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1.
  • Di Angelantonio, Emanuele, et al. (author)
  • Association of Cardiometabolic Multimorbidity With Mortality : The Emerging Risk Factors Collaboration
  • 2015
  • In: Journal of the American Medical Association (JAMA). - : American Medical Association (AMA). - 0098-7484 .- 1538-3598. ; 314:1, s. 52-60
  • Journal article (peer-reviewed)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.
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2.
  • Robinson-Cohen, Cassianne, et al. (author)
  • Genetic Variants Associated with Circulating Parathyroid Hormone.
  • 2017
  • In: Journal of the American Society of Nephrology : JASN. - 1533-3450. ; 28:5, s. 1553-1565
  • Journal article (peer-reviewed)abstract
    • Parathyroid hormone (PTH) is a primary calcium regulatory hormone. Elevated serum PTH concentrations in primary and secondary hyperparathyroidism have been associated with bone disease, hypertension, and in some studies, cardiovascular mortality. Genetic causes of variation in circulating PTH concentrations are incompletely understood. We performed a genome-wide association study of serum PTH concentrations among 29,155 participants of European ancestry from 13 cohort studies (n=22,653 and n=6502 in discovery and replication analyses, respectively). We evaluated the association of single nucleotide polymorphisms (SNPs) with natural log-transformed PTH concentration adjusted for age, sex, season, study site, and principal components of ancestry. We discovered associations of SNPs from five independent regions with serum PTH concentration, including the strongest association with rs6127099 upstream of CYP24A1 (P=4.2 × 10(-53)), a gene that encodes the primary catabolic enzyme for 1,25-dihydroxyvitamin D and 25-dihydroxyvitamin D. Each additional copy of the minor allele at this SNP associated with 7% higher serum PTH concentration. The other SNPs associated with serum PTH concentration included rs4074995 within RGS14 (P=6.6 × 10(-17)), rs219779 adjacent to CLDN14 (P=3.5 × 10(-16)), rs4443100 near RTDR1 (P=8.7 × 10(-9)), and rs73186030 near CASR (P=4.8 × 10(-8)). Of these five SNPs, rs6127099, rs4074995, and rs219779 replicated. Thus, common genetic variants located near genes involved in vitamin D metabolism and calcium and renal phosphate transport associated with differences in circulating PTH concentrations. Future studies could identify the causal variants at these loci, and the clinical and functional relevance of these variants should be pursued.
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3.
  • Eichenlaub, Manuel, et al. (author)
  • Comparator Data Characteristics and Testing Procedures for the Clinical Performance Evaluation of Continuous Glucose Monitoring Systems
  • 2024
  • In: Diabetes Technology & Therapeutics. - : Mary Ann Liebert. - 1520-9156 .- 1557-8593. ; 26:4, s. 263-275
  • Journal article (peer-reviewed)abstract
    • Comparing the performance of different continuous glucose monitoring (CGM) systems is challenging due to the lack of comprehensive guidelines for clinical study design. In particular, the absence of concise requirements for the distribution of comparator (reference) blood glucose (BG) concentrations and their rate of change (RoC), that are used to evaluate CGM performance, impairs comparability. For this article, several experts in the field of CGM performance testing have collaborated to propose characteristics of the distribution of comparator measurements that should be collected during CGM performance testing. Specifically, it is proposed that at least 7.5% of comparator BG concentrations are <70 mg/dL (3.9 mmol/L) and >300 mg/dL (16.7 mmol/L), respectively and that at least 7.5% of BG-RoC combinations indicate fast BG changes with impending hypo- or hyperglycemia, respectively. These proposed characteristics of the comparator data can facilitate the harmonization of testing conditions across different studies and CGM systems and ensure that the most relevant scenarios representing real-life situations are established during performance testing. In addition, a study protocol and testing procedure for the manipulation of glucose levels is suggested that enables the collection of comparator data with these characteristics. This work is an important step towards establishing a future standard for the performance evaluation of CGM systems.
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4.
  • Inker, Lesley A., et al. (author)
  • New creatinine- and cystatin C-based equations to estimate GFR without race
  • 2021
  • In: New England Journal of Medicine. - 0028-4793. ; 385:19, s. 1737-1749
  • Journal article (peer-reviewed)abstract
    • Background: Current equations for estimated glomerular filtration rate (eGFR) that use serum creatinine or cystatin C incorporate age, sex, and race to estimate measured GFR. However, race in eGFR equations is a social and not a biologic construct.Methods: We developed new eGFR equations without race using data from two development data sets: 10 studies (8254 participants, 31.5% Black) for serum creatinine and 13 studies (5352 participants, 39.7% Black) for both serum creatinine and cystatin C. In a validation data set of 12 studies (4050 participants, 14.3% Black), we compared the accuracy of new eGFR equations to measured GFR. We projected the prevalence of chronic kidney disease (CKD) and GFR stages in a sample of U.S. adults, using current and new equations.Results: In the validation data set, the current creatinine equation that uses age, sex, and race overestimated measured GFR in Blacks (median, 3.7 ml per minute per 1.73 m2 of body-surface area; 95% confidence interval [CI], 1.8 to 5.4) and to a lesser degree in non-Blacks (median, 0.5 ml per minute per 1.73 m2; 95% CI, 0.0 to 0.9). When the adjustment for Black race was omitted from the current eGFR equation, measured GFR in Blacks was underestimated (median, 7.1 ml per minute per 1.73 m2; 95% CI, 5.9 to 8.8). A new equation using age and sex and omitting race underestimated measured GFR in Blacks (median, 3.6 ml per minute per 1.73 m2; 95% CI, 1.8 to 5.5) and overestimated measured GFR in non-Blacks (median, 3.9 ml per minute per 1.73 m2; 95% CI, 3.4 to 4.4). For all equations, 85% or more of the eGFRs for Blacks and non-Blacks were within 30% of measured GFR. New creatinine-cystatin C equations without race were more accurate than new creatinine equations, with smaller differences between race groups. As compared with the current creatinine equation, the new creatinine equations, but not the new creatinine-cystatin C equations, increased population estimates of CKD prevalence among Blacks and yielded similar or lower prevalence among non-Blacks.Conclusions: New eGFR equations that incorporate creatinine and cystatin C but omit race are more accurate and led to smaller differences between Black participants and non-Black participants than new equations without race with either creatinine or cystatin C alone.
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5.
  • Lee, Crystal Man Ying, et al. (author)
  • Comparing different definitions of prediabetes with subsequent risk of diabetes: an individual participant data meta-analysis involving 76 513 individuals and 8208 cases of incident diabetes.
  • 2019
  • In: BMJ open diabetes research & care. - : BMJ. - 2052-4897. ; 7:1
  • Journal article (peer-reviewed)abstract
    • There are currently five widely used definition of prediabetes. We compared the ability of these to predict 5-year conversion to diabetes and investigated whether there were other cut-points identifying risk of progression to diabetes that may be more useful.We conducted an individual participant meta-analysis using longitudinal data included in the Obesity, Diabetes and Cardiovascular Disease Collaboration. Cox regression models were used to obtain study-specific HRs for incident diabetes associated with each prediabetes definition. Harrell's C-statistics were used to estimate how well each prediabetes definition discriminated 5-year risk of diabetes. Spline and receiver operating characteristic curve (ROC) analyses were used to identify alternative cut-points.Sixteen studies, with 76513 participants and 8208 incident diabetes cases, were available. Compared with normoglycemia, current prediabetes definitions were associated with four to eight times higher diabetes risk (HRs (95% CIs): 3.78 (3.11 to 4.60) to 8.36 (4.88 to 14.33)) and all definitions discriminated 5-year diabetes risk with good accuracy (C-statistics 0.79-0.81). Cut-points identified through spline analysis were fasting plasma glucose (FPG) 5.1mmol/L and glycated hemoglobin (HbA1c) 5.0% (31 mmol/mol) and cut-points identified through ROC analysis were FPG 5.6mmol/L, 2-hour postload glucose 7.0mmol/L and HbA1c 5.6% (38 mmol/mol).In terms of identifying individuals at greatest risk of developing diabetes within 5years, using prediabetes definitions that have lower values produced non-significant gain. Therefore, deciding which definition to use will ultimately depend on the goal for identifying individuals at risk of diabetes.
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6.
  • Mahajan, Anubha, et al. (author)
  • Refining the accuracy of validated target identification through coding variant fine-mapping in type 2 diabetes
  • 2018
  • In: Nature Genetics. - : Nature Publishing Group. - 1061-4036 .- 1546-1718. ; 50:4, s. 559-571
  • Journal article (peer-reviewed)abstract
    • We aggregated coding variant data for 81,412 type 2 diabetes cases and 370,832 controls of diverse ancestry, identifying 40 coding variant association signals (P < 2.2 × 10−7); of these, 16 map outside known risk-associated loci. We make two important observations. First, only five of these signals are driven by low-frequency variants: even for these, effect sizes are modest (odds ratio ≤1.29). Second, when we used large-scale genome-wide association data to fine-map the associated variants in their regional context, accounting for the global enrichment of complex trait associations in coding sequence, compelling evidence for coding variant causality was obtained for only 16 signals. At 13 others, the associated coding variants clearly represent ‘false leads’ with potential to generate erroneous mechanistic inference. Coding variant associations offer a direct route to biological insight for complex diseases and identification of validated therapeutic targets; however, appropriate mechanistic inference requires careful specification of their causal contribution to disease predisposition.
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7.
  • Merino, Jordi, et al. (author)
  • Quality of dietary fat and genetic risk of type 2 diabetes : individual participant data meta-analysis
  • 2019
  • In: BMJ. British Medical Journal. - : BMJ Publishing Group Ltd. - 0959-8146 .- 0959-535X. ; 366
  • Journal article (peer-reviewed)abstract
    • OBJECTIVE To investigate whether the genetic burden of type 2 diabetes modifies the association between the quality of dietary fat and the incidence of type 2 diabetes.DESIGN Individual participant data meta-analysis.DATA SOURCES Eligible prospective cohort studies were systematically sourced from studies published between January 1970 and February 2017 through electronic searches in major medical databases (Medline, Embase, and Scopus) and discussion with investigators.REVIEW METHODS Data from cohort studies or multicohort consortia with available genome-wide genetic data and information about the quality of dietary fat and the incidence of type 2 diabetes in participants of European descent was sought. Prospective cohorts that had accrued five or more years of follow-up were included. The type 2 diabetes genetic risk profile was characterized by a 68-variant polygenic risk score weighted by published effect sizes. Diet was recorded by using validated cohort-specific dietary assessment tools. Outcome measures were summary adjusted hazard ratios of incident type 2 diabetes for polygenic risk score, isocaloric replacement of carbohydrate (refined starch and sugars) with types of fat, and the interaction of types of fat with polygenic risk score.RESULTS Of 102 305 participants from 15 prospective cohort studies, 20 015 type 2 diabetes cases were documented after a median follow-up of 12 years (interquartile range 9.4-14.2). The hazard ratio of type 2 diabetes per increment of 10 risk alleles in the polygenic risk score was 1.64 (95% confidence interval 1.54 to 1.75, I-2 = 7.1%, tau(2) = 0.003). The increase of polyunsaturated fat and total omega 6 polyunsaturated fat intake in place of carbohydrate was associated with a lower risk of type 2 diabetes, with hazard ratios of 0.90 (0.82 to 0.98, I-2 = 18.0%, tau(2) = 0.006; per 5% of energy) and 0.99 (0.97 to 1.00, I-2 = 58.8%, tau(2) = 0.001; per increment of 1 g/d), respectively. Increasing monounsaturated fat in place of carbohydrate was associated with a higher risk of type 2 diabetes (hazard ratio 1.10, 95% confidence interval 1.01 to 1.19, I-2 = 25.9%, tau(2) = 0.006; per 5% of energy). Evidence of small study effects was detected for the overall association of polyunsaturated fat with the risk of type 2 diabetes, but not for the omega 6 polyunsaturated fat and monounsaturated fat associations. Significant interactions between dietary fat and polygenic risk score on the risk of type 2 diabetes (P>0.05 for interaction) were not observed.CONCLUSIONS These data indicate that genetic burden and the quality of dietary fat are each associated with the incidence of type 2 diabetes. The findings do not support tailoring recommendations on the quality of dietary fat to individual type 2 diabetes genetic risk profiles for the primary prevention of type 2 diabetes, and suggest that dietary fat is associated with the risk of type 2 diabetes across the spectrum of type 2 diabetes genetic risk.
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9.
  • Saadatagah, Seyedmohammad, et al. (author)
  • Atrial Fibrillation and Clonal Hematopoiesis in TET2 and ASXL1
  • 2024
  • In: JAMA CARDIOLOGY. - 2380-6583 .- 2380-6591. ; 9:6, s. 497-506
  • Journal article (peer-reviewed)abstract
    • ImportanceClonal hematopoiesis of indeterminate potential (CHIP) may contribute to the risk of atrial fibrillation (AF) through its association with inflammation and cardiac remodeling. ObjectiveTo determine whether CHIP was associated with AF, inflammatory and cardiac biomarkers, and cardiac structural changes. Design, Setting, and ParticipantsThis was a population-based, prospective cohort study in participants of the Atherosclerosis Risk in Communities (ARIC) study and UK Biobank (UKB) cohort. Samples were collected and echocardiography was performed from 2011 to 2013 in the ARIC cohort, and samples were collected from 2006 to 2010 in the UKB cohort. Included in this study were adults without hematologic malignancies, mitral valve stenosis, or previous mitral valve procedure from both the ARIC and UKB cohorts; additionally, participants without hypertrophic cardiomyopathy and congenital heart disease from the UKB cohort were also included. Data analysis was completed in 2023. ExposuresCHIP (variant allele frequency [VAF] >= 2%), common gene-specific CHIP subtypes (DNMT3A, TET2, ASXL1), large CHIP (VAF >= 10%), inflammatory and cardiac biomarkers (high-sensitivity C-reactive protein, interleukin 6 [IL-6], IL-18, high-sensitivity troponin T [hs-TnT] and hs-TnI, N-terminal pro-B-type natriuretic peptide), and echocardiographic indices. Main Outcome MeasureIncident AF. ResultsA total of 199 982 adults were included in this study. In ARIC participants (4131 [2.1%]; mean [SD] age, 76 [5] years; 2449 female [59%]; 1682 male [41%]; 935 Black [23%] and 3196 White [77%]), 1019 had any CHIP (24.7%), and 478 had large CHIP (11.6%). In UKB participants (195 851 [97.9%]; mean [SD] age, 56 [8] years; 108 370 female [55%]; 87 481 male [45%]; 3154 Black [2%], 183 747 White [94%], and 7971 other race [4%]), 11 328 had any CHIP (5.8%), and 5189 had large CHIP (2.6%). ARIC participants were followed up for a median (IQR) period of 7.0 (5.3-7.7) years, and UKB participants were followed up for a median (IQR) period of 12.2 (11.3-13.0) years. Meta-analyzed hazard ratios for AF were 1.12 (95% CI, 1.01-1.25; P = .04) for participants with vs without large CHIP, 1.29 (95% CI, 1.05-1.59; P = .02) for those with vs without large TET2 CHIP (seen in 1340 of 197 209 [0.67%]), and 1.45 (95% CI, 1.02-2.07; P = .04) for those with vs without large ASXL1 CHIP (seen in 314 of 197 209 [0.16%]). Large TET2 CHIP was associated with higher IL-6 levels. Additionally, large ASXL1 was associated with higher hs-TnT level and increased left ventricular mass index. Conclusions and RelevanceLarge TET2 and ASXL1, but not DNMT3A, CHIP was associated with higher IL-6 level, indices of cardiac remodeling, and increased risk for AF. Future research is needed to elaborate on the mechanisms driving the associations and to investigate potential interventions to reduce the risk.
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10.
  • Seshasai, Sreenivasa Rao Kondapally, et al. (author)
  • Diabetes mellitus, fasting glucose, and risk of cause-specific death.
  • 2011
  • In: The New England journal of medicine. - 1533-4406 .- 0028-4793. ; 364:9, s. 829-41
  • Journal article (peer-reviewed)abstract
    • The extent to which diabetes mellitus or hyperglycemia is related to risk of death from cancer or other nonvascular conditions is uncertain.
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11.
  • Tobias, Deirdre K, et al. (author)
  • Second international consensus report on gaps and opportunities for the clinical translation of precision diabetes medicine
  • 2023
  • In: Nature Medicine. - 1546-170X. ; 29:10, s. 2438-2457
  • Research review (peer-reviewed)abstract
    • Precision medicine is part of the logical evolution of contemporary evidence-based medicine that seeks to reduce errors and optimize outcomes when making medical decisions and health recommendations. Diabetes affects hundreds of millions of people worldwide, many of whom will develop life-threatening complications and die prematurely. Precision medicine can potentially address this enormous problem by accounting for heterogeneity in the etiology, clinical presentation and pathogenesis of common forms of diabetes and risks of complications. This second international consensus report on precision diabetes medicine summarizes the findings from a systematic evidence review across the key pillars of precision medicine (prevention, diagnosis, treatment, prognosis) in four recognized forms of diabetes (monogenic, gestational, type 1, type 2). These reviews address key questions about the translation of precision medicine research into practice. Although not complete, owing to the vast literature on this topic, they revealed opportunities for the immediate or near-term clinical implementation of precision diabetes medicine; furthermore, we expose important gaps in knowledge, focusing on the need to obtain new clinically relevant evidence. Gaps include the need for common standards for clinical readiness, including consideration of cost-effectiveness, health equity, predictive accuracy, liability and accessibility. Key milestones are outlined for the broad clinical implementation of precision diabetes medicine.
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12.
  • Wheeler, Eleanor, et al. (author)
  • Impact of common genetic determinants of Hemoglobin A1c on type 2 diabetes risk and diagnosis in ancestrally diverse populations : A transethnic genome-wide meta-analysis
  • 2017
  • In: PLoS Medicine. - : PUBLIC LIBRARY SCIENCE. - 1549-1277 .- 1549-1676. ; 14:9
  • Journal article (peer-reviewed)abstract
    • Background: Glycated hemoglobin (HbA1c) is used to diagnose type 2 diabetes (T2D) and assess glycemic control in patients with diabetes. Previous genome-wide association studies (GWAS) have identified 18 HbA1c-associated genetic variants. These variants proved to be classifiable by their likely biological action as erythrocytic (also associated with erythrocyte traits) or glycemic (associated with other glucose-related traits). In this study, we tested the hypotheses that, in a very large scale GWAS, we would identify more genetic variants associated with HbA1c and that HbA1c variants implicated in erythrocytic biology would affect the diagnostic accuracy of HbA1c. We therefore expanded the number of HbA1c-associated loci and tested the effect of genetic risk-scores comprised of erythrocytic or glycemic variants on incident diabetes prediction and on prevalent diabetes screening performance. Throughout this multiancestry study, we kept a focus on interancestry differences in HbA1c genetics performance that might influence race-ancestry differences in health outcomes.Methods & findings: Using genome-wide association meta-analyses in up to 159,940 individuals from 82 cohorts of European, African, East Asian, and South Asian ancestry, we identified 60 common genetic variants associated with HbA1c. We classified variants as implicated in glycemic, erythrocytic, or unclassified biology and tested whether additive genetic scores of erythrocytic variants (GS-E) or glycemic variants (GS-G) were associated with higher T2D incidence in multiethnic longitudinal cohorts (N = 33,241). Nineteen glycemic and 22 erythrocytic variants were associated with HbA1c at genome-wide significance. GS-G was associated with higher T2D risk (incidence OR = 1.05, 95% CI 1.04-1.06, per HbA1c-raising allele, p = 3 x 10-29); whereas GS-E was not (OR = 1.00, 95% CI 0.99-1.01, p = 0.60). In Europeans and Asians, erythrocytic variants in aggregate had only modest effects on the diagnostic accuracy of HbA1c. Yet, in African Americans, the X-linked G6PD G202A variant (T-allele frequency 11%) was associated with an absolute decrease in HbA1c of 0.81%-units (95% CI 0.66-0.96) per allele in hemizygous men, and 0.68%-units (95% CI 0.38-0.97) in homozygous women. The G6PD variant may cause approximately 2% (N = 0.65 million, 95% CI0.55-0.74) of African American adults with T2Dto remain undiagnosed when screened with HbA1c. Limitations include the smaller sample sizes for non-European ancestries and the inability to classify approximately one-third of the variants. Further studies in large multiethnic cohorts with HbA1c, glycemic, and erythrocytic traits are required to better determine the biological action of the unclassified variants.Conclusions: As G6PD deficiency can be clinically silent until illness strikes, we recommend investigation of the possible benefits of screening for the G6PD genotype along with using HbA1c to diagnose T2D in populations of African ancestry or groups where G6PD deficiency is common. Screening with direct glucose measurements, or genetically-informed HbA1c diagnostic thresholds in people with G6PD deficiency, may be required to avoid missed or delayed diagnoses.
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