Specialized 16SrX phytoplasmas induce diverse morphological and physiological changes in their respective fruit crops

The host-pathogen combinations-Malus domestica (apple)/`Candidatus Phytoplasma mali´, Prunus persica (peach)/`Ca. P. prunorum´ and Pyrus communis (pear)/`Ca. P. pyri´ show different courses of diseases although the phytoplasma strains belong to the same 16SrX group. While infected apple trees can survive for decades, peach and pear trees die within weeks to few years. To this date, neither morphological nor physiological differences caused by phytoplasmas have been studied in these host plants. In this study, phytoplasma-induced morphological changes of the vascular system as well as physiological changes of the phloem sap and leaf phytohormones were analysed and compared with non-infected plants. Unlike peach and pear, infected apple trees showed substantial reductions in leaf and vascular area, affecting phloem mass flow. In contrast, in infected pear mass flow and physicochemical characteristics of phloem sap increased. Additionally, an increased callose deposition was detected in pear and peach leaves but not in apple trees in response to phytoplasma infection. The phytohormone levels in pear were not affected by an infection, while in apple and peach trees concentrations of defence- and stress-related phytohormones were increased. Compared with peach and pear trees, data from apple suggest that the long-lasting morphological adaptations in the vascular system, which likely cause reduced sap flow, triggers the ability of apple trees to survive phytoplasma infection. Some phytohormone-mediated defences might support the tolerance

Exome-wide association study of pancreatic cancer risk

We conducted a case-control exome-wide association study to discover germline variants in coding regions that affect risk for pancreatic cancer, combining data from 5 studies. We analyzed exome and genome sequencing data from 437 patients with pancreatic cancer (cases) and 1922 individuals not known to have cancer (controls). In the primary analysis, BRCA2 had the strongest enrichment for rare inactivating variants (17/437 cases vs 3/1922 controls) (P=3.27x10(-6); exome-wide statistical significance threshold P<2.5x10(-6)). Cases had more rare inactivating variants in DNA repair genes than controls, even after excluding 13 genes known to predispose to pancreatic cancer (adjusted odds ratio, 1.35, P=.045). At the suggestive threshold (P<.001), 6 genes were enriched for rare damaging variants (UHMK1, AP1G2, DNTA, CHST6, FGFR3, and EPHA1) and 7 genes had associations with pancreatic cancer risk, based on the sequence-kernel association test. We confirmed variants in BRCA2 as the most common high-penetrant genetic factor associated with pancreatic cancer and we also identified candidate pancreatic cancer genes. Large collaborations and novel approaches are needed to overcome the genetic heterogeneity of pancreatic cancer predisposition

Identification of genes expressed by immune cells of the colon that are regulated by colorectal cancer-associated variants.

A locus on human chromosome 11q23 tagged by marker rs3802842 was associated with colorectal cancer (CRC) in a genome-wide association study; this finding has been replicated in case-control studies worldwide. In order to identify biologic factors at this locus that are related to the etiopathology of CRC, we used microarray-based target selection methods, coupled to next-generation sequencing, to study 103 kb at the 11q23 locus. We genotyped 369 putative variants from 1,030 patients with CRC (cases) and 1,061 individuals without CRC (controls) from the Ontario Familial Colorectal Cancer Registry. Two previously uncharacterized genes, COLCA1 and COLCA2, were found to be co-regulated genes that are transcribed from opposite strands. Expression levels of COLCA1 and COLCA2 transcripts correlate with rs3802842 genotypes. In colon tissues, COLCA1 co-localizes with crystalloid granules of eosinophils and granular organelles of mast cells, neutrophils, macrophages, dendritic cells and differentiated myeloid-derived cell lines. COLCA2 is present in the cytoplasm of normal epithelial, immune and other cell lineages, as well as tumor cells. Tissue microarray analysis demonstrates the association of rs3802842 with lymphocyte density in the lamina propria (p = 0.014) and levels of COLCA1 in the lamina propria (p = 0.00016) and COLCA2 (tumor cells, p = 0.0041 and lamina propria, p = 6 × 10(-5)). In conclusion, genetic, expression and immunohistochemical data implicate COLCA1 and COLCA2 in the pathogenesis of colon cancer. Histologic analyses indicate the involvement of immune pathways

Colorectal cancer linkage on chromosomes 4q21, 8q13, 12q24, and 15q22

A substantial proportion of familial colorectal cancer (CRC) is not a consequence of known susceptibility loci, such as mismatch repair (MMR) genes, supporting the existence of additional loci. To identify novel CRC loci, we conducted a genome-wide linkage scan in 356 white families with no evidence of defective MMR (i.e., no loss of tumor expression of MMR proteins, no microsatellite instability (MSI)-high tumors, or no evidence of linkage to MMR genes). Families were ascertained via the Colon Cancer Family Registry multi-site NCI-supported consortium (Colon CFR), the City of Hope Comprehensive Cancer Center, and Memorial University of Newfoundland. A total of 1,612 individuals (average 5.0 per family including 2.2 affected) were genotyped using genome-wide single nucleotide polymorphism linkage arrays; parametric and non-parametric linkage analysis used MERLIN in a priori-defined family groups. Five lod scores greater than 3.0 were observed assuming heterogeneity. The greatest were among families with mean age of diagnosis less than 50 years at 4q21.1 (dominant HLOD = 4.51, α = 0.84, 145.40 cM, rs10518142) and among all families at 12q24.32 (dominant HLOD = 3.60, α = 0.48, 285.15 cM, rs952093). Among families with four or more affected individuals and among clinic-based families, a common peak was observed at 15q22.31 (101.40 cM, rs1477798; dominant HLOD = 3.07, α = 0.29; dominant HLOD = 3.03, α = 0.32, respectively). Analysis of families with only two affected individuals yielded a peak at 8q13.2 (recessive HLOD = 3.02, α = 0.51, 132.52 cM, rs1319036). These previously unreported linkage peaks demonstrate the continued utility of family-based data in complex traits and suggest that new CRC risk alleles remain to be elucidated. © 2012 Cicek et al

Using honey to heal diabetic foot ulcers

Diabetic ulcers seem to be arrested in the inflammatory/proliferative stage of the healing process, allowing infection and inflammation to preclude healing. Antibiotic-resistant bacteria have become a major cause of infections, including diabetic foot infections. It is proposed here that the modern developments of an ancient and traditional treatment for wounds, dressing them with honey, provide the solution to the problem of getting diabetic ulcers to move on from the arrested state of healing. Honeys selected to have a high level of antibacterial activity have been shown to be very effective against antibiotic-resistant strains of bacteria in laboratory and clinical studies. The potent anti-inflammatory action of honey is also likely to play an important part in overcoming the impediment to healing that inflammation causes in diabetic ulcers, as is the antioxidant activity of honey. The action of honey in promotion of tissue regeneration through stimulation of angiogenesis and the growth of fibroblasts and epithelial cells, and its insulin-mimetic effect, would also be of benefit in stimulating the healing of diabetic ulcers. The availability of honey-impregnated dressings which conveniently hold honey in place on ulcers has provided a means of rapidly debriding ulcers and removing the bacterial burden so that good healing rates can be achieved with neuropathic ulcers. With ischemic ulcers, where healing cannot occur because of lack of tissue viability, these honey dressings keep the ulcers clean and prevent infection occurring

Incorporating multiple sets of eQTL weights into gene-by-environment interaction analysis identifies novel susceptibility loci for pancreatic cancer.

It is of great scientific interest to identify interactions between genetic variants and environmental exposures that may modify the risk of complex diseases. However, larger sample sizes are usually required to detect gene-by-environment interaction (G × E) than required to detect genetic main association effects. To boost the statistical power and improve the understanding of the underlying molecular mechanisms, we incorporate functional genomics information, specifically, expression quantitative trait loci (eQTLs), into a data-adaptive G × E test, called aGEw. This test adaptively chooses the best eQTL weights from multiple tissues and provides an extra layer of weighting at the genetic variant level. Extensive simulations show that the aGEw test can control the Type 1 error rate, and the power is resilient to the inclusion of neutral variants and noninformative external weights. We applied the proposed aGEw test to the Pancreatic Cancer Case-Control Consortium (discovery cohort of 3,585 cases and 3,482 controls) and the PanScan II genome-wide association study data (replication cohort of 2,021 cases and 2,105 controls) with smoking as the exposure of interest. Two novel putative smoking-related pancreatic cancer susceptibility genes, TRIP10 and KDM3A, were identified. The aGEw test is implemented in an R package aGE.We thank the two anonymous reviewers for their constructive comments. This research was supported by the National Institutes of Health (NIH) grant R01CA169122; P.W. was supported by NIH grants R01HL116720 and R21HL126032. S.H.O. was supported by NIH grant P30CA008748. R.E.N. and the Queensland Pancreatic Cancer Study were funded by the Australian National Health and Medical Research Council. The authors thank Ms. Jessica Swann and the National Institute of Statistical Sciences writing workshop for editorial assistance and suggestions. The authors acknowledge the Texas Advanced Computing Center at The University of Texas at Austin for providing computing resources. The authors alone are responsible for the views expressed in this article and they do not necessarily represent the views, decisions or policies of the institutions with which they are affiliated. The authors declare that there is no conflict of interest