Publications

Abstract Objective To examine the association of long-term weight change with RA risk in a large prospective cohort study. Methods The Nurses’ Health Study II started in 1989 (baseline); after exclusions, we studied 108 505 women 25–42 years old without RA. Incident RA was reported by participants and confirmed by medical record review. Body weight was reported biennially through 2015. We investigated two time-varying exposures: weight changes from baseline and from age 18; change was divided into five categories. We used a marginal structural model approach to account for time-varying weight change and covariates. Results Over 2 583 266 person-years, with a median follow-up time of 25.3 years, 541 women developed RA. Compared with women with stable weight from baseline, weight change was significantly associated with increased RA risk [weight gain 2–<10 kg: RR = 1.98 (95% CI 1.38, 2.85); 10–<20 kg: RR = 3.28 (95% CI 2.20, 4.89); ≥20 kg: RR = 3.81 (95% CI 2.39, 6.07); and weight loss >2 kg: RR = 2.05 (95% CI 1.28, 3.28)]. Weight gain of 10 kg or more from age 18 compared with stable weight was also associated with increased RA risk [10–< 20 kg: RR = 2.12 (95% CI 1.37, 3.27), ≥20 kg: RR = 2.31 (95% CI 1.50, 3.56)]. Consistent findings were observed for seropositive and seronegative RA. Conclusion Long-term weight gain was strongly associated with increased RA risk in women, with weight gain of ≥20 kg associated with more than a three-fold increased RA risk. Maintenance of healthy weight may be a strategy to prevent or delay RA.

Introduction: Evidence on the relationship between type 2 diabetes onset age, duration, and mortality risk has been influenced by limited follow-up, inadequate control for confounding, and inability to cover the full range of onset age, duration, and the full spectrum of major causes of death. Moreover, there are scarce data dissecting how type 2 diabetes onset age and duration shape life expectancy. Hypothesis We assessed the hypothesis that early onset of type 2 diabetes and longer disease duration may be associated with higher risk of all-cause and cause-specific mortality and greater loss in life expectancy. Methods: We prospectively followed 270,075 eligible participants in the Nurses’ Health Study, Nurses’ Health Study II, and Health Professionals Follow-up Study longitudinal cohorts for up to 40 years. The exposures include type 2 diabetes onset age (<40, ≥40 to <50, ≥50 to <60, ≥60 to <70, ≥70 to <80, and ≥80 years) and duration (<10, ≥10 to <20, ≥20 to <30, and ≥30 years). Cox models were used to estimate hazard ratios (HRs) and 95% confidence intervals (CIs), adjusting for age and a wide spectrum of potential confounders. Results: We documented 73,076 deaths during 8,166,216 person-years of follow-up. In fully-adjusted analyses, incident early-onset type 2 diabetes (diagnosed <40 years of age) was associated with significantly higher mortality from all-causes (HR, 95% CI was 3.16, 2.64-3.79; vs. individuals without type 2 diabetes), cardiovascular disease (6.56, 4.27-10.1), respiratory disease (3.43, 1.38-8.51), neurodegenerative disease (5.13, 2.09-12.6), kidney disease (8.55, 1.98-36.9), and suggestively increased mortality from diabetes-related cancer (1.63, 0.94-2.83) and obesity-related cancer (1.63, 0.92-2.88). The relative risk elevations declined dramatically with each higher decade of age at type 2 diabetes diagnosis for deaths from most of these causes, though the absolute risk difference increased continuously. A substantially higher cumulative incidence of mortality and a greater loss in life expectancy were associated with younger age at type 2 diabetes diagnosis. Comparing individuals with early-onset type 2 diabetes to those without type 2 diabetes, their estimated multivariable-adjusted cumulative incidence of all-cause mortality at age 80 was 0.43 vs. 0.20, and the estimated life expectancy loss at age 40 was 2.5 years. Longer disease duration was associated with generally higher relative and absolute risk of mortality. Conclusions: Early onset of type 2 diabetes and longer disease duration are associated with substantially increased risk of all-cause and cause-specific mortality and greater loss in life expectancy. The effect of early-onset type 2 diabetes on mortality risk is stronger than that of later-onset type 2 diabetes.

Introduction: The relationship between artificially sweetened beverage (ASB) intake and type 2 diabetes (T2D) risk remains inconclusive. Few studies have evaluated whether circulating metabolites that reflect ASB consumption may unveil potential mechanisms underlying the association between ASB consumption and T2D risk. Hypothesis: We hypothesized that a novel metabolomic profile reflecting habitual ASB consumption would positively associate with incident T2D among US adults. Methods: We quantified 120 plasma metabolites with liquid chromatography-mass spectroscopy in N=3,424 Nurses’ Health Study (NHS), NHSII, and Health Professionals Follow-up Study (HPFS) discovery cohort participants, and N=1,870 Framingham Heart Study (FHS) replication cohort participants. Habitual ASB consumption (servings/day; low-calorie cola or other carbonated beverages) was estimated from food frequency questionnaires at the time of blood draw. We used elastic net regression with 10-fold-cross-validation to age- and body mass index- adjusted metabolite levels to identify a metabolite profile associated with higher ASB consumption (ln-transformed). We then derived the continuous ASB metabolomic score as the weighted sum of these metabolites and replicated the analysis in an internal testing set and FHS. Finally, we evaluated the association of quartiles (Q) of the ASB-derived metabolomic score in NHS/NHSII/HPFS and FHS cohorts with incident T2D risk after blood draw (baseline for analysis) using Cox regression models to estimate hazard ratios (HR) and 95% confidence interval (CI), adjusted for demographics, lifestyle, diet, and body mass index at blood draw. Results: The ASB-derived metabolomic profile included 61 metabolites, primarily lipids and amino acids (Pearson correlation coefficients [ r ] between ASB self-reported intake and metabolomic score: r=0.08 [95% CI: 0.05, 0.11; p <0.0001] and r=0.09 [95% CI: 0.04, 0.14; p =0.001], for discovery and replication, respectively). Mean follow-up was 20 and 16 years from blood draw, including 359 and 241 confirmed incident T2D cases for NHS/NHSII/HPFS and FHS, respectively. Compared with participants in the lowest quartile of the ASB-derived metabolomic profile, higher quartiles were incrementally and significantly at higher T2D risk in NHS/NHSII/HPFS (HR [CI] for Q2, Q3, Q4 vs. Q1: 1.45 [1.04, 2.02], 1.83 [1.33, 2.52], 1.62 [1.18, 2.22], respectively; p-trend =0.003) and FHS (1.76 [1.24, 2.48], 1.82 [1.28, 2.58], 2.45 [1.77, 3.40], respectively; p-trend <0.0001). Conclusions: A robust metabolomic profile of ASB intake was not identified, yet the objective and replicable ASB-derived metabolomic profile was associated with higher incident T2D risk. The identified metabolites may reflect ASB intake, western dietary patterns, underlying metabolic health, and/or T2D-related pathophysiology.

OBJECTIVES: To prospectively analyze the associations between urea cycle metabolites and incident atrial fibrillation (AF) or heart failure (HF), and to evaluate the effect of a Mediterranean diet (MD) intervention on such associations. METHODS: We designed two nested case-control studies within the PREDIMED trial, a randomized controlled trial aimed to evaluate the effect of two MD interventions, supplemented with either extra virgin olive oil (EVOO) or nuts, on cardiovascular disease (CVD). Fasting blood samples were collected at baseline and urea cycle metabolites (arginine, citrulline, and ornithine) and methylarginines (asymmetric dimethylarginine/symmetric dimethylarginine ratio (ADMA/SDMA ratio)) were determined using liquid chromatography tandem mass spectrometry. We used conditional logistic regression models, adjusted for potential confounders, to analyze the associations between the metabolites and incident AF or HF. Potential interactions between metabolites and intervention (MD groups vs control group) were tested with the likelihood ratio test. RESULTS: The study population comprised a total of 1241 participants (509 cases) for AF case-control and 824 participants (326 cases) for HF case-control. Arginine was inversely associated with incident AF (OR per SD 0.83, 95% CI 0.73; 0.94) and HF (OR per SD 0.82, 95% CI 0.69; 0.97). Whereas ADMA/SDMA ratio was positively associated with AF (OR per SD 1.19, 95% CI 1.02; 1.41) but not with HF risk. A statistically significant interaction (P = 0.044) was found between arginine and intervention on HF risk. The lower risk of HF associated with arginine was only observed in participants of the MD groups (EVOO + nuts). CONCLUSIONS: The results of the present study suggest that urea cycle metabolites, arginine and ADMA/SDMA ratio specifically, could be involved in AF and HF pathophysiology. Moreover, the dietary intervention may modify the association between arginine and HF. FUNDING SOURCES: National Institutes of Health (NIH), Spanish Government Official Agency for funding biomedical research-Instituto de Salud Carlos III (ISCIII) and CIBEROBN

Raman D-band spectra are reported for several different SWNTs using two different laser energies ${(E}_{\mathrm{laser}}=1.58$ and 2.41 eV). At a fixed ${E}_{\mathrm{laser}},$ individual isolated SWNTs exhibit different diameter-dependent D-band frequencies ${\ensuremath{\omega}}_{D}$ around an average value. For both semiconducting and metallic tubes, ${\ensuremath{\omega}}_{D}$ decreases with decreasing nanotube diameter, though ${\ensuremath{\omega}}_{D}$ for isolated metallic SWNTs is higher than for isolated semiconducting SWNTs. The average D-band frequency depends linearly on ${E}_{\mathrm{laser}},$ as previously observed for SWNT bundles, suggesting that the D-band in SWNTs is activated by defects or by the finite size of the SWNTs.

A single-nucleotide polymorphism (rs10911021) was identified that was significantly associated with CHD among persons with diabetes but not in those without diabetes and was functionally related to glutamic acid metabolism, suggesting a mechanistic link.

Various data sharing platforms are being developed to enhance the sharing of cohort data by addressing the fragmented state of data storage and access systems. However, policy challenges in several domains remain unresolved. The euCanSHare workshop was organized to identify and discuss these challenges and to set the future research agenda. Concerns over the multiplicity and long-term sustainability of platforms, lack of resources, access of commercial parties to medical data, credit and recognition mechanisms in academia and the organization of data access committees are outlined. Within these areas, solutions need to be devised to ensure an optimal functioning of platforms.

Hemoglobin (Hb) is the main carrier of oxygen. In general, high-end Hb levels within the normal range are considered beneficial for health 1 . However, activation of the hypoxia response has been shown to protect mice against metabolic dysfunction 2-4 . We used Hb levels as an indicator for oxygenation status and studied its association with >170 anthropometric and metabolic parameters in two Finnish birth cohorts both in cross-sectional and longitudinal design (max n = 7,175). Here we show a positive linear association between Hb levels and body mass index (BMI). Subjects with the lower Hb levels had better glucose tolerance, lower cholesterol and blood pressure levels, less adverse metabolite profiles and lower inflammatory load. Notably, these associations were not only mediated by the lower BMI, and the effect size of many of them increased with age. Polygenic risk score (PRS) analyses indicated shared genetic determinants between Hb levels and BMI, insulin, triglyceride and HDL cholesterol levels. Mendelian randomization (MR) analyses could not demonstrate causal relationships between Hb and metabolic parameters. However, manipulation of Hb levels by venesection in mice showed evidence for causal associations with body weight and metabolic parameters. Our findings suggest that lower-end normal Hb levels may be favorable for systemic metabolism involving mild chronic activation of the hypoxia response. Therefore modulation of Hb levels could be a novel strategy towards maintenance of metabolic health.

Observational studies have reported different effects of adiposity on cardiovascular risk factors across age and sex. Since cardiovascular risk factors are enriched in obese individuals, it has not been easy to dissect the effects of adiposity from those of other risk factors. We used a Mendelian randomization approach, applying a set of 32 genetic markers to estimate the causal effect of adiposity on blood pressure, glycemic indices, circulating lipid levels, and markers of inflammation and liver disease in up to 67,553 individuals. All analyses were stratified by age (cutoff 55 years of age) and sex. The genetic score was associated with BMI in both nonstratified analysis (P = 2.8 × 10−107) and stratified analyses (all P < 3.3 × 10−30). We found evidence of a causal effect of adiposity on blood pressure, fasting levels of insulin, C-reactive protein, interleukin-6, HDL cholesterol, and triglycerides in a nonstratified analysis and in the <55-year stratum. Further, we found evidence of a smaller causal effect on total cholesterol (P for difference = 0.015) in the ≥55-year stratum than in the <55-year stratum, a finding that could be explained by biology, survival bias, or differential medication. In conclusion, this study extends previous knowledge of the effects of adiposity by providing sex- and age-specific causal estimates on cardiovascular risk factors.