Risk of 16 cancers across the full glycemic spectrum: a population-based cohort study using the UK Biobank.

INTRODUCTION: Diabetes is observed to increase cancer risk, leading to hypothesized direct effects of either hyperglycemia or medication. We investigated associations between glycosylated hemoglobin (HbA1c) across the whole glycemic spectrum and incidence of 16 cancers in a population sample with comprehensive adjustment for risk factors and medication. RESEARCH DESIGN AND METHODS: Linked data from the UK Biobank and UK cancer registry for all individuals with baseline HbA1c and no history of cancer at enrollment were used. Incident cancer was based on International Classification of Diseases - 10th Edition diagnostic codes. Age-standardized incidence rates were estimated by HbA1c category. Associations between HbA1c, modeled as a restricted cubic spline, and cancer risk were estimated using Cox proportional hazards models. RESULTS: Among 378 253 individuals with average follow-up of 7.1 years, 21 172 incident cancers occurred. While incidence for many of the 16 cancers was associated with hyperglycemia in crude analyses, these associations disappeared after multivariable adjustment, except for pancreatic cancer (HR 1.55, 95% CI 1.22 to 1.98 for 55 vs 35 mmol/mol), and a novel finding of an inverse association between HbA1c and premenopausal breast cancer (HR 1.27, 95% CI 1.00 to 1.60 for 25 vs 35 mmol/mol; HR 0.71, 95% CI 0.54 to 0.94 for 45 vs 35 mmol/mol), not observed for postmenopausal breast cancer. Adjustment for diabetes medications had no appreciable impact on HRs for cancer. CONCLUSIONS: Apart from pancreatic cancer, we did not demonstrate any independent positive association between HbA1c and cancer risk. These findings suggest that the potential for a cancer-inducing, direct effect of hyperglycemia may be misplaced

HbA1c and brain health across the entire glycaemic spectrum.

AIM: To understand the relationship between HbA1c and brain health across the entire glycaemic spectrum. MATERIALS AND METHODS: We used data from the UK Biobank cohort consisting of 500,000 individuals aged 40-69?years. HbA1c and diabetes diagnosis were used to define baseline glycaemic categories. Our outcomes included incident all-cause dementia, vascular dementia (VD), Alzheimer's dementia (AD), hippocampal volume (HV), white matter hyperintensity (WMH) volume, cognitive function and decline. The reference group was normoglycaemic individuals (HbA1c ?35 & <42 mmol/mol). Our maximum analytical sample contained 449,973 individuals with complete data. RESULTS: Prediabetes and known diabetes increased incident VD (HR 1.54; 95% CI = 1.04, 2.28 and HR 2.97; 95% CI = 2.26, 3.90, respectively). Known diabetes increased all-cause and AD risk (HR 1.91; 95% CI = 1.66, 2.21 and HR 1.84; 95% CI = 1.44, 2.36, respectively). Prediabetes and known diabetes elevated the risks of cognitive decline (OR 1.42; 1.48, 2.96 and OR 1.39; 1.04, 1.75, respectively). Prediabetes, undiagnosed and known diabetes conferred higher WMH volumes (3%, 22% and 7%, respectively) and lower HV (36, 80 and 82?mm3 , respectively), whereas low-normal HbA1c had 1% lower WMH volume and 12?mm3 greater HV. CONCLUSION: Both prediabetes and known diabetes are harmful in terms of VD, cognitive decline and AD risks, as well as lower HV. Associations appeared to be somewhat driven by antihypertensive medication, which implies that certain cardiovascular drugs may ameliorate some of the excess risk. Low-normal HbA1c levels, however, are associated with more favourable brain health outcomes and warrant more in-depth investigation

Is glycaemia associated with poorer brain health and risk of dementia? Cross sectional and follow-up analysis of the UK Biobank

ABSTRACTINTRODUCTIONTo understand the relationship across the glycaemic spectrum, with brain health.METHODSUK Biobank participants. HbA1c and diabetes diagnosis define baseline glycaemic categories. Outcomes: incident vascular dementia (VD), Alzheimer’s dementia (AD), hippocampal volume (HV), white matter hyperintensity (WMH) volume, cognitive function and decline. Reference group: normoglycaemic individuals (HbA1c 35-&lt;42 mmol/mol).RESULTSPre- and known diabetes increased incident VD, (HR 1.54, 95%CI=1.04;2.28 and 2.97, 95%CI=2.26;3.90). Known diabetes increased AD risk (HR 1.84, 95%CI=1.44;2.36). Pre- and known diabetes elevated risks of cognitive decline (OR 1.42, 1.48;2.96 and 1.39, 1.04;1.75). Pre-diabetes, undiagnosed and known diabetes conferred higher WMH volumes (4%, 26%, 5%,) and lower HV (22.4mm3, 15.2mm3, 62.2mm3). Low-normal HbA1c had 2% lower WMH volume and 13.6mm3 greater HV.DISCUSSIONPre and known diabetes increase VD risks; known diabetes increases AD risk. Low-normal HbA1c associates with favourable neuroimaging outcomes. Our findings may have implications for cardiovascular medication in hyperglycaemia for brain health.</jats:sec

Chromosome 9p copy number gains involving PD-L1 are associated with a specific proliferation and immune-modulating gene expression program active across major cancer types

BACKGROUND: Inhibition of the PD-L1/PD-1 immune checkpoint axis represents one of the most promising approaches of immunotherapy for various cancer types. However, immune checkpoint inhibition is successful only in subpopulations of patients emphasizing the need for powerful biomarkers that adequately reflect the complex interaction between the tumor and the immune system. Recently, recurrent copy number gains (CNG) in chromosome 9p involving PD-L1 were detected in many cancer types including lung cancer, melanoma, bladder cancer, head and neck cancer, cervical cancer, soft tissue sarcoma, prostate cancer, gastric cancer, ovarian cancer, and triple-negative breast cancer. METHODS: Here, we applied functional genomics to analyze global mRNA expression changes associated with chromosome 9p gains. Using the TCGA data set, we identified a list of 75 genes that were strongly up-regulated in tumors with chromosome 9p gains across many cancer types. RESULTS: As expected, the gene set was enriched for chromosome 9p and in particular chromosome 9p24 (36 genes and 23 genes). Furthermore, we found enrichment of two expression programs derived from genes within and beyond 9p: one implicated in cell cycle regulation (22 genes) and the other implicated in modulation of the immune system (16 genes). Among these were specific cytokines and chemokines, e.g. CCL4, CCL8, CXCL10, CXCL11, other immunoregulatory genes such as IFN-G and IDO1 as well as highly expressed proliferation-related kinases and genes including PLK1, TTK, MELK and CDC20 that represent potential drug targets. CONCLUSIONS: Collectively, these data shed light on mechanisms of immune escape and stimulation of proliferation in cancer with PD-L1 CNG and highlight additional vulnerabilities that may be therapeutically exploitable

The tourism and economic growth enigma: Examining an ambiguous relationship through multiple prisms

This paper revisits the ambiguous relationship between tourism and economic growth, providing a comprehensive study of destinations across the globe which takes into account the key dynamics that influence tourism and economic performance. We focus on 113 countries over the period 1995-2014, clustered, for the first time, around six criteria that reflect their economic, political and tourism dimensions. A Panel Vector Autoregressive model is employed which, in contrast to previous studies, allows the data to reveal any tourism-economy interdependencies across these clusters, without imposing a priori the direction of causality. Overall, the economic-driven tourism growth hypothesis seems to prevail in countries which are developing, non-democratic, highly bureaucratic and have low tourism specialization. Conversely, bidirectional relationships are established for economies which are stronger, democratic and with higher levels of government effectiveness. Thus, depending on the economic, political and tourism status of a destination, different policy implications apply

Natural variation of potato allene oxide synthase 2 causes differential levels of jasmonates and pathogen resistance in Arabidopsis

Natural variation of plant pathogen resistance is often quantitative. This type of resistance can be genetically dissected in quantitative resistance loci (QRL). To unravel the molecular basis of QRL in potato (Solanum tuberosum), we employed the model plant Arabidopsis thaliana for functional analysis of natural variants of potato allene oxide synthase 2 (StAOS2). StAOS2 is a candidate gene for QRL on potato chromosome XI against the oömycete Phytophthora infestans causing late blight, and the bacterium Erwinia carotovora ssp. atroseptica causing stem black leg and tuber soft rot, both devastating diseases in potato cultivation. StAOS2 encodes a cytochrome P450 enzyme that is essential for biosynthesis of the defense signaling molecule jasmonic acid. Allele non-specific dsRNAi-mediated silencing of StAOS2 in potato drastically reduced jasmonic acid production and compromised quantitative late blight resistance. Five natural StAOS2 alleles were expressed in the null Arabidopsis aos mutant under control of the Arabidopsis AOS promoter and tested for differential complementation phenotypes. The aos mutant phenotypes evaluated were lack of jasmonates, male sterility and susceptibility to Erwinia carotovora ssp. carotovora. StAOS2 alleles that were associated with increased disease resistance in potato complemented all aos mutant phenotypes better than StAOS2 alleles associated with increased susceptibility. First structure models of ‘quantitative resistant’ versus ‘quantitative susceptible’ StAOS2 alleles suggested potential mechanisms for their differential activity. Our results demonstrate how a candidate gene approach in combination with using the homologous Arabidopsis mutant as functional reporter can help to dissect the molecular basis of complex traits in non model crop plants

A reference panel of 64,976 haplotypes for genotype imputation.

We describe a reference panel of 64,976 human haplotypes at 39,235,157 SNPs constructed using whole-genome sequence data from 20 studies of predominantly European ancestry. Using this resource leads to accurate genotype imputation at minor allele frequencies as low as 0.1% and a large increase in the number of SNPs tested in association studies, and it can help to discover and refine causal loci. We describe remote server resources that allow researchers to carry out imputation and phasing consistently and efficiently