Publications by authors named "Nick Wareham"

308 Publications

Identifying adults at high-risk for change in weight and BMI in England: a longitudinal, large-scale, population-based cohort study using electronic health records.

Lancet Diabetes Endocrinol 2021 10 2;9(10):681-694. Epub 2021 Sep 2.

Institute of Health Informatics, University College London, London, UK; Health Data Research UK, University College London, London, UK; National Institute of Health Research, University College London Hospitals Biomedical Research Centre, London, UK.

Background: Targeted obesity prevention policies would benefit from the identification of population groups with the highest risk of weight gain. The relative importance of adult age, sex, ethnicity, geographical region, and degree of social deprivation on weight gain is not known. We aimed to identify high-risk groups for changes in weight and BMI using electronic health records (EHR).

Methods: In this longitudinal, population-based cohort study we used linked EHR data from 400 primary care practices (via the Clinical Practice Research Datalink) in England, accessed via the CALIBER programme. Eligible participants were aged 18-74 years, were registered at a general practice clinic, and had BMI and weight measurements recorded between Jan 1, 1998, and June 30, 2016, during the period when they had eligible linked data with at least 1 year of follow-up time. We calculated longitudinal changes in BMI over 1, 5, and 10 years, and investigated the absolute risk and odds ratios (ORs) of transitioning between BMI categories (underweight, normal weight, overweight, obesity class 1 and 2, and severe obesity [class 3]), as defined by WHO. The associations of demographic factors with BMI transitions were estimated by use of logistic regression analysis, adjusting for baseline BMI, family history of cardiovascular disease, use of diuretics, and prevalent chronic conditions.

Findings: We included 2 092 260 eligible individuals with more than 9 million BMI measurements in our study. Young adult age was the strongest risk factor for weight gain at 1, 5, and 10 years of follow-up. Compared with the oldest age group (65-74 years), adults in the youngest age group (18-24 years) had the highest OR (4·22 [95% CI 3·86-4·62]) and greatest absolute risk (37% vs 24%) of transitioning from normal weight to overweight or obesity at 10 years. Likewise, adults in the youngest age group with overweight or obesity at baseline were also at highest risk to transition to a higher BMI category; OR 4·60 (4·06-5·22) and absolute risk (42% vs 18%) of transitioning from overweight to class 1 and 2 obesity, and OR 5·87 (5·23-6·59) and absolute risk (22% vs 5%) of transitioning from class 1 and 2 obesity to class 3 obesity. Other demographic factors were consistently less strongly associated with these transitions; for example, the OR of transitioning from normal weight to overweight or obesity in people living in the most socially deprived versus least deprived areas was 1·23 (1·18-1·27), for men versus women was 1·12 (1·08-1·16), and for Black individuals versus White individuals was 1·13 (1·04-1·24). We provide an open access online risk calculator, and present high-resolution obesity risk charts over a 1-year, 5-year, and 10-year follow-up period.

Interpretation: A radical shift in policy is required to focus on individuals at the highest risk of weight gain (ie, young adults aged 18-24 years) for individual-level and population-level prevention of obesity and its long-term consequences for health and health care.

Funding: The British Hearth Foundation, Health Data Research UK, the UK Medical Research Council, and the National Institute for Health Research.
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http://dx.doi.org/10.1016/S2213-8587(21)00207-2DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8440227PMC
October 2021

Mitochondrial DNA variants modulate N-formylmethionine, proteostasis and risk of late-onset human diseases.

Nat Med 2021 Sep 23;27(9):1564-1575. Epub 2021 Aug 23.

Human Genetics Department, Wellcome Sanger Institute (WT), Hinxton, UK.

Mitochondrial DNA (mtDNA) variants influence the risk of late-onset human diseases, but the reasons for this are poorly understood. Undertaking a hypothesis-free analysis of 5,689 blood-derived biomarkers with mtDNA variants in 16,220 healthy donors, here we show that variants defining mtDNA haplogroups Uk and H4 modulate the level of circulating N-formylmethionine (fMet), which initiates mitochondrial protein translation. In human cytoplasmic hybrid (cybrid) lines, fMet modulated both mitochondrial and cytosolic proteins on multiple levels, through transcription, post-translational modification and proteolysis by an N-degron pathway, abolishing known differences between mtDNA haplogroups. In a further 11,966 individuals, fMet levels contributed to all-cause mortality and the disease risk of several common cardiovascular disorders. Together, these findings indicate that fMet plays a key role in common age-related disease through pleiotropic effects on cell proteostasis.
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http://dx.doi.org/10.1038/s41591-021-01441-3DOI Listing
September 2021

Association of Cycling With All-Cause and Cardiovascular Disease Mortality Among Persons With Diabetes: The European Prospective Investigation Into Cancer and Nutrition (EPIC) Study.

JAMA Intern Med 2021 Sep;181(9):1196-1205

University of Southern Denmark, Odense, Denmark.

Importance: Premature death from all causes and cardiovascular disease (CVD) causes is higher among persons with diabetes.

Objective: To investigate the association between time spent cycling and all-cause and CVD mortality among persons with diabetes, as well as to evaluate the association between change in time spent cycling and risk of all-cause and CVD mortality.

Design, Setting, And Participants: This prospective cohort study included 7459 adults with diabetes from the European Prospective Investigation into Cancer and Nutrition study. Questionnaires regarding medical history, sociodemographic, and lifestyle information were administered in 10 Western European countries from 1992 through 2000 (baseline examination) and at a second examination 5 years after baseline. A total of 5423 participants with diabetes completed both examinations. The final updated primary analysis was conducted on November 13, 2020.

Exposures: The primary exposure was self-reported time spent cycling per week at the baseline examination. The secondary exposure was change in cycling status from baseline to the second examination.

Main Outcomes And Measures: The primary and secondary outcomes were all-cause and CVD mortality, respectively, adjusted for other physical activity modalities, diabetes duration, and sociodemographic and lifestyle factors.

Results: Of the 7459 adults with diabetes included in the analysis, the mean (SD) age was 55.9 (7.7) years, and 3924 (52.6%) were female. During 110 944 person-years of follow-up, 1673 deaths from all causes were registered. Compared with the reference group of people who reported no cycling at baseline (0 min/wk), the multivariable-adjusted hazard ratios for all-cause mortality were 0.78 (95% CI, 0.61-0.99), 0.76 (95% CI, 0.65-0.88), 0.68 (95% CI, 0.57-0.82), and 0.76 (95% CI, 0.63-0.91) for cycling 1 to 59, 60 to 149, 150 to 299, and 300 or more min/wk, respectively. In an analysis of change in time spent cycling with 57 802 person-years of follow-up, a total of 975 deaths from all causes were recorded. Compared with people who reported no cycling at both examinations, the multivariable-adjusted hazard ratios for all-cause mortality were 0.90 (95% CI, 0.71-1.14) in those who cycled and then stopped, 0.65 (95% CI, 0.46-0.92) in initial noncyclists who started cycling, and 0.65 (95% CI, 0.53-0.80) for people who reported cycling at both examinations. Similar results were observed for CVD mortality.

Conclusion And Relevance: In this cohort study, cycling was associated with lower all-cause and CVD mortality risk among people with diabetes independent of practicing other types of physical activity. Participants who took up cycling between the baseline and second examination had a considerably lower risk of both all-cause and CVD mortality compared with consistent noncyclists.
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http://dx.doi.org/10.1001/jamainternmed.2021.3836DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8290339PMC
September 2021

Sugar-Sweetened Beverage Consumption May Modify Associations Between Genetic Variants in the CHREBP (Carbohydrate Responsive Element Binding Protein) Locus and HDL-C (High-Density Lipoprotein Cholesterol) and Triglyceride Concentrations.

Circ Genom Precis Med 2021 Aug 16;14(4):e003288. Epub 2021 Jul 16.

Department of Clinical Epidemiology (R.L.G., D.O.M.-K., F.R.R., R.dM.), Leiden University Medical Center, the Netherlands.

Background: ChREBP (carbohydrate responsive element binding protein) is a transcription factor that responds to sugar consumption. Sugar-sweetened beverage (SSB) consumption and genetic variants in the locus have separately been linked to HDL-C (high-density lipoprotein cholesterol) and triglyceride concentrations. We hypothesized that SSB consumption would modify the association between genetic variants in the locus and dyslipidemia.

Methods: Data from 11 cohorts from the Cohorts for Heart and Aging Research in Genomic Epidemiology consortium (N=63 599) and the UK Biobank (N=59 220) were used to quantify associations of SSB consumption, genetic variants, and their interaction on HDL-C and triglyceride concentrations using linear regression models. A total of 1606 single nucleotide polymorphisms within or near were considered. SSB consumption was estimated from validated questionnaires, and participants were grouped by their estimated intake.

Results: In a meta-analysis, rs71556729 was significantly associated with higher HDL-C concentrations only among the highest SSB consumers (β, 2.12 [95% CI, 1.16-3.07] mg/dL per allele; <0.0001), but not significantly among the lowest SSB consumers (=0.81; <0.0001). Similar results were observed for 2 additional variants (rs35709627 and rs71556736). For triglyceride, rs55673514 was positively associated with triglyceride concentrations only among the highest SSB consumers (β, 0.06 [95% CI, 0.02-0.09] ln-mg/dL per allele, =0.001) but not the lowest SSB consumers (=0.84; =0.0005).

Conclusions: Our results identified genetic variants in the locus that may protect against SSB-associated reductions in HDL-C and other variants that may exacerbate SSB-associated increases in triglyceride concentrations. Registration: URL: https://www.clinicaltrials.gov; Unique identifier: NCT00005133, NCT00005121, NCT00005487, and NCT00000479.
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http://dx.doi.org/10.1161/CIRCGEN.120.003288DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8373451PMC
August 2021

Plasma concentrations of persistent organic pollutants and pancreatic cancer risk.

Int J Epidemiol 2021 Jul 14. Epub 2021 Jul 14.

Cancer Registry and Histopathology Department, "Civic-M.P. Arezzo" Hospital, ASP Ragusa, Ragusa, Italy.

Background: Findings and limitations of previous studies on persistent organic pollutants (POPs) and pancreatic cancer risk support conducting further research in prospective cohorts.

Methods: We conducted a prospective case-control study nested within the European Prospective Investigation into Cancer and Nutrition (EPIC) cohort. Participants were 513 pancreatic cancer cases and 1020 matched controls. Concentrations of 22 POPs were measured in plasma collected at baseline.

Results: Some associations were observed at higher concentrations of p, p'-DDT, trans-nonachlor, β-hexachlorocyclohexane and the sum of six organochlorine pesticides and of 16 POPs. The odds ratio (OR) for the upper quartile of trans-nonachlor was 1.55 (95% confidence interval 1.06-2.26; P for trend = 0.025). Associations were stronger in the groups predefined as most valid (participants having fasted >6 h, with microscopic diagnostic confirmation, normal weight, and never smokers), and as most relevant (follow-up ≥10 years). Among participants having fasted >6 h, the ORs were relevant for 10 of 11 exposures. Higher ORs were also observed among cases with microscopic confirmation than in cases with a clinical diagnosis, and among normal-weight participants than in the rest of participants. Among participants with a follow-up ≥10 years, estimates were higher than in participants with a shorter follow-up (for trans-nonachlor: OR = 2.14, 1.01 to 4.53, P for trend = 0.035). Overall, trans-nonachlor, three PCBs and the two sums of POPs were the exposures most clearly associated with pancreatic cancer risk.

Conclusions: Individually or in combination, most of the 22 POPs analysed did not or only moderately increased the risk of pancreatic cancer.
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http://dx.doi.org/10.1093/ije/dyab115DOI Listing
July 2021

The trans-ancestral genomic architecture of glycemic traits.

Nat Genet 2021 06 31;53(6):840-860. Epub 2021 May 31.

Department of Epidemiology, University of Groningen, University Medical Center Groningen, Groningen, the Netherlands.

Glycemic traits are used to diagnose and monitor type 2 diabetes and cardiometabolic health. To date, most genetic studies of glycemic traits have focused on individuals of European ancestry. Here we aggregated genome-wide association studies comprising up to 281,416 individuals without diabetes (30% non-European ancestry) for whom fasting glucose, 2-h glucose after an oral glucose challenge, glycated hemoglobin and fasting insulin data were available. Trans-ancestry and single-ancestry meta-analyses identified 242 loci (99 novel; P < 5 × 10), 80% of which had no significant evidence of between-ancestry heterogeneity. Analyses restricted to individuals of European ancestry with equivalent sample size would have led to 24 fewer new loci. Compared with single-ancestry analyses, equivalent-sized trans-ancestry fine-mapping reduced the number of estimated variants in 99% credible sets by a median of 37.5%. Genomic-feature, gene-expression and gene-set analyses revealed distinct biological signatures for each trait, highlighting different underlying biological pathways. Our results increase our understanding of diabetes pathophysiology by using trans-ancestry studies for improved power and resolution.
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http://dx.doi.org/10.1038/s41588-021-00852-9DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7610958PMC
June 2021

Comparative performance of lung cancer risk models to define lung screening eligibility in the United Kingdom.

Br J Cancer 2021 Jun 12;124(12):2026-2034. Epub 2021 Apr 12.

International Agency for Research on Cancer, Lyon, France.

Background: The National Health Service England (NHS) classifies individuals as eligible for lung cancer screening using two risk prediction models, PLCOm2012 and Liverpool Lung Project-v2 (LLPv2). However, no study has compared the performance of lung cancer risk models in the UK.

Methods: We analysed current and former smokers aged 40-80 years in the UK Biobank (N = 217,199), EPIC-UK (N = 30,813), and Generations Study (N = 25,777). We quantified model calibration (ratio of expected to observed cases, E/O) and discrimination (AUC).

Results: Risk discrimination in UK Biobank was best for the Lung Cancer Death Risk Assessment Tool (LCDRAT, AUC = 0.82, 95% CI = 0.81-0.84), followed by the LCRAT (AUC = 0.81, 95% CI = 0.79-0.82) and the Bach model (AUC = 0.80, 95% CI = 0.79-0.81). Results were similar in EPIC-UK and the Generations Study. All models overestimated risk in all cohorts, with E/O in UK Biobank ranging from 1.20 for LLPv3 (95% CI = 1.14-1.27) to 2.16 for LLPv2 (95% CI = 2.05-2.28). Overestimation increased with area-level socioeconomic status. In the combined cohorts, USPSTF 2013 criteria classified 50.7% of future cases as screening eligible. The LCDRAT and LCRAT identified 60.9%, followed by PLCOm2012 (58.3%), Bach (58.0%), LLPv3 (56.6%), and LLPv2 (53.7%).

Conclusion: In UK cohorts, the ability of risk prediction models to classify future lung cancer cases as eligible for screening was best for LCDRAT/LCRAT, very good for PLCOm2012, and lowest for LLPv2. Our results highlight the importance of validating prediction tools in specific countries.
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http://dx.doi.org/10.1038/s41416-021-01278-0DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8184952PMC
June 2021

n-3 Fatty Acid Biomarkers and Incident Type 2 Diabetes: An Individual Participant-Level Pooling Project of 20 Prospective Cohort Studies.

Diabetes Care 2021 05 3;44(5):1133-1142. Epub 2021 Mar 3.

Department of Epidemiology and Public Health, Graduate School of Medical Sciences, Kyushu University, Fukuoka, Japan.

Objective: Prospective associations between n-3 fatty acid biomarkers and type 2 diabetes (T2D) risk are not consistent in individual studies. We aimed to summarize the prospective associations of biomarkers of α-linolenic acid (ALA), eicosapentaenoic acid (EPA), docosapentaenoic acid (DPA), and docosahexaenoic acid (DHA) with T2D risk through an individual participant-level pooled analysis.

Research Design And Methods: For our analysis we incorporated data from a global consortium of 20 prospective studies from 14 countries. We included 65,147 participants who had blood measurements of ALA, EPA, DPA, or DHA and were free of diabetes at baseline. De novo harmonized analyses were performed in each cohort following a prespecified protocol, and cohort-specific associations were pooled using inverse variance-weighted meta-analysis.

Results: A total of 16,693 incident T2D cases were identified during follow-up (median follow-up ranging from 2.5 to 21.2 years). In pooled multivariable analysis, per interquintile range (difference between the 90th and 10th percentiles for each fatty acid), EPA, DPA, DHA, and their sum were associated with lower T2D incidence, with hazard ratios (HRs) and 95% CIs of 0.92 (0.87, 0.96), 0.79 (0.73, 0.85), 0.82 (0.76, 0.89), and 0.81 (0.75, 0.88), respectively (all < 0.001). ALA was not associated with T2D (HR 0.97 [95% CI 0.92, 1.02]) per interquintile range. Associations were robust across prespecified subgroups as well as in sensitivity analyses.

Conclusions: Higher circulating biomarkers of seafood-derived n-3 fatty acids, including EPA, DPA, DHA, and their sum, were associated with lower risk of T2D in a global consortium of prospective studies. The biomarker of plant-derived ALA was not significantly associated with T2D risk.
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http://dx.doi.org/10.2337/dc20-2426DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8132316PMC
May 2021

Appetite disinhibition rather than hunger explains genetic effects on adult BMI trajectory.

Int J Obes (Lond) 2021 04 14;45(4):758-765. Epub 2021 Jan 14.

Institute of Epidemiology and Health Care, University College London, London, UK.

Background/objectives: The mediating role of eating behaviors in genetic susceptibility to weight gain during mid-adult life is not fully understood. This longitudinal study aims to help us understand contributions of genetic susceptibility and appetite to weight gain.

Subjects/methods: We followed the body-mass index (BMI) trajectories of 2464 adults from 45 to 65 years of age by measuring weight and height on four occasions at 5-year intervals. Genetic risk of obesity (gene risk score: GRS) was ascertained, comprising 92 BMI-associated single-nucleotide polymorphisms and split at a median (=high and low risk). At the baseline, the Eating Inventory was used to assess appetite-related traits of 'disinhibition', indicative of opportunistic eating or overeating and 'hunger' which is susceptibility to/ability to cope with the sensation of hunger. Roles of the GRS and two appetite-related scores for BMI trajectories were examined using a mixed model adjusted for the cohort effect and sex.

Results: Disinhibition was associated with higher BMI (β = 2.96; 95% CI: 2.66-3.25 kg/m), and accounted for 34% of the genetically-linked BMI difference at age 45. Hunger was also associated with higher BMI (β = 1.20; 0.82-1.59 kg/m) during mid-life and slightly steeper weight gain, but did not attenuate the effect of disinhibition.

Conclusions: Appetite disinhibition is most likely to be a defining characteristic of genetic susceptibility to obesity. High levels of appetite disinhibition, rather than hunger, may underlie genetic vulnerability to obesogenic environments in two-thirds of the population of European ancestry.
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http://dx.doi.org/10.1038/s41366-020-00735-9DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8005371PMC
April 2021

Longitudinal Trends in Childhood Insulin Levels and Body Mass Index and Associations With Risks of Psychosis and Depression in Young Adults.

JAMA Psychiatry 2021 04;78(4):416-425

Department of Psychiatry, University of Cambridge School of Clinical Medicine, Cambridge, United Kingdom.

Importance: Cardiometabolic disorders often occur concomitantly with psychosis and depression, contribute to high mortality rates, and are detectable from the onset of the psychiatric disorders. However, it is unclear whether longitudinal trends in cardiometabolic traits from childhood are associated with risks for adult psychosis and depression.

Objective: To examine whether specific developmental trajectories of fasting insulin (FI) levels and body mass index (BMI) from early childhood were longitudinally associated with psychosis and depression in young adults.

Design, Setting, And Participants: A cohort study from the Avon Longitudinal Study of Parents and Children, a prospective study including a population-representative British cohort of 14 975 individuals, was conducted using data from participants aged 1 to 24 years. Body mass index and FI level data were used for growth mixture modeling to delineate developmental trajectories, and associations with psychosis and depression were assessed. The study was conducted between July 15, 2019, and March 24, 2020.

Exposures: Fasting insulin levels were measured at 9, 15, 18, and 24 years, and BMI was measured at 1, 2, 3, 4, 7, 9, 10, 11, 12, 15, 18, and 24 years. Data on sex, race/ethnicity, paternal social class, childhood emotional and behavioral problems, and cumulative scores of sleep problems, average calorie intake, physical activity, smoking, and alcohol and substance use in childhood and adolescence were examined as potential confounders.

Main Outcomes And Measures: Psychosis risk (definite psychotic experiences, psychotic disorder, at-risk mental state status, and negative symptom score) depression risk (measured using the computerized Clinical Interview Schedule-Revised) were assessed at 24 years.

Results: From data available on 5790 participants (3132 [54.1%] female) for FI levels and data available on 10 463 participants (5336 [51.0%] female) for BMI, 3 distinct trajectories for FI levels and 5 distinct trajectories for BMI were noted, all of which were differentiated by mid-childhood. The persistently high FI level trajectory was associated with a psychosis at-risk mental state (adjusted odds ratio [aOR], 5.01; 95% CI, 1.76-13.19) and psychotic disorder (aOR, 3.22; 95% CI, 1.29-8.02) but not depression (aOR, 1.38; 95% CI, 0.75-2.54). A puberty-onset major increase in BMI was associated with depression (aOR, 4.46; 95% CI, 2.38-9.87) but not psychosis (aOR, 1.98; 95% CI, 0.56-7.79).

Conclusions And Relevance: The cardiometabolic comorbidity of psychosis and depression may have distinct, disorder-specific early-life origins. Disrupted insulin sensitivity could be a shared risk factor for comorbid cardiometabolic disorders and psychosis. A puberty-onset major increase in BMI could be a risk factor or risk indicator for adult depression. These markers may represent targets for prevention and treatment of cardiometabolic disorders in individuals with psychosis and depression.
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http://dx.doi.org/10.1001/jamapsychiatry.2020.4180DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7807390PMC
April 2021

Correlates of change in accelerometer-assessed total sedentary time and prolonged sedentary bouts among older English adults: results from five-year follow-up in the EPIC-Norfolk cohort.

Aging (Albany NY) 2021 01 11;13(1):134-149. Epub 2021 Jan 11.

MRC Epidemiology Unit, University of Cambridge, School of Clinical Medicine, Cambridge, UK.

Background: Development of effective strategies to reduce sedentary time among older adults necessitates understanding of its determinants but longitudinal studies of this utilising objective measures are scarce.

Methods: Among 1536 older adults (≥60 years) in the EPIC-Norfolk study, sedentary time was assessed for seven days at two time-points using accelerometers. We assessed associations of change in total and prolonged bouts of sedentary time (≥ 30 minutes) with change in demographic and behavioural factors using multi-level regression.

Results: Over follow-up (5.3±1.9 years), greater increases in total sedentary time were associated with older age, being male, higher rate of increase in BMI, lower rate of increase in gardening (0.5 min/day/yr greater sedentary time per hour/week/yr less gardening, 95% CI 0.1, 1.0), a lower rate of increase in walking (0.2 min/day/yr greater sedentary time per hour/week/yr less walking, 95% CI 0.1, 0.3) and a higher rate of increase in television viewing. Correlates of change in prolonged sedentary bouts were similar.

Conclusion: Individuals in specific sub-groups (older, male, higher BMI) and who differentially participate in certain behaviours (less gardening, less walking and more television viewing) but not others increase their sedentary time at a higher rate than others; utilising this information could inform successful intervention content and targeting.
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http://dx.doi.org/10.18632/aging.202497DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7835006PMC
January 2021

Replacement of Red and Processed Meat With Other Food Sources of Protein and the Risk of Type 2 Diabetes in European Populations: The EPIC-InterAct Study.

Diabetes Care 2020 11 31;43(11):2660-2667. Epub 2020 Aug 31.

CIBER de Epidemiología y Salud Pública (CIBERESP), Madrid, Spain.

Objective: There is sparse evidence for the association of suitable food substitutions for red and processed meat on the risk of type 2 diabetes. We modeled the association between replacing red and processed meat with other protein sources and the risk of type 2 diabetes and estimated its population impact.

Research Design And Methods: The European Prospective Investigation into Cancer (EPIC)-InterAct case cohort included 11,741 individuals with type 2 diabetes and a subcohort of 15,450 participants in eight countries. We modeled the replacement of self-reported red and processed meat with poultry, fish, eggs, legumes, cheese, cereals, yogurt, milk, and nuts. Country-specific hazard ratios (HRs) for incident type 2 diabetes were estimated by Prentice-weighted Cox regression and pooled using random-effects meta-analysis.

Results: There was a lower hazard for type 2 diabetes for the modeled replacement of red and processed meat (50 g/day) with cheese (HR 0.90, 95% CI 0.83-0.97) (30 g/day), yogurt (0.90, 0.86-0.95) (70 g/day), nuts (0.90, 0.84-0.96) (10 g/day), or cereals (0.92, 0.88-0.96) (30 g/day) but not for replacements with poultry, fish, eggs, legumes, or milk. If a causal association is assumed, replacing red and processed meat with cheese, yogurt, or nuts could prevent 8.8%, 8.3%, or 7.5%, respectively, of new cases of type 2 diabetes.

Conclusions: Replacement of red and processed meat with cheese, yogurt, nuts, or cereals was associated with a lower rate of type 2 diabetes. Substituting red and processed meat by other protein sources may contribute to the prevention of incident type 2 diabetes in European populations.
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http://dx.doi.org/10.2337/dc20-1038DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7576430PMC
November 2020

Wearable-device-measured physical activity and future health risk.

Nat Med 2020 09 17;26(9):1385-1391. Epub 2020 Aug 17.

MRC Epidemiology Unit, Institute of Metabolic Science, University of Cambridge, Cambridge, UK.

Use of wearable devices that monitor physical activity is projected to increase more than fivefold per half-decade. We investigated how device-based physical activity energy expenditure (PAEE) and different intensity profiles were associated with all-cause mortality. We used a network harmonization approach to map dominant-wrist acceleration to PAEE in 96,476 UK Biobank participants (mean age 62 years, 56% female). We also calculated the fraction of PAEE accumulated from moderate-to-vigorous-intensity physical activity (MVPA). Over the median 3.1-year follow-up period (302,526 person-years), 732 deaths were recorded. Higher PAEE was associated with a lower hazard of all-cause mortality for a constant fraction of MVPA (for example, 21% (95% confidence interval 4-35%) lower hazard for 20 versus 15 kJ kg d PAEE with 10% from MVPA). Similarly, a higher MVPA fraction was associated with a lower hazard when PAEE remained constant (for example, 30% (8-47%) lower hazard when 20% versus 10% of a fixed 15 kJ kg d PAEE volume was from MVPA). Our results show that higher volumes of PAEE are associated with reduced mortality rates, and achieving the same volume through higher-intensity activity is associated with greater reductions than through lower-intensity activity. The linkage of device-measured activity to energy expenditure creates a framework for using wearables for personalized prevention.
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http://dx.doi.org/10.1038/s41591-020-1012-3DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7116559PMC
September 2020

Incorporating multiple sets of eQTL weights into gene-by-environment interaction analysis identifies novel susceptibility loci for pancreatic cancer.

Genet Epidemiol 2020 11 10;44(8):880-892. Epub 2020 Aug 10.

Department of Biostatistics, The University of Texas MD Anderson Cancer Center, Houston, Texas.

It is of great scientific interest to identify interactions between genetic variants and environmental exposures that may modify the risk of complex diseases. However, larger sample sizes are usually required to detect gene-by-environment interaction (G × E) than required to detect genetic main association effects. To boost the statistical power and improve the understanding of the underlying molecular mechanisms, we incorporate functional genomics information, specifically, expression quantitative trait loci (eQTLs), into a data-adaptive G × E test, called aGEw. This test adaptively chooses the best eQTL weights from multiple tissues and provides an extra layer of weighting at the genetic variant level. Extensive simulations show that the aGEw test can control the Type 1 error rate, and the power is resilient to the inclusion of neutral variants and noninformative external weights. We applied the proposed aGEw test to the Pancreatic Cancer Case-Control Consortium (discovery cohort of 3,585 cases and 3,482 controls) and the PanScan II genome-wide association study data (replication cohort of 2,021 cases and 2,105 controls) with smoking as the exposure of interest. Two novel putative smoking-related pancreatic cancer susceptibility genes, TRIP10 and KDM3A, were identified. The aGEw test is implemented in an R package aGE.
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http://dx.doi.org/10.1002/gepi.22348DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7657998PMC
November 2020

Metabolic perturbations prior to hepatocellular carcinoma diagnosis: Findings from a prospective observational cohort study.

Int J Cancer 2021 02 28;148(3):609-625. Epub 2020 Aug 28.

Public Health Directorate, Asturias, Spain.

Hepatocellular carcinoma (HCC) development entails changes in liver metabolism. Current knowledge on metabolic perturbations in HCC is derived mostly from case-control designs, with sparse information from prospective cohorts. Our objective was to apply comprehensive metabolite profiling to detect metabolites whose serum concentrations are associated with HCC development, using biological samples from within the prospective European Prospective Investigation into Cancer and Nutrition (EPIC) cohort (>520 000 participants), where we identified 129 HCC cases matched 1:1 to controls. We conducted high-resolution untargeted liquid chromatography-mass spectrometry-based metabolomics on serum samples collected at recruitment prior to cancer diagnosis. Multivariable conditional logistic regression was applied controlling for dietary habits, alcohol consumption, smoking, body size, hepatitis infection and liver dysfunction. Corrections for multiple comparisons were applied. Of 9206 molecular features detected, 220 discriminated HCC cases from controls. Detailed feature annotation revealed 92 metabolites associated with HCC risk, of which 14 were unambiguously identified using pure reference standards. Positive HCC-risk associations were observed for N1-acetylspermidine, isatin, p-hydroxyphenyllactic acid, tyrosine, sphingosine, l,l-cyclo(leucylprolyl), glycochenodeoxycholic acid, glycocholic acid and 7-methylguanine. Inverse risk associations were observed for retinol, dehydroepiandrosterone sulfate, glycerophosphocholine, γ-carboxyethyl hydroxychroman and creatine. Discernible differences for these metabolites were observed between cases and controls up to 10 years prior to diagnosis. Our observations highlight the diversity of metabolic perturbations involved in HCC development and replicate previous observations (metabolism of bile acids, amino acids and phospholipids) made in Asian and Scandinavian populations. These findings emphasize the role of metabolic pathways associated with steroid metabolism and immunity and specific dietary and environmental exposures in HCC development.
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http://dx.doi.org/10.1002/ijc.33236DOI Listing
February 2021

Cross-sectional and prospective relationship between occupational and leisure-time inactivity and cognitive function in an ageing population: the European Prospective Investigation into Cancer and Nutrition in Norfolk (EPIC-Norfolk) study.

Int J Epidemiol 2020 08;49(4):1338-1352

Department of Public Health and Primary Care, Institute of Public Health, University of Cambridge, Cambridge, UK.

Background: The current evidence for higher physical activity and better cognitive function and lower risk of dementia is strong but not conclusive. More robust evidence is needed to inform public-health policy. We provide further insight into discrepancies observed across studies, reporting on habitual inactivity including that during work.

Methods: We examined cross-sectional and prospective relationships of physical inactivity during leisure and occupation time, with cognitive performance using a validated physical-activity index in a cohort of 8585 men and women aged 40-79 years at baseline (1993-1997) for different domains using a range of cognitive measures. Cognitive testing was conducted between 2006 and 2011 (including a pilot phase 2004-2006). Associations were examined using multinomial logistic-regression adjusting for socio-demographic and health variables as well total habitual physical activity.

Results: Inactivity during work was inversely associated with poor cognitive performance (bottom 10th percentile of a composite cognition score): odds ratio (OR) = 0.68 [95% confidence interval (CI) 0.54, 0.86], P = 0.001. Results were similar cross-sectionally: OR = 0.65 (95% CI 0.45, 0.93), P = 0.02. Manual workers had increased risk of poor performance compared with those with an occupation classified as inactive. Inactivity during leisure time was associated with increased risk of poor performance in the cross-sectional analyses only.

Conclusions: The relationship between inactivity and cognition is strongly confounded by education, social class and occupation. Physical activity during leisure may be protective for cognition, but work-related physical activity is not protective. A greater understanding of the mechanisms and confounding underlying these paradoxical findings is needed.
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http://dx.doi.org/10.1093/ije/dyaa067DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7660150PMC
August 2020

Fatty acids in the de novo lipogenesis pathway and incidence of type 2 diabetes: A pooled analysis of prospective cohort studies.

PLoS Med 2020 06 12;17(6):e1003102. Epub 2020 Jun 12.

MRC Epidemiology Unit, University of Cambridge, Cambridge, United Kingdom.

Background: De novo lipogenesis (DNL) is the primary metabolic pathway synthesizing fatty acids from carbohydrates, protein, or alcohol. Our aim was to examine associations of in vivo levels of selected fatty acids (16:0, 16:1n7, 18:0, 18:1n9) in DNL with incidence of type 2 diabetes (T2D).

Methods And Findings: Seventeen cohorts from 12 countries (7 from Europe, 7 from the United States, 1 from Australia, 1 from Taiwan; baseline years = 1970-1973 to 2006-2010) conducted harmonized individual-level analyses of associations of DNL-related fatty acids with incident T2D. In total, we evaluated 65,225 participants (mean ages = 52.3-75.5 years; % women = 20.4%-62.3% in 12 cohorts recruiting both sexes) and 15,383 incident cases of T2D over the 9-year follow-up on average. Cohort-specific association of each of 16:0, 16:1n7, 18:0, and 18:1n9 with incident T2D was estimated, adjusted for demographic factors, socioeconomic characteristics, alcohol, smoking, physical activity, dyslipidemia, hypertension, menopausal status, and adiposity. Cohort-specific associations were meta-analyzed with an inverse-variance-weighted approach. Each of the 4 fatty acids positively related to incident T2D. Relative risks (RRs) per cohort-specific range between midpoints of the top and bottom quintiles of fatty acid concentrations were 1.53 (1.41-1.66; p < 0.001) for 16:0, 1.40 (1.33-1.48; p < 0.001) for 16:1n-7, 1.14 (1.05-1.22; p = 0.001) for 18:0, and 1.16 (1.07-1.25; p < 0.001) for 18:1n9. Heterogeneity was seen across cohorts (I2 = 51.1%-73.1% for each fatty acid) but not explained by lipid fractions and global geographical regions. Further adjusted for triglycerides (and 16:0 when appropriate) to evaluate associations independent of overall DNL, the associations remained significant for 16:0, 16:1n7, and 18:0 but were attenuated for 18:1n9 (RR = 1.03, 95% confidence interval (CI) = 0.94-1.13). These findings had limitations in potential reverse causation and residual confounding by imprecisely measured or unmeasured factors.

Conclusions: Concentrations of fatty acids in the DNL were positively associated with T2D incidence. Our findings support further work to investigate a possible role of DNL and individual fatty acids in the development of T2D.
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http://dx.doi.org/10.1371/journal.pmed.1003102DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7292352PMC
June 2020

Genomic analysis of diet composition finds novel loci and associations with health and lifestyle.

Mol Psychiatry 2021 Jun 11;26(6):2056-2069. Epub 2020 May 11.

Department of Endocrinology, University of Groningen, University Medical Center Groningen, Hanzeplein 1, 9713 GZ, Groningen, The Netherlands.

We conducted genome-wide association studies (GWAS) of relative intake from the macronutrients fat, protein, carbohydrates, and sugar in over 235,000 individuals of European ancestries. We identified 21 unique, approximately independent lead SNPs. Fourteen lead SNPs are uniquely associated with one macronutrient at genome-wide significance (P < 5 × 10), while five of the 21 lead SNPs reach suggestive significance (P < 1 × 10) for at least one other macronutrient. While the phenotypes are genetically correlated, each phenotype carries a partially unique genetic architecture. Relative protein intake exhibits the strongest relationships with poor health, including positive genetic associations with obesity, type 2 diabetes, and heart disease (r ≈ 0.15-0.5). In contrast, relative carbohydrate and sugar intake have negative genetic correlations with waist circumference, waist-hip ratio, and neighborhood deprivation (|r| ≈ 0.1-0.3) and positive genetic correlations with physical activity (r ≈ 0.1 and 0.2). Relative fat intake has no consistent pattern of genetic correlations with poor health but has a negative genetic correlation with educational attainment (r ≈-0.1). Although our analyses do not allow us to draw causal conclusions, we find no evidence of negative health consequences associated with relative carbohydrate, sugar, or fat intake. However, our results are consistent with the hypothesis that relative protein intake plays a role in the etiology of metabolic dysfunction.
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http://dx.doi.org/10.1038/s41380-020-0697-5DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7767645PMC
June 2021

Meta-analysis of 542,934 subjects of European ancestry identifies new genes and mechanisms predisposing to refractive error and myopia.

Nat Genet 2020 04 30;52(4):401-407. Epub 2020 Mar 30.

Section of Ophthalmology, School of Life Course Sciences, King's College London, London, UK.

Refractive errors, in particular myopia, are a leading cause of morbidity and disability worldwide. Genetic investigation can improve understanding of the molecular mechanisms that underlie abnormal eye development and impaired vision. We conducted a meta-analysis of genome-wide association studies (GWAS) that involved 542,934 European participants and identified 336 novel genetic loci associated with refractive error. Collectively, all associated genetic variants explain 18.4% of heritability and improve the accuracy of myopia prediction (area under the curve (AUC) = 0.75). Our results suggest that refractive error is genetically heterogeneous, driven by genes that participate in the development of every anatomical component of the eye. In addition, our analyses suggest that genetic factors controlling circadian rhythm and pigmentation are also involved in the development of myopia and refractive error. These results may enable the prediction of refractive error and the development of personalized myopia prevention strategies in the future.
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http://dx.doi.org/10.1038/s41588-020-0599-0DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7145443PMC
April 2020

Descriptive epidemiology of energy expenditure in the UK: findings from the National Diet and Nutrition Survey 2008-15.

Int J Epidemiol 2020 06;49(3):1007-1021

MRC Epidemiology Unit, University of Cambridge, Cambridge, UK.

Background: Little is known about population levels of energy expenditure, as national surveillance systems typically employ only crude measures. The National Diet and Nutrition Survey (NDNS) in the UK measured energy expenditure in a 10% subsample by gold-standard doubly labelled water (DLW).

Methods: DLW-subsample participants from the NDNS (383 males, 387 females) aged 4-91 years were recruited between 2008 and 2015 (rolling programme). Height and weight were measured and body-fat percentage estimated by deuterium dilution.

Results: Absolute total energy expenditure (TEE) increased steadily throughout childhood, ranging from 6.2 and 7.2 MJ/day in 4- to 7-year-olds to 9.7 and 11.7 MJ/day for 14- to 16-year-old girls and boys, respectively. TEE peaked in 17- to 27-year-old women (10.7 MJ/day) and 28- to 43-year-old men (14.4 MJ/day), before decreasing gradually in old age. Physical-activity energy expenditure (PAEE) declined steadily with age from childhood (87 kJ/day/kg in 4- to 7-year-olds) through to old age (38 kJ/day/kg in 71- to 91-year-olds). No differences were observed by time, region and macronutrient composition. Body-fat percentage was strongly inversely associated with PAEE throughout life, irrespective of expressing PAEE relative to body mass or fat-free mass. Compared with females with <30% body fat, females with >40% recorded 29 kJ/day/kg body mass and 18 kJ/day/kg fat-free mass less PAEE in analyses adjusted for age, geographical region and time of assessment. Similarly, compared with males with <25% body fat, males with >35% recorded 26 kJ/day/kg body mass and 10 kJ/day/kg fat-free mass less PAEE.

Conclusions: This first nationally representative study reports levels of human-energy expenditure as measured by gold-standard methodology; values may serve as a reference for other population studies. Age, sex and body composition are the main determinants of energy expenditure. Key Messages This is the first nationally representative study of human energy expenditure, covering the UK in the period 2008-2015. Total energy expenditure (MJ/day) increases steadily with age throughout childhood and adolescence, peaks in the 3rd decade of life in women and 4th decade of life in men, before decreasing gradually in old age. Physical activity energy expenditure (kJ/day/kg or kJ/day/kg fat-free mass) declines steadily with age from childhood to old age, more steeply so in males. Body-fat percentage is strongly inversely associated with physical activity energy expenditure. We found little evidence that energy expenditure varied by geographical region, over time, or by dietary macronutrient composition.
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http://dx.doi.org/10.1093/ije/dyaa005DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7394951PMC
June 2020

Lifestyle factors and risk of multimorbidity of cancer and cardiometabolic diseases: a multinational cohort study.

BMC Med 2020 01 10;18(1). Epub 2020 Jan 10.

Cancer Epidemiology Unit, Nuffield Department of Population Health, University of Oxford, Oxford, UK.

Background: Although lifestyle factors have been studied in relation to individual non-communicable diseases (NCDs), their association with development of a subsequent NCD, defined as multimorbidity, has been scarcely investigated. The aim of this study was to investigate associations between five lifestyle factors and incident multimorbidity of cancer and cardiometabolic diseases.

Methods: In this prospective cohort study, 291,778 participants (64% women) from seven European countries, mostly aged 43 to 58 years and free of cancer, cardiovascular disease (CVD), and type 2 diabetes (T2D) at recruitment, were included. Incident multimorbidity of cancer and cardiometabolic diseases was defined as developing subsequently two diseases including first cancer at any site, CVD, and T2D in an individual. Multi-state modelling based on Cox regression was used to compute hazard ratios (HR) and 95% confidence intervals (95% CI) of developing cancer, CVD, or T2D, and subsequent transitions to multimorbidity, in relation to body mass index (BMI), smoking status, alcohol intake, physical activity, adherence to the Mediterranean diet, and their combination as a healthy lifestyle index (HLI) score. Cumulative incidence functions (CIFs) were estimated to compute 10-year absolute risks for transitions from healthy to cancer at any site, CVD (both fatal and non-fatal), or T2D, and to subsequent multimorbidity after each of the three NCDs.

Results: During a median follow-up of 11 years, 1910 men and 1334 women developed multimorbidity of cancer and cardiometabolic diseases. A higher HLI, reflecting healthy lifestyles, was strongly inversely associated with multimorbidity, with hazard ratios per 3-unit increment of 0.75 (95% CI, 0.71 to 0.81), 0.84 (0.79 to 0.90), and 0.82 (0.77 to 0.88) after cancer, CVD, and T2D, respectively. After T2D, the 10-year absolute risks of multimorbidity were 40% and 25% for men and women, respectively, with unhealthy lifestyle, and 30% and 18% for men and women with healthy lifestyles.

Conclusion: Pre-diagnostic healthy lifestyle behaviours were strongly inversely associated with the risk of cancer and cardiometabolic diseases, and with the prognosis of these diseases by reducing risk of multimorbidity.
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http://dx.doi.org/10.1186/s12916-019-1474-7DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6953215PMC
January 2020

Descriptive epidemiology of physical activity energy expenditure in UK adults (The Fenland study).

Int J Behav Nutr Phys Act 2019 12 9;16(1):126. Epub 2019 Dec 9.

MRC Epidemiology Unit, University of Cambridge, School of Clinical Medicine, Institute of Metabolic Science, Cambridge Biomedical Campus, Box 285, Cambridge, CB2 0QQ, UK.

Background: Physical activity (PA) plays a role in the prevention of a range of diseases including obesity and cardiometabolic disorders. Large population-based descriptive studies of PA, incorporating precise measurement, are needed to understand the relative burden of insufficient PA levels and to inform the tailoring of interventions. Combined heart and movement sensing enables the study of physical activity energy expenditure (PAEE) and intensity distribution. We aimed to describe the sociodemographic correlates of PAEE and moderate-to-vigorous physical activity (MVPA) in UK adults.

Methods: The Fenland study is a population-based cohort study of 12,435 adults aged 29-64 years-old in Cambridgeshire, UK. Following individual calibration (treadmill), participants wore a combined heart rate and movement sensor continuously for 6 days in free-living, from which we derived PAEE (kJ•day•kg) and time in MVPA (> 3 & > 4 METs) in bouts greater than 1 min and 10 min. Socio-demographic information was self-reported. Stratum-specific summary statistics and multivariable analyses were performed.

Results: Women accumulated a mean (sd) 50(20) kJ•day•kg of PAEE, and 83(67) and 33(39) minutes•day of 1-min bouted and 10-min bouted MVPA respectively. By contrast, men recorded 59(23) kJ•day•kg, 124(84) and 60(58) minutes•day. Age and BMI were also important correlates of PA. Association with age was inverse in both sexes, more strongly so for PAEE than MVPA. Obese individuals accumulated less PA than their normal-weight counterparts, whether considering PAEE or allometrically-scaled PAEE (- 10 kJ•day•kg or - 15 kJ•day•kg in men). Higher income and manual work were associated with higher PA; manual workers recorded 13-16 kJ•kg•day more PAEE than sedentary counterparts. Overall, 86% of women and 96% of men accumulated a daily average of MVPA (> 3 METs) corresponding to 150 min per week. These values were 49 and 74% if only considering bouts > 10 min (15 and 31% for > 4 METs).

Conclusions: PA varied by age, sex and BMI, and was higher in manual workers and those with higher incomes. Light physical activity was the main driver of PAEE; a component of PA that is currently not quantified as a target in UK guidelines.
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http://dx.doi.org/10.1186/s12966-019-0882-6DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6902569PMC
December 2019

Functional Screening of Candidate Causal Genes for Insulin Resistance in Human Preadipocytes and Adipocytes.

Circ Res 2020 01 19;126(3):330-346. Epub 2019 Nov 19.

From the Beth Israel Deaconess Medical Center, Cardiovascular Institute, Harvard Medical School, Boston, MA (Z.C., H.Y., X.S., M.F., T.B.M., M.D.B., R.E.G, C.A.C.).

Genome-wide association studies have identified genetic loci associated with insulin resistance (IR) but pinpointing the causal genes of a risk locus has been challenging. To identify candidate causal genes for IR, we screened regional and biologically plausible genes (16 in total) near the top 10 IR-loci in risk-relevant cell types, namely preadipocytes and adipocytes. We generated 16 human Simpson-Golabi-Behmel syndrome preadipocyte knockout lines each with a single IR-gene knocked out by lentivirus-mediated CRISPR (clustered regularly interspaced short palindromic repeats)/Cas9 system. We evaluated each gene knockout by screening IR-relevant phenotypes in the 3 insulin-sensitizing mechanisms, including adipogenesis, lipid metabolism, and insulin signaling. We performed genetic analyses using data on the genotype-tissue expression portal expression quantitative trait loci database and accelerating medicines partnership type 2 diabetes mellitus Knowledge Portal to evaluate whether candidate genes prioritized by our in vitro studies were expression quantitative trait loci genes in human subcutaneous adipose tissue, and whether expression of these genes is associated with risk of IR, type 2 diabetes mellitus, and cardiovascular diseases. We further validated the functions of 3 new adipose IR genes by overexpression-based phenotypic rescue in the Simpson-Golabi-Behmel syndrome preadipocyte knockout lines. Twelve genes, , , , , , , , , , , and , showed diverse phenotypes in the 3 insulin-sensitizing mechanisms, and the first 7 of these genes could affect all the 3 mechanisms. Five out of 6 expression quantitative trait loci genes are among the top candidate causal genes and the abnormal expression levels of these genes (, , , , and ) in human subcutaneous adipose tissue could be associated with increased risk of IR, type 2 diabetes mellitus, and cardiovascular disease. Phenotypic rescue by overexpression of the candidate causal genes (, , and ) in the Simpson-Golabi-Behmel syndrome preadipocyte knockout lines confirmed their function in adipose IR. Twelve genes showed diverse phenotypes indicating differential roles in insulin sensitization, suggesting mechanisms bridging the association of their genomic loci with IR. We prioritized , , , , , and as top candidate genes. Our work points to novel roles for , , and in adipose tissue, with consequences for cardiometabolic diseases.
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http://dx.doi.org/10.1161/CIRCRESAHA.119.315246DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7115834PMC
January 2020

Early Outcomes From the English National Health Service Diabetes Prevention Programme.

Diabetes Care 2020 01 12;43(1):152-160. Epub 2019 Nov 12.

Public Health England, London, U.K.

Objective: To assess weight and HbA changes in the Healthier You: National Health Service Diabetes Prevention Programme (NHS DPP), the largest DPP globally to achieve universal population coverage.

Research Design And Methods: A service evaluation assessed intervention effectiveness for adults with nondiabetic hyperglycemia (HbA 42-47 mmol/mol [6.0-6.4%] or fasting plasma glucose 5.5-6.9 mmol/L) between program launch in June 2016 and December 2018, using prospectively collected, national service-level data in England.

Results: By December 2018, 324,699 people had been referred, 152,294 had attended the initial assessment, and 96,442 had attended at least 1 of 13 group-based intervention sessions. Allowing sufficient time to elapse, 53% attended an initial assessment, 36% attended at least one group-based session, and 19% completed the intervention (attended >60% of sessions). Of the 32,665 who attended at least one intervention session and had sufficient time to finish, 17,252 (53%) completed: intention-to-treat analyses demonstrated a mean weight loss of 2.3 kg (95% CI 2.2, 2.3) and an HbA reduction of 1.26 mmol/mol (1.20, 1.31) (0.12% [0.11, 0.12]); completer analysis demonstrated a mean weight loss of 3.3 kg (3.2, 3.4) and an HbA reduction of 2.04 mmol/mol (1.96, 2.12) (0.19% [0.18, 0.19]). Younger age, female sex, Asian and black ethnicity, lower socioeconomic status, and normal baseline BMI were associated with less weight loss. Older age, female sex, black ethnicity, lower socioeconomic status, and baseline overweight and obesity were associated with a smaller HbA reduction.

Conclusions: Reductions in weight and HbA compare favorably with those reported in recent meta-analyses of pragmatic studies and suggest likely future reductions in participant type 2 diabetes incidence.
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http://dx.doi.org/10.2337/dc19-1425DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7115827PMC
January 2020

Do older English adults exhibit day-to-day compensation in sedentary time and in prolonged sedentary bouts? An EPIC-Norfolk cohort analysis.

PLoS One 2019 25;14(10):e0224225. Epub 2019 Oct 25.

MRC Epidemiology Unit, University of Cambridge, School of Clinical Medicine, Cambridge, United Kingdom.

Introduction: Compensatory behaviours may be one of the reasons for the limited success of sedentary time interventions in older adults, but this possibility remains unexplored. Activity compensation is the idea that if we change activity levels at one time we compensate for them at a later time to maintain a set point. We aimed to assess, among adults aged ≥60 years, whether sedentary time and time spent in prolonged sedentary bouts (≥30 mins) on one day were associated with sedentary time and time spent in prolonged sedentary bouts (≥30 mins) on the following day. We also sought to determine whether these associations varied by sociodemographic and comorbid factors.

Methods: Sedentary time was assessed for seven days using hip-worn accelerometers (ActiGraph GT1M) for 3459 adults who participated in the EPIC-Norfolk Study between 2004 and 2011. We assessed day-to-day associations in total and prolonged bouts of sedentary time using multi-level regressions. We included interaction terms to determine whether associations varied by age, sex, smoking, body mass index, social class, retirement, education and comorbid factors (stroke, diabetes, myocardial infarction and cancer).

Results: Participants (mean age = 70.3, SD = 6.8 years) accumulated 540 sedentary mins/day (SD = 80.1). On any given day, every 60 minutes spent in sedentary time was associated with 9.9 extra sedentary minutes on the following day (95% CI 9.0, 10.2). This association was greater in non-retired compared to retired participants (non-retired 2.57 extra minutes, p = 0.024) and in current compared to former and never-smokers (5.26 extra mins for current vs former; 5.52 extra mins for current vs never, p = 0.023 and 0.017, respectively). On any given day, every 60 minutes spent in prolonged bouts was associated with 7.8 extra minutes in these bouts the following day (95% CI 7.6, 8.4). This association was greater in older individuals (0.18 extra minutes/year of age, 95% CI 0.061, 0.29), and for retired versus non-retired (retired 2.74 extra minutes, 95% CI 0.21, 5.74).

Conclusion: Older adults did not display day-to-day compensation. Instead, individuals demonstrate a large stable component of day-to-day time spent sedentary and in prolonged bouts with a small but important capacity for positive variation. Therefore older adults appear to be largely habitual in their sedentary behaviour. Strategies to augment these patterns may be possible, given they may differ by age, smoking, and working status.
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http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0224225PLOS
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6814223PMC
March 2020

Impact of follow-up time and analytical approaches to account for reverse causality on the association between physical activity and health outcomes in UK Biobank.

Int J Epidemiol 2020 02;49(1):162-172

MRC Epidemiology Unit, Institute of Metabolic Science, University of Cambridge, Cambridge, UK.

Background: The advent of very large cohort studies (n > 500 000) has given rise to prospective analyses of health outcomes being undertaken after short (<4 years) follow-up periods. However, these studies are potentially at risk of reverse causality bias. We investigated differences in the associations between self-reported physical activity and all-cause and cardiovascular disease (CVD) mortality, and incident CVD, using different follow-up time cut-offs and methods to account for reverse causality bias.

Methods: Data were from n = 452 933 UK Biobank participants, aged 38-73 years at baseline. Median available follow-up time was 7 years (for all-cause and CVD mortality) and 6.1 years (for incident CVD). We additionally analysed associations at 1-, 2- and 4-year cut-offs after baseline. We fit up to four models: (1) adjusting for prevalent CVD and cancer, (2) excluding prevalent disease, (3) and (4) Model 2 excluding incident cases in the first 12 and 24 months, respectively.

Results: The strength of associations decreased as follow-up time cut-off increased. For all-cause mortality, Model 1 hazard ratios were 0.73 (0.69-0.78) after 1 year and 0.86 (0.84-0.87) after 7 years. Associations were weaker with increasing control for possible reverse causality. After 7-years follow-up, the hazard ratios were 0.86 (0.84-0.87) and 0.88 (0.86-0.90) for Models 1 and 4, respectively. Associations with CVD outcomes followed similar trends.

Conclusions: As analyses with longer follow-up times and increased control for reverse causality showed weaker associations, there are implications for the decision about when to analyse a cohort study with ongoing data collection, the interpretation of study results and their contribution to meta-analyses.
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http://dx.doi.org/10.1093/ije/dyz212DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7124507PMC
February 2020
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