Habitual dietary intake of IBD patients differs from population controls:a case-control study

BACKGROUND: Since evidence-based dietary guidelines are lacking for IBD patients, they tend to follow "unguided" dietary habits; potentially leading to nutritional deficiencies and detrimental effects on disease course. Therefore, we compared dietary intake of IBD patients with controls. METHODS: Dietary intake of macronutrients and 25 food groups of 493 patients (207 UC, 286 CD), and 1291 controls was obtained via a food frequency questionnaire. RESULTS: 38.6% of patients in remission had protein intakes below the recommended 0.8 g/kg and 86.7% with active disease below the recommended 1.2 g/kg. Multinomial logistic regression, corrected for age, gender and BMI, showed that (compared to controls) UC patients consumed more meat and spreads, but less alcohol, breads, coffee and dairy; CD patients consumed more non-alcoholic drinks, potatoes, savoury snacks and sugar and sweets but less alcohol, dairy, nuts, pasta and prepared meals. Patients with active disease consumed more meat, soup and sugar and sweets but less alcohol, coffee, dairy, prepared meals and rice; patients in remission consumed more potatoes and spreads but less alcohol, breads, dairy, nuts, pasta and prepared meals. CONCLUSIONS: Patients avoiding potentially favourable foods and gourmandizing potentially unfavourable foods are of concern. Special attention is needed for protein intake in the treatment of these patients

Cohort profile: LifeLines DEEP, a prospective, general population cohort study in the northern Netherlands:Study design and baseline characteristics

Purpose There is a critical need for population-based prospective cohort studies because they follow individuals before the onset of disease, allowing for studies that can identify biomarkers and disease-modifying effects, and thereby contributing to systems epidemiology. Participants This paper describes the design and baseline characteristics of an intensively examined subpopulation of the LifeLines cohort in the Netherlands. In this unique subcohort, LifeLines DEEP, we included 1539 participants aged 18 years and older. Findings to date We collected additional blood (n=1387), exhaled air (n=1425) and faecal samples (n=1248), and elicited responses to gastrointestinal health questionnaires (n=1176) for analysis of the genome, epigenome, transcriptome, microbiome, metabolome and other biological levels. Here, we provide an overview of the different data layers in LifeLines DEEP and present baseline characteristics of the study population including food intake and quality of life. We also describe how the LifeLines DEEP cohort allows for the detailed investigation of genetic, genomic and metabolic variation for a wide range of phenotypic outcomes. Finally, we examine the determinants of gastrointestinal health, an area of particular interest to us that can be addressed by LifeLines DEEP. Future plans We have established a cohort of which multiple data levels allow for the integrative analysis of populations for translation of this information into biomarkers for disease, and which will offer new insights into disease mechanisms and prevention

Lifelines NEXT:a prospective birth cohort adding the next generation to the three-generation Lifelines cohort study

Epidemiological research has shown there to be a strong relationship between preconceptional, prenatal, birth and early-life factors and lifelong health. The Lifelines NEXT is a birth cohort designed to study the effects of intrinsic and extrinsic determinants on health and disease in a four-generation design. It is embedded within the Lifelines cohort study, a prospective three-generation population-based cohort study recording the health and health-related aspects of 167,729 individuals living in Northern Netherlands. In Lifelines NEXT we aim to include 1500 pregnant Lifelines participants and intensively follow them, their partners and their children until at least 1 year after birth. Longer-term follow-up of physical and psychological health will then be embedded following Lifelines procedures. During the Lifelines NEXT study period biomaterials-including maternal and neonatal (cord) blood, placental tissue, feces, breast milk, nasal swabs and urine-will be collected from the mother and child at 10 time points. We will also collect data on medical, social, lifestyle and environmental factors via questionnaires at 14 different time points and continuous data via connected devices. The extensive collection of different (bio)materials from mother and child during pregnancy and afterwards will provide the means to relate environmental factors including maternal and neonatal microbiome composition) to (epi)genetics, health and developmental outcomes. The nesting of the study within Lifelines enables us to include preconceptional transgenerational data and can be used to identify other extended families within the cohort

Sex and Gender-Related Differences in COVID-19 Diagnoses and SARS-CoV-2 Testing Practices During the First Wave of the Pandemic:The Dutch Lifelines COVID-19 Cohort Study

Background: Although sex differences are described in Coronavirus Disease 2019 (COVID-19) diagnoses and testing, many studies neglect possible gender-related influences. Additionally, research is often performed in clinical populations, while most COVID-19 patients are not hospitalized. Therefore, we investigated associations between sex and gender-related variables, and COVID-19 diagnoses and testing practices in a large general population cohort during the first wave of the pandemic when testing capacity was limited. Methods: We used data from the Lifelines COVID-19 Cohort (N = 74,722; 60.8% female). We applied bivariate and multiple logistic regression analyses. The outcomes were a COVID-19 diagnosis (confirmed by SARS-CoV-2 PCR testing or physician's clinical diagnosis) and PCR testing. Independent variables included among others participants' sex, age, somatic comorbidities, occupation, and smoking status. Sex-by-comorbidity and sex-by-occupation interaction terms were included to investigate sex differences in associations between the presence of comorbidities or an occupation with COVID-19 diagnoses or testing practices. Results: In bivariate analyses female sex was significantly associated with COVID-19 diagnoses and testing, but significance did not persist in multiple logistic regression analyses. However, a gender-related variable, being a health care worker, was significantly associated with COVID-19 diagnoses (OR = 1.68; 95%CI = 1.30-2.17) and testing (OR = 12.5; 95%CI = 8.55-18.3). Female health care workers were less often diagnosed and tested than male health care workers (ORinteraction = 0.54; 95%CI = 0.32-0.92, ORinteraction = 0.53; 95%CI = 0.29-0.97, respectively). Conclusions: We found no sex differences in COVID-19 diagnoses and testing in the general population. Among health care workers, a male preponderance in COVID-19 diagnoses and testing was observed. This could be explained by more pronounced COVID-19 symptoms in males or by gender inequities

Workplace impact on employees:A Lifelines Corona Research Initiative on the return to work

A large proportion of the global workforce migrated home during the COVID-19 pandemic and subsequent lockdowns. It remains unclear what the exact differences between home workers and non-home workers were, especially during the pandemic when a return to work was imminent. How were building, workplace, and related facilities associated with workers’ perceptions and health? What are the lessons to be learned? Lifelines Corona Research Initiative was used to compare employees’ workplaces and related concerns, facilities, work quality, and health in a complete case analysis (N = 12,776) when return to work was imminent. Mann-Whitney U, logistic regression, and Wilcoxon matched-pairs were used for analyses. Notwithstanding small differences, the results show that home workers had less favourable scores for concerns about and facilities of on-site buildings and workplaces upon return to work, but better scores for work quality and health than non-home workers. However, additional analyses also suggest that building, workplace, and related facilities may have had the capacity to positively influence employees’ affective responses and work quality, but not always their health.</p

Circulating miRNAs as Potential Biomarkers for Celiac Disease Development

BACKGROUND & AIMS: Celiac disease (CeD), an immune-mediated disease with enteropathy triggered by gluten, affects ~1% of the general European population. Currently, there are no biomarkers to predict CeD development. MicroRNAs (miRNAs) are short RNAs involved in post-transcriptional gene regulation, and certain disease- and stage-specific miRNA profiles have been found previously. We aimed to investigate whether circulating miRNAs can predict the development of CeD. METHODS: Using next-generation miRNA-sequencing, we determined miRNAs in >200 serum samples from 53 participants of the PreventCD study, of whom 33 developed CeD during follow-up. Following study inclusion at 3 months of age, samples were drawn at predefined ages, diagnosis (first anti-transglutaminase antibody (TGA) positivity or diagnostic biopsy) and after the start of a gluten-free diet (GFD). This allowed identification of circulating miRNAs that are deregulated before TGA positivity. For validation of the biomarkers for CeD and GFD response, two additional cohorts were included in subsequent meta-analyses. Additionally, miRNAs were measured in duodenal biopsies in a case-control cohort. RESULTS: 53 circulating miRNAs were increased (27) or decreased (26) in CeD versus controls. We assessed specific trends in these individual miRNAs in the PreventCD cohort by grouping the pre-diagnostic samples of the CeD patients (all had negative TGA) by how close to seroconversion (first sample positive TGA) the samples were taken. 8/53 miRNAs differed significantly between controls and samples taken <1 year before TGA positivity: miR-21-3p, miR-374a-5p, 144-3p, miR-500a-3p, miR-486-3p let-7d-3p, let-7e-5p and miR-3605-3p. 6/26 downregulated miRNAs reconstituted upon GFD, including miR-150-5p/-3p, whereas no upregulated miRNAs were downregulated upon GFD. 15/53 biomarker candidates also differed between CeD biopsies and controls, with a concordant direction, indicating that these circulating miRNAs might originate from the intestine. CONCLUSIONS: We identified 53 circulating miRNAs that are potential early biomarkers for CeD, of which several can be detected more than a year before TGA positivity and some start to normalize upon GFD

The Gut Microbiome Contributes to a Substantial Proportion of the Variation in Blood Lipids

Rationale: Evidence suggests that the gut microbiome is involved in the development of cardiovascular disease, with the host–microbe interaction regulating immune and metabolic pathways. However, there was no firm evidence for associations between microbiota and metabolic risk factors for cardiovascular disease from large-scale studies in humans. In particular, there was no strong evidence for association between cardiovascular disease and aberrant blood lipid levels. Objectives: To identify intestinal bacteria taxa, whose proportions correlate with body mass index and lipid levels, and to determine whether lipid variance can be explained by microbiota relative to age, sex, and host genetics. Methods and Results: We studied 893 subjects from the LifeLines-DEEP population cohort. After correcting for age and sex, we identified 34 bacterial taxa associated with body mass index and blood lipids; most are novel associations. Cross-validation analysis revealed that microbiota explain 4.5% of the variance in body mass index, 6% in triglycerides, and 4% in high-density lipoproteins, independent of age, sex, and genetic risk factors. A novel risk model, including the gut microbiome explained ≤25.9% of high-density lipoprotein variance, significantly outperforming the risk model without microbiome. Strikingly, the microbiome had little effect on low-density lipoproteins or total cholesterol. Conclusions: Our studies suggest that the gut microbiome may play an important role in the variation in body mass index and blood lipid levels, independent of age, sex, and host genetics. Our findings support the potential of therapies altering the gut microbiome to control body mass, triglycerides, and high-density lipoproteins

Lifelines COVID-19 cohort:investigating COVID-19 infection and its health and societal impacts in a Dutch population-based cohort

Purpose The Lifelines COVID-19 cohort was set up to assess the psychological and societal impacts of the COVID-19 pandemic and investigate potential risk factors for COVID-19 within the Lifelines prospective population cohort.Participants Participants were recruited from the 140 000 eligible participants of Lifelines and the Lifelines NEXT birth cohort, who are all residents of the three northern provinces of the Netherlands. Participants filled out detailed questionnaires about their physical and mental health and experiences on a weekly basis starting in late March 2020, and the cohort consists of everyone who filled in at least one questionnaire in the first 8 weeks of the project.Findings to date &gt;71 000 unique participants responded to the questionnaires at least once during the first 8 weeks, with &gt;22 000 participants responding to seven questionnaires. Compiled questionnaire results are continuously updated and shared with the public through the Corona Barometer website. Early results included a clear signal that younger people living alone were experiencing greater levels of loneliness due to lockdown, and subsequent results showed the easing of anxiety as lockdown was eased in June 2020.Future plans Questionnaires were sent on a (bi)weekly basis starting in March 2020 and on a monthly basis starting July 2020, with plans for new questionnaire rounds to continue through 2020 and early 2021. Questionnaire frequency can be increased again for subsequent waves of infections. Cohort data will be used to address how the COVID-19 pandemic developed in the northern provinces of the Netherlands, which environmental and genetic risk factors predict disease susceptibility and severity and the psychological and societal impacts of the crisis. Cohort data are linked to the extensive health, lifestyle and sociodemographic data held for these participants by Lifelines, a 30-year project that started in 2006, and to data about participants held in national databases