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Genome-wide association analysis in humans links nucleotide metabolism to leukocyte telomere length
(2020)
Leukocyte telomere length (LTL) is a heritable biomarker of genomic aging. In this study, we perform a genome-wide meta-analysis of LTL by pooling densely genotyped and imputed association results across large-scale European-descent studies including up to 78,592 individuals. We identify 49 genomic regions at a false dicovery rate (FDR) < 0.05 threshold and prioritize genes at 31, with five highlighting nucleotide metabolism as an important regulator of LTL. We report six genome-wide significant loci in or near SENP7, MOB1B, CARMIL1 , PRRC2A, TERF2, and RFWD3, and our results support recently identified PARP1, POT1, ATM, and MPHOSPH6 loci. Phenome-wide analyses in >350,000 UK Biobank participants suggest that genetically shorter telomere length increases the risk of hypothyroidism and decreases the risk of thyroid cancer, lymphoma, and a range of proliferative conditions. Our results replicate previously reported associations with increased risk of coronary artery disease and lower risk for multiple cancer types. Our findings substantially expand current knowledge on genes that regulate LTL and their impact on human health and disease.
Background: Population-specificity of exploratory dietary patterns limits their generalizability in investigations with type 2 diabetes incidence.
Objective: The aim of this study was to derive country-specific exploratory dietary patterns, investigate their association with type 2 diabetes incidence, and replicate diabetes-associated dietary patterns in other countries.
Methods: Dietary intake data were used, assessed by country-specific questionnaires at baseline of 11,183 incident diabetes cases and 14,694 subcohort members (mean age 52.9 y) from 8 countries, nested within the European Prospective Investigation into Cancer and Nutrition study (mean follow-up time 6.9 y). Exploratory dietary patterns were derived by principal component analysis. HRs for incident type 2 diabetes were calculated by Prentice-weighted Cox proportional hazard regression models. Diabetes-associated dietary patterns were simplified or replicated to be applicable in other countries. A meta-analysis across all countries evaluated the generalizability of the diabetes-association.
Results: Two dietary patterns per country/UK-center, of which overall 3 dietary patterns were diabetes-associated, were identified. A risk-lowering French dietary pattern was not confirmed across other countries: pooled HRFrance per 1 SD: 1.00; 95% CI: 0.90, 1.10. Risk-increasing dietary patterns, derived in Spain and UK-Norfolk, were confirmed, but only the latter statistically significantly: HRSpain: 1.09; 95% CI: 0.97, 1.22 and HRUK-Norfolk: 1.12; 95% CI: 1.04, 1.20. Respectively, this dietary pattern was characterized by relatively high intakes of potatoes, processed meat, vegetable oils, sugar, cake and cookies, and tea. Conclusions: Only few country/center-specific dietary patterns (3 of 18) were statistically significantly associated with diabetes incidence in this multicountry European study population. One pattern, whose association with diabetes was confirmed across other countries, showed overlaps in the food groups potatoes and processed meat with identified diabetes-associated dietary patterns from other studies. The study demonstrates that replication of associations of exploratory patterns with health outcomes is feasible and a necessary step to overcome population-specificity in associations from such analyses.
Several meta-analyses have been published summarizing the associations of the Mediterranean diet (MedDiet) with chronic diseases. We evaluated the quality and credibility of evidence from these meta-analyses as well as characterized the different indices used to define MedDiet and re-calculated the associations with the different indices identified. We conducted an umbrella review of meta-analyses on cohort studies evaluating the association of the MedDiet with type 2 diabetes, cardiovascular disease, cancer and cognitive-related diseases. We used the AMSTAR (A MeaSurement Tool to Assess systematic Reviews) checklist to evaluate the methodological quality of the meta-analyses, and the NutriGrade scoring system to evaluate the credibility of evidence. We also identified different indices used to define MedDiet; tests for subgroup differences were performed to compare the associations with the different indices when at least 2 studies were available for different definitions. Fourteen publications were identified and within them 27 meta-analyses which were based on 70 primary studies. Almost all meta-analyses reported inverse associations between MedDiet and risk of chronic disease, but the credibility of evidence was rated low to moderate. Moreover, substantial heterogeneity was observed on the use of the indices assessing adherence to the MedDiet, but two indices were the most used ones [Trichopoulou MedDiet (tMedDiet) and alternative MedDiet (aMedDiet)]. Overall, we observed little difference in risk associations comparing different MedDiet indices in the subgroup meta-analyses. Future prospective cohort studies are advised to use more homogenous definitions of the MedDiet to improve the comparability across meta-analyses.
Purpose: The present work aimed to delineate (i) a revised protocol according to recent methodological developments in evidence generation, to (ii) describe its interpretation, the assessment of the overall certainty of evidence and to (iii) outline an Evidence to Decision framework for deriving an evidence-based guideline on quantitative and qualitative aspects of dietary protein intake. Methods A methodological protocol to systematically investigate the association between dietary protein intake and several health outcomes and for deriving dietary protein intake recommendations for the primary prevention of various non-communicable diseases in the general adult population was developed. Results The developed methodological protocol relies on umbrella reviews including systematic reviews with or without meta-analyses. Systematic literature searches in three databases will be performed for each health-related outcome. The methodological quality of all selected systematic reviews will be evaluated using a modified version of AMSTAR 2, and the outcome-specific certainty of evidence for systematic reviews with or without meta-analysis will be assessed with NutriGrade. The general outline of the Evidence to Decision framework foresees that recommendations in the derived guideline will be given based on the overall certainty of evidence as well as on additional criteria such as sustainability. Conclusion The methodological protocol permits a systematic evaluation of published systematic reviews on dietary protein intake and its association with selected health-related outcomes. An Evidence to Decision framework will be the basis for the overall conclusions and the resulting recommendations for dietary protein intake.
Fetuin-A, a hepatic-origin protein, is strongly positively associated with risk of type 2 diabetes in human observational studies, but it is unknown whether this association is causal. Weaimed to study the potential causal relation of circulating fetuin-A to risk of type 2 diabetes in a Mendelian randomization study with single nucleotide polymorphisms located in the fetuin-A-encoding AHSG gene. We used data from eight European countries of the European Prospective Investigation into Cancer and Nutrition (EPIC)-InterAct case-cohort study including 10,020 incident cases. Plasma fetuin-A concentration was measured in a subset of 965 subcohort participants and 654 case subjects. A genetic score of the AHSG single nucleotide polymorphisms was strongly associated with fetuin-A (28% explained variation). Using the genetic score as instrumental variable of fetuin-A, we observed no significant association of a 50 mu g/mL higher fetuin-A concentration with diabetes risk (hazard ratio 1.02 [95% CI 0.97, 1.07]). Combining our results with those from the DIAbetes Genetics Replication And Meta-analysis (DIAGRAM) consortium (12,171 case subjects) also did not suggest a clear significant relation of fetuin-A with diabetes risk. In conclusion, although there is mechanistic evidence for an effect of fetuin-A on insulin sensitivity and secretion, this study does not support a strong, relevant relationship between circulating fetuin-A and diabetes risk in the general population.
Aims/hypothesis This study aimed to evaluate associations of height as well as components of height (sitting height and leg length) with risk of type 2 diabetes and to explore to what extent associations are explainable by liver fat and cardiometabolic risk markers. Methods A case-cohort study within the European Prospective Investigation into Cancer and Nutrition (EPIC)-Potsdam study comprising 26,437 participants who provided blood samples was designed. We randomly selected a subcohort of 2500 individuals (2029 diabetes-free at baseline and with anamnestic, anthropometrical and metabolic data for analysis). Of the 820 incident diabetes cases identified in the full cohort during 7 years of follow-up, 698 remained for analyses after similar exclusions. Results After adjustment for age, potential lifestyle confounders, education and waist circumference, greater height was related to lower diabetes risk (HR per 10 cm, men 0.59 [95% CI 0.47, 0.75] and women 0.67 [0.51, 0.88], respectively). Leg length was related to lower risk among men and women, but only among men if adjusted for total height. Adjustment for liver fat and triacylglycerols, adiponectin and C-reactive protein substantially attenuated associations between height and diabetes risk, particularly among women. Conclusions/interpretation We observed inverse associations between height and risk of type 2 diabetes, which was largely related to leg length among men. The inverse associations may be partly driven by lower liver fat content and a more favourable cardiometabolic profile.
IMPORTANCE Inflammatory processes have been suggested to have an important role in colorectal cancer (CRC) etiology. Chemerin is a recently discovered inflammatory biomarker thought to exert chemotactic, adipogenic, and angiogenic functions. However, its potential link with CRC has not been sufficiently explored. OBJECTIVE To evaluate the prospective association of circulating plasma chemerin concentrations with incident CRC. DESIGN, SETTING, AND PARTICIPANTS Prospective case-cohort study based on 27 548 initially healthy participants from the European Prospective Investigation Into Cancer and Nutrition (EPIC)-Potsdam cohort who were followed for up to 16 years. Baseline study information and samples were collected between August 23, 1994, and September 25, 1998. Recruitment was according to random registry sampling from the geographical area of Potsdam, Germany, and surrounding municipalities. The last date of study follow-up was May 10, 2010. Statistical analysis was conducted in 2018. MAIN OUTCOMES AND MEASURES Incident CRC, colon cancer, and rectal cancer. Baseline chemerin plasma concentrations were measured by enzyme-linked immunosorbent assay. CONCLUSIONS AND RELEVANCE This study found that the association between chemerin concentration and the risk of incident CRC was linear and independent of established CRC risk factors. Further studies are warranted to evaluate chemerin as a novel immune-inflammatory agent in colorectal carcinogenesis.
The Net Reclassification Improvement (NRI) has become a popular metric for evaluating improvement in disease prediction models through the past years. The concept is relatively straightforward but usage and interpretation has been different across studies. While no thresholds exist for evaluating the degree of improvement, many studies have relied solely on the significance of the NRI estimate. However, recent studies recommend that statistical testing with the NRI should be avoided. We propose using confidence ellipses around the estimated values of event and non-event NRIs which might provide the best measure of variability around the point estimates. Our developments are illustrated using practical examples from EPIC-Potsdam study.
The Net Reclassification Improvement (NRI) has become a popular metric for evaluating improvement in disease prediction models through the past years. The concept is relatively straightforward but usage and interpretation has been different across studies. While no thresholds exist for evaluating the degree of improvement, many studies have relied solely on the significance of the NRI estimate. However, recent studies recommend that statistical testing with the NRI should be avoided. We propose using confidence ellipses around the estimated values of event and non-event NRIs which might provide the best measure of variability around the point estimates. Our developments are illustrated using practical examples from EPIC-Potsdam study.