 5 ATP2B4 SNPs in linkage disequilibrium with the tagSNP rs10900585. We confirmed the association of rs10900585 and also found significant associations of severe malaria with our candidate SNPs (rs11240734, rs1541252, rs1541253, rs1541254, and rs1541255) in a Senegalese population. Then, we showed that this region had both promoter and enhancer activities and that both individual SNPs and the combination of SNPs had regulatory effects using luciferase reporter assays. Moreover, CRISPR/Cas9-mediated deletion of this region decreased ATP2B4 transcript and protein levels and increased Ca2+ intracellular concentration in the K562 cell line. Taken together, our data show that severe malaria-associated genetic variants alter the activity of a promoter with enhancer function. We showed that this regulatory element controls the expression of ATP2B4 that encodes a plasma membrane calcium-transporting ATPase 4 (PMCA4), which is the major calcium pump on red blood cells. Altering the activity of this regulatory element affects the risk of severe malaria probably through calcium concentration effect on parasitaemia.

Tobacco consumption has interaction effect with protein coding genes to increase esophageal squamous cell Carcinoma risk: A case-control study in Chinese high-incidence region

Background: Esophageal squamous cell carcinoma (ESCC) has reported that smoking was a major risk factor. Genetic predisposition can partially explain the pathogenesis of esophageal cancer in alcohol drinkers. It would also be interesting to investigate the genetic basis underlying the significant disparities in ESCC risk in populations exposed to the same level of smoking. Methods: We recruited 1030 ESCC patients and 1783 healthy individuals in Taixing, China, and selected 101 ESCC-related SNPs for analysis. Logistic regression model was employed with an interaction term for smoking and individual SNPs. The level of smoking was categorized based on pack-years as never smokers, moderate smokers (≤30), and heavy smokers (>30). The relative excess risk of interaction (RERI) and the synergy index (S) were used to evaluate interaction on an additive scale. Genetic risk score was established to quantify gene risk. Results: The SNP HECTD4 rs11066280, CASP8 rs3769823 and ADH1B rs1042026 had an interaction effect with smoking on ESCC risk. Specifically, for rs11066280 T/A, the adjusted OR for moderate and heavy smokers was 1.43 (95% CI = 1.01-2.02) and 1.80 (95% CI = 1.28–2.53), ADH1B rs1042026 showed strong effect in both smoker and alcohol drinkers. GRS indicated that these three SNPs had unsignificant effect in non-smokers and a 2.92-fold risk (95%CI = 1.69-5.11) in smokers.Discussion and Conclusion: In this study, we provide new insights for disease prevention and control of ESCC based on smoking behavior and genetic predisposition.

Genomic regions associated with resistance to Fusarium wilt in castor identified through linkage and association mapping approaches

Fusarium wilt caused by <i>Fusarium oxysporum</i> f. sp <i>ricini</i> is the most destructive disease in castor. Host plant resistance is the best strategy for management of wilt problem. Identification of molecular markers linked to wilt resistance will enhance the efficiency and effectiveness of breeding for wilt resistance. In the present study, mapping of genomic regions linked to wilt resistance was attempted using a bi-parental population of 185 F₆- RILs and a genetically diverse panel of 300 germplasm accessions. Quantitative trait loci (QTL) analysis performed using a linkage map consisting of 1,090 SNP markers identified a major QTL on chromosome-7 with LOD score of 18.7, which explained 44 per cent of phenotypic variance. The association mapping performed using genotypic data from 3,465 SNP loci revealed 69 significant associations (p <1×10-4) for wilt resistance. The phenotypic variance explained by the individual SNPs ranged from 0.063 to 0.210. The QTL detected in the bi-parental mapping population was not identified in the association analysis. Thus, the results of this study indicate the possibility of vast gene diversity for Fusarium wilt resistance in castor.

Discrimination between 34 of 36 Possible Combinations of Three C>T SNP Genotypes in the MGMT Promoter by High Resolution Melting Analysis Coupled with Pyrosequencing Using a Single Primer Set

Due to its cost-efficiency, high resolution melting (HRM) analysis plays an important role in genotyping of candidate single nucleotide polymorphisms (SNPs). Studies indicate that HRM analysis is not only suitable for genotyping individual SNPs, but also allows genotyping of multiple SNPs in one and the same amplicon, although with limited discrimination power. By targeting the three C>T SNPs rs527559815, rs547832288, and rs16906252, located in the promoter of the O6-methylguanine-DNA methyltransferase (MGMT) gene within a distance of 45 bp, we investigated whether the discrimination power can be increased by coupling HRM analysis with pyrosequencing (PSQ). After optimizing polymerase chain reaction (PCR) conditions, PCR products subjected to HRM analysis could directly be used for PSQ. By analyzing oligodeoxynucleotide controls, representing the 36 theoretically possible variant combinations for diploid human cells (8 triple-homozygous, 12 double-homozygous, 12 double-heterozygous and 4 triple-heterozygous combinations), 34 out of the 36 variant combinations could be genotyped unambiguously by combined analysis of HRM and PSQ data, compared to 22 variant combinations by HRM analysis and 16 variant combinations by PSQ. Our approach was successfully applied to genotype stable cell lines of different origin, primary human tumor cell lines from glioma patients, and breast tissue samples.

Pharmacogenomic Single Nucleotide Polymorphism (SNP) Variants As Predictors of Toxicity Phenotypes in the Treatment of Acute Childhood Leukemia

Introduction: Despite cure rates in acute lymphoblastic leukemia (ALL) exceeding 90% in clinical trials, morbidity due to drug toxicities is high. Genetic polymorphisms can influence gene expression and activity, impacting pharmacokinetics and causing inter-individual variation in drug levels, which contributes to toxicity if levels are high or relapse if levels are low. We hypothesize that pharmacogenomic testing will identify patient specific variations in genes involved in metabolism of cytotoxic agents. This knowledge will allow clinicians to optimize therapy by providing pharmacogenomics based biomarkers related to increased toxicities. Data has shown that treatment interruptions and omissions due to toxicities affect outcomes and morbidities in children with cancer. Objective : To correlate pharmacogenomic biomarkers with toxicity phenotypes in children receiving therapy for ALL. Methods: This cross-sectional study involved subjects at a tertiary academic center (Fig. 1A). Subjects aged 1 year to 26 years with ALL treated after May 2012 were eligible. A total of 75 patients treated between 2012 and 2020 were included. Pharmacogenomic testing was performed on peripheral blood. Genomic DNA was tested for 118 single-nucleotide polymorphisms (SNP) in 55 genes for transport and metabolism of cytarabine, vincristine, methotrexate, dauno/doxorubicin, and mercaptopurine/thioguanine were analyzed using the Sequenom-based genotyping that uses MALDI-TOF based chemistry. SNPs were tested using logistic regression models for association with toxicities in additive, dominant, and recessive modes of inheritance. CTCAE v4.0 was used for grading all toxicities during the first 100 days of therapy. For endocrine (endo) and neurological (neuro) toxicities, 25 patients exhibited between grade 1-3 toxicities. For gastrointestinal (GI) toxicities, 25 patients exhibited between grade 2-3 toxicities. For hematological (heme) toxicities, 11 patients exhibited between grade 2-4 toxicities. Odds ratio and 95% confidence interval were calculated for each test and SNPs with association P-value &lt;0.05 were considered significant. To conduct multivariable SNP combinations analysis, SNPs with univariate association p-value &lt;0.1 were selected for each toxicity, and then SNP combinations (up to 3 SNPs per model) were tested for association with each toxicity. The combination model with the 1000 permutation p-value &lt;0.05 and lowest BIC value was selected to build a SNP score after considering the mode of inheritance and the direction of association with the toxicity for the individual genotypes. A SNP score was generated by summation of genotype scores for the individual SNPs passing the top model. Patients were further classified into either of the 3 following SNP score groups: &gt;0, 0 or &lt;0. Results: For a GI toxicity score derived from 3 SNPs (TYMS-rs151264360, FPGS-rs1544105, and GSTM5-rs3754446), patients with &gt;0 score had 79% incidence of GI toxicity (N=67) as compared to 10% in patients with score of 0 and 8% in patients with score &lt;0 (p=2.07E-05, Fig 1B). For the SNP score (AKR1C3-rs6621365, ABCB1-rs4148737, and CTPS1-rs12067645) generated for heme toxicity, higher SNP scores were associated with high toxicity (p=0.003, Figure 1C). For neurotoxicity, the 3 SNPs (DCTD-rs6829021, SCL28A3-rs17343066, and CTPS1-rs12067635) involved were all in cytarabine metabolic pathway and predicted greater neurotoxicity (56%) with a score of &gt;0; no toxicity was observed in patients with neurotoxicity score of &lt;0 (p=0.0005, Fig. 1D). For SNP endo toxicity score (AKR1C3-rs1937840, TYMS-rs2853539, and CTS-rs648743), we observed 91% incidence of endo toxicity in patients with toxicity score of &gt;0 (p=4.7E-08, Fig. 1E). None of the patients with a score of &lt;0 experienced endo toxicity. Discussion: We identified germline SNPs predictive of toxicity phenotypes in a cohort of 75 subjects with ALL. The results of our multivariable SNP combination analysis suggest susceptibility to chemotherapy-induced toxicities is likely multigenic in nature. Instead of a single SNP approach, identification of combinations of mutations in drug pathways increases the robustness of predicting a patient's response to chemotherapy. Our results provide promising SNP models that can help establish clinically relevant biomarkers allowing for individualization of cancer therapy to optimize treatment for each patient. Figure 1 Figure 1. Disclosures No relevant conflicts of interest to declare.

Mitochondrial DNA and Alzheimer's Disease: A First Case-control Study of the Tunisian Population

Background: Alzheimer’s disease (AD) is the most common neurodegenerative disorder in humans and presents a major health problem throughout the world. The etiology of AD is complex, and many factors are implicated, including mitochondria. Mitochondrial alteration has been proposed as a possible cause of AD Therefore, several studies have focused on finding an association between inherited mitochondrial DNA variants and AD onset.Methods: In this study, we looked, for the first time, for a potential association between mitochondrial haplogroups or polymorphisms and AD in the Tunisian population. We also evaluated the distribution of the major genetic risk factor for AD, the apolipoprotein E epsilon 4 (APOE ε4), in this population. In total, 159 single-nucleotide polymorphisms (SNPs) of mitochondrial DNA haplogroups were genotyped in 254 individuals (58 patients and 196 controls). An additional genotyping of APOE ε4 was performed.Results: No significant association between mitochondrial haplogroups and AD was found. However, two individual SNPs, A5656G (p = 0.03821, OR = 10.46) and A13759G (p = 0.03719, OR = 10.78), showed a significant association with AD. APOE 4 was confirmed as a risk factor for AD (p = 0.000014). Conclusion: Our findings may confirm the absence of a relation between mitochondrial haplogroups and AD and support the possible involvement of some inherited variants in the pathogenicity of AD.

A Comprehensive Comparison of Haplotype-Based Single-Step Genomic Predictions in Livestock Populations With Different Genetic Diversity Levels: A Simulation Study

The level of genetic diversity in a population is inversely proportional to the linkage disequilibrium (LD) between individual single nucleotide polymorphisms (SNPs) and quantitative trait loci (QTLs), leading to lower predictive ability of genomic breeding values (GEBVs) in high genetically diverse populations. Haplotype-based predictions could outperform individual SNP predictions by better capturing the LD between SNP and QTL. Therefore, we aimed to evaluate the accuracy and bias of individual-SNP- and haplotype-based genomic predictions under the single-step-genomic best linear unbiased prediction (ssGBLUP) approach in genetically diverse populations. We simulated purebred and composite sheep populations using literature parameters for moderate and low heritability traits. The haplotypes were created based on LD thresholds of 0.1, 0.3, and 0.6. Pseudo-SNPs from unique haplotype alleles were used to create the genomic relationship matrix (G) in the ssGBLUP analyses. Alternative scenarios were compared in which the pseudo-SNPs were combined with non-LD clustered SNPs, only pseudo-SNPs, or haplotypes fitted in a second G (two relationship matrices). The GEBV accuracies for the moderate heritability-trait scenarios fitting individual SNPs ranged from 0.41 to 0.55 and with haplotypes from 0.17 to 0.54 in the most (Ne ≅ 450) and less (Ne &lt; 200) genetically diverse populations, respectively, and the bias fitting individual SNPs or haplotypes ranged between −0.14 and −0.08 and from −0.62 to −0.08, respectively. For the low heritability-trait scenarios, the GEBV accuracies fitting individual SNPs ranged from 0.24 to 0.32, and for fitting haplotypes, it ranged from 0.11 to 0.32 in the more (Ne ≅ 250) and less (Ne ≅ 100) genetically diverse populations, respectively, and the bias ranged between −0.36 and −0.32 and from −0.78 to −0.33 fitting individual SNPs or haplotypes, respectively. The lowest accuracies and largest biases were observed fitting only pseudo-SNPs from blocks constructed with an LD threshold of 0.3 (p &lt; 0.05), whereas the best results were obtained using only SNPs or the combination of independent SNPs and pseudo-SNPs in one or two G matrices, in both heritability levels and all populations regardless of the level of genetic diversity. In summary, haplotype-based models did not improve the performance of genomic predictions in genetically diverse populations.

Real-time monitoring and analysis of SARS-CoV-2 nanopore sequencing with minoTour.

Motivation: The ongoing SARS-CoV-2 pandemic has demonstrated the utility of real-time analysis of sequencing data, with a wide range of databases and resources for analysis now available. Here we show how the real-time nature of Oxford Nanopore Technologies sequencers can accelerate consensus generation, lineage and variant status assignment. We exploit the fact that multiplexed viral sequencing libraries quickly generate sufficient data for the majority of samples, with diminishing returns on remaining samples as the sequencing run progresses. We demonstrate methods to determine when a sequencing run has passed this point in order to reduce the time required and cost of sequencing. Results: We extended MinoTour, our real-time analysis and monitoring platform for nanopore sequencers, to provide SARS-CoV2 analysis using ARTIC network pipelines. We additionally developed an algorithm to predict which samples will achieve sufficient coverage, automatically running the ARTIC medaka informatics pipeline once specific coverage thresholds have been reached on these samples. After testing on run data, we find significant run time savings are possible, enabling flow cells to be used more efficiently and enabling higher throughput data analysis. The resultant consensus genomes are assigned both PANGO lineage and variant status as defined by Public Health England. Samples from within individual runs are used to generate phylogenetic trees incorporating optional background samples as well as summaries of individual SNPs. As minoTour uses ARTIC pipelines, new primer schemes and pathogens can be added to allow minoTour to aid in real-time analysis of pathogens in the future.