Publications by authors named "Frank J A van Rooij"

83 Publications

Design, implementation and initial findings of COVID-19 research in the Rotterdam Study: leveraging existing infrastructure for population-based investigations on an emerging disease.

Eur J Epidemiol 2021 Jun 17;36(6):649-654. Epub 2021 Jul 17.

Department of Epidemiology, Erasmus MC - University Medical Center Rotterdam, Rotterdam, The Netherlands.

The Rotterdam Study is an ongoing prospective, population-based cohort study that started in 1989 in the city of Rotterdam, the Netherlands. The study aims to unravel etiology, preclinical course, natural history and potential targets for intervention for chronic diseases in mid-life and late-life. It focuses on cardiovascular, endocrine, hepatic, neurological, ophthalmic, psychiatric, dermatological, otolaryngological, locomotor, and respiratory diseases. In response to the COVID-19 pandemic, a substudy was designed and embedded within the Rotterdam Study. On the 20th of April, 2020, all living non-institutionalized participants of the Rotterdam Study (n = 8732) were invited to participate in this sub-study by filling out a series of questionnaires administered over a period of 8 months. These questionnaires included questions on COVID-19 related symptoms and risk factors, characterization of lifestyle and mental health changes, and determination of health care seeking and health care avoiding behavior during the pandemic. As of May 2021, the questionnaire had been sent out repeatedly for a total of six times with an overall response rate of 76%. This article provides an overview of the rationale, design, and implementation of this sub-study nested within the Rotterdam Study. Finally, initial results on participant characteristics and prevalence of COVID-19 in this community-dwelling population are shown.
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http://dx.doi.org/10.1007/s10654-021-00789-7DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8286166PMC
June 2021

Common and Rare Variants Genetic Association Analysis of Circulating Neutrophil Extracellular Traps.

Front Immunol 2021 24;12:615527. Epub 2021 Feb 24.

Department of Epidemiology, Erasmus University Medical Center, Rotterdam, Netherlands.

Introduction: Neutrophils contribute to host defense through different mechanisms, including the formation of neutrophil extracellular traps (NETs). The genetic background and underlying mechanisms contributing to NET formation remain unclear.

Materials And Methods: We performed a genome-wide association study (GWAS) and exome-sequencing analysis to identify common and rare genetic variants associated with plasma myeloperoxidase (MPO)-DNA complex levels, a biomarker for NETs, in the population-based Rotterdam Study cohort. GWAS was performed using haplotype reference consortium(HRC)-imputed genotypes of common variants in 3,514 individuals from the first and 2,076 individuals from the second cohort of the Rotterdam Study. We additionally performed exome-sequencing analysis in 960 individuals to investigate rare variants in candidate genes.

Results: The GWAS yielded suggestive associations (p-value < 5.0 × 10) of SNPs annotated to four genes. In the exome-sequencing analysis, a variant in gene was significantly associated with MPO-DNA complex levels (p-value < 3.06×10). Moreover, gene-based analysis showed ten genes () to be associated with MPO-DNA complex levels (p-value between 4.48 × 10 and 1.05 × 10). Pathway analysis of the identified genes showed their involvement in cellular development, molecular transport, RNA trafficking, cell-to-cell signaling and interaction, cellular growth and proliferation. Cancer was the top disease linked to the NET-associated genes.

Conclusion: In this first GWAS and exome-sequencing analysis of NETs levels, we found several genes that were associated with NETs. The precise mechanism of how these genes may contribute to neutrophil function or the formation of NETs remains unclear and should be further investigated in experimental studies.
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http://dx.doi.org/10.3389/fimmu.2021.615527DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7944992PMC
July 2021

Genome-wide association study identifies 48 common genetic variants associated with handedness.

Nat Hum Behav 2021 01 28;5(1):59-70. Epub 2020 Sep 28.

Institute of Biological Psychiatry, Mental Health Services of Copenhagen, Copenhagen, Denmark.

Handedness has been extensively studied because of its relationship with language and the over-representation of left-handers in some neurodevelopmental disorders. Using data from the UK Biobank, 23andMe and the International Handedness Consortium, we conducted a genome-wide association meta-analysis of handedness (N = 1,766,671). We found 41 loci associated (P < 5 × 10) with left-handedness and 7 associated with ambidexterity. Tissue-enrichment analysis implicated the CNS in the aetiology of handedness. Pathways including regulation of microtubules and brain morphology were also highlighted. We found suggestive positive genetic correlations between left-handedness and neuropsychiatric traits, including schizophrenia and bipolar disorder. Furthermore, the genetic correlation between left-handedness and ambidexterity is low (r = 0.26), which implies that these traits are largely influenced by different genetic mechanisms. Our findings suggest that handedness is highly polygenic and that the genetic variants that predispose to left-handedness may underlie part of the association with some psychiatric disorders.
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http://dx.doi.org/10.1038/s41562-020-00956-yDOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7116623PMC
January 2021

The Polygenic and Monogenic Basis of Blood Traits and Diseases.

Cell 2020 09;182(5):1214-1231.e11

Laboratory of Epidemiology and Population Science, National Institute on Aging/NIH, Baltimore, MD, 21224, USA.

Blood cells play essential roles in human health, underpinning physiological processes such as immunity, oxygen transport, and clotting, which when perturbed cause a significant global health burden. Here we integrate data from UK Biobank and a large-scale international collaborative effort, including data for 563,085 European ancestry participants, and discover 5,106 new genetic variants independently associated with 29 blood cell phenotypes covering a range of variation impacting hematopoiesis. We holistically characterize the genetic architecture of hematopoiesis, assess the relevance of the omnigenic model to blood cell phenotypes, delineate relevant hematopoietic cell states influenced by regulatory genetic variants and gene networks, identify novel splice-altering variants mediating the associations, and assess the polygenic prediction potential for blood traits and clinical disorders at the interface of complex and Mendelian genetics. These results show the power of large-scale blood cell trait GWAS to interrogate clinically meaningful variants across a wide allelic spectrum of human variation.
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http://dx.doi.org/10.1016/j.cell.2020.08.008DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7482360PMC
September 2020

Trans-ethnic and Ancestry-Specific Blood-Cell Genetics in 746,667 Individuals from 5 Global Populations.

Cell 2020 09;182(5):1198-1213.e14

Massachusetts Veterans Epidemiology Research and Information Center (MAVERIC), VA Boston Healthcare System, Boston, MA 02130, USA; Department of Medicine, Division on Aging, Brigham and Women's Hospital, Boston, MA 02115, USA; Department of Medicine, Harvard Medical School, Boston, MA 02115, USA.

Most loci identified by GWASs have been found in populations of European ancestry (EUR). In trans-ethnic meta-analyses for 15 hematological traits in 746,667 participants, including 184,535 non-EUR individuals, we identified 5,552 trait-variant associations at p < 5 × 10, including 71 novel associations not found in EUR populations. We also identified 28 additional novel variants in ancestry-specific, non-EUR meta-analyses, including an IL7 missense variant in South Asians associated with lymphocyte count in vivo and IL-7 secretion levels in vitro. Fine-mapping prioritized variants annotated as functional and generated 95% credible sets that were 30% smaller when using the trans-ethnic as opposed to the EUR-only results. We explored the clinical significance and predictive value of trans-ethnic variants in multiple populations and compared genetic architecture and the effect of natural selection on these blood phenotypes between populations. Altogether, our results for hematological traits highlight the value of a more global representation of populations in genetic studies.
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http://dx.doi.org/10.1016/j.cell.2020.06.045DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7480402PMC
September 2020

Associations of Activity and Sleep With Quality of Life: A Compositional Data Analysis.

Am J Prev Med 2020 09 23;59(3):412-419. Epub 2020 Jul 23.

Department of Epidemiology, Erasmus University Medical Center, Rotterdam, The Netherlands. Electronic address:

Introduction: Associations between time spent on physical activity, sedentary behavior, and sleep and quality of life are usually studied without considering that their combined time is fixed. This study investigates the reallocation of time spent on physical activity, sedentary behavior, and sleep during the 24-hour day and their associations with quality of life.

Methods: Data from the 2011-2016 Rotterdam Study were used to perform this cross-sectional analysis among 1,934 participants aged 51-94 years. Time spent in activity levels (sedentary, light-intensity physical activity, moderate-to-vigorous physical activity, and sleep) were objectively measured with a wrist-worn accelerometer combined with a sleep diary. Quality of life was measured using the EuroQoL 5D-3L questionnaire. The compositional isotemporal substitution method was used in 2018 to examine the association between the distribution of time spent in different activity behaviors and quality of life.

Results: Reallocation of 30 minutes from sedentary behavior, light-intensity physical activity, or sleep to moderate-to-vigorous physical activity was associated with a higher quality of life, whereas reallocation from moderate-to-vigorous physical activity to sedentary behavior, light-intensity physical activity, or sleep was associated with lower quality of life. To illustrate this, a reallocation of 30 minutes from sedentary behavior to moderate-to-vigorous physical activity was associated with a 3% (95% CI=2, 4) higher quality of life score. By contrast, a reallocation of 30 minutes from moderate-to-vigorous physical activity to sedentary behavior was associated with a 4% (95% CI=2, 6) lower quality of life score.

Conclusions: Moderate-to-vigorous physical activity is important with regard to the quality of life of middle-aged and elderly individuals. The benefits of preventing less time spent in moderate-to-vigorous physical activity were greater than the benefits of more time spent in moderate-to-vigorous physical activity. These results could shift the attention to interventions focused on preventing reductions in moderate-to-vigorous physical activity levels. Further longitudinal studies are needed to confirm these findings and explore causality.
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http://dx.doi.org/10.1016/j.amepre.2020.03.029DOI Listing
September 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

Mendelian randomization analysis does not support causal associations of birth weight with hypertension risk and blood pressure in adulthood.

Eur J Epidemiol 2020 Jul 7;35(7):685-697. Epub 2020 May 7.

Department of Clinical Sciences, Genetic and Molecular Epidemiology Unit, Skåne University Hospital Malmö, Lund University, 21741, Malmö, Sweden.

Epidemiology studies suggested that low birthweight was associated with a higher risk of hypertension in later life. However, little is known about the causality of such associations. In our study, we evaluated the causal association of low birthweight with adulthood hypertension following a standard analytic protocol using the study-level data of 183,433 participants from 60 studies (CHARGE-BIG consortium), as well as that with blood pressure using publicly available summary-level genome-wide association data from EGG consortium of 153,781 participants, ICBP consortium and UK Biobank cohort together of 757,601 participants. We used seven SNPs as the instrumental variable in the study-level analysis and 47 SNPs in the summary-level analysis. In the study-level analyses, decreased birthweight was associated with a higher risk of hypertension in adults (the odds ratio per 1 standard deviation (SD) lower birthweight, 1.22; 95% CI 1.16 to 1.28), while no association was found between genetically instrumented birthweight and hypertension risk (instrumental odds ratio for causal effect per 1 SD lower birthweight, 0.97; 95% CI 0.68 to 1.41). Such results were consistent with that from the summary-level analyses, where the genetically determined low birthweight was not associated with blood pressure measurements either. One SD lower genetically determined birthweight was not associated with systolic blood pressure (β = - 0.76, 95% CI - 2.45 to 1.08 mmHg), 0.06 mmHg lower diastolic blood pressure (β = - 0.06, 95% CI - 0.93 to 0.87 mmHg), or pulse pressure (β = - 0.65, 95% CI - 1.38 to 0.69 mmHg, all p > 0.05). Our findings suggest that the inverse association of birthweight with hypertension risk from observational studies was not supported by large Mendelian randomization analyses.
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http://dx.doi.org/10.1007/s10654-020-00638-zDOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7867117PMC
July 2020

Objectives, design and main findings until 2020 from the Rotterdam Study.

Eur J Epidemiol 2020 May 4;35(5):483-517. Epub 2020 May 4.

Department of Epidemiology, Erasmus University Medical Center, PO Box 2040, 3000 CA, Rotterdam, The Netherlands.

The Rotterdam Study is an ongoing prospective cohort study that started in 1990 in the city of Rotterdam, The Netherlands. The study aims to unravel etiology, preclinical course, natural history and potential targets for intervention for chronic diseases in mid-life and late-life. The study focuses on cardiovascular, endocrine, hepatic, neurological, ophthalmic, psychiatric, dermatological, otolaryngological, locomotor, and respiratory diseases. As of 2008, 14,926 subjects aged 45 years or over comprise the Rotterdam Study cohort. Since 2016, the cohort is being expanded by persons aged 40 years and over. The findings of the Rotterdam Study have been presented in over 1700 research articles and reports. This article provides an update on the rationale and design of the study. It also presents a summary of the major findings from the preceding 3 years and outlines developments for the coming period.
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http://dx.doi.org/10.1007/s10654-020-00640-5DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7250962PMC
May 2020

Macronutrient intake and frailty: the Rotterdam Study.

Eur J Nutr 2020 Oct 14;59(7):2919-2928. Epub 2019 Nov 14.

Department of Epidemiology, Erasmus University Medical Center, Rotterdam, The Netherlands.

Purpose: To investigate the longitudinal association between the macronutrient composition of the diet and frailty.

Methods: Data were obtained from 5205 Dutch middle-aged and older adults participating in the Rotterdam Study. Frailty was measured using a frailty index based on the accumulation of 38 health-related deficits, score between 0 and 100, and a higher score indicating more frailty. Frailty was assessed at baseline and 11 years later (range of 23 years). Macronutrient intake was assessed using food-frequency questionnaires. The association between macronutrients and frailty over time was evaluated using multivariable linear regression, adjusted for the frailty index at baseline, energy intake, and other relevant confounders. All analyses were performed in strata of BMI.

Results: Median frailty index score was 13.8 points (IQR 9.6; 19.1) at baseline and increased by a median of 2.3 points (IQR - 2.0; 7.6) after 11 years. Overall, we found no significant associations between intake of carbohydrates or fat and frailty over time. We did observe a significant positive association between an iso-energetic intake of 10 g protein and frailty over time (β 0.31 (95% CI 0.06; 0.55)) which was mainly driven by animal protein (β 0.31 (95% CI 0.07; 0.56)). It did not depend on whether it was substituted fat or carbohydrates.

Conclusions: Our findings suggest that a reduction in the intake of animal protein may improve the overall health status over time in a relatively healthy population. More research is needed on the optimal macronutrient composition of the diet and frailty in more vulnerable populations.
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http://dx.doi.org/10.1007/s00394-019-02131-0DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7501120PMC
October 2020

Associations of autozygosity with a broad range of human phenotypes.

Nat Commun 2019 10 31;10(1):4957. Epub 2019 Oct 31.

Department of Neurology, Brain Centre Rudolf Magnus, University Medical Centre Utrecht, Utrecht University, Utrecht, 3584 CX, The Netherlands.

In many species, the offspring of related parents suffer reduced reproductive success, a phenomenon known as inbreeding depression. In humans, the importance of this effect has remained unclear, partly because reproduction between close relatives is both rare and frequently associated with confounding social factors. Here, using genomic inbreeding coefficients (F) for >1.4 million individuals, we show that F is significantly associated (p < 0.0005) with apparently deleterious changes in 32 out of 100 traits analysed. These changes are associated with runs of homozygosity (ROH), but not with common variant homozygosity, suggesting that genetic variants associated with inbreeding depression are predominantly rare. The effect on fertility is striking: F equivalent to the offspring of first cousins is associated with a 55% decrease [95% CI 44-66%] in the odds of having children. Finally, the effects of F are confirmed within full-sibling pairs, where the variation in F is independent of all environmental confounding.
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http://dx.doi.org/10.1038/s41467-019-12283-6DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6823371PMC
October 2019

Ascertainment of cancer in longitudinal research: The concordance between the Rotterdam Study and the Netherlands Cancer Registry.

Int J Cancer 2020 08 7;147(3):633-640. Epub 2019 Nov 7.

Department of Epidemiology, Erasmus MC - University Medical Center Rotterdam, Rotterdam, The Netherlands.

Complete and accurate registration of cancer is needed to provide reliable data on cancer incidence and to investigate aetiology. Such data can be derived from national cancer registries, but also from large population-based cohort studies. Yet, the concordance and discordance between these two data sources remain unknown. We evaluated completeness and accuracy of cancer registration by studying the concordance between the population-based Rotterdam Study (RS) and the Netherlands Cancer Registry (NCR) between 1989 and 2012 using the independent case ascertainment method. We compared all incident cancers in participants of the RS (aged ≥45 years) to registered cancers in the NCR in the same persons based on the date of diagnosis and the International Classification of Diseases (ICD) code. In total, 2,977 unique incident cancers among 2,685 persons were registered. Two hundred eighty-eight cancers (9.7%) were coded by the RS that were not present in the NCR. These were mostly nonpathology-confirmed lung and haematological cancers. Furthermore, 116 cancers were coded by the NCR, but not by the RS (3.9%), of which 20.7% were breast cancers. Regarding pathology-confirmed cancer diagnoses, completeness was >95% in both registries. Eighty per cent of the cancers registered in both registries were coded with the same date of diagnosis and ICD code. Of the remaining cancers, 344 (14.5%) were misclassified with regard to date of diagnosis and 72 (3.0%) with regard to ICD code. Our findings indicate that multiple sources on cancer are complementary and should be combined to ensure reliable data on cancer incidence.
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http://dx.doi.org/10.1002/ijc.32750DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7317466PMC
August 2020

Association of Birth Weight With Type 2 Diabetes and Glycemic Traits: A Mendelian Randomization Study.

JAMA Netw Open 2019 09 4;2(9):e1910915. Epub 2019 Sep 4.

Division of Obstetrics and Gynaecology, School of Medicine, University of Western Australia, Crawley, Western Australia, Australia.

Importance: Observational studies have shown associations of birth weight with type 2 diabetes (T2D) and glycemic traits, but it remains unclear whether these associations represent causal associations.

Objective: To test the association of birth weight with T2D and glycemic traits using a mendelian randomization analysis.

Design, Setting, And Participants: This mendelian randomization study used a genetic risk score for birth weight that was constructed with 7 genome-wide significant single-nucleotide polymorphisms. The associations of this score with birth weight and T2D were tested in a mendelian randomization analysis using study-level data. The association of birth weight with T2D was tested using both study-level data (7 single-nucleotide polymorphisms were used as an instrumental variable) and summary-level data from the consortia (43 single-nucleotide polymorphisms were used as an instrumental variable). Data from 180 056 participants from 49 studies were included.

Main Outcomes And Measures: Type 2 diabetes and glycemic traits.

Results: This mendelian randomization analysis included 49 studies with 41 155 patients with T2D and 80 008 control participants from study-level data and 34 840 patients with T2D and 114 981 control participants from summary-level data. Study-level data showed that a 1-SD decrease in birth weight due to the genetic risk score was associated with higher risk of T2D among all participants (odds ratio [OR], 2.10; 95% CI, 1.69-2.61; P = 4.03 × 10-5), among European participants (OR, 1.96; 95% CI, 1.42-2.71; P = .04), and among East Asian participants (OR, 1.39; 95% CI, 1.18-1.62; P = .04). Similar results were observed from summary-level analyses. In addition, each 1-SD lower birth weight was associated with 0.189 SD higher fasting glucose concentration (β = 0.189; SE = 0.060; P = .002), but not with fasting insulin, 2-hour glucose, or hemoglobin A1c concentration.

Conclusions And Relevance: In this study, a genetic predisposition to lower birth weight was associated with increased risk of T2D and higher fasting glucose concentration, suggesting genetic effects on retarded fetal growth and increased diabetes risk that either are independent of each other or operate through alterations of integrated biological mechanisms.
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http://dx.doi.org/10.1001/jamanetworkopen.2019.10915DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6755534PMC
September 2019

Genome-wide meta-analysis of macronutrient intake of 91,114 European ancestry participants from the cohorts for heart and aging research in genomic epidemiology consortium.

Mol Psychiatry 2019 12 9;24(12):1920-1932. Epub 2018 Jul 9.

Department of Clinical Chemistry, Fimlab Laboratories, Finnish Cardiovascular Research Center - Tampere, Faculty of Medicine and Life Sciences, University of Tampere, Tampere, Finland.

Macronutrient intake, the proportion of calories consumed from carbohydrate, fat, and protein, is an important risk factor for metabolic diseases with significant familial aggregation. Previous studies have identified two genetic loci for macronutrient intake, but incomplete coverage of genetic variation and modest sample sizes have hindered the discovery of additional loci. Here, we expanded the genetic landscape of macronutrient intake, identifying 12 suggestively significant loci (P < 1 × 10) associated with intake of any macronutrient in 91,114 European ancestry participants. Four loci replicated and reached genome-wide significance in a combined meta-analysis including 123,659 European descent participants, unraveling two novel loci; a common variant in RARB locus for carbohydrate intake and a rare variant in DRAM1 locus for protein intake, and corroborating earlier FGF21 and FTO findings. In additional analysis of 144,770 participants from the UK Biobank, all identified associations from the two-stage analysis were confirmed except for DRAM1. Identified loci might have implications in brain and adipose tissue biology and have clinical impact in obesity-related phenotypes. Our findings provide new insight into biological functions related to macronutrient intake.
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http://dx.doi.org/10.1038/s41380-018-0079-4DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6326896PMC
December 2019

Physical activity and cause-specific mortality: the Rotterdam Study.

Int J Epidemiol 2018 10;47(5):1705-1713

Department of Epidemiology, Erasmus MC - University Medical Center, Rotterdam, The Netherlands.

Background: Physical activity (PA) is associated with lower risk for all-cause mortality. However, in elderly people, it remains unknown which types of PA are associated with mortality and whether the association between PA and mortality differs by cause of death.

Methods: We assessed the association of total PA, walking, cycling, domestic work, sports and gardening with all-cause mortality, and the association of total PA with cause-specific mortality, using Cox proportional hazard models among 7225 older adults (mean age: 70 years) from the prospective population-based Rotterdam Study. Deaths were classified as due to cardiovascular diseases (CVDs), cancer, infections, external causes, dementia, chronic lung diseases or other causes. Activities were categorized into tertiles (lowest tertile as reference). To account for the possibility of reverse causation, we excluded the first 5 and 10 years of follow-up.

Results: Over a median of 13.1 years of follow-up (interquartile range: 8.4-14.6 years), 3261 participants died. The hazard ratios (HRs) and 95% confidence intervals (95% CIs) associated with high total PA compared with low were 0.69 (0.63, 0.75), 0.69 (0.58, 0.81), 0.44 (0.27, 0.71), 0.47 (0.32, 0.71) and 0.56 (0.46, 0.69) for mortality from all causes, CVDs, chronic lung diseases, infections and other causes, respectively. With longer exclusion times, the strength of these associations was attenuated. All PA types were associated with lower all-cause mortality risk.

Conclusions: Engagement in higher PA levels was associated with lower risk of mortality from CVDs, chronic lung diseases, infections and other causes. Participating in any PA might reduce mortality risk in older adults.
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http://dx.doi.org/10.1093/ije/dyy058DOI Listing
October 2018

Seasonality of physical activity, sedentary behavior, and sleep in a middle-aged and elderly population: The Rotterdam study.

Maturitas 2018 Apr 27;110:41-50. Epub 2018 Jan 27.

Department of Epidemiology, Erasmus MC, University Medical Centre, Rotterdam, The Netherlands.

Introduction: Physical activity (PA) and sedentary behavior (SB) have seasonal patterns. It remains unclear how these patterns are associated with sleep, meteorological factors, and health.

Methods: Activity levels were continuously measured with an accelerometer for seven days between July 2011 and May 2016, among middle-aged (50-64 years), young-elderly (65-74 years) and old-elderly (≥75 years) participants of a population-based Dutch cohort study (n = 1116). Meteorological factors (ambient temperature, wind speed, sunlight hours, precipitation, and minimum visibility) were locally recorded. We first examined the seasonality of PA, SB, and nighttime sleep, stratified by age group. Second, we examined the influence of meteorological factors. Third, we modeled the potential seasonality of the all-cause mortality risk due to the seasonality of PA and SB, by using previously published relative risks.

Results: Levels of light and moderate-to-vigorous PA were higher in summer than in winter among middle-aged (seasonal variation = 18.1 and 14.8 min/day) and young-elderly adults (12.8 and 8.6 min/day). The pattern was explained by ambient temperature and sunlight hours. Nighttime sleep was 31.8 min/day longer in winter among middle-aged adults. SB did not show a seasonal pattern. No seasonality in activity levels was observed among old-elderly adults. The all-cause mortality risk may be higher in winter than in summer due to the accumulation of low levels of moderate to vigorous PA and high levels of SB.

Conclusion: PA has a larger degree of seasonality than SB and nighttime sleep among middle-aged and young-elderly adults. SB appears strongly ingrained in daily routine. Recommending the interruption of SB with light PA might be a good starting point for public health institutions.
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http://dx.doi.org/10.1016/j.maturitas.2018.01.016DOI Listing
April 2018

The association between lifestyle and overall health, using the frailty index.

Arch Gerontol Geriatr 2018 May - Jun;76:85-91. Epub 2018 Feb 13.

Department of Epidemiology, Erasmus MC, University Medical Center, Rotterdam, the Netherlands; Department of Internal Medicine, Erasmus MC, University Medical Center, Rotterdam, the Netherlands. Electronic address:

Objective: To evaluate the associations of four individual lifestyle factors with frailty.

Methods: We used cross-sectional data from 11,539 participants of the Rotterdam Study, a population-based cohort, running from 1990 till now. A frailty index was used with a range from 0 to 100 (higher values indicating increasing frailty). We examined physical activity, dietary quality, alcohol intake, and smoking and calculated a sum-score of these, with a range from 0 (lowest) to 8 (highest). The associations between each lifestyle factor and the lifestyle score with frailty were evaluated.

Results: Each lifestyle factor was independently associated with frailty. Participants with high physical activity levels had lower frailty scores than participants with low physical activity (β = -4.70,95%CI = -5.10,-4.30). High diet quality, compared to low diet quality was associated with less frailty (β=-0.88,95%CI = -1.35,-0.42). Low alcohol intake was associated more frailty (β = 0.84, 95%CI = 0.39, 1.29). Never-smokers or former smokers had on average 1.15 (95%CI = -1.60,-0.69) and 1.28 (95%CI = -1.78,-0.79) better frailty scores than smokers. A one-unit increment of the lifestyle score was associated with lower frailty (β = -0.62;95%CI = -0.84,-0.53).

Conclusions: The prevention of frailty can lead to lower health care costs and a higher quality of life among the growing group of elderly people. Our results emphasize that there is an urgent need for preventions that combine several lifestyle factors to improve healthy ageing.
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http://dx.doi.org/10.1016/j.archger.2018.02.006DOI Listing
March 2019

Genome-wide association meta-analysis of fish and EPA+DHA consumption in 17 US and European cohorts.

PLoS One 2017 13;12(12):e0186456. Epub 2017 Dec 13.

Department of Biostatistics, Boston University School of Public Health, Boston, MA, United States of America.

Background: Regular fish and omega-3 consumption may have several health benefits and are recommended by major dietary guidelines. Yet, their intakes remain remarkably variable both within and across populations, which could partly owe to genetic influences.

Objective: To identify common genetic variants that influence fish and dietary eicosapentaenoic acid plus docosahexaenoic acid (EPA+DHA) consumption.

Design: We conducted genome-wide association (GWA) meta-analysis of fish (n = 86,467) and EPA+DHA (n = 62,265) consumption in 17 cohorts of European descent from the CHARGE (Cohorts for Heart and Aging Research in Genomic Epidemiology) Consortium Nutrition Working Group. Results from cohort-specific GWA analyses (additive model) for fish and EPA+DHA consumption were adjusted for age, sex, energy intake, and population stratification, and meta-analyzed separately using fixed-effect meta-analysis with inverse variance weights (METAL software). Additionally, heritability was estimated in 2 cohorts.

Results: Heritability estimates for fish and EPA+DHA consumption ranged from 0.13-0.24 and 0.12-0.22, respectively. A significant GWA for fish intake was observed for rs9502823 on chromosome 6: each copy of the minor allele (FreqA = 0.015) was associated with 0.029 servings/day (~1 serving/month) lower fish consumption (P = 1.96x10-8). No significant association was observed for EPA+DHA, although rs7206790 in the obesity-associated FTO gene was among top hits (P = 8.18x10-7). Post-hoc calculations demonstrated 95% statistical power to detect a genetic variant associated with effect size of 0.05% for fish and 0.08% for EPA+DHA.

Conclusions: These novel findings suggest that non-genetic personal and environmental factors are principal determinants of the remarkable variation in fish consumption, representing modifiable targets for increasing intakes among all individuals. Genes underlying the signal at rs72838923 and mechanisms for the association warrant further investigation.
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http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0186456PLOS
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5728559PMC
January 2018

Genome-wide meta-analysis associates HLA-DQA1/DRB1 and LPA and lifestyle factors with human longevity.

Nat Commun 2017 10 13;8(1):910. Epub 2017 Oct 13.

Centre for Epidemiology, Division of Population Health, Health Services Research & Primary Care, The University of Manchester, Manchester, Greater, Manchester, M13 9PL, UK.

Genomic analysis of longevity offers the potential to illuminate the biology of human aging. Here, using genome-wide association meta-analysis of 606,059 parents' survival, we discover two regions associated with longevity (HLA-DQA1/DRB1 and LPA). We also validate previous suggestions that APOE, CHRNA3/5, CDKN2A/B, SH2B3 and FOXO3A influence longevity. Next we show that giving up smoking, educational attainment, openness to new experience and high-density lipoprotein (HDL) cholesterol levels are most positively genetically correlated with lifespan while susceptibility to coronary artery disease (CAD), cigarettes smoked per day, lung cancer, insulin resistance and body fat are most negatively correlated. We suggest that the effect of education on lifespan is principally mediated through smoking while the effect of obesity appears to act via CAD. Using instrumental variables, we suggest that an increase of one body mass index unit reduces lifespan by 7 months while 1 year of education adds 11 months to expected lifespan.Variability in human longevity is genetically influenced. Using genetic data of parental lifespan, the authors identify associations at HLA-DQA/DRB1 and LPA and find that genetic variants that increase educational attainment have a positive effect on lifespan whereas increasing BMI negatively affects lifespan.
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http://dx.doi.org/10.1038/s41467-017-00934-5DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5715013PMC
October 2017

Adherence to the 2015 Dutch dietary guidelines and risk of non-communicable diseases and mortality in the Rotterdam Study.

Eur J Epidemiol 2017 11 19;32(11):993-1005. Epub 2017 Aug 19.

Department of Epidemiology, Erasmus MC, University Medical Center, Rotterdam, The Netherlands.

We aimed to evaluate the criterion validity of the 2015 food-based Dutch dietary guidelines, which were formulated based on evidence on the relation between diet and major chronic diseases. We studied 9701 participants of the Rotterdam Study, a population-based prospective cohort in individuals aged 45 years and over [median 64.1 years (95%-range 49.0-82.8)]. Dietary intake was assessed at baseline with a food-frequency questionnaire. For all participants, we examined adherence (yes/no) to fourteen items of the guidelines: vegetables (≥200 g/day), fruit (≥200 g/day), whole-grains (≥90 g/day), legumes (≥135 g/week), nuts (≥15 g/day), dairy (≥350 g/day), fish (≥100 g/week), tea (≥450 mL/day), ratio whole-grains:total grains (≥50%), ratio unsaturated fats and oils:total fats (≥50%), red and processed meat (<300 g/week), sugar-containing beverages (≤150 mL/day), alcohol (≤10 g/day) and salt (≤6 g/day). Total adherence was calculated as sum-score of the adherence to the individual items (0-14). Information on disease incidence and all-cause mortality during a median follow-up period of 13.5 years (range 0-27.0) was obtained from data collected at our research center and from medical records. Using Cox proportional-hazards models adjusted for confounders, we observed every additional component adhered to was associated with a 3% lower mortality risk (HR 0.97, 95% CI 0.95; 0.98), lower risk of stroke (HR 0.95, 95% CI 0.92; 0.99), chronic obstructive pulmonary disease (HR 0.94, 95% CI 0.91; 0.98), colorectal cancer (HR 0.90, 95% CI 0.84; 0.96), and depression (HR 0.97, 95% CI 0.95; 0.999), but not with incidence of coronary heart disease, type 2 diabetes, heart failure, lung cancer, breast cancer, or dementia. These associations were not driven by any of the individual dietary components. To conclude, adherence to the Dutch dietary guidelines was associated with a lower mortality risk and a lower risk of developing some but not all of the chronic diseases on which the guidelines were based.
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http://dx.doi.org/10.1007/s10654-017-0295-2DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5684301PMC
November 2017

Objective Measures of Activity in the Elderly: Distribution and Associations With Demographic and Health Factors.

J Am Med Dir Assoc 2017 Oct;18(10):838-847

Department of Epidemiology, Erasmus University Medical Center, Rotterdam, The Netherlands.

Background: Little is known about the distribution of activity over the full 24-hour spectrum in late old age and its association with demographic and health factors. Therefore, we aimed to evaluate the distribution of physical activity (PA), sedentary behavior, and sleep, and associated factors in the elderly population.

Methods: Our study included 1210 participants (51.9% women) aged 70-94 years [mean age 77.5 years, standard deviation (SD) 5.0] from the population-based Rotterdam Study. Participants wore a triaxial accelerometer (GENEActiv) around the wrist for 7 days between July 2014 and June 2016. We examined if PA, sedentary behavior, and sleep differed by age, sex, body mass index (BMI), smoking status, alcohol consumption, education, season, functional capacity, marital status, presence of chronic disease, and use of sleep medication.

Results: Mean total PA, expressed in milli-gravity (mg) units, was slightly higher for women (20.3, SD 5.6) than for men (19.3, SD 5.2, P < .01). Mean (SD) daily duration spent in sedentary behavior and light and moderate-to-vigorous PA was 13.3 (1.5) h/d, 147.5 (31.5) min/d, and 75.0 (25.5) min/d, respectively, among women; and 13.8 (1.6) h/d, 140.5 (31.1) min/d, and 71.5 (24.5) min/d, respectively, among men. Women spent on average 6.7 (SD 1.1) h/d sleeping and men 6.6 (1.4) h/d. Across increasing categories of age and BMI and in participants with chronic disease and disability, time spent in light and moderate-to-vigorous PA was decreased. Higher age and BMI were associated with more sedentary time. In addition, obese men spent slightly more time sleeping than their normal weight counterparts and women spent slightly less time sleeping in the summer than in spring.

Conclusions: PA and sedentary behavior in the elderly differed by sex, age, BMI, prevalence of chronic disease, and disability, whereas there were no clear patterns for sleep. On average, our participants spent up to 79.5% of their time awake being sedentary and 7%-8% in moderate-to-vigorous PA. Replacing sedentary behavior with light PA would be a good starting point for those with the lowest level of PA. Older adults, those with high BMI and worse health could benefit from targeted interventions to increase PA.
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http://dx.doi.org/10.1016/j.jamda.2017.04.017DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6276982PMC
October 2017

Meta-GWAS Accuracy and Power (MetaGAP) Calculator Shows that Hiding Heritability Is Partially Due to Imperfect Genetic Correlations across Studies.

PLoS Genet 2017 Jan 17;13(1):e1006495. Epub 2017 Jan 17.

Erasmus University Rotterdam Institute for Behavior and Biology, Erasmus School of Economics, Rotterdam, the Netherlands.

Large-scale genome-wide association results are typically obtained from a fixed-effects meta-analysis of GWAS summary statistics from multiple studies spanning different regions and/or time periods. This approach averages the estimated effects of genetic variants across studies. In case genetic effects are heterogeneous across studies, the statistical power of a GWAS and the predictive accuracy of polygenic scores are attenuated, contributing to the so-called 'missing heritability'. Here, we describe the online Meta-GWAS Accuracy and Power (MetaGAP) calculator (available at www.devlaming.eu) which quantifies this attenuation based on a novel multi-study framework. By means of simulation studies, we show that under a wide range of genetic architectures, the statistical power and predictive accuracy provided by this calculator are accurate. We compare the predictions from the MetaGAP calculator with actual results obtained in the GWAS literature. Specifically, we use genomic-relatedness-matrix restricted maximum likelihood to estimate the SNP heritability and cross-study genetic correlation of height, BMI, years of education, and self-rated health in three large samples. These estimates are used as input parameters for the MetaGAP calculator. Results from the calculator suggest that cross-study heterogeneity has led to attenuation of statistical power and predictive accuracy in recent large-scale GWAS efforts on these traits (e.g., for years of education, we estimate a relative loss of 51-62% in the number of genome-wide significant loci and a relative loss in polygenic score R2 of 36-38%). Hence, cross-study heterogeneity contributes to the missing heritability.
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http://dx.doi.org/10.1371/journal.pgen.1006495DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5240919PMC
January 2017

Genome-wide Trans-ethnic Meta-analysis Identifies Seven Genetic Loci Influencing Erythrocyte Traits and a Role for RBPMS in Erythropoiesis.

Am J Hum Genet 2017 Jan 22;100(1):51-63. Epub 2016 Dec 22.

Icahn Institute for Multiscale Biology, Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA.

Genome-wide association studies (GWASs) have identified loci for erythrocyte traits in primarily European ancestry populations. We conducted GWAS meta-analyses of six erythrocyte traits in 71,638 individuals from European, East Asian, and African ancestries using a Bayesian approach to account for heterogeneity in allelic effects and variation in the structure of linkage disequilibrium between ethnicities. We identified seven loci for erythrocyte traits including a locus (RBPMS/GTF2E2) associated with mean corpuscular hemoglobin and mean corpuscular volume. Statistical fine-mapping at this locus pointed to RBPMS at this locus and excluded nearby GTF2E2. Using zebrafish morpholino to evaluate loss of function, we observed a strong in vivo erythropoietic effect for RBPMS but not for GTF2E2, supporting the statistical fine-mapping at this locus and demonstrating that RBPMS is a regulator of erythropoiesis. Our findings show the utility of trans-ethnic GWASs for discovery and characterization of genetic loci influencing hematologic traits.
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http://dx.doi.org/10.1016/j.ajhg.2016.11.016DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5223059PMC
January 2017

Sedentary time assessed by actigraphy and mortality: The Rotterdam Study.

Prev Med 2017 02 6;95:59-65. Epub 2016 Dec 6.

Department of Epidemiology, Erasmus MC, University Medical Center Rotterdam, PO Box 2040, 3000 CA Rotterdam, The Netherlands; Department of Child and Adolescent Psychiatry, Erasmus MC, University Medical Center Rotterdam, PO Box 2040, 3000 CA Rotterdam, The Netherlands. Electronic address:

Research suggests that sedentary behavior is a risk factor for mortality. However, most studies rely on questionnaires, which are prone to reporting error. We examined the association between sedentary time assessed by actigraphy and mortality among 1839 participants, aged 45-98years, from the prospective population-based Rotterdam Study, enrolled between 2004 and 2007. Participants wore an actigraph around the wrist for seven days. Sedentary time was evaluated continuously, per 1h/day increase, and categorically in three groups (<8, 8-11, ≥11h/day). The lowest category was used as reference. Mortality risks were examined using Cox proportional hazard models, adjusted for confounders and biological risk factors. We examined the association between sedentary behavior and mortality over and beyond other activity measures (including physical activity (PA) and activities of daily living (ADL)) in a final model. During 11years of follow-up (median: 7.5years, interquartile range: 6.6-8.3years), 212 participants (11.5%) died. In the multivariable model, the hazard ratio (HR) and 95% confidence interval (95% CI) per 1 more hour/day sedentary time was 1.09 (1.00, 1.18). The HR (95% CI) after adjustment for PA and ADL was 1.04 (0.96, 1.13). Participants sedentary for ≥11h/day had a higher mortality risk (HR: 1.80, 95% CI: 1.14, 2.84) than those sedentary <8h/day, in the multivariable model. After adjusting for PA and ADL, this association was clearly attenuated (HR: 1.50, 95% CI: 0.93, 2.41). In conclusion, our study suggests that sedentary behavior is a risk factor for mortality. Further investigation is needed to examine whether this association is distinct from the effect of other measures of activity.
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http://dx.doi.org/10.1016/j.ypmed.2016.11.021DOI Listing
February 2017

Whole-Exome Sequencing Identifies Loci Associated with Blood Cell Traits and Reveals a Role for Alternative GFI1B Splice Variants in Human Hematopoiesis.

Am J Hum Genet 2016 08;99(2):481-8

Cardiovascular Health Research Unit and Department of Medicine, University of Washington, Seattle, WA 98195, USA.

Circulating blood cell counts and indices are important indicators of hematopoietic function and a number of clinical parameters, such as blood oxygen-carrying capacity, inflammation, and hemostasis. By performing whole-exome sequence association analyses of hematologic quantitative traits in 15,459 community-dwelling individuals, followed by in silico replication in up to 52,024 independent samples, we identified two previously undescribed coding variants associated with lower platelet count: a common missense variant in CPS1 (rs1047891, MAF = 0.33, discovery + replication p = 6.38 × 10(-10)) and a rare synonymous variant in GFI1B (rs150813342, MAF = 0.009, discovery + replication p = 1.79 × 10(-27)). By performing CRISPR/Cas9 genome editing in hematopoietic cell lines and follow-up targeted knockdown experiments in primary human hematopoietic stem and progenitor cells, we demonstrate an alternative splicing mechanism by which the GFI1B rs150813342 variant suppresses formation of a GFI1B isoform that preferentially promotes megakaryocyte differentiation and platelet production. These results demonstrate how unbiased studies of natural variation in blood cell traits can provide insight into the regulation of human hematopoiesis.
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http://dx.doi.org/10.1016/j.ajhg.2016.06.016DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4974169PMC
August 2016

Large-Scale Exome-wide Association Analysis Identifies Loci for White Blood Cell Traits and Pleiotropy with Immune-Mediated Diseases.

Am J Hum Genet 2016 Jul 23;99(1):22-39. Epub 2016 Jun 23.

Department of Genetics, University of North Carolina, Chapel Hill, NC 27514, USA.

White blood cells play diverse roles in innate and adaptive immunity. Genetic association analyses of phenotypic variation in circulating white blood cell (WBC) counts from large samples of otherwise healthy individuals can provide insights into genes and biologic pathways involved in production, differentiation, or clearance of particular WBC lineages (myeloid, lymphoid) and also potentially inform the genetic basis of autoimmune, allergic, and blood diseases. We performed an exome array-based meta-analysis of total WBC and subtype counts (neutrophils, monocytes, lymphocytes, basophils, and eosinophils) in a multi-ancestry discovery and replication sample of ∼157,622 individuals from 25 studies. We identified 16 common variants (8 of which were coding variants) associated with one or more WBC traits, the majority of which are pleiotropically associated with autoimmune diseases. Based on functional annotation, these loci included genes encoding surface markers of myeloid, lymphoid, or hematopoietic stem cell differentiation (CD69, CD33, CD87), transcription factors regulating lineage specification during hematopoiesis (ASXL1, IRF8, IKZF1, JMJD1C, ETS2-PSMG1), and molecules involved in neutrophil clearance/apoptosis (C10orf54, LTA), adhesion (TNXB), or centrosome and microtubule structure/function (KIF9, TUBD1). Together with recent reports of somatic ASXL1 mutations among individuals with idiopathic cytopenias or clonal hematopoiesis of undetermined significance, the identification of a common regulatory 3' UTR variant of ASXL1 suggests that both germline and somatic ASXL1 mutations contribute to lower blood counts in otherwise asymptomatic individuals. These association results shed light on genetic mechanisms that regulate circulating WBC counts and suggest a prominent shared genetic architecture with inflammatory and autoimmune diseases.
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http://dx.doi.org/10.1016/j.ajhg.2016.05.003DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5005433PMC
July 2016

Platelet-Related Variants Identified by Exomechip Meta-analysis in 157,293 Individuals.

Am J Hum Genet 2016 Jul 23;99(1):40-55. Epub 2016 Jun 23.

Department of Cardiology, Heart Center, Tampere University Hospital, Tampere 33521, Finland; University of Tampere, School of Medicine, Tampere 33514, Finland.

Platelet production, maintenance, and clearance are tightly controlled processes indicative of platelets' important roles in hemostasis and thrombosis. Platelets are common targets for primary and secondary prevention of several conditions. They are monitored clinically by complete blood counts, specifically with measurements of platelet count (PLT) and mean platelet volume (MPV). Identifying genetic effects on PLT and MPV can provide mechanistic insights into platelet biology and their role in disease. Therefore, we formed the Blood Cell Consortium (BCX) to perform a large-scale meta-analysis of Exomechip association results for PLT and MPV in 157,293 and 57,617 individuals, respectively. Using the low-frequency/rare coding variant-enriched Exomechip genotyping array, we sought to identify genetic variants associated with PLT and MPV. In addition to confirming 47 known PLT and 20 known MPV associations, we identified 32 PLT and 18 MPV associations not previously observed in the literature across the allele frequency spectrum, including rare large effect (FCER1A), low-frequency (IQGAP2, MAP1A, LY75), and common (ZMIZ2, SMG6, PEAR1, ARFGAP3/PACSIN2) variants. Several variants associated with PLT/MPV (PEAR1, MRVI1, PTGES3) were also associated with platelet reactivity. In concurrent BCX analyses, there was overlap of platelet-associated variants with red (MAP1A, TMPRSS6, ZMIZ2) and white (PEAR1, ZMIZ2, LY75) blood cell traits, suggesting common regulatory pathways with shared genetic architecture among these hematopoietic lineages. Our large-scale Exomechip analyses identified previously undocumented associations with platelet traits and further indicate that several complex quantitative hematological, lipid, and cardiovascular traits share genetic factors.
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http://dx.doi.org/10.1016/j.ajhg.2016.05.005DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5005441PMC
July 2016

Exome Genotyping Identifies Pleiotropic Variants Associated with Red Blood Cell Traits.

Am J Hum Genet 2016 Jul 23;99(1):8-21. Epub 2016 Jun 23.

Department of Biomedical Informatics and Medical Education, University of Washington, Seattle, WA 98195, USA.

Red blood cell (RBC) traits are important heritable clinical biomarkers and modifiers of disease severity. To identify coding genetic variants associated with these traits, we conducted meta-analyses of seven RBC phenotypes in 130,273 multi-ethnic individuals from studies genotyped on an exome array. After conditional analyses and replication in 27,480 independent individuals, we identified 16 new RBC variants. We found low-frequency missense variants in MAP1A (rs55707100, minor allele frequency [MAF] = 3.3%, p = 2 × 10(-10) for hemoglobin [HGB]) and HNF4A (rs1800961, MAF = 2.4%, p < 3 × 10(-8) for hematocrit [HCT] and HGB). In African Americans, we identified a nonsense variant in CD36 associated with higher RBC distribution width (rs3211938, MAF = 8.7%, p = 7 × 10(-11)) and showed that it is associated with lower CD36 expression and strong allelic imbalance in ex vivo differentiated human erythroblasts. We also identified a rare missense variant in ALAS2 (rs201062903, MAF = 0.2%) associated with lower mean corpuscular volume and mean corpuscular hemoglobin (p < 8 × 10(-9)). Mendelian mutations in ALAS2 are a cause of sideroblastic anemia and erythropoietic protoporphyria. Gene-based testing highlighted three rare missense variants in PKLR, a gene mutated in Mendelian non-spherocytic hemolytic anemia, associated with HGB and HCT (SKAT p < 8 × 10(-7)). These rare, low-frequency, and common RBC variants showed pleiotropy, being also associated with platelet, white blood cell, and lipid traits. Our association results and functional annotation suggest the involvement of new genes in human erythropoiesis. We also confirm that rare and low-frequency variants play a role in the architecture of complex human traits, although their phenotypic effect is generally smaller than originally anticipated.
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http://dx.doi.org/10.1016/j.ajhg.2016.05.007DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5005438PMC
July 2016
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