| 21. |
- Wang, Z., et al.
(author)
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Genome-wide association analyses of physical activity and sedentary behavior provide insights into underlying mechanisms and roles in disease prevention
- 2022
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In: Nature Genetics. - : Springer Science and Business Media LLC. - 1061-4036 .- 1546-1718. ; 54:9, s. 1332-1344
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Journal article (peer-reviewed)abstract
- Although physical activity and sedentary behavior are moderately heritable, little is known about the mechanisms that influence these traits. Combining data for up to 703,901 individuals from 51 studies in a multi-ancestry meta-analysis of genome-wide association studies yields 99 loci that associate with self-reported moderate-to-vigorous intensity physical activity during leisure time (MVPA), leisure screen time (LST) and/or sedentary behavior at work. Loci associated with LST are enriched for genes whose expression in skeletal muscle is altered by resistance training. A missense variant in ACTN3 makes the alpha-actinin-3 filaments more flexible, resulting in lower maximal force in isolated type IIA muscle fibers, and possibly protection from exercise-induced muscle damage. Finally, Mendelian randomization analyses show that beneficial effects of lower LST and higher MVPA on several risk factors and diseases are mediated or confounded by body mass index (BMI). Our results provide insights into physical activity mechanisms and its role in disease prevention. Multi-ancestry meta-analyses of genome-wide association studies for self-reported physical activity during leisure time, leisure screen time, sedentary commuting and sedentary behavior at work identify 99 loci associated with at least one of these traits.
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| 22. |
- Beral, V., et al.
(author)
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Ovarian Cancer and Body Size : Individual Participant Meta-Analysis Including 25,157 Women with Ovarian Cancer from 47 Epidemiological Studies
- 2012
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In: PLoS Medicine. - : PUBLIC LIBRARY SCIENCE. - 1549-1277 .- 1549-1676. ; 9:4
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Journal article (peer-reviewed)abstract
- Background: Only about half the studies that have collected information on the relevance of women's height and body mass index to their risk of developing ovarian cancer have published their results, and findings are inconsistent. Here, we bring together the worldwide evidence, published and unpublished, and describe these relationships. Methods and Findings: Individual data on 25,157 women with ovarian cancer and 81,311 women without ovarian cancer from 47 epidemiological studies were collected, checked, and analysed centrally. Adjusted relative risks of ovarian cancer were calculated, by height and by body mass index. Ovarian cancer risk increased significantly with height and with body mass index, except in studies using hospital controls. For other study designs, the relative risk of ovarian cancer per 5 cm increase in height was 1.07 (95% confidence interval [CI], 1.05-1.09; p<0.001); this relationship did not vary significantly by women's age, year of birth, education, age at menarche, parity, menopausal status, smoking, alcohol consumption, having had a hysterectomy, having first degree relatives with ovarian or breast cancer, use of oral contraceptives, or use of menopausal hormone therapy. For body mass index, there was significant heterogeneity (p<0.001) in the findings between ever-users and never-users of menopausal hormone therapy, but not by the 11 other factors listed above. The relative risk for ovarian cancer per 5 kg/m(2) increase in body mass index was 1.10 (95% CI, 1.07-1.13; p<0.001) in never-users and 0.95 (95% CI, 0.92-0.99; p = 0.02) in ever-users of hormone therapy. Conclusions: Ovarian cancer is associated with height and, among never-users of hormone therapy, with body mass index. In high-income countries, both height and body mass index have been increasing in birth cohorts now developing the disease. If all other relevant factors had remained constant, then these increases in height and weight would be associated with a 3% increase in ovarian cancer incidence per decade.
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| 23. |
- Gapstur, S. M., et al.
(author)
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Menopausal hormone use and ovarian cancer risk: individual participant meta-analysis of 52 epidemiological studies
- 2015
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In: The Lancet. - 1474-547X. ; 385:9980, s. 1835-1842
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Journal article (peer-reviewed)abstract
- Background Half the epidemiological studies with information about menopausal hormone therapy and ovarian cancer risk remain unpublished, and some retrospective studies could have been biased by selective participation or recall. We aimed to assess with minimal bias the effects of hormone therapy on ovarian cancer risk. Methods Individual participant datasets from 52 epidemiological studies were analysed centrally. The principal analyses involved the prospective studies (with last hormone therapy use extrapolated forwards for up to 4 years). Sensitivity analyses included the retrospective studies. Adjusted Poisson regressions yielded relative risks (RRs) versus never-use. Findings During prospective follow-up, 12 110 postmenopausal women, 55% (6601) of whom had used hormone therapy, developed ovarian cancer. Among women last recorded as current users, risk was increased even with <5 years of use (RR 1.43, 95% CI 1.31-1.56; p<0.0001). Combining current-or-recent use (any duration, but stopped <5 years before diagnosis) resulted in an RR of 1.37 (95% CI 1.29-1.46; p<0.0001); this risk was similar in European and American prospective studies and for oestrogen-only and oestrogen-progestagen preparations, but differed across the four main tumour types (heterogeneity p<0.0001), being definitely increased only for the two most common types, serous (RR 1.53, 95% CI 1.40-1.66; p<0.0001) and endometrioid (1.42, 1.20-1.67; p<0.0001). Risk declined the longer ago use had ceased, although about 10 years after stopping long-duration hormone therapy use there was still an excess of serous or endometrioid tumours (RR 1.25, 95% CI 1.07-1.46, p=0.005). Interpretation The increased risk may well be largely or wholly causal; if it is, women who use hormone therapy for 5 years from around age 50 years have about one extra ovarian cancer per 1000 users and, if its prognosis is typical, about one extra ovarian cancer death per 1700 users.
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| 24. |
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| 25. |
- Silventoinen, K., et al.
(author)
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The CODATwins Project : The current status and recent findings of COllaborative Project of Development of Anthropometrical Measures in Twins
- 2019
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In: Twin Research and Human Genetics. - : Cambridge University Press. - 1832-4274 .- 1839-2628. ; 22:6, s. 800-808
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Journal article (peer-reviewed)abstract
- The COllaborative project of Development of Anthropometrical measures in Twins (CODATwins) project is a large international collaborative effort to analyze individual-level phenotype data from twins in multiple cohorts from different environments. The main objective is to study factors that modify genetic and environmental variation of height, body mass index (BMI, kg/m2) and size at birth, and additionally to address other research questions such as long-term consequences of birth size. The project started in 2013 and is open to all twin projects in the world having height and weight measures on twins with information on zygosity. Thus far, 54 twin projects from 24 countries have provided individual-level data. The CODATwins database includes 489,981 twin individuals (228,635 complete twin pairs). Since many twin cohorts have collected longitudinal data, there is a total of 1,049,785 height and weight observations. For many cohorts, we also have information on birth weight and length, own smoking behavior and own or parental education. We found that the heritability estimates of height and BMI systematically changed from infancy to old age. Remarkably, only minor differences in the heritability estimates were found across cultural-geographic regions, measurement time and birth cohort for height and BMI. In addition to genetic epidemiological studies, we looked at associations of height and BMI with education, birth weight and smoking status. Within-family analyses examined differences within same-sex and opposite-sex dizygotic twins in birth size and later development. The CODATwins project demonstrates the feasibility and value of international collaboration to address gene-by-exposure interactions that require large sample sizes and address the effects of different exposures across time, geographical regions and socioeconomic status.
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| 26. |
- Smith, Jennifer A, et al.
(author)
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Genome-wide association study identifies 74 loci associated with educational attainment
- 2016
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In: Nature (London). - : Springer Science and Business Media LLC. - 1476-4687 .- 0028-0836. ; 533:7604, s. 539-542
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Journal article (peer-reviewed)abstract
- Educational attainment is strongly influenced by social and other environmental factors, but genetic factors are estimated to account for at least 20% of the variation across individuals. Here we report the results of a genome-wide association study (GWAS) for educational attainment that extends our earlier discovery sample of 101,069 individuals to 293,723 individuals, and a replication study in an independent sample of 111,349 individuals from the UK Biobank. We identify 74 genome-wide significant loci associated with the number of years of schooling completed. Single-nucleotide polymorphisms associated with educational attainment are disproportionately found in genomic regions regulating gene expression in the fetal brain. Candidate genes are preferentially expressed in neural tissue, especially during the prenatal period, and enriched for biological pathways involved in neural development. Our findings demonstrate that, even for a behavioural phenotype that is mostly environmentally determined, a well-powered GWAS identifies replicable associated genetic variants that suggest biologically relevant pathways. Because educational attainment is measured in large numbers of individuals, it will continue to be useful as a proxy phenotype in efforts to characterize the genetic influences of related phenotypes, including cognition and neuropsychiatric diseases.
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| 27. |
- Wightman, D. P., et al.
(author)
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A genome-wide association study with 1,126,563 individuals identifies new risk loci for Alzheimer’s disease
- 2021
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In: Nature Genetics. - : Springer Nature. - 1061-4036 .- 1546-1718. ; 53:9, s. 1276-1282
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Journal article (peer-reviewed)abstract
- Late-onset Alzheimer’s disease is a prevalent age-related polygenic disease that accounts for 50–70% of dementia cases. Currently, only a fraction of the genetic variants underlying Alzheimer’s disease have been identified. Here we show that increased sample sizes allowed identification of seven previously unidentified genetic loci contributing to Alzheimer’s disease. This study highlights microglia, immune cells and protein catabolism as relevant to late-onset Alzheimer’s disease, while identifying and prioritizing previously unidentified genes of potential interest. We anticipate that these results can be included in larger meta-analyses of Alzheimer’s disease to identify further genetic variants that contribute to Alzheimer’s pathology.
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| 28. |
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| 29. |
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| 30. |
- Czamara, D, et al.
(author)
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Integrated analysis of environmental and genetic influences on cord blood DNA methylation in new-borns
- 2019
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In: Nature communications. - : Springer Science and Business Media LLC. - 2041-1723. ; 10:1, s. 2548-
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Journal article (peer-reviewed)abstract
- Epigenetic processes, including DNA methylation (DNAm), are among the mechanisms allowing integration of genetic and environmental factors to shape cellular function. While many studies have investigated either environmental or genetic contributions to DNAm, few have assessed their integrated effects. Here we examine the relative contributions of prenatal environmental factors and genotype on DNA methylation in neonatal blood at variably methylated regions (VMRs) in 4 independent cohorts (overall n = 2365). We use Akaike’s information criterion to test which factors best explain variability of methylation in the cohort-specific VMRs: several prenatal environmental factors (E), genotypes in cis (G), or their additive (G + E) or interaction (GxE) effects. Genetic and environmental factors in combination best explain DNAm at the majority of VMRs. The CpGs best explained by either G, G + E or GxE are functionally distinct. The enrichment of genetic variants from GxE models in GWAS for complex disorders supports their importance for disease risk.
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