Finite pp-groups with a minimal non-abelian subgroup of index pp (IV)

In this paper, we completely classify the finite $p$-groups $G$ such that $\Phi(G')G_3\le C_p^2$, $\Phi(G')G_3\le Z(G)$ and $G/\Phi(G')G_3$ is minimal non-abelian. This paper is a part of the classification of finite $p$-groups with a minimal non-abelian subgroup of index $p$. Together with other four papers, we solve a problem proposed by Y. Berkovich

Secreted Frizzled Related Protein 2 Modulates Epithelial–Mesenchymal Transition and Stemness via Wnt/β-Catenin Signaling in Choriocarcinoma

Background/Aims: Choriocarcinoma (CC) is a highly aggressive gestational trophoblastic neoplasia; however, the underlying molecular mechanisms of its invasiveness and metastasis remain poorly understood. Human secreted frizzled-related protein 2 (SFRP2) could function as a tumor promoter or suppressor in different tumors, yet the role it plays in CC’s invasion and metastasis is thoroughly unclear. The current study was aimed to explore the function and underlying mechanism of SFRP2 in CC. Methods: The expression of SFRP2 in CC tissues was examined via immunohistochemistry. The methylation level and expression of SFRP2 in CC cell lines, JEG-3 and JAR were examined via bisulfite sequencing PCR (BSP), western blotting and quantitative RT-PCR. The biological role of increasing expressed SFRP2 through its promoter demethylation with 5-Aza-2’-deoxycytidine (5-Aza) was examined by a series of in vitro functional studies. Furthermore, lentivirus transfection technology was adopted to investigate the biological roles of SFRP2 knockdown in JEG-3 and JAR cells in vitro and in vivo. Moreover, its downstream signaling pathway was investigated. Results: SFRP2 was downregulated in CC tissues, and its expression was inversely related to its promoter hypermethylation frequency in JEG-3 and JAR cells. Increased SFRP2 through its promoter demethylation inhibited cell migration, invasion and colony formation in JEG-3 and JAR cells, whereas decreased SFRP2 reversed the epithelial-mesenchymal transition (EMT) process and stemness in JEG-3 and JAR cells both in vitro and vivo. Mechanistically, SFRP2 regulated the EMT and stemness of CC cell lines via canonical Wnt/β-catenin signaling, validated by the usage of a Wnt activator and inhibitor. Conclusion: The current study indicates that downregulated SFRP2 has potent tumor-promotive effects in CC through the modulation of cancer stemness and the EMT phenotype via activation of Wnt/β-catenin signaling in vitro and in vivo

Refining the accuracy of validated target identification through coding variant fine-mapping in type 2 diabetes.

We aggregated coding variant data for 81,412 type 2 diabetes cases and 370,832 controls of diverse ancestry, identifying 40 coding variant association signals (P < 2.2 × 10-7); of these, 16 map outside known risk-associated loci. We make two important observations. First, only five of these signals are driven by low-frequency variants: even for these, effect sizes are modest (odds ratio ≤1.29). Second, when we used large-scale genome-wide association data to fine-map the associated variants in their regional context, accounting for the global enrichment of complex trait associations in coding sequence, compelling evidence for coding variant causality was obtained for only 16 signals. At 13 others, the associated coding variants clearly represent 'false leads' with potential to generate erroneous mechanistic inference. Coding variant associations offer a direct route to biological insight for complex diseases and identification of validated therapeutic targets; however, appropriate mechanistic inference requires careful specification of their causal contribution to disease predisposition

Adjuvant Chemotherapy Versus Adjuvant Concurrent Chemoradiotherapy After Radical Surgery for Early-Stage Cervical Cancer: A Randomized, Non-Inferiority, Multicenter Trial

We conducted a prospective study to assess the non-inferiority of adjuvant chemotherapy alone versus adjuvant concurrent chemoradiotherapy (CCRT) as an alternative strategy for patients with early-stage (FIGO 2009 stage IB-IIA) cervical cancer having risk factors after surgery. The condition was assessed in terms of prognosis, adverse effects, and quality of life. This randomized trial involved nine centers across China. Eligible patients were randomized to receive adjuvant chemotherapy or CCRT after surgery. The primary end-point was progression-free survival (PFS). From December 2012 to December 2014, 337 patients were subjected to randomization. Final analysis included 329 patients, including 165 in the adjuvant chemotherapy group and 164 in the adjuvant CCRT group. The median follow-up was 72.1 months. The three-year PFS rates were both 91.9%, and the five-year OS was 90.6% versus 90.0% in adjuvant chemotherapy and CCRT groups, respectively. No significant differences were observed in the PFS or OS between groups. The adjusted HR for PFS was 0.854 (95% confidence interval 0.415-1.757; P = 0.667) favoring adjuvant chemotherapy, excluding the predefined non-inferiority boundary of 1.9. The chemotherapy group showed a tendency toward good quality of life. In comparison with post-operative adjuvant CCRT, adjuvant chemotherapy treatment showed non-inferior efficacy in patients with early-stage cervical cancer having pathological risk factors. Adjuvant chemotherapy alone is a favorable alternative post-operative treatment

Sugar-sweetened beverage intake associations with fasting glucose and insulin concentrations are not modified by selected genetic variants in a ChREBP-FGF21 pathway : a meta-analysis

Aims/hypothesis Sugar-sweetened beverages (SSBs) are a major dietary contributor to fructose intake. A molecular pathway involving the carbohydrate responsive element-binding protein (ChREBP) and the metabolic hormone fibroblast growth factor 21 (FGF21) may influence sugar metabolism and, thereby, contribute to fructose-induced metabolic disease. We hypothesise that common variants in 11 genes involved in fructose metabolism and the ChREBP-FGF21 pathway may interact with SSB intake to exacerbate positive associations between higher SSB intake and glycaemic traits. Methods Data from 11 cohorts (six discovery and five replication) in the CHARGE (Cohorts for Heart and Aging Research in Genomic Epidemiology) Consortium provided association and interaction results from 34,748 adults of European descent. SSB intake (soft drinks, fruit punches, lemonades or other fruit drinks) was derived from food-frequency questionnaires and food diaries. In fixed-effects meta-analyses, we quantified: (1) the associations between SSBs and glycaemic traits (fasting glucose and fasting insulin); and (2) the interactions between SSBs and 18 independent SNPs related to the ChREBP-FGF21 pathway. Results In our combined meta-analyses of discovery and replication cohorts, after adjustment for age, sex, energy intake, BMI and other dietary covariates, each additional serving of SSB intake was associated with higher fasting glucose (beta +/- SE 0.014 +/- 0.004 [mmol/l], p = 1.5 x 10(-3)) and higher fasting insulin (0.030 +/- 0.005 [log(e) pmol/l], p = 2.0 x 10(-10)). No significant interactions on glycaemic traits were observed between SSB intake and selected SNPs. While a suggestive interaction was observed in the discovery cohorts with a SNP (rs1542423) in the beta-Klotho (KLB) locus on fasting insulin (0.030 +/- 0.011 log(e) pmol/l, uncorrected p = 0.006), results in the replication cohorts and combined meta-analyses were non-significant. Conclusions/interpretation In this large meta-analysis, we observed that SSB intake was associated with higher fasting glucose and insulin. Although a suggestive interaction with a genetic variant in the ChREBP-FGF21 pathway was observed in the discovery cohorts, this observation was not confirmed in the replication analysis.Peer reviewe

Rare and low-frequency coding variants alter human adult height

Height is a highly heritable, classic polygenic trait with ~700 common associated variants identified so far through genome - wide association studies . Here , we report 83 height - associated coding variants with lower minor allele frequenc ies ( range of 0.1 - 4.8% ) and effects of up to 2 16 cm /allele ( e.g. in IHH , STC2 , AR and CRISPLD2 ) , >10 times the average effect of common variants . In functional follow - up studies, rare height - increasing alleles of STC2 (+1 - 2 cm/allele) compromise d proteolytic inhibition of PAPP - A and increased cleavage of IGFBP - 4 in vitro , resulting in higher bioavailability of insulin - like growth factors . The se 83 height - associated variants overlap genes mutated in monogenic growth disorders and highlight new biological candidates ( e.g. ADAMTS3, IL11RA, NOX4 ) and pathways ( e.g . proteoglycan/ glycosaminoglycan synthesis ) involved in growth . Our results demonstrate that sufficiently large sample sizes can uncover rare and low - frequency variants of moderate to large effect associated with polygenic human phenotypes , and that these variants implicate relevant genes and pathways

The trans-ancestral genomic architecture of glycemic traits

Glycemic traits are used to diagnose and monitor type 2 diabetes and cardiometabolic health. To date, most genetic studies of glycemic traits have focused on individuals of European ancestry. Here we aggregated genome-wide association studies comprising up to 281,416 individuals without diabetes (30% non-European ancestry) for whom fasting glucose, 2-h glucose after an oral glucose challenge, glycated hemoglobin and fasting insulin data were available. Trans-ancestry and single-ancestry meta-analyses identified 242 loci (99 novel; P < 5 x 10(-8)), 80% of which had no significant evidence of between-ancestry heterogeneity. Analyses restricted to individuals of European ancestry with equivalent sample size would have led to 24 fewer new loci. Compared with single-ancestry analyses, equivalent-sized trans-ancestry fine-mapping reduced the number of estimated variants in 99% credible sets by a median of 37.5%. Genomic-feature, gene-expression and gene-set analyses revealed distinct biological signatures for each trait, highlighting different underlying biological pathways. Our results increase our understanding of diabetes pathophysiology by using trans-ancestry studies for improved power and resolution. A trans-ancestry meta-analysis of GWAS of glycemic traits in up to 281,416 individuals identifies 99 novel loci, of which one quarter was found due to the multi-ancestry approach, which also improves fine-mapping of credible variant sets.Peer reviewe

Genetic Drivers of Heterogeneity in Type 2 Diabetes Pathophysiology

Type 2 diabetes (T2D) is a heterogeneous disease that develops through diverse pathophysiological processes1,2 and molecular mechanisms that are often specific to cell type3,4. Here, to characterize the genetic contribution to these processes across ancestry groups, we aggregate genome-wide association study data from 2,535,601 individuals (39.7% not of European ancestry), including 428,452 cases of T2D. We identify 1,289 independent association signals at genome-wide significance (P \u3c 5 × 10-8) that map to 611 loci, of which 145 loci are, to our knowledge, previously unreported. We define eight non-overlapping clusters of T2D signals that are characterized by distinct profiles of cardiometabolic trait associations. These clusters are differentially enriched for cell-type-specific regions of open chromatin, including pancreatic islets, adipocytes, endothelial cells and enteroendocrine cells. We build cluster-specific partitioned polygenic scores5 in a further 279,552 individuals of diverse ancestry, including 30,288 cases of T2D, and test their association with T2D-related vascular outcomes. Cluster-specific partitioned polygenic scores are associated with coronary artery disease, peripheral artery disease and end-stage diabetic nephropathy across ancestry groups, highlighting the importance of obesity-related processes in the development of vascular outcomes. Our findings show the value of integrating multi-ancestry genome-wide association study data with single-cell epigenomics to disentangle the aetiological heterogeneity that drives the development and progression of T2D. This might offer a route to optimize global access to genetically informed diabetes care

Genetic drivers of heterogeneity in type 2 diabetes pathophysiology

Type 2 diabetes (T2D) is a heterogeneous disease that develops through diverse pathophysiological processes1,2 and molecular mechanisms that are often specific to cell type3,4. Here, to characterize the genetic contribution to these processes across ancestry groups, we aggregate genome-wide association study data from 2,535,601 individuals (39.7% not of European ancestry), including 428,452 cases of T2D. We identify 1,289 independent association signals at genome-wide significance (P &lt; 5 × 10-8) that map to 611 loci, of which 145 loci are, to our knowledge, previously unreported. We define eight non-overlapping clusters of T2D signals that are characterized by distinct profiles of cardiometabolic trait associations. These clusters are differentially enriched for cell-type-specific regions of open chromatin, including pancreatic islets, adipocytes, endothelial cells and enteroendocrine cells. We build cluster-specific partitioned polygenic scores5 in a further 279,552 individuals of diverse ancestry, including 30,288 cases of T2D, and test their association with T2D-related vascular outcomes. Cluster-specific partitioned polygenic scores are associated with coronary artery disease, peripheral artery disease and end-stage diabetic nephropathy across ancestry groups, highlighting the importance of obesity-related processes in the development of vascular outcomes. Our findings show the value of integrating multi-ancestry genome-wide association study data with single-cell epigenomics to disentangle the aetiological heterogeneity that drives the development and progression of T2D. This might offer a route to optimize global access to genetically informed diabetes care.</p

Large-scale exome array summary statistics resources for glycemic traits to aid effector gene prioritization

BACKGROUND: Genome-wide association studies for glycemic traits have identified hundreds of loci associated with these biomarkers of glucose homeostasis. Despite this success, the challenge remains to link variant associations to genes, and underlying biological pathways. METHODS: To identify coding variant associations which may pinpoint effector genes at both novel and previously established genome-wide association loci, we performed meta-analyses of exome-array studies for four glycemic traits: glycated hemoglobin (HbA1c, up to 144,060 participants), fasting glucose (FG, up to 129,665 participants), fasting insulin (FI, up to 104,140) and 2hr glucose post-oral glucose challenge (2hGlu, up to 57,878). In addition, we performed network and pathway analyses. RESULTS: Single-variant and gene-based association analyses identified coding variant associations at more than 60 genes, which when combined with other datasets may be useful to nominate effector genes. Network and pathway analyses identified pathways related to insulin secretion, zinc transport and fatty acid metabolism. HbA1c associations were strongly enriched in pathways related to blood cell biology. CONCLUSIONS: Our results provided novel glycemic trait associations and highlighted pathways implicated in glycemic regulation. Exome-array summary statistic results are being made available to the scientific community to enable further discoveries