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1.
  • Lotta, Luca A., et al. (författare)
  • Association between low-density lipoprotein cholesterol-lowering genetic variants and risk of type 2 diabetes : A meta-analysis
  • 2016
  • Ingår i: JAMA: the journal of the American Medical Association. - American Medical Association. - 0098-7484. ; 316:13, s. 1383-1391
  • Tidskriftsartikel (refereegranskat)abstract
    • IMPORTANCE Low-density lipoprotein cholesterol (LDL-C)-lowering alleles in or near NPC1L1 or HMGCR, encoding the respective molecular targets of ezetimibe and statins, have previously been used as proxies to study the efficacy of these lipid-lowering drugs. Alleles near HMGCR are associated with a higher risk of type 2 diabetes, similar to the increased incidence of new-onset diabetes associated with statin treatment in randomized clinical trials. It is unknown whether alleles near NPC1L1 are associated with the risk of type 2 diabetes. OBJECTIVE To investigate whether LDL-C-lowering alleles in or near NPC1L1 and other genes encoding current or prospective molecular targets of lipid-lowering therapy (ie, HMGCR, PCSK9, ABCG5/G8, LDLR) are associated with the risk of type 2 diabetes. DESIGN, SETTING, AND PARTICIPANTS The associations with type 2 diabetes and coronary artery disease of LDL-C-lowering genetic variants were investigated in meta-analyses of genetic association studies. Meta-analyses included 50 775 individuals with type 2 diabetes and 270 269 controls and 60 801 individuals with coronary artery disease and 123 504 controls. Data collection took place in Europe and the United States between 1991 and 2016. EXPOSURES Low-density lipoprotein cholesterol-lowering alleles in or near NPC1L1, HMGCR, PCSK9, ABCG5/G8, and LDLR. MAIN OUTCOMES AND MEASURES Odds ratios (ORs) for type 2 diabetes and coronary artery disease. RESULTS Low-density lipoprotein cholesterol-lowering genetic variants at NPC1L1 were inversely associated with coronary artery disease (OR for a genetically predicted 1-mmol/L [38.7-mg/dL] reduction in LDL-C of 0.61 [95%CI, 0.42-0.88]; P = .008) and directly associated with type 2 diabetes (OR for a genetically predicted 1-mmol/L reduction in LDL-C of 2.42 [95%CI, 1.70-3.43]; P .001). For PCSK9 genetic variants, the OR for type 2 diabetes per 1-mmol/L genetically predicted reduction in LDL-C was 1.19 (95%CI, 1.02-1.38; P = .03). For a given reduction in LDL-C, genetic variants were associated with a similar reduction in coronary artery disease risk (I2 = 0%for heterogeneity in genetic associations; P = .93). However, associations with type 2 diabetes were heterogeneous (I2 = 77.2%; P = .002), indicating gene-specific associations with metabolic risk of LDL-C-lowering alleles. CONCLUSIONS AND RELEVANCE In thismeta-analysis, exposure to LDL-C-lowering genetic variants in or near NPC1L1 and other geneswas associated with a higher risk of type 2 diabetes. These data provide insights into potential adverse effects of LDL-C-lowering therapy.
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2.
3.
  • Blunden, Jessica, et al. (författare)
  • State of the Climate in 2012
  • 2013
  • Ingår i: Bulletin of The American Meteorological Society - (BAMS). - 0003-0007. ; 94:8, s. S1-S258
  • Tidskriftsartikel (refereegranskat)abstract
    • For the first time in serveral years, the El Nino-Southern Oscillation did not dominate regional climate conditions around the globe. A weak La Ni a dissipated to ENSOneutral conditions by spring, and while El Nino appeared to be emerging during summer, this phase never fully developed as sea surface temperatures in the eastern conditions. Nevertheless, other large-scale climate patterns and extreme weather events impacted various regions during the year. A negative phase of the Arctic Oscillation from mid-January to early February contributed to frigid conditions in parts of northern Africa, eastern Europe, and western Asia. A lack of rain during the 2012 wet season led to the worst drought in at least the past three decades for northeastern Brazil. Central North America also experienced one of its most severe droughts on record. The Caribbean observed a very wet dry season and it was the Sahel's wettest rainy season in 50 years. Overall, the 2012 average temperature across global land and ocean surfaces ranked among the 10 warmest years on record. The global land surface temperature alone was also among the 10 warmest on record. In the upper atmosphere, the average stratospheric temperature was record or near-record cold, depending on the dataset. After a 30-year warming trend from 1970 to 1999 for global sea surface temperatures, the period 2000-12 had little further trend. This may be linked to the prevalence of La Ni a-like conditions during the 21st century. Heat content in the upper 700 m of the ocean remained near record high levels in 2012. Net increases from 2011 to 2012 were observed at 700-m to 2000-m depth and even in the abyssal ocean below. Following sharp decreases in to the effects of La Ni a, sea levels rebounded to reach records highs in 2012. The increased hydrological cycle seen in recent years continued, with more evaporation in drier locations and more precipitation in rainy areas. In a pattern that has held since 2004, salty areas of the ocean surfaces and subsurfaces were anomalously salty on average, while fresher areas were anomalously fresh. Global tropical cyclone activity during 2012 was near average, with a total of 84 storms compared with the 1981-2010 average of 89. Similar to 2010 and 2011, the North Atlantic was the only hurricane basin that experienced above-normal activity. In this basin, Sandy brought devastation to Cuba and parts of the eastern North American seaboard. All other basins experienced either near-or below-normal tropical cyclone activity. Only three tropical cyclones reached Category 5 intensity-all in Bopha became the only storm in the historical record to produce winds greater than 130 kt south of 7 N. It was also the costliest storm to affect the Philippines and killed more than 1000 residents. Minimum Arctic sea ice extent in September and Northern Hemisphere snow cover extent in June both reached new record lows. June snow cover extent is now declining at a faster rate (-17.6% per decade) than September sea ice extent (-13.0% per decade). Permafrost temperatures reached record high values in northernmost Alaska. A new melt extent record occurred on 11-12 July on the Greenland ice sheet; 97% of the ice sheet showed some form of melt, four times greater than the average melt for this time of year. The climate in Antarctica was relatively stable overall. The largest maximum sea ice extent since records begain in 1978 was observed in September 2012. In the stratosphere, warm air led to the second smallest ozone hole in the past two decades. Even so, the springtime ozone layer above Antarctica likely will not return to its early 1980s state until about 2060. Following a slight decline associated with the global 2 emissions from fossil fuel combustion and cement production reached a record 9.5 +/- 0.5 Pg C in 2011 and a new record of 9.7 +/- 0.5 Pg C is estimated for 2012. Atmospheric CO2 concentrations increased by 2.1 ppm in 2012, to 392.6 ppm. In spring 2012, 2 concentration exceeded 400 ppm at 7 of the 13 Arctic observation sites. Globally, other greenhouse gases including methane and nitrous oxide also continued to rise in concentration and the combined effect now represents a 32% increase in radiative forcing over a 1990 baseline. Concentrations of most ozone depleting substances continued to fall.
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4.
  • Burgess, Stephen, et al. (författare)
  • Bayesian methods for meta-analysis of causal relationships estimated using genetic instrumental variables
  • 2010
  • Ingår i: Statistics in Medicine. - 0277-6715. ; 29:12, s. 1298-1311
  • Tidskriftsartikel (refereegranskat)abstract
    • Genetic markers can be used as instrumental variables, in an analogous way to randomization in a clinical trial, to estimate the causal relationship between a phenotype and an outcome variable. Our purpose is to extend the existing methods for such Mendelian randomization studies to the context of multiple genetic markers measured in multiple studies, based on the analysis of individual participant data. First, for a single genetic marker in one study, we show that the usual ratio of coefficients approach can be reformulated as a regression with heterogeneous error in the explanatory variable. This can be implemented using a Bayesian approach, which is next extended to include multiple genetic markers. We then propose a hierarchical model for undertaking a meta-analysis of multiple studies, in which it is not necessary that the same genetic markers are measured in each study. This provides an overall estimate of the causal relationship between the phenotype and the outcome, and an assessment of its heterogeneity across studies. As an example, we estimate the causal relationship of blood concentrations of C-reactive protein on fibrinogen levels using data from 11 studies. These methods provide a flexible framework for efficient estimation of causal relationships derived from multiple studies. Issues discussed include weak instrument bias, analysis of binary outcome data such as disease risk, missing genetic data, and the use of haplotypes.
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5.
  • Di Angelantonio, Emanuele, et al. (författare)
  • Association of Cardiometabolic Multimorbidity With Mortality
  • 2015
  • Ingår i: JAMA. - 0098-7484 .- 1538-3598. ; 314:1, s. 52-60
  • Tidskriftsartikel (refereegranskat)abstract
    • IMPORTANCE The prevalence of cardiometabolic multimorbidity is increasing.OBJECTIVE To estimate reductions in life expectancy associated with cardiometabolic multimorbidity.DESIGN, SETTING, AND PARTICIPANTS Age-and sex-adjusted mortality rates and hazard ratios (HRs) were calculated using individual participant data from the Emerging Risk Factors Collaboration (689 300 participants; 91 cohorts; years of baseline surveys: 1960-2007; latest mortality follow-up: April 2013; 128 843 deaths). The HRs from the Emerging Risk Factors Collaboration were compared with those from the UK Biobank (499 808 participants; years of baseline surveys: 2006-2010; latest mortality follow-up: November 2013; 7995 deaths). Cumulative survival was estimated by applying calculated age-specific HRs for mortality to contemporary US age-specific death rates. EXPOSURES A history of 2 or more of the following: diabetes mellitus, stroke, myocardial infarction (MI).MAIN OUTCOMES AND MEASURES All-cause mortality and estimated reductions in life expectancy.RESULTS In participants in the Emerging Risk Factors Collaboration without a history of diabetes, stroke, or MI at baseline (reference group), the all-cause mortality rate adjusted to the age of 60 years was 6.8 per 1000 person-years. Mortality rates per 1000 person-years were 15.6 in participants with a history of diabetes, 16.1 in those with stroke, 16.8 in those with MI, 32.0 in those with both diabetes and MI, 32.5 in those with both diabetes and stroke, 32.8 in those with both stroke and MI, and 59.5 in those with diabetes, stroke, and MI. Compared with the reference group, the HRs for all-cause mortality were 1.9 (95% CI, 1.8-2.0) in participants with a history of diabetes, 2.1 (95% CI, 2.0-2.2) in those with stroke, 2.0 (95% CI, 1.9-2.2) in those with MI, 3.7 (95% CI, 3.3-4.1) in those with both diabetes and MI, 3.8 (95% CI, 3.5-4.2) in those with both diabetes and stroke, 3.5 (95% CI, 3.1-4.0) in those with both stroke and MI, and 6.9 (95% CI, 5.7-8.3) in those with diabetes, stroke, and MI. The HRs from the Emerging Risk Factors Collaboration were similar to those from the more recently recruited UK Biobank. The HRs were little changed after further adjustment for markers of established intermediate pathways (eg, levels of lipids and blood pressure) and lifestyle factors (eg, smoking, diet). At the age of 60 years, a history of any 2 of these conditions was associated with 12 years of reduced life expectancy and a history of all 3 of these conditions was associated with 15 years of reduced life expectancy.CONCLUSIONS AND RELEVANCE Mortality associated with a history of diabetes, stroke, or MI was similar for each condition. Because any combination of these conditions was associated with multiplicative mortality risk, life expectancy was substantially lower in people with multimorbidity.
6.
  • Freitag, Daniel F., et al. (författare)
  • Cardiometabolic effects of genetic upregulation of the interleukin 1 receptor antagonist: a Mendelian randomisation analysis
  • 2015
  • Ingår i: The Lancet Diabetes & Endocrinology. - Elsevier. - 2213-8595. ; 3:4, s. 243-253
  • Tidskriftsartikel (refereegranskat)abstract
    • Background To investigate potential cardiovascular and other effects of long-term pharmacological interleukin 1 (IL-1) inhibition, we studied genetic variants that produce inhibition of IL-1, a master regulator of inflammation. Methods We created a genetic score combining the effects of alleles of two common variants (rs6743376 and rs1542176) that are located upstream of IL1RN, the gene encoding the IL-1 receptor antagonist (IL-1Ra; an endogenous inhibitor of both IL-1 alpha and IL-1 beta); both alleles increase soluble IL-1Ra protein concentration. We compared effects on inflammation biomarkers of this genetic score with those of anakinra, the recombinant form of IL-1Ra, which has previously been studied in randomised trials of rheumatoid arthritis and other inflammatory disorders. In primary analyses, we investigated the score in relation to rheumatoid arthritis and four cardiometabolic diseases (type 2 diabetes, coronary heart disease, ischaemic stroke, and abdominal aortic aneurysm; 453 411 total participants). In exploratory analyses, we studied the relation of the score to many disease traits and to 24 other disorders of proposed relevance to IL-1 signalling (746 171 total participants). Findings For each IL1RN minor allele inherited, serum concentrations of IL-1Ra increased by 0.22 SD (95% CI 0.18-0.25; 12.5%; p=9.3 x 10(-33)), concentrations of interleukin 6 decreased by 0.02 SD (-0.04 to -0.01; -1,7%; p=3.5 x 10(-3)), and concentrations of C-reactive protein decreased by 0.03 SD (-0.04 to -0.02; -3.4%; p=7.7 x 10(-14)). We noted the effects of the genetic score on these inflammation biomarkers to be directionally concordant with those of anakinra. The allele count of the genetic score had roughly log-linear, dose-dependent associations with both IL-1Ra concentration and risk of coronary heart disease. For people who carried four IL-1Ra-raising alleles, the odds ratio for coronary heart disease was 1.15 (1.08-1.22; p=1.8 x 10(-6)) compared with people who carried no IL-1Ra-raising alleles; the per-allele odds ratio for coronary heart disease was 1.03 (1.02-1.04; p=3.9 x 10(-10)). Perallele odds ratios were 0.97 (0.95-0.99; p=9.9 x 10(-4)) for rheumatoid arthritis, 0.99 (0.97-1.01; p=0.47) for type 2 diabetes, 1.00 (0.98-1.02; p=0.92) for ischaemic stroke, and 1.08 (1.04-1.12; p=1.8 x 10(-5)) for abdominal aortic aneurysm. In exploratory analyses, we observed per-allele increases in concentrations of proatherogenic lipids, including LDL-cholesterol, but no clear evidence of association for blood pressure, glycaemic traits, or any of the 24 other disorders studied. Modelling suggested that the observed increase in LDL-cholesterol could account for about a third of the association observed between the genetic score and increased coronary risk. Interpretation Human genetic data suggest that long-term dual IL-1 alpha/beta inhibition could increase cardiovascular risk and, conversely, reduce the risk of development of rheumatoid arthritis. The cardiovascular risk might, in part, be mediated through an increase in proatherogenic lipid concentrations. Copyright (C) The Interleukin 1 Genetics Consortium. Open Access article distributed under the terms of CC-BY-NC-ND.
7.
  • Haycock, Philip C., et al. (författare)
  • Association Between Telomere Length and Risk of Cancer and Non-Neoplastic Diseases A Mendelian Randomization Study
  • 2017
  • Ingår i: JAMA Oncology. - American Medical Association. - 2374-2437. ; 3:5, s. 636-651
  • Tidskriftsartikel (refereegranskat)abstract
    • IMPORTANCE: The causal direction and magnitude of the association between telomere length and incidence of cancer and non-neoplastic diseases is uncertain owing to the susceptibility of observational studies to confounding and reverse causation. OBJECTIVE: To conduct a Mendelian randomization study, using germline genetic variants as instrumental variables, to appraise the causal relevance of telomere length for risk of cancer and non-neoplastic diseases. DATA SOURCES: Genomewide association studies (GWAS) published up to January 15, 2015. STUDY SELECTION: GWAS of noncommunicable diseases that assayed germline genetic variation and did not select cohort or control participants on the basis of preexisting diseases. Of 163 GWAS of noncommunicable diseases identified, summary data from 103 were available. DATA EXTRACTION AND SYNTHESIS: Summary association statistics for single nucleotide polymorphisms (SNPs) that are strongly associated with telomere length in the general population. MAIN OUTCOMES AND MEASURES: Odds ratios (ORs) and 95% confidence intervals (CIs) for disease per standard deviation (SD) higher telomere length due to germline genetic variation. RESULTS: Summary data were available for 35 cancers and 48 non-neoplastic diseases, corresponding to 420 081 cases (median cases, 2526 per disease) and 1 093 105 controls (median, 6789 per disease). Increased telomere length due to germline genetic variation was generally associated with increased risk for site-specific cancers. The strongest associations (ORs [ 95% CIs] per 1-SD change in genetically increased telomere length) were observed for glioma, 5.27 (3.15-8.81); serous low-malignant-potential ovarian cancer, 4.35 (2.39-7.94); lung adenocarcinoma, 3.19 (2.40-4.22); neuroblastoma, 2.98 (1.92-4.62); bladder cancer, 2.19 (1.32-3.66); melanoma, 1.87 (1.55-2.26); testicular cancer, 1.76 (1.02-3.04); kidney cancer, 1.55 (1.08-2.23); and endometrial cancer, 1.31 (1.07-1.61). Associations were stronger for rarer cancers and at tissue sites with lower rates of stem cell division. There was generally little evidence of association between genetically increased telomere length and risk of psychiatric, autoimmune, inflammatory, diabetic, and other non-neoplastic diseases, except for coronary heart disease (OR, 0.78 [ 95% CI, 0.67-0.90]), abdominal aortic aneurysm (OR, 0.63 [ 95% CI, 0.49-0.81]), celiac disease (OR, 0.42 [ 95% CI, 0.28-0.61]) and interstitial lung disease (OR, 0.09 [ 95% CI, 0.05-0.15]). CONCLUSIONS AND RELEVANCE: It is likely that longer telomeres increase risk for several cancers but reduce risk for some non-neoplastic diseases, including cardiovascular diseases.
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8.
  • Pennells, Lisa, et al. (författare)
  • Equalization of four cardiovascular risk algorithms after systematic recalibration individual-participant meta-analysis of 86 prospective studies
  • 2019
  • Ingår i: European Heart Journal. - 0195-668X .- 1522-9645. ; 40:7, s. 621-
  • Tidskriftsartikel (refereegranskat)abstract
    • Aims: There is debate about the optimum algorithm for cardiovascular disease (CVD) risk estimation. We conducted head-to-head comparisons of four algorithms recommended by primary prevention guidelines, before and after ‘recalibration’, a method that adapts risk algorithms to take account of differences in the risk characteristics of the populations being studied.Methods and results: Using individual-participant data on 360 737 participants without CVD at baseline in 86 prospective studies from 22 countries, we compared the Framingham risk score (FRS), Systematic COronary Risk Evaluation (SCORE), pooled cohort equations (PCE), and Reynolds risk score (RRS). We calculated measures of risk discrimination and calibration, and modelled clinical implications of initiating statin therapy in people judged to be at ‘high’ 10 year CVD risk. Original risk algorithms were recalibrated using the risk factor profile and CVD incidence of target populations. The four algorithms had similar risk discrimination. Before recalibration, FRS, SCORE, and PCE over-predicted CVD risk on average by 10%, 52%, and 41%, respectively, whereas RRS under-predicted by 10%. Original versions of algorithms classified 29–39% of individuals aged ≥40 years as high risk. By contrast, recalibration reduced this proportion to 22–24% for every algorithm. We estimated that to prevent one CVD event, it would be necessary to initiate statin therapy in 44–51 such individuals using original algorithms, in contrast to 37–39 individuals with recalibrated algorithms.Conclusion: Before recalibration, the clinical performance of four widely used CVD risk algorithms varied substantially. By contrast, simple recalibration nearly equalized their performance and improved modelled targeting of preventive action to clinical need.
9.
  • Vissers, Linda E. T., et al. (författare)
  • Dairy product intake and risk of type 2 diabetes in EPIC-interact : A mendelian randomization study
  • 2019
  • Ingår i: Diabetes Care. - American Diabetes Association. - 0149-5992. ; 42:4, s. 568-575
  • Tidskriftsartikel (refereegranskat)abstract
    • OBJECTIVE To estimate the causal association between intake of dairy products and incident type 2 diabetes. RESEARCH DESIGN AND METHODS The analysis included 21,820 European individuals (9,686 diabetes cases) of the European Prospective Investigation into Cancer and Nutrition (EPIC)-InterAct case-cohort study. Participants were genotyped, and rs4988235 (LCT-12910C>T), a single nucleotide polymorphism (SNP) for lactase persistence (LP) that enables digestion of dairy sugar, i.e., lactose, was imputed. Baseline dietary intakes were assessed with diet questionnaires. We investigated the associations between imputed SNP dosage for rs4988235 and intake of dairy products and other foods through linear regression. Mendelian randomization (MR) estimates for the milk-diabetes relationship were obtained through a two-stage least squares regression. RESULTS Each additional LP allele was associated with a higher intake of milk (b 17.1 g/day, 95% CI 10.6–23.6) and milk beverages (b 2.8 g/day, 95% CI 1.0–4.5) but not with intake of other dairy products. Other dietary intakes associated with rs4988235 included fruits (b 27.0 g/day, 95% CI 212.4 to 21.7 per additional LP allele), nonalcoholic beverages (b 218.0 g/day, 95% CI 234.4 to 21.6), and wine (b 24.8 g/day, 95% CI 29.1 to 20.6). In instrumental variable analysis, LP-associated milk intake was not associated with diabetes (hazard ratio per 15 g/day 0.99, 95% CI 0.93–1.05). CONCLUSIONS rs4988235 was associated with milk intake but not with intake of other dairy products. This MR study does not suggest that milk intake is associated with diabetes, which is consistent with previous observational and genetic associations. LP may be associated with intake of other foods as well, but owing to the modest associations, we consider it unlikely that this caused the observed null result.
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10.
  • Wensley, Frances, et al. (författare)
  • Association between C reactive protein and coronary heart disease : mendelian randomisation analysis based on individual participant data
  • 2011
  • Ingår i: BMJ. British Medical Journal. - BMJ Publishing Group. ; 342, s. d548
  • Tidskriftsartikel (refereegranskat)abstract
    • Objective To use genetic variants as unconfounded proxies of C reactive protein concentration to study its causal role in coronary heart disease. Design Mendelian randomisation meta-analysis of individual participant data from 47 epidemiological studies in 15 countries. Participants 194 418 participants, including 46 557 patients with prevalent or incident coronary heart disease. Information was available on four CRP gene tagging single nucleotide polymorphisms (rs3093077, rs1205, rs1130864, rs1800947), concentration of C reactive protein, and levels of other risk factors. Main outcome measures Risk ratios for coronary heart disease associated with genetically raised C reactive protein versus risk ratios with equivalent differences in C reactive protein concentration itself, adjusted for conventional risk factors and variability in risk factor levels within individuals. Results CRP variants were each associated with up to 30% per allele difference in concentration of C reactive protein (P<10(-34)) and were unrelated to other risk factors. Risk ratios for coronary heart disease per additional copy of an allele associated with raised C reactive protein were 0.93 (95% confidence interval 0.87 to 1.00) for rs3093077; 1.00 (0.98 to 1.02) for rs1205; 0.98 (0.96 to 1.00) for rs1130864; and 0.99 (0.94 to 1.03) for rs1800947. In a combined analysis, the risk ratio for coronary heart disease was 1.00 (0.90 to 1.13) per 1 SD higher genetically raised natural log (ln) concentration of C reactive protein. The genetic findings were discordant with the risk ratio observed for coronary heart disease of 1.33 (1.23 to 1.43) per 1 SD higher circulating ln concentration of C reactive protein in prospective studies (P=0.001 for difference). Conclusion Human genetic data indicate that C reactive protein concentration itself is unlikely to be even a modest causal factor in coronary heart disease.
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