Scope
Diet and exercise are significant players in obesity and metabolic diseases. Time‐restricted feeding (tRF) has been shown to improve metabolic responses by regulating circadian clocks but ...whether it acts synergically with exercise remains unknown. It is hypothesized that forced exercise alone or combined with tRF alleviates obesity and its metabolic complications.
Methods and results
Male C57bl6 mice are fed with high‐fat or a control diet for 12 weeks either ad libitum or tRF for 10 h during their active period. High‐fat diet (HFD)‐fed mice are divided into exercise (treadmill for 1 h at 12 m min−1 alternate days for 9 weeks and 16 m min−1 daily for the following 3 weeks) and non‐exercise groups. tRF and tRF‐Ex significantly decreased body weight, food intake, and plasma lipids, and improved glucose tolerance. However, exercise reduced only body weight and plasma lipids. tRF and tRF‐Ex significantly downregulated Fasn, Hmgcr, and Srebp1c, while exercise only Hmgcr. HFD feeding disrupted clock genes, but exercise, tRF, and tRF‐Ex coordinated the circadian clock genes Bmal1, Per2, and Rev‐Erbα in the liver, adipose tissue, and skeletal muscles.
Conclusion
HFD feeding disrupted clock genes in the peripheral organs while exercise, tRF, and their combination restored clock genes and improved metabolic consequences induced by high‐fat diet feeding.
High‐fat diet feeding disrupts metabolic and circadian clock genes in mice. Forced exercise, time‐restricted feeding, and their combinations resynchronize clock genes in peripheral organs and improve metabolic consequences. The combination of exercise and time‐restricted feeding results in the greatest reduction in body weight, plasma lipids, and improved insulin sensitivity compared to either exercise or time‐restricted feeding alone.
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BFBNIB, FZAB, GIS, IJS, KILJ, NLZOH, NUK, OILJ, SBCE, SBMB, UL, UM, UPUK
Background
Observational findings for high‐density lipoprotein (HDL)‐mediated cholesterol efflux capacity (HDL‐CEC) and coronary heart disease (CHD) appear inconsistent, and knowledge of the genetic ...architecture of HDL‐CEC is limited.
Objectives
A large‐scale observational study on the associations of HDL‐CEC and other HDL‐related measures with CHD and the largest genome‐wide association study (GWAS) of HDL‐CEC.
Participants/methods
Six independent cohorts were included with follow‐up data for 14,438 participants to investigate the associations of HDL‐related measures with incident CHD (1,570 events). The GWAS of HDL‐CEC was carried out in 20,372 participants.
Results
HDL‐CEC did not associate with CHD when adjusted for traditional risk factors and HDL cholesterol (HDL‐C). In contradiction, almost all HDL‐related concentration measures associated consistently with CHD after corresponding adjustments. There were no genetic loci associated with HDL‐CEC independent of HDL‐C and triglycerides.
Conclusion
HDL‐CEC is not unequivocally associated with CHD in contrast to HDL‐C, apolipoprotein A‐I, and most of the HDL subclass particle concentrations.
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BFBNIB, FZAB, GIS, IJS, KILJ, NLZOH, NUK, OILJ, SBCE, SBMB, UL, UM, UPUK
Our work is motivated by the search for metabolite quantitative trait loci (QTL) in a cohort of more than 5000 people. There are 158 metabolites measured by NMR spectroscopy in the 31‐year follow‐up ...of the Northern Finland Birth Cohort 1966 (NFBC66). These metabolites, as with many multivariate phenotypes produced by high‐throughput biomarker technology, exhibit strong correlation structures. Existing approaches for combining such data with genetic variants for multivariate QTL analysis generally ignore phenotypic correlations or make restrictive assumptions about the associations between phenotypes and genetic loci. We present a computationally efficient Bayesian seemingly unrelated regressions model for high‐dimensional data, with cell‐sparse variable selection and sparse graphical structure for covariance selection. Cell sparsity allows different phenotype responses to be associated with different genetic predictors and the graphical structure is used to represent the conditional dependencies between phenotype variables. To achieve feasible computation of the large model space, we exploit a factorisation of the covariance matrix. Applying the model to the NFBC66 data with 9000 directly genotyped single nucleotide polymorphisms, we are able to simultaneously estimate genotype–phenotype associations and the residual dependence structure among the metabolites. The R package BayesSUR with full documentation is available at https://cran.r‐project.org/web/packages/BayesSUR/
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BFBNIB, FZAB, GIS, IJS, IZUM, KILJ, NLZOH, NUK, OILJ, PILJ, SAZU, SBCE, SBMB, UL, UM, UPUK
Metabolite associations with insulin resistance were studied in 7,098 young Finns (age 31 ± 3 years; 52% women) to elucidate underlying metabolic pathways. Insulin resistance was assessed by the ...homeostasis model (HOMA-IR) and circulating metabolites quantified by high-throughput nuclear magnetic resonance spectroscopy in two population-based cohorts. Associations were analyzed using regression models adjusted for age, waist, and standard lipids. Branched-chain and aromatic amino acids, gluconeogenesis intermediates, ketone bodies, and fatty acid composition and saturation were associated with HOMA-IR (P < 0.0005 for 20 metabolite measures). Leu, Ile, Val, and Tyr displayed sex- and obesity-dependent interactions, with associations being significant for women only if they were abdominally obese. Origins of fasting metabolite levels were studied with dietary and physical activity data. Here, protein energy intake was associated with Val, Phe, Tyr, and Gln but not insulin resistance index. We further tested if 12 genetic variants regulating the metabolites also contributed to insulin resistance. The genetic determinants of metabolite levels were not associated with HOMA-IR, with the exception of a variant in GCKR associated with 12 metabolites, including amino acids (P < 0.0005). Nonetheless, metabolic signatures extending beyond obesity and lipid abnormalities reflected the degree of insulin resistance evidenced in young, normoglycemic adults with sex-specific fingerprints.
Adults who were born preterm with a very low birth weight have higher blood pressure and impaired glucose regulation later in life compared with those born at term. We investigated cardiometabolic ...risk factors in young adults who were born at any degree of prematurity in the Preterm Birth and Early Life Programming of Adult Health and Disease (ESTER) Study, a population-based cohort study of individuals born in 1985-1989 in Northern Finland. In 2009-2011, 3 groups underwent clinical examination: 134 participants born at less than 34 gestational weeks (early preterm), 242 born at 34-36 weeks (late preterm), and 344 born at 37 weeks or later (controls). Compared with controls, adults who were born preterm had higher body fat percentages (after adjustment for sex, age, and cohort (1985-1986 or 1987-1989), for those born early preterm, difference = 6.2%, 95% confidence interval (CI): 0.4, 13.2; for those born late preterm, difference = 8.0%, 95% CI: 2.4, 13.8), waist circumferences, blood pressure (for those born early preterm, difference = 3.0 mm Hg, 95% CI: 0.9, 5.1; for those born late preterm, difference = 1.7, 95% CI: -0.1, 3.4), plasma uric acid levels (for those born early preterm, difference = 20.1%, 95% CI: 7.9, 32.3; for those born late preterm, difference = 20.2%, 95% CI: 10.7, 30.5), alanine aminotransferase levels, and aspartate transaminase levels. They were also more likely to have metabolic syndrome (for those born early preterm, odds ratio = 3.7, 95% CI: 1.6, 8.2; for those born late preterm, odds ratio = 2.5, 95% CI: 1.2, 5.3). Elevated levels of conventional and emerging risk factors suggest a higher risk of cardiometabolic disease later in life. These risk factors are also present in the large group of adults born late preterm.
Introduction
The aim of the study was to determine the association of body mass index (BMI), self‐reported symptoms or diagnosis of polycystic ovary syndrome (PCOS), and hyperandrogenemia with the ...occurrence of gestational diabetes mellitus (GDM) through reproductive life.
Material and methods
A cohort of women born in 1966 were investigated at ages 14, 31 and 46. Women with self‐reported PCOS symptoms (presence of both oligo‐amenorrhea and hirsutism) at age 31 or with formally diagnosed polycystic ovaries (PCO)/PCOS by age 46 formed the group of self‐reported PCOS (srPCOS, n = 222) and were compared with women without self‐reported PCOS symptoms or diagnosis (n = 1357). We investigated also the association of hyperandrogenism (hirsutism or biochemical hyperandrogenism) at age 31 with the occurrence of GDM throughout reproductive life.
Results
Self‐reported PCOS alone was not a risk factor for GDM, but combined with overweight at age 31 (odds ratio OR 2.43, 95% confidence interval CI 1.22‐4.86) or 46 (OR 3.04, 95% CI 1.58‐5.83) srPCOS was associated with GDM when compared with normal weight controls. The association disappeared when comparing overweight srPCOS women with overweight controls. However, hyperandrogenemia at age 31, but not hirsutism, was associated with GDM even after adjustment for BMI.
Conclusions
The increased risk of GDM in women with srPCOS was mostly attributed to overweight or obesity. Importantly, normal weight women with srPCOS did not seem to be at increased risk for developing GDM. However, hyperandrogenemia was associated with GDM even after adjustment for BMI. These findings strengthen the importance of weight management in reproductive‐age women and suggest a noteworthy role of hyperandrogenemia in the pathophysiology of GDM.
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BFBNIB, FZAB, GIS, IJS, KILJ, NLZOH, NUK, OILJ, SBCE, SBMB, UL, UM, UPUK
Free fatty acids provide an important energy source as nutrients, and act as signalling molecules in various cellular processes. Several G-protein-coupled receptors have been identified as ...free-fatty-acid receptors important in physiology as well as in several diseases. GPR120 (also known as O3FAR1) functions as a receptor for unsaturated long-chain free fatty acids and has a critical role in various physiological homeostasis mechanisms such as adipogenesis, regulation of appetite and food preference. Here we show that GPR120-deficient mice fed a high-fat diet develop obesity, glucose intolerance and fatty liver with decreased adipocyte differentiation and lipogenesis and enhanced hepatic lipogenesis. Insulin resistance in such mice is associated with reduced insulin signalling and enhanced inflammation in adipose tissue. In human, we show that GPR120 expression in adipose tissue is significantly higher in obese individuals than in lean controls. GPR120 exon sequencing in obese subjects reveals a deleterious non-synonymous mutation (p.R270H) that inhibits GPR120 signalling activity. Furthermore, the p.R270H variant increases the risk of obesity in European populations. Overall, this study demonstrates that the lipid sensor GPR120 has a key role in sensing dietary fat and, therefore, in the control of energy balance in both humans and rodents.
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DOBA, IJS, IZUM, KILJ, KISLJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
Context:
Obesity affects the majority of women with polycystic ovary syndrome (PCOS), but previous studies are inconsistent about the prevalence of obesity and the importance of weight gain in the ...development of the syndrome.
Objective:
Our objective was to explore the association between weight, weight gain, hyperandrogenism, and PCOS from adolescence to late adulthood.
Design:
The study includes a prospective Northern Finland Birth Cohort 1966 study including 5889 females born in 1966 and followed at the ages of 14, 31, and 46 years.
Setting:
The setting was the general community.
Participants:
Women presenting both oligo/amenorrhea (OA) and hirsutism (H) at age 31 (N = 125) or with formally diagnosed PCOS by age 46 (N = 181) were compared with women without PCOS symptoms or diagnosis (n = 1577).
Interventions:
None.
Main Outcome Measures:
Body mass index (BMI), weight change through life, waist circumference, Free Androgen Index, lipids, glucose, insulin, high-sensitivity C-reactive protein, homeostatic model assessment for insulin resistance, and PCOS.
Results:
Women with OA+H at age 31 or diagnosis of PCOS by age 46 had the highest BMI at all ages compared with the controls. Increase of BMI between ages 14 and 31, but not between 31 and 46, was greater in women with isolated OA (P = .006), OA+H (P = .001), and diagnosis of PCOS (P = .001) compared with controls. In the multivariate analysis, PCOS was significantly associated with BMI at all ages (BMI at age 31: odds ratio OR = 1.05 95% confidence interval (CI), 1.00–1.10, Free Androgen Index (OR = 1.08 95% CI, 1.03–1.14), serum levels of insulin (OR = 1.05 95% CI, 1.00–1.09), and triglycerides (OR = 1.48 95% CI, 1.08–2.03).
Conclusions:
Symptoms or diagnosis of PCOS are associated with dyslipidemia, hyperandrogenemia, and significantly increased weight gain, especially in early adulthood. This observation is important because it may identify a sensitive time period when weight gain plays a crucial role in the emergence of PCOS and when preventive actions against metabolic and cardiovascular diseases should be implemented.
Most uterine cervical high-risk human papillomavirus (HPV) infections are transient, with only a small fraction developing into cervical cancer. Family aggregation studies and heritability estimates ...suggest a significant inherited genetic component. Candidate gene studies and previous genome-wide association studies (GWASs) report associations between the HLA region and cervical cancer. Adopting a genome-wide approach, we aimed to compare genetic variation in women with invasive cervical cancer and cervical intraepithelial neoplasia (CIN) grade 3 with that in healthy controls.
We did a GWAS in a cohort of unrelated European individuals using data from UK Biobank, a population-based cohort including 273 377 women aged 40–69 years at recruitment between March 13, 2006, and Oct 1, 2010. We used an additive univariate logistic regression model to analyse genetic variants associated with invasive cervical cancer or CIN3. We sought replication of candidate associations in FinnGen, a large independent dataset of 128 123 individuals. We also did a two-sample mendelian randomisation approach to explore the role of risk factors in the genetic risk of cervical cancer.
We included 4769 CIN3 and invasive cervical cancer case samples and 145 545 control samples in the GWAS. Of 9 600 464 assayed and imputed single-nucleotide polymorphisms (SNPs), six independent variants were associated with CIN3 and invasive cervical cancer. These included novel loci rs10175462 (PAX8; odds ratio OR 0·87, 95% CI 0·84–0·91; p=1·07 × 10−9) and rs27069 (CLPTM1L; 0·88, 0·84–0·92; p=2·51 × 10−9), and previously reported signals at rs9272050 (HLA-DQA1; 1·27, 1·21–1·32; p=2·51 × 10−28), rs6938453 (MICA; 0·79, 0·75–0·83; p=1·97 × 10−17), rs55986091 (HLA-DQB1; 0·66, 0·60–0·72; p=6·42 × 10−28), and rs9266183 (HLA-B; 0·73, 0·64–0·83; p=1·53 × 10−6). Three SNPs were replicated in the independent Finnish dataset of 1648 invasive cervical cancer cases: PAX8 (rs10175462; p=0·015), CLPTM1L (rs27069; p=2·54 × 10−7), and HLA-DQA1 (rs9272050; p=7·90 × 10−8). Mendelian randomisation further supported the complementary role of smoking (OR 2·46, 95% CI 1·64–3·69), older age at first pregnancy (0·80, 0·68–0·95), and number of sexual partners (1·95, 1·44–2·63) in the risk of developing cervical cancer.
Our results provide new evidence for the genetic susceptibility to cervical cancer, specifically the PAX8, CLPTM1L, and HLA genes, suggesting disruption in apoptotic and immune function pathways. Future studies integrating host and viral, genetic, and epigenetic variation, could further elucidate complex host–viral interactions.
NIHR Imperial BRC Wellcome 4i Clinician Scientist Training Programme.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
Apolipoprotein A-I (apoA-I) infusions represent a potential novel therapeutic approach for the prevention of coronary artery disease (CAD). Although circulating apoA-I concentrations inversely ...associate with risk of CAD, the evidence base of this representing a causal relationship is lacking. The aim was to assess the causal role of apoA-I using human genetics.
We identified a variant (rs12225230) in APOA1 locus that associated with circulating apoA-I concentrations (p < 5 × 10−8) in 20,370 Finnish participants, and meta-analyzed our data with a previous GWAS of apoA-I. We obtained genetic estimates of CAD from UK Biobank and CARDIoGRAMplusC4D (totaling 122,733 CAD cases) and conducted a two-sample Mendelian randomization analysis. We compared our genetic findings to observational associations of apoA-I with risk of CAD in 918 incident CAD cases among 11,535 individuals from population-based prospective cohorts.
ApoA-I was associated with a lower risk of CAD in observational analyses (HR 0.81; 95%CI: 0.75, 0.88; per 1-SD higher apoA-I), with the association showing a dose-response relationship. Rs12225230 associated with apoA-I concentrations (per-C allele beta 0.076 SD; SE: 0.013; p = 1.5 × 10−9) but not with confounders. In Mendelian randomization analyses, apoA-I was not related to risk of CAD (OR 1.13; 95%CI: 0.98,1.30 per 1-SD higher apoA-I), which was different from the observational association. Similar findings were observed using an independent ABCA1 variant in sensitivity analysis.
Genetic evidence fails to support a cardioprotective role for apoA-I. This is in line with the cumulative evidence showing that HDL-related phenotypes are unlikely to have a protective role in CAD.
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•Apolipoprotein A-I relates to lower observational risk of coronary artery disease.•Robust evidence of atheroprotective properties of apolipoprotein A-I is lacking.•Mendelian randomization was used to assess the causality of apolipoprotein A-I.•Apolipoprotein A-I association with coronary artery disease is likely not causal.•Apolipoprotein A-I increasing therapies unlikely reduce risk of heart disease.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, PNG, SAZU, SBCE, SBJE, UL, UM, UPUK, ZRSKP
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