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- Bais, A. F., et al.
(author)
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Environmental effects of ozone depletion, UV radiation and interactions with climate change: UNEP Environmental Effects Assessment Panel, update 2017
- 2018
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In: Photochemical & Photobiological Sciences. - : Springer Science and Business Media LLC. - 1474-905X .- 1474-9092. ; 17:2, s. 127-179
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Journal article (peer-reviewed)abstract
- The Environmental Effects Assessment Panel (EEAP) is one of three Panels of experts that inform the Parties to the Montreal Protocol. The EEAP focuses on the effects of UV radiation on human health, terrestrial and aquatic ecosystems, air quality, and materials, as well as on the interactive effects of UV radiation and global climate change. When considering the effects of climate change, it has become clear that processes resulting in changes in stratospheric ozone are more complex than previously held. Because of the Montreal Protocol, there are now indications of the beginnings of a recovery of stratospheric ozone, although the time required to reach levels like those before the 1960s is still uncertain, particularly as the effects of stratospheric ozone on climate change and vice versa, are not yet fully understood. Some regions will likely receive enhanced levels of UV radiation, while other areas will likely experience a reduction in UV radiation as ozone- and climate-driven changes affect the amounts of UV radiation reaching the Earth's surface. Like the other Panels, the EEAP produces detailed Quadrennial Reports every four years; the most recent was published as a series of seven papers in 2015 (Photochem. Photobiol. Sci., 2015, 14, 1-184). In the years in between, the EEAP produces less detailed and shorter Update Reports of recent and relevant scientific findings. The most recent of these was for 2016 (Photochem. Photobiol. Sci., 2017, 16, 107-145). The present 2017 Update Report assesses some of the highlights and new insights about the interactive nature of the direct and indirect effects of UV radiation, atmospheric processes, and climate change. A full 2018 Quadrennial Assessment, will be made available in 2018/2019.
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- Manning, Alisa, et al.
(author)
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A Low-Frequency Inactivating AKT2 Variant Enriched in the Finnish Population Is Associated With Fasting Insulin Levels and Type 2 Diabetes Risk
- 2017
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In: Diabetes. - : AMER DIABETES ASSOC. - 0012-1797 .- 1939-327X. ; 66:7, s. 2019-2032
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Journal article (peer-reviewed)abstract
- To identify novel coding association signals and facilitate characterization of mechanisms influencing glycemic traits and type 2 diabetes risk, we analyzed 109,215 variants derived from exome array genotyping together with an additional 390,225 variants from exome sequence in up to 39,339 normoglycemic individuals from five ancestry groups. We identified a novel association between the coding variant (p.Pro50Thr) in AKT2 and fasting plasma insulin (FI), a gene in which rare fully penetrant mutations are causal for monogenic glycemic disorders. The low-frequency allele is associated with a 12% increase in FI levels. This variant is present at 1.1% frequency in Finns but virtually absent in individuals from other ancestries. Carriers of the FI-increasing allele had increased 2-h insulin values, decreased insulin sensitivity, and increased risk of type 2 diabetes (odds ratio 1.05). In cellular studies, the AKT2-Thr50 protein exhibited a partial loss of function. We extend the allelic spectrum for coding variants in AKT2 associated with disorders of glucose homeostasis and demonstrate bidirectional effects of variants within the pleckstrin homology domain of AKT2.
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- Weiner, D. J., et al.
(author)
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Polygenic transmission disequilibrium confirms that common and rare variation act additively to create risk for autism spectrum disorders
- 2017
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In: Nature Genetics. - : Springer Science and Business Media LLC. - 1061-4036 .- 1546-1718. ; 49:7
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Journal article (peer-reviewed)abstract
- Autism spectrum disorder (ASD) risk is influenced by common polygenic and de novo variation. We aimed to clarify the influence of polygenic risk for ASD and to identify subgroups of ASD cases, including those with strongly acting de novo variants, in which polygenic risk is relevant. Using a novel approach called the polygenic transmission disequilibrium test and data from 6,454 families with a child with ASD, we show that polygenic risk for ASD, schizophrenia, and greater educational attainment is over-transmitted to children with ASD. These findings hold independent of proband IQ. We find that polygenic variation contributes additively to risk in ASD cases who carry a strongly acting de novo variant. Lastly, we show that elements of polygenic risk are independent and differ in their relationship with phenotype. These results confirm that the genetic influences on ASD are additive and suggest that they create risk through at least partially distinct etiologic pathways.
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- Anney, R. J. L., et al.
(author)
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Meta-analysis of GWAS of over 16,000 individuals with autism spectrum disorder highlights a novel locus at 10q24.32 and a significant overlap with schizophrenia
- 2017
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In: Molecular Autism. - : Springer Science and Business Media LLC. - 2040-2392. ; 8
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Journal article (peer-reviewed)abstract
- Background: Over the past decade genome-wide association studies (GWAS) have been applied to aid in the understanding of the biology of traits. The success of this approach is governed by the underlying effect sizes carried by the true risk variants and the corresponding statistical power to observe such effects given the study design and sample size under investigation. Previous ASD GWAS have identified genome-wide significant (GWS) risk loci; however, these studies were of only of low statistical power to identify GWS loci at the lower effect sizes (odds ratio (OR) < 1.15). Methods: We conducted a large-scale coordinated international collaboration to combine independent genotyping data to improve the statistical power and aid in robust discovery of GWS loci. This study uses genome-wide genotyping data from a discovery sample (7387 ASD cases and 8567 controls) followed by meta-analysis of summary statistics from two replication sets (7783 ASD cases and 11359 controls; and 1369 ASD cases and 137308 controls). Results: We observe a GWS locus at 10q24.32 that overlaps several genes including PITX3, which encodes a transcription factor identified as playing a role in neuronal differentiation and CUEDC2 previously reported to be associated with social skills in an independent population cohort. We also observe overlap with regions previously implicated in schizophrenia which was further supported by a strong genetic correlation between these disorders (Rg = 0.23; P= 9 x10(-6)). We further combined these Psychiatric Genomics Consortium (PGC) ASD GWAS data with the recent PGC schizophrenia GWAS to identify additional regions which may be important in a common neurodevelopmental phenotype and identified 12 novel GWS loci. These include loci previously implicated in ASD such as FOXP1 at 3p13, ATP2B2 at 3p25.3, and a 'neurodevelopmental hub' on chromosome 8p11.23. Conclusions: This study is an important step in the ongoing endeavour to identify the loci which underpin the common variant signal in ASD. In addition to novel GWS loci, we have identified a significant genetic correlation with schizophrenia and association of ASD with several neurodevelopmental- related genes such as EXT1, ASTN2, MACROD2, and HDAC4.
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- Flannick, Jason, et al.
(author)
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Data Descriptor : Sequence data and association statistics from 12,940 type 2 diabetes cases and controls
- 2017
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In: Scientific Data. - : Springer Science and Business Media LLC. - 2052-4463. ; 4
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Journal article (peer-reviewed)abstract
- To investigate the genetic basis of type 2 diabetes (T2D) to high resolution, the GoT2D and T2D-GENES consortia catalogued variation from whole-genome sequencing of 2,657 European individuals and exome sequencing of 12,940 individuals of multiple ancestries. Over 27M SNPs, indels, and structural variants were identified, including 99% of low-frequency (minor allele frequency [MAF] 0.1-5%) non-coding variants in the whole-genome sequenced individuals and 99.7% of low-frequency coding variants in the whole-exome sequenced individuals. Each variant was tested for association with T2D in the sequenced individuals, and, to increase power, most were tested in larger numbers of individuals (> 80% of low-frequency coding variants in similar to ~82 K Europeans via the exome chip, and similar to ~90% of low-frequency non-coding variants in similar to ~44 K Europeans via genotype imputation). The variants, genotypes, and association statistics from these analyses provide the largest reference to date of human genetic information relevant to T2D, for use in activities such as T2D-focused genotype imputation, functional characterization of variants or genes, and other novel analyses to detect associations between sequence variation and T2D.
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- Fuchsberger, Christian, et al.
(author)
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The genetic architecture of type 2 diabetes
- 2016
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In: Nature. - : Springer Science and Business Media LLC. - 0028-0836 .- 1476-4687. ; 536:7614, s. 41-47
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Journal article (peer-reviewed)abstract
- The genetic architecture of common traits, including the number, frequency, and effect sizes of inherited variants that contribute to individual risk, has been long debated. Genome-wide association studies have identified scores of common variants associated with type 2 diabetes, but in aggregate, these explain only a fraction of the heritability of this disease. Here, to test the hypothesis that lower-frequency variants explain much of the remainder, the GoT2D and T2D-GENES consortia performed whole-genome sequencing in 2,657 European individuals with and without diabetes, and exome sequencing in 12,940 individuals from five ancestry groups. To increase statistical power, we expanded the sample size via genotyping and imputation in a further 111,548 subjects. Variants associated with type 2 diabetes after sequencing were overwhelmingly common and most fell within regions previously identified by genome-wide association studies. Comprehensive enumeration of sequence variation is necessary to identify functional alleles that provide important clues to disease pathophysiology, but large-scale sequencing does not support the idea that lower-frequency variants have a major role in predisposition to type 2 diabetes.
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