Screening and Isolation of Cytotoxic Compounds From Local Marine Aaptos Species

Over the recent years, marine sponges have been the target of research as a source of new chemicals with therapeutic potential. They have been proven to have a high strike rate especially for cytotoxic compounds. Thirteen species of marine sponges collected from Pulau Kapas, Pulau Bidong and Pulau Redang were preliminarily identified as Aaptos sp. (I), Xestospongia exigua (2), unidentified sp. (3), Xestospongia sp. (4), Xestospongia testudinaria (5), Callyspongia sp. (6), Theonella sp. (7), Theonella sp. (S), Sigmaducza arnbolnenuris (9), Ircinia sp. (lo), Dysedza sp. (1 I), unidentified sp. (12) and Ircinia Halisarca (13). The crude methanol extracts of these samples were screened for cytotoxic activities against a panel of cell lines, namely HL-60 (promyelocytic leukemia), CEM-SS (T-lymphoblastic leukemia), MCF-7 (breast cancer), HeLa (cervical cancer), HT-29 (colon cancer) and L929 (murine fibrosarcoma from mouse) using a colorimetric tetrmlium (MTT) assay. Crude extracts from 1 and 10 were active against all six cell lines with CDm values ranging from 1.05 to 24.1 pglml whereas extracts 2, 3 and 8 showed activity only against H1L-60, CEM-SS and HT-29 with CDso values ranpg from 12.95 to 29.5 pglml. Aaptos sp. (1) was chosen for further investigations due to its abundance and strong cytotoxic activity. Bioassay guided isolation and purification of compounds afforded three cytotoxic alkaloids. H19 was identified as the previously isolated aaptamine [I] and the two orange compounds were established as the new aaptaminoid alkaloids, 01 and 02. All three compounds exhibited significant cytotoxic activity against CEM-SS cells with respective CD50 values of 15.0,5.3 and 6.7 pg/ml. When tested against 3T3 (normal mouse fibroblast), all three compounds displayed weak cytotoxicities. The CDS0 of compound 01 and 02 were determined as 21.2 and 21.0 pg/ml respectively. On the other hand, compound 3319 did not achieve a CDSo. Phase contrast microscopic analysis showed that compound H19, 01 and 02 induced apoptosis in CEM-SS cells. The apoptotic features observed include cell shrinkage, condensation of chromatin material, membrane blebbing and the formation of apoptotic bodies. Due to insufficient quantity of 0 1 and 02, only H19 was subjected to subsequent evaluation using fluorescence microscopy. These results further supported that H19 induce apoptosis in CEM-SS as exemplified by the morphological changes observed

Arecoline induces HA22T/VGH hepatoma cells to undergo anoikis - involvement of STAT3 and RhoA activation

<p>Abstract</p> <p>Background</p> <p>Our previous study showed that, in basal cell carcinoma cells, arecoline reduces levels of the tumor cell survival factor interleukin-6 (IL-6), increases levels of tumor suppressor factor p53, and elicits cell cycle arrest, followed by apoptosis. In preliminarily studies, we observed that arecoline induces detachment of the human-derived hepatoma cell line HA22T/VGH from the extracellular matrix. In the present study, we explored the fate of the detached HA22T/VGH cells and investigated the underlying mechanism.</p> <p>Methods</p> <p>HA22T/VGH cells or primary cultured rat hepatocytes were treated with arecoline, then changes in morphology, viability, apoptosis, and the expression of surface β1-integrin, apoptosis-related proteins, and IL-6 were examined. Furthermore, activation of the signal transducer and activator of transcription 3 (STAT3) pathway and the RhoA/Rock signaling pathway, including p190RhoGAP and Src homology-2 domain-containing phosphatase SHP2, was examined.</p> <p>Results</p> <p>A low concentration of arecoline (≤ 100 μg/ml) caused cytoskeletal changes in HA22T/VGH cells, but not hepatocytes, and this was accompanied by decreased β1-integrin expression and followed by apoptosis, indicating that HA22T/VGH cells undergo anoikis after arecoline treatment. IL-6 expression and phosphorylation of STAT3, which provides protection against anoikis, were inhibited and levels of downstream signaling proteins, including Bcl-X_Land Bcl-2, were decreased, while Bax expression, mitochondrial cytochrome c release, and caspase-3 activity were increased. In addition, phosphorylation/activation of p190RhoGAP, a RhoA inhibitor, and of its upstream regulator, SHP2, was inhibited by arecoline treatment, while Rho/Rock activation was increased. Addition of the RhoA inhibitor attenuated the effects of arecoline.</p> <p>Conclusions</p> <p>This study demonstrated that arecoline induces anoikis of HA22T/VGH cells involving inhibition of STAT3 and increased RhoA/Rock activation and that the STAT3 and RhoA/Rock signaling pathways are connected.</p

Cytotoxic Aaptamines from Malaysian Aaptos aaptos

In a preliminary screen, Aaptos aaptos showed significant cytotoxic activity towards a panel of cell lines and was thus subjected to bioassay-guided isolation of the bioactive constituents. In addition to the known aaptamine, two new derivatives of the alkaloid were isolated from the bioactive chloroform fraction of the crude methanolic extract. Detailed analysis by NMR and mass spectroscopy enabled their identification to be 3-(phenethylamino)demethyl(oxy)aaptamine and 3-(isopentylamino)demethyl(oxy) aaptamine. The cytotoxic activities of the three alkaloids were further evaluated against CEM-SS cells

Progesterone Increases Apoptosis and Inversely Decreases Autophagy in Human Hepatoma HA22T/VGH Cells Treated with Epirubicin

Hepatocellular carcinoma (HCC) is the leading cause of cancer-related deaths worldwide. Epirubicin can induce intracellular reactive oxygen species and is widely used to treat unresectable HCC. Progesterone has been found to inhibit the proliferation of hepatoma cells. This study was designed to test the combined effects of epirubicin and progesterone on human hepatoma cell line, HA22T/VGH. These cells were treated with different concentrations of epirubicin with or without the coaddition of 30 μM progesterone and then analyzed for apoptosis, autophagy, and expressions of apoptotic-related proteins and multidrug-resistant gene. Epirubicin treatment dose-dependently inhibited the growth of HA22T/VGH cells. Addition of 30 μM progesterone, which was inactive alone, augmented the effect of epirubicin on the inhibition of growth of HA22T/VGH cells. Cotreatment with progesterone enhanced epirubicin-induced apoptosis, as evidenced by greater increase in caspase-3 activity and in the ratio of the apoptosis-regulating protein, Bax/Bcl-XL. The combination also caused a decrease in autophagy and in the expression of multidrug resistance-related protein 1 mRNA compared to epirubicin alone. This study shows the epirubicin/progesterone combination was more effective in increasing apoptosis and inversely decreasing autophagy on HA22T/VGH cells treated with epirubicin alone, suggesting that this combination can potentially be used to treat HCC

Screening for eukaryotic signal transduction and Mycobacterium isocitrate lyase inhibitor from actinomycetes and fungi of dipterocarp rain forests at Imabak Valey, Sabah, Malaysia

A diversity of actinomycetes and fungi was isolated from various sites during the Imbak Valley Scientific Expedition 2000. A total of 144 soil samples were collected under trees that have been identified to species or genus level. Imbak Valley is a lowland dipterocarp forest, which is interestingly dominated by Dryobalanops beccarii. Isolation of Streptomyces and non-Streptomyces actinomycetes on HV medium and other specific isolation media for non-Streptomyces yielded 203 isolates from 89 soil samples. Morphological characterisation of the isolated actinomycetes was carried out based on aerial mycelium colour, substrate mycelium colour and diffusible pigment production on oatmeal medium. Nine strains of fungi were isolated from the six soil samples plated on PDA medium. All actinomycetes isolates were grown under aerobic condition in liquid culture and extracted with acetone, and used for screening against proteins involved eukaryotic signal transduction. Yeast MAPK kinase and MAP kinase phosphatase were some of the targeted proteins used in this research. MKK1P386 and MKK1P386-MSG5 mutant yeasts were used to screen for these inhibitors, as these yeast kinase and phosphatase have homologous proteins in the MAP kinase signal transduction pathway in human. No inhibitors in the extracts were found in these screenings. Type 1 protein serine/ threonine phosphatase (GLC7) in yeast was used to screen inhibitors against PP1 inhibitors and no inhibitor was found. None of the fungal extracts showed any inhibitory activities in all the screening systems. No Ras/Raf inhibitor was found in the in vivo Ras/Raf interaction with the yeast two-hybrid screening system, which used to screen for inhibitor against Ras/ Raf protein interaction inhibitor. There were 11 actinomycetes extracts that showed toxicity against yeast strain LZ (transformant of Ras/ Raf). H7667, a Streptomycete toxic to yeast is further screened for inhibitors of the GSK3-beta pathway. H7763, a Streptomyces species that showed positive in the primary screen for inhibitor of isocitrate lyase (ICL) which is not itaconic acid (known ICL inhibitor). H7240 showed the strongest susceptibility towards the resin in which the concentration of 5g/l of resin is sufficient to produce growth inhibition of the bacteria

New genetic loci link adipose and insulin biology to body fat distribution.

Body fat distribution is a heritable trait and a well-established predictor of adverse metabolic outcomes, independent of overall adiposity. To increase our understanding of the genetic basis of body fat distribution and its molecular links to cardiometabolic traits, here we conduct genome-wide association meta-analyses of traits related to waist and hip circumferences in up to 224,459 individuals. We identify 49 loci (33 new) associated with waist-to-hip ratio adjusted for body mass index (BMI), and an additional 19 loci newly associated with related waist and hip circumference measures (P < 5 × 10(-8)). In total, 20 of the 49 waist-to-hip ratio adjusted for BMI loci show significant sexual dimorphism, 19 of which display a stronger effect in women. The identified loci were enriched for genes expressed in adipose tissue and for putative regulatory elements in adipocytes. Pathway analyses implicated adipogenesis, angiogenesis, transcriptional regulation and insulin resistance as processes affecting fat distribution, providing insight into potential pathophysiological mechanisms

Erratum: Global, regional, and national comparative risk assessment of 84 behavioural, environmental and occupational, and metabolic risks or clusters of risks for 195 countries and territories, 1990–2017: a systematic analysis for the Global Burden of Disease Study 2017

Interpretation: By quantifying levels and trends in exposures to risk factors and the resulting disease burden, this assessment offers insight into where past policy and programme efforts might have been successful and highlights current priorities for public health action. Decreases in behavioural, environmental, and occupational risks have largely offset the effects of population growth and ageing, in relation to trends in absolute burden. Conversely, the combination of increasing metabolic risks and population ageing will probably continue to drive the increasing trends in non-communicable diseases at the global level, which presents both a public health challenge and opportunity. We see considerable spatiotemporal heterogeneity in levels of risk exposure and risk-attributable burden. Although levels of development underlie some of this heterogeneity, O/E ratios show risks for which countries are overperforming or underperforming relative to their level of development. As such, these ratios provide a benchmarking tool to help to focus local decision making. Our findings reinforce the importance of both risk exposure monitoring and epidemiological research to assess causal connections between risks and health outcomes, and they highlight the usefulness of the GBD study in synthesising data to draw comprehensive and robust conclusions that help to inform good policy and strategic health planning

Global, regional, and national comparative risk assessment of 84 behavioural, environmental and occupational, and metabolic risks or clusters of risks for 195 countries and territories, 1990-2017: a systematic analysis for the Global Burden of Disease Study 2017

Background The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2017 comparative risk assessment (CRA) is a comprehensive approach to risk factor quantification that offers a useful tool for synthesising evidence on risks and risk–outcome associations. With each annual GBD study, we update the GBD CRA to incorporate improved methods, new risks and risk–outcome pairs, and new data on risk exposure levels and risk–outcome associations. Methods We used the CRA framework developed for previous iterations of GBD to estimate levels and trends in exposure, attributable deaths, and attributable disability-adjusted life-years (DALYs), by age group, sex, year, and location for 84 behavioural, environmental and occupational, and metabolic risks or groups of risks from 1990 to 2017. This study included 476 risk–outcome pairs that met the GBD study criteria for convincing or probable evidence of causation. We extracted relative risk and exposure estimates from 46 749 randomised controlled trials, cohort studies, household surveys, census data, satellite data, and other sources. We used statistical models to pool data, adjust for bias, and incorporate covariates. Using the counterfactual scenario of theoretical minimum risk exposure level (TMREL), we estimated the portion of deaths and DALYs that could be attributed to a given risk. We explored the relationship between development and risk exposure by modelling the relationship between the Socio-demographic Index (SDI) and risk-weighted exposure prevalence and estimated expected levels of exposure and risk-attributable burden by SDI. Finally, we explored temporal changes in risk-attributable DALYs by decomposing those changes into six main component drivers of change as follows: (1) population growth; (2) changes in population age structures; (3) changes in exposure to environmental and occupational risks; (4) changes in exposure to behavioural risks; (5) changes in exposure to metabolic risks; and (6) changes due to all other factors, approximated as the risk-deleted death and DALY rates, where the risk-deleted rate is the rate that would be observed had we reduced the exposure levels to the TMREL for all risk factors included in GBD 2017. Findings In 2017, 34·1 million (95% uncertainty interval [UI] 33·3–35·0) deaths and 1·21 billion (1·14–1·28) DALYs were attributable to GBD risk factors. Globally, 61·0% (59·6–62·4) of deaths and 48·3% (46·3–50·2) of DALYs were attributed to the GBD 2017 risk factors. When ranked by risk-attributable DALYs, high systolic blood pressure (SBP) was the leading risk factor, accounting for 10·4 million (9·39–11·5) deaths and 218 million (198–237) DALYs, followed by smoking (7·10 million [6·83–7·37] deaths and 182 million [173–193] DALYs), high fasting plasma glucose (6·53 million [5·23–8·23] deaths and 171 million [144–201] DALYs), high body-mass index (BMI; 4·72 million [2·99–6·70] deaths and 148 million [98·6–202] DALYs), and short gestation for birthweight (1·43 million [1·36–1·51] deaths and 139 million [131–147] DALYs). In total, risk-attributable DALYs declined by 4·9% (3·3–6·5) between 2007 and 2017. In the absence of demographic changes (ie, population growth and ageing), changes in risk exposure and risk-deleted DALYs would have led to a 23·5% decline in DALYs during that period. Conversely, in the absence of changes in risk exposure and risk-deleted DALYs, demographic changes would have led to an 18·6% increase in DALYs during that period. The ratios of observed risk exposure levels to exposure levels expected based on SDI (O/E ratios) increased globally for unsafe drinking water and household air pollution between 1990 and 2017. This result suggests that development is occurring more rapidly than are changes in the underlying risk structure in a population. Conversely, nearly universal declines in O/E ratios for smoking and alcohol use indicate that, for a given SDI, exposure to these risks is declining. In 2017, the leading Level 4 risk factor for age-standardised DALY rates was high SBP in four super-regions: central Europe, eastern Europe, and central Asia; north Africa and Middle East; south Asia; and southeast Asia, east Asia, and Oceania. The leading risk factor in the high-income super-region was smoking, in Latin America and Caribbean was high BMI, and in sub-Saharan Africa was unsafe sex. O/E ratios for unsafe sex in sub-Saharan Africa were notably high, and those for alcohol use in north Africa and the Middle East were notably low. Interpretation By quantifying levels and trends in exposures to risk factors and the resulting disease burden, this assessment offers insight into where past policy and programme efforts might have been successful and highlights current priorities for public health action. Decreases in behavioural, environmental, and occupational risks have largely offset the effects of population growth and ageing, in relation to trends in absolute burden. Conversely, the combination of increasing metabolic risks and population ageing will probably continue to drive the increasing trends in non-communicable diseases at the global level, which presents both a public health challenge and opportunity. We see considerable spatiotemporal heterogeneity in levels of risk exposure and risk-attributable burden. Although levels of development underlie some of this heterogeneity, O/E ratios show risks for which countries are overperforming or underperforming relative to their level of development. As such, these ratios provide a benchmarking tool to help to focus local decision making. Our findings reinforce the importance of both risk exposure monitoring and epidemiological research to assess causal connections between risks and health outcomes, and they highlight the usefulness of the GBD study in synthesising data to draw comprehensive and robust conclusions that help to inform good policy and strategic health planning

Identification and characterization of novel associations in the CASP8/ALS2CR12 region on chromosome 2 with breast cancer risk.

Previous studies have suggested that polymorphisms in CASP8 on chromosome 2 are associated with breast cancer risk. To clarify the role of CASP8 in breast cancer susceptibility, we carried out dense genotyping of this region in the Breast Cancer Association Consortium (BCAC). Single-nucleotide polymorphisms (SNPs) spanning a 1 Mb region around CASP8 were genotyped in 46 450 breast cancer cases and 42 600 controls of European origin from 41 studies participating in the BCAC as part of a custom genotyping array experiment (iCOGS). Missing genotypes and SNPs were imputed and, after quality exclusions, 501 typed and 1232 imputed SNPs were included in logistic regression models adjusting for study and ancestry principal components. The SNPs retained in the final model were investigated further in data from nine genome-wide association studies (GWAS) comprising in total 10 052 case and 12 575 control subjects. The most significant association signal observed in European subjects was for the imputed intronic SNP rs1830298 in ALS2CR12 (telomeric to CASP8), with per allele odds ratio and 95% confidence interval [OR (95% confidence interval, CI)] for the minor allele of 1.05 (1.03-1.07), P = 1 × 10(-5). Three additional independent signals from intronic SNPs were identified, in CASP8 (rs36043647), ALS2CR11 (rs59278883) and CFLAR (rs7558475). The association with rs1830298 was replicated in the imputed results from the combined GWAS (P = 3 × 10(-6)), yielding a combined OR (95% CI) of 1.06 (1.04-1.08), P = 1 × 10(-9). Analyses of gene expression associations in peripheral blood and normal breast tissue indicate that CASP8 might be the target gene, suggesting a mechanism involving apoptosis.Part of this work was supported by the European Community´s Seventh Framework Programme under grant agreement number 223175 (grant number HEALTH-F2-2009-223175) (COGS). Funding for the iCOGS infrastructure came from: the European Community's Seventh Framework Programme under grant agreement n° 223175 (HEALTH-F2-2009-223175) (COGS), Cancer Research UK (C1287/A10118, C1287/A 10710, C12292/A11174, C1281/A12014, C5047/A8384, C5047/A15007, C5047/A10692), the National Institutes of Health (CA128978) and Post-Cancer GWAS initiative (1U19 CA148537, 1U19 CA148065 and 1U19 CA148112 - the GAME-ON initiative), the Department of Defence (W81XWH-10-1-0341), the Canadian Institutes of Health Research (CIHR) for the CIHR Team in Familial Risks of Breast Cancer, Komen Foundation for the Cure, the Breast Cancer Research Foundation, and the Ovarian Cancer Research Fund. The ABCFS, NC-BCFR and OFBCR work was supported by the United States National Cancer Institute, National Institutes of Health (NIH) under RFA-CA-06-503 and through cooperative agreements with members of the Breast Cancer Family Registry (BCFR) and Principal Investigators, including Cancer Care Ontario (U01 CA69467), Northern California Cancer Center (U01 CA69417), University of Melbourne (U01 CA69638). Samples from the NC-BCFR were processed and distributed by the Coriell Institute for Medical Research. The content of this manuscript does not necessarily reflect the views or policies of the National Cancer Institute or any of the collaborating centers in the BCFR, nor does mention of trade names, commercial products, or organizations imply endorsement by the US Government or the BCFR. The ABCFS was also supported by the National Health and Medical Research Council of Australia, the New South Wales Cancer Council, the Victorian Health Promotion Foundation (Australia) and the Victorian Breast Cancer Research Consortium. J.L.H. is a National Health and Medical Research Council (NHMRC) Australia Fellow and a Victorian Breast Cancer Research Consortium Group Leader. M.C.S. is a NHMRC Senior Research Fellow and a Victorian Breast Cancer Research Consortium Group Leader. The ABCS was supported by the Dutch Cancer Society [grants NKI 2007-3839; 2009 4363]; BBMRI-NL, which is a Research Infrastructure financed by the Dutch government (NWO 184.021.007); and the Dutch National Genomics Initiative. The ACP study is funded by the Breast Cancer Research Trust, UK. The work of the BBCC was partly funded by ELAN-Fond of the University Hospital of Erlangen. The BBCS is funded by Cancer Research UK and Breakthrough Breast Cancer and acknowledges NHS funding to the NIHR Biomedical Research Centre, and the National Cancer Research Network (NCRN). The BBCS GWAS received funding from The Institut National de Cancer. ES is supported by NIHR Comprehensive Biomedical Research Centre, Guy's & St. Thomas' NHS Foundation Trust in partnership with King's College London, United Kingdom. IT is supported by the Oxford Biomedical Research Centre. The BSUCH study was supported by the Dietmar-Hopp Foundation, the Helmholtz Society and the German Cancer Research Center (DKFZ). The CECILE study was funded by Fondation de France, Institut National du Cancer (INCa), Ligue Nationale contre le Cancer, Ligue contre le Cancer Grand Ouest, Agence Nationale de Sécurité Sanitaire (ANSES), Agence Nationale de la Recherche (ANR). The was supported by the Chief Physician Johan Boserup and Lise Boserup Fund, the Danish Medical Research Council and Herlev Hospital. The CNIO-BCS was supported by the Genome Spain Foundation, the Red Temática de Investigación Cooperativa en Cáncer and grants from the Asociación Española Contra el Cáncer and the Fondo de Investigación Sanitario (PI11/00923 and PI081120). The Human Genotyping-CEGEN Unit (CNIO) is supported by the Instituto de Salud Carlos III. The CTS was supported by the California Breast Cancer Act of 1993; National Institutes of Health (grants R01 CA77398 and the Lon V Smith Foundation [LVS39420].); the California Breast Cancer Research Fund (contract 97-10500). Collection of cancer incidence data used in this study was supported by the California Department of Public Health as part of the statewide cancer reporting program mandated by California Health and Safety Code Section 103885. The ESTHER study was supported by a grant from the Baden Württemberg Ministry of Science, Research and Arts. Additional cases were recruited in the context of the VERDI study, which was supported by a grant from the German Cancer Aid (Deutsche Krebshilfe). The GC-HBOC was supported by Deutsche Krebshilfe (107 352). The GENICA was funded by the Federal Ministry of Education and Research (BMBF) Germany grants 01KW9975/5, 01KW9976/8, 01KW9977/0 and 01KW0114, the Robert Bosch Foundation, Stuttgart, Deutsches Krebsforschungszentrum (DKFZ), Heidelberg, Institute for Prevention and Occupational Medicine of the German Social Accident Insurance, Institute of the Ruhr University Bochum (IPA), Bochum, Germany, as well as the Department of Internal Medicine, Evangelische Kliniken Bonn gGmbH, Johanniter Krankenhaus, Bonn, Germany. The HEBCS was financially supported by the Helsinki University Central Hospital Research Fund, Academy of Finland (266528), the Finnish Cancer Society, The Nordic Cancer Union and the Sigrid Juselius Foundation. The GWS population allele and genotype frequencies were obtained from the data source funded by the Nordic Center of Excellence in Disease Genetics based on samples regionally selected from Finland, Sweden and Denmark. The HERPACC was supported by a Grant-in-Aid for Scientific Research on Priority Areas from the Ministry of Education, Science, Sports, Culture and Technology of Japan, by a Grant-in-Aid for the Third Term Comprehensive 10-Year Strategy for Cancer Control from Ministry Health, Labour and Welfare of Japan, by Health and Labour Sciences Research Grants for Research on Applying Health Technology from Ministry Health, Labour and Welfare of Japan and by National Cancer Center Research and Development Fund. The HMBCS was supported by a grant from the Friends of Hannover Medical School and by the Rudolf Bartling Foundation. Financial support for KARBAC was provided through the regional agreement on medical training and clinical research (ALF) between Stockholm County Council and Karolinska Institutet, The Swedish Cancer Society and the Gustav V Jubilee foundation. The KBCP was financially supported by the special Government Funding (EVO) of Kuopio University Hospital grants, Cancer Fund of North Savo, the Finnish Cancer Organizations, the Academy of Finland and by the strategic funding of the University of Eastern Finland. kConFab is supported by grants from the National Breast Cancer Foundation, the NHMRC, the Queensland Cancer Fund, the Cancer Councils of New South Wales, Victoria, Tasmania and South Australia and the Cancer Foundation of Western Australia. The kConFab Clinical Follow Up Study was funded by the NHMRC [145684, 288704, 454508]. Financial support for the AOCS was provided by the United States Army Medical Research and Materiel Command [DAMD17-01-1-0729], the Cancer Council of Tasmania and Cancer Foundation of Western Australia and the NHMRC [199600]. G.C.T. and P.W. are supported by the NHMRC. LAABC is supported by grants (1RB-0287, 3PB-0102, 5PB-0018, 10PB-0098) from the California Breast Cancer Research Program. Incident breast cancer cases were collected by the USC Cancer Surveillance Program (CSP), which is supported under subcontract by the California Department of Health. The CSP is also part of the National Cancer Institute's Division of Cancer Prevention and Control Surveillance, Epidemiology, and End Results Program, under contract number N01CN25403. LMBC is supported by the 'Stichting tegen Kanker' (232-2008 and 196-2010). Diether Lambrechts is supported by the FWO and the KULPFV/10/016-SymBioSysII. The MARIE study was supported by the Deutsche Krebshilfe e.V. [70-2892-BR I], the Hamburg Cancer Society, the German Cancer Research Center and the Federal Ministry of Education and Research (BMBF) Germany [01KH0402, 01KH0408, 01KH0409]. MBCSG is supported by grants from the Italian Association for Cancer Research (AIRC) and by funds from the Italian citizens who allocated the 5/1000 share of their tax payment in support of the Fondazione IRCCS Istituto Nazionale Tumori, according to Italian laws (INT-Institutional strategic projects “5x1000”). The MCBCS was supported by the NIH grant CA128978, an NIH Specialized Program of Research Excellence (SPORE) in Breast Cancer [CA116201], the Breast Cancer Research Foundation, a generous gift from the David F. and Margaret T. Grohne Family Foundation and the Ting Tsung and Wei Fong Chao Foundation. MCCS cohort recruitment was funded by VicHealth and Cancer Council Victoria. The MCCS was further supported by Australian NHMRC grants 209057, 251553 and 504711 and by infrastructure provided by Cancer Council Victoria. The MEC was support by NIH grants CA63464, CA54281, CA098758 and CA132839. The work of MTLGEBCS was supported by the Quebec Breast Cancer Foundation, the Canadian Institutes of Health Research for the “CIHR Team in Familial Risks of Breast Cancer” program – grant # CRN-87521 and the Ministry of Economic Development, Innovation and Export Trade – grant # PSR-SIIRI-701. MYBRCA is funded by research grants from the Malaysian Ministry of Science, Technology and Innovation (MOSTI), Malaysian Ministry of Higher Education (UM.C/HlR/MOHE/06) and Cancer Research Initiatives Foundation (CARIF). Additional controls were recruited by the Singapore Eye Research Institute, which was supported by a grant from the Biomedical Research Council (BMRC08/1/35/19/550), Singapore and the National medical Research Council, Singapore (NMRC/CG/SERI/2010). The NBCS was supported by grants from the Norwegian Research council, 155218/V40, 175240/S10 to ALBD, FUGE-NFR 181600/V11 to VNK and a Swizz Bridge Award to ALBD. The NBCS was supported by grants from the Norwegian Research council, 155218/V40, 175240/S10 to ALBD, FUGE-NFR 181600/V11 to VNK and a Swizz Bridge Award to ALBD. The NBHS was supported by NIH grant R01CA100374. Biological sample preparation was conducted the Survey and Biospecimen Shared Resource, which is supported by P30 CA68485. The OBCS was supported by research grants from the Finnish Cancer Foundation, the Academy of Finland Centre of Excellence grant 251314, the Sigrid Juselius Foundation, the University of Oulu, and the Oulu University Hospital special Govermental EVO Research Funds. The OFBCR work was supported by grant UM1 CA164920 from the National Cancer Institute. The content of this manuscript does not necessarily reflect the views or policies of the National Cancer Institute or any of the collaborating centers in the Breast Cancer Family Registry (BCFR), nor does mention of trade names, commercial products, or organizations imply endorsement by the US Government or the BCFR. The ORIGO study was supported by the Dutch Cancer Society (RUL 1997-1505) and the Biobanking and Biomolecular Resources Research Infrastructure (BBMRI-NL CP16). The PBCS was funded by Intramural Research Funds of the National Cancer Institute, Department of Health and Human Services, USA. The pKARMA study was supported by Märit and Hans Rausings Initiative Against Breast Cancer. The RBCS was funded by the Dutch Cancer Society (DDHK 2004-3124, DDHK 2009-4318). The SASBAC study was supported by funding from the Agency for Science, Technology and Research of Singapore (A*STAR), the US National Institute of Health (NIH) and the Susan G. Komen Breast Cancer Foundation. The SBCGS was supported primarily by NIH grants R01CA64277, R01CA148667, and R37CA70867. Biological sample preparation was conducted the Survey and Biospecimen Shared Resource, which is supported by P30 CA68485. The SBCS was supported by Yorkshire Cancer Research awards S295, S299, S305PA, and by the Sheffield Experimental Cancer Medicine Centre Network. NJC was supported by NCI grant R01 CA163353 and The Avon Foundation (02-2009-080). The SCCS is supported by a grant from the National Institutes of Health (R01 CA092447). Data on SCCS cancer cases used in this publication were provided by the Alabama Statewide Cancer Registry; Kentucky Cancer Registry, Lexington, KY; Tennessee Department of Health, Office of Cancer Surveillance; Florida Cancer Data System; North Carolina Central Cancer Registry, North Carolina Division of Public Health; Georgia Comprehensive Cancer Registry; Louisiana Tumor Registry; Mississippi Cancer Registry; South Carolina Central Cancer Registry; Virginia Department of Health, Virginia Cancer Registry; Arkansas Department of Health, Cancer Registry, 4815 W. Markham, Little Rock, AR 72205. The Arkansas Central Cancer Registry is fully funded by a grant from National Program of Cancer Registries, Centers for Disease Control and Prevention (CDC). Data on SCCS cancer cases from Mississippi were collected by the Mississippi Cancer Registry which participates in the National Program of Cancer Registries (NPCR) of the Centers for Disease Control and Prevention (CDC). The contents of this publication are solely the responsibility of the authors and do not necessarily represent the official views of the CDC or the Mississippi Cancer Registry. SEARCH is funded by programme grants from Cancer Research UK [C490/A10124, C490/A16561] and supported by the UK National Institute for Health Research Biomedical Research Centre at the University of Cambridge. The SEBCS was supported by the Korea Health 21 R&D Project [AO30001], Ministry of Health and Welfare, Republic of Korea. SGBCC is funded by the National Medical Research Council start-up Grant and Centre Grant (NMRC/CG/NCIS /2010). Additional controls were recruited by the Singapore Consortium of Cohort Studies-Multi-ethnic cohort (SCCS-MEC), which was funded by the Biomedical Research Council, grant number: 05/1/21/19/425. SKKDKFZS is supported by the DKFZ. The SZBCS was supported by Grant PBZ_KBN_122/P05/2004. The TBCS was funded by The National Cancer Institute Thailand. The TNBCC was supported by: MCBCS (National Institutes of Health Grants CA122340 and a Specialized Program of Research Excellence (SPORE) in Breast Cancer (CA116201), a generous gift from the David F. and Margaret T. Grohne Family Foundation and the Ting Tsung and Wei Fong Chao Foundation. This research has been partly financed by the European Union (European Social Fund – ESF) and Greek national funds through the Operational Program "Education and Lifelong Learning" of the National Strategic Reference Framework (NSRF) - Research Funding Program of the General Secretariat for Research & Technology: ARISTEIA. Investing in knowledge society through the European Social Fund; and the Stefanie Spielman Breast Fund and the Ohio State University Comprehensive Cancer Center. The TWBCS is supported by the Taiwan Biobank project of the Institute of Biomedical Sciences, Academia Sinica, Taiwan. The UKBGS is funded by Breakthrough Breast Cancer and the Institute of Cancer Research (ICR). ICR acknowledges NHS funding to the NIHR Biomedical Research Centre. The Nurses’ Health Studies (CGEMS) are supported by NIH grants CA 65725, CA87969, CA49449, CA67262, CA50385 and 5UO1CA098233. The UK2 GWAS was funded by Wellcome Trust and Cancer Research UK. It included samples collected through the FBCS study, which is funded by Cancer Research UK [C8620/A8372]. It included control data obtained through the WTCCC which was funded by the Wellcome Trust. The DFBBCS GWAS was funded by The Netherlands Organisation for Scientific Research (NWO) as part of a ZonMw/VIDI grant number 91756341. Control GWA genotype data from the Rotterdam Study were funded by NWO Groot Investments (project nr. 175.010.2005.011). We thank all the individuals who took part in these studies and all the researchers, clinicians, technicians and administrative staff who have enabled this work to be carried out. This study would not have been possible without the contributions of the following: Andrew Berchuck (OCAC), Rosalind A. Eeles, Ali Amin Al Olama, Zsofia Kote-Jarai, Sara Benlloch (PRACTICAL), Antonis Antoniou, Lesley McGuffog, Ken Offit (CIMBA), Andrew Lee, and Ed Dicks, and the staff of the Centre for Genetic Epidemiology Laboratory, the staff of the CNIO genotyping unit, Sylvie LaBoissière and Frederic Robidoux and the staff of the McGill University and Génome Québec Innovation Centre, the staff of the Copenhagen DNA laboratory, and Julie M. Cunningham, Sharon A. Windebank, Christopher A. Hilker, Jeffrey Meyer and the staff of Mayo Clinic Genotyping Core Facility. We also thank Maggie Angelakos, Judi Maskiell, Gillian Dite (ABCFS), and extend our thanks to the many women and their families that generously participated in the Australian Breast Cancer Family Study and consented to us accessing their pathology material. JLH is a National Health and Medical Research Council Australia Fellow. MCS is a National Health and Medical Research Council Senior Research Fellow. JLH and MCS are both group leaders of the Victoria Breast Cancer Research Consortium. We thank Sten Cornelissen, Richard van Hien, Linde Braaf, Frans Hogervorst, Senno Verhoef, Ellen van der Schoot, Femke Atsma (ABCS). The ACP study wishes to thank the participants in the Thai Breast Cancer study. Special Thanks also go to the Thai Ministry of Public Health (MOPH), doctors and nurses who helped with the data collection process. Finally, the study would like to thank Dr Prat Boonyawongviroj, the former Permanent Secretary of MOPH and Dr Pornthep Siriwanarungsan, the Department Director-General of Disease Control who have supported the study throughout. We thank Eileen Williams, Elaine Ryder-Mills, Kara Sargus (BBCS), Niall McInerney, Gabrielle Colleran, Andrew Rowan, Angela Jones (BIGGS), Peter Bugert, and Medical Faculty Mannheim (BSUCH). We thank the staff and participants of the Copenhagen General Population Study, and for excellent technical assistance: Dorthe Uldall Andersen, Maria Birna Arnadottir, Anne Bank, and Dorthe Kjeldgård Hansen. The Danish Breast Cancer Group (DBCG) is acknowledged for the tumor information. We thank Guillermo Pita, Charo Alonso, Daniel Herrero, Nuria Álvarez, Pilar Zamora, Primitiva Menendez, the Human Genotyping-CEGEN Unit (CNIO), Hartwig Ziegler, Sonja Wolf, and Volker Hermann (ESTHER). We thank Heide Hellebrand, Stefanie Engert (GC-HBOC). GC-HBOC would like to thank the following persons for providing additional informations and samples: Prof. Dr. Norbert Arnold, Dr. Sabine Preissler-Adams, Dr. Monika Mareeva-Varon, Dr. Dieter Niederacher, Prof. Dr. Brigitte Schlegelberger, Dr. Clemens Mül. The GENICA Network: Dr. Margarete Fischer-Bosch-Institute of Clinical Pharmacology, Stuttgart, and University of Tübingen, Germany; [HB, Wing-Yee Lo, Christina Justenhoven], German Cancer Consortium (DKTK) and German Cancer Research Center (DKFZ) [HB], Department of Internal Medicine, Evangelische Kliniken Bonn gGmbH, Johanniter Krankenhaus, Bonn, Germany [YDK, Christian Baisch], Institute of Pathology, University of Bonn, Germany [Hans-Peter Fischer], Molecular Genetics of Breast Cancer, Deutsches Krebsforschungszentrum (DKFZ), Heidelberg, Germany [Ute Hamann] and Institute for Prevention and Occupational Medicine of the German Social Accident Insurance, Institute of the Ruhr University Bochum (IPA), Bochum, Germany [TB, Beate Pesch, Sylvia Rabstein, Anne Lotz]; Institute of Occupational Medicine and Maritime Medicine, University Medical Center Hamburg-Eppendorf, Germany [Volker Harth]. HEBCS thanks Kirsimari Aaltonen, Tuomas Heikkinen, and Dr. Karl von Smitten and RN Irja Erkkilä for their help with the HEBCS data and samples. We thank Peter Hillemanns, Hans Christiansen and Johann H. Karstens (HMBCS), Eija Myöhänen, Helena Kemiläinen (KBCP). kConFab thanks Heather Thorne, Eveline Niedermayr, the AOCS Management Group (D Bowtell, G Chenevix-Trench, A deFazio, D Gertig, A Green, P Webb), the ACS Management Group (A

Global, regional, and national comparative risk assessment of 84 behavioural, environmental and occupational, and metabolic risks or clusters of risks for 195 countries and territories, 1990-2017: a systematic analysis for the Global Burden of Disease Study 2017.

BACKGROUND: The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2017 comparative risk assessment (CRA) is a comprehensive approach to risk factor quantification that offers a useful tool for synthesising evidence on risks and risk-outcome associations. With each annual GBD study, we update the GBD CRA to incorporate improved methods, new risks and risk-outcome pairs, and new data on risk exposure levels and risk-outcome associations. METHODS: We used the CRA framework developed for previous iterations of GBD to estimate levels and trends in exposure, attributable deaths, and attributable disability-adjusted life-years (DALYs), by age group, sex, year, and location for 84 behavioural, environmental and occupational, and metabolic risks or groups of risks from 1990 to 2017. This study included 476 risk-outcome pairs that met the GBD study criteria for convincing or probable evidence of causation. We extracted relative risk and exposure estimates from 46 749 randomised controlled trials, cohort studies, household surveys, census data, satellite data, and other sources. We used statistical models to pool data, adjust for bias, and incorporate covariates. Using the counterfactual scenario of theoretical minimum risk exposure level (TMREL), we estimated the portion of deaths and DALYs that could be attributed to a given risk. We explored the relationship between development and risk exposure by modelling the relationship between the Socio-demographic Index (SDI) and risk-weighted exposure prevalence and estimated expected levels of exposure and risk-attributable burden by SDI. Finally, we explored temporal changes in risk-attributable DALYs by decomposing those changes into six main component drivers of change as follows: (1) population growth; (2) changes in population age structures; (3) changes in exposure to environmental and occupational risks; (4) changes in exposure to behavioural risks; (5) changes in exposure to metabolic risks; and (6) changes due to all other factors, approximated as the risk-deleted death and DALY rates, where the risk-deleted rate is the rate that would be observed had we reduced the exposure levels to the TMREL for all risk factors included in GBD 2017