| 11. |
- Shungin, Dmitry, et al.
(author)
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New genetic loci link adipose and insulin biology to body fat distribution.
- 2015
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In: Nature. - : Springer Science and Business Media LLC. - 0028-0836 .- 1476-4687. ; 518:7538, s. 187-378
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Journal article (peer-reviewed)abstract
- Body fat distribution is a heritable trait and a well-established predictor of adverse metabolic outcomes, independent of overall adiposity. To increase our understanding of the genetic basis of body fat distribution and its molecular links to cardiometabolic traits, here we conduct genome-wide association meta-analyses of traits related to waist and hip circumferences in up to 224,459 individuals. We identify 49 loci (33 new) associated with waist-to-hip ratio adjusted for body mass index (BMI), and an additional 19 loci newly associated with related waist and hip circumference measures (P < 5 × 10(-8)). In total, 20 of the 49 waist-to-hip ratio adjusted for BMI loci show significant sexual dimorphism, 19 of which display a stronger effect in women. The identified loci were enriched for genes expressed in adipose tissue and for putative regulatory elements in adipocytes. Pathway analyses implicated adipogenesis, angiogenesis, transcriptional regulation and insulin resistance as processes affecting fat distribution, providing insight into potential pathophysiological mechanisms.
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| 12. |
- Speliotes, Elizabeth K., et al.
(author)
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Association analyses of 249,796 individuals reveal 18 new loci associated with body mass index
- 2010
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In: Nature Genetics. - : Springer Science and Business Media LLC. - 1061-4036 .- 1546-1718. ; 42:11, s. 937-948
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Journal article (peer-reviewed)abstract
- Obesity is globally prevalent and highly heritable, but its underlying genetic factors remain largely elusive. To identify genetic loci for obesity susceptibility, we examined associations between body mass index and ~2.8 million SNPs in up to 123,865 individuals with targeted follow up of 42 SNPs in up to 125,931 additional individuals. We confirmed 14 known obesity susceptibility loci and identified 18 new loci associated with body mass index (P < 5 × 10−8), one of which includes a copy number variant near GPRC5B. Some loci (at MC4R, POMC, SH2B1 and BDNF) map near key hypothalamic regulators of energy balance, and one of these loci is near GIPR, an incretin receptor. Furthermore, genes in other newly associated loci may provide new insights into human body weight regulation.
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| 13. |
- Thompson, Paul M., et al.
(author)
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The ENIGMA Consortium : large-scale collaborative analyses of neuroimaging and genetic data
- 2014
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In: BRAIN IMAGING BEHAV. - : Springer Science and Business Media LLC. - 1931-7557 .- 1931-7565. ; 8:2, s. 153-182
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Journal article (peer-reviewed)abstract
- The Enhancing NeuroImaging Genetics through Meta-Analysis (ENIGMA) Consortium is a collaborative network of researchers working together on a range of large-scale studies that integrate data from 70 institutions worldwide. Organized into Working Groups that tackle questions in neuroscience, genetics, and medicine, ENIGMA studies have analyzed neuroimaging data from over 12,826 subjects. In addition, data from 12,171 individuals were provided by the CHARGE consortium for replication of findings, in a total of 24,997 subjects. By meta-analyzing results from many sites, ENIGMA has detected factors that affect the brain that no individual site could detect on its own, and that require larger numbers of subjects than any individual neuroimaging study has currently collected. ENIGMA's first project was a genome-wide association study identifying common variants in the genome associated with hippocampal volume or intracranial volume. Continuing work is exploring genetic associations with subcortical volumes (ENIGMA2) and white matter microstructure (ENIGMA-DTI). Working groups also focus on understanding how schizophrenia, bipolar illness, major depression and attention deficit/hyperactivity disorder (ADHD) affect the brain. We review the current progress of the ENIGMA Consortium, along with challenges and unexpected discoveries made on the way.
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| 14. |
- Watts, Nick, et al.
(author)
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Health and climate change : policy responses to protect public health
- 2015
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In: The Lancet. - 0140-6736 .- 1474-547X. ; 386:10006, s. 1861-1914
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Research review (peer-reviewed)abstract
- The 2015 Lancet Commission on Health and Climate Change has been formed to map out the impacts of climate change, and the necessary policy responses, in order to ensure the highest attainable standards of health for populations worldwide. This Commission is multidisciplinary and international in nature, with strong collaboration between academic centres in Europe and China. The central finding from the Commission's work is that tackling climate change could be the greatest global health opportunity of the 21st century. The key messages from the Commission are summarised below, accompanied by ten underlying recommendations to accelerate action in the next 5 years.
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| 15. |
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| 16. |
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| 17. |
- Watts, Nick, et al.
(author)
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The 2020 report of The Lancet Countdown on health and climate change : responding to converging crises
- 2021
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In: The Lancet. - : Elsevier. - 0140-6736 .- 1474-547X. ; 397:10269, s. 129-170
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Research review (peer-reviewed)abstract
- The Lancet Countdown is an international collaboration established to provide an independent, global monitoring system dedicated to tracking the emerging health profile of the changing climate.The 2020 report presents 43 indicators across five sections: climate change impacts, exposures, and vulnerabilities; adaptation, planning, and resilience for health; mitigation actions and health co-benefits; economics and finance; and public and political engagement. This report represents the findings and consensus of the 35 leading academic institutions and UN agencies that make up The Lancet Countdown, and draws on the expertise of climate scientists, geographers, engineers, experts in energy, food, and transport, economists, social, and political scientists, data scientists, public health professionals, and doctors.
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| 18. |
- Watts, Nick, et al.
(author)
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The Lancet Countdown : tracking progress on health and climate change
- 2017
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In: The Lancet. - 0140-6736 .- 1474-547X. ; 389:10074, s. 1151-1164
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Research review (peer-reviewed)abstract
- The Lancet Countdown: tracking progress on health and climate change is an international, multidisciplinary research collaboration between academic institutions and practitioners across the world. It follows on from the work of the 2015 Lancet Commission, which concluded that the response to climate change could be "the greatest global health opportunity of the 21st century". The Lancet Countdown aims to track the health impacts of climate hazards; health resilience and adaptation; health co-benefits of climate change mitigation; economics and finance; and political and broader engagement. These focus areas form the five thematic working groups of the Lancet Countdown and represent different aspects of the complex association between health and climate change. These thematic groups will provide indicators for a global overview of health and climate change; national case studies highlighting countries leading the way or going against the trend; and engagement with a range of stakeholders. The Lancet Countdown ultimately aims to report annually on a series of indicators across these five working groups. This paper outlines the potential indicators and indicator domains to be tracked by the collaboration, with suggestions on the methodologies and datasets available to achieve this end. The proposed indicator domains require further refinement, and mark the beginning of an ongoing consultation process-from November, 2016 to early 2017-to develop these domains, identify key areas not currently covered, and change indicators where necessary. This collaboration will actively seek to engage with existing monitoring processes, such as the UN Sustainable Development Goals and WHO's climate and health country profiles. The indicators will also evolve over time through ongoing collaboration with experts and a range of stakeholders, and be dependent on the emergence of new evidence and knowledge. During the course of its work, the Lancet Countdown will adopt a collaborative and iterative process, which aims to complement existing initiatives, welcome engagement with new partners, and be open to developing new research projects on health and climate change.
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| 19. |
- Watts, Nick, et al.
(author)
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The Lancet Countdown on health and climate change : from 25 years of inaction to a global transformation for public health
- 2018
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In: The Lancet. - : Elsevier. - 0140-6736 .- 1474-547X. ; 391:10120, s. 581-630
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Research review (peer-reviewed)abstract
- The Lancet Countdown tracks progress on health and climate change and provides an independent assessment of the health effects of climate change, the implementation of the Paris Agreement, 1 and the health implications of these actions. It follows on from the work of the 2015 Lancet Commission on Health and Climate Change, 2 which concluded that anthropogenic climate change threatens to undermine the past 50 years of gains in public health, and conversely, that a comprehensive response to climate change could be "the greatest global health opportunity of the 21st century". The Lancet Countdown is a collaboration between 24 academic institutions and intergovernmental organisations based in every continent and with representation from a wide range of disciplines. The collaboration includes climate scientists, ecologists, economists, engineers, experts in energy, food, and transport systems, geographers, mathematicians, social and political scientists, public health professionals, and doctors. It reports annual indicators across five sections: climate change impacts, exposures, and vulnerability; adaptation planning and resilience for health; mitigation actions and health co-benefits; economics and finance; and public and political engagement. The key messages from the 40 indicators in the Lancet Countdown's 2017 report are summarised below.
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| 20. |
- Yang, Jian, et al.
(author)
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FTO genotype is associated with phenotypic variability of body mass index
- 2012
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In: Nature. - : Springer Science and Business Media LLC. - 0028-0836 .- 1476-4687. ; 490:7419, s. 267-272
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Journal article (peer-reviewed)abstract
- There is evidence across several species for genetic control of phenotypic variation of complex traits(1-4), such that the variance among phenotypes is genotype dependent. Understanding genetic control of variability is important in evolutionary biology, agricultural selection programmes and human medicine, yet for complex traits, no individual genetic variants associated with variance, as opposed to the mean, have been identified. Here we perform a meta-analysis of genome-wide association studies of phenotypic variation using similar to 170,000 samples on height and body mass index (BMI) in human populations. We report evidence that the single nucleotide polymorphism (SNP) rs7202116 at the FTO gene locus, which is known to be associated with obesity (as measured by mean BMI for each rs7202116 genotype)(5-7), is also associated with phenotypic variability. We show that the results are not due to scale effects or other artefacts, and find no other experiment-wise significant evidence for effects on variability, either at loci other than FTO for BMI or at any locus for height. The difference in variance for BMI among individuals with opposite homozygous genotypes at the FTO locus is approximately 7%, corresponding to a difference of similar to 0.5 kilograms in the standard deviation of weight. Our results indicate that genetic variants can be discovered that are associated with variability, and that between-person variability in obesity can partly be explained by the genotype at the FTO locus. The results are consistent with reported FTO by environment interactions for BMI8, possibly mediated by DNA methylation(9,10). Our BMI results for other SNPs and our height results for all SNPs suggest that most genetic variants, including those that influence mean height or mean BMI, are not associated with phenotypic variance, or that their effects on variability are too small to detect even with samples sizes greater than 100,000.
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