| 1. |
- Niemi, MEK, et al.
(author)
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- 2021
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swepub:Mat__t
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| 2. |
- Kanai, M, et al.
(author)
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- 2023
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swepub:Mat__t
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| 3. |
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| 4. |
- Blunden, Jessica, et al.
(author)
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State of the Climate in 2012
- 2013
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In: Bulletin of The American Meteorological Society - (BAMS). - 0003-0007 .- 1520-0477. ; 94:8, s. S1-S258
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Journal article (peer-reviewed)abstract
- For the first time in serveral years, the El Nino-Southern Oscillation did not dominate regional climate conditions around the globe. A weak La Ni a dissipated to ENSOneutral conditions by spring, and while El Nino appeared to be emerging during summer, this phase never fully developed as sea surface temperatures in the eastern conditions. Nevertheless, other large-scale climate patterns and extreme weather events impacted various regions during the year. A negative phase of the Arctic Oscillation from mid-January to early February contributed to frigid conditions in parts of northern Africa, eastern Europe, and western Asia. A lack of rain during the 2012 wet season led to the worst drought in at least the past three decades for northeastern Brazil. Central North America also experienced one of its most severe droughts on record. The Caribbean observed a very wet dry season and it was the Sahel's wettest rainy season in 50 years. Overall, the 2012 average temperature across global land and ocean surfaces ranked among the 10 warmest years on record. The global land surface temperature alone was also among the 10 warmest on record. In the upper atmosphere, the average stratospheric temperature was record or near-record cold, depending on the dataset. After a 30-year warming trend from 1970 to 1999 for global sea surface temperatures, the period 2000-12 had little further trend. This may be linked to the prevalence of La Ni a-like conditions during the 21st century. Heat content in the upper 700 m of the ocean remained near record high levels in 2012. Net increases from 2011 to 2012 were observed at 700-m to 2000-m depth and even in the abyssal ocean below. Following sharp decreases in to the effects of La Ni a, sea levels rebounded to reach records highs in 2012. The increased hydrological cycle seen in recent years continued, with more evaporation in drier locations and more precipitation in rainy areas. In a pattern that has held since 2004, salty areas of the ocean surfaces and subsurfaces were anomalously salty on average, while fresher areas were anomalously fresh. Global tropical cyclone activity during 2012 was near average, with a total of 84 storms compared with the 1981-2010 average of 89. Similar to 2010 and 2011, the North Atlantic was the only hurricane basin that experienced above-normal activity. In this basin, Sandy brought devastation to Cuba and parts of the eastern North American seaboard. All other basins experienced either near-or below-normal tropical cyclone activity. Only three tropical cyclones reached Category 5 intensity-all in Bopha became the only storm in the historical record to produce winds greater than 130 kt south of 7 N. It was also the costliest storm to affect the Philippines and killed more than 1000 residents. Minimum Arctic sea ice extent in September and Northern Hemisphere snow cover extent in June both reached new record lows. June snow cover extent is now declining at a faster rate (-17.6% per decade) than September sea ice extent (-13.0% per decade). Permafrost temperatures reached record high values in northernmost Alaska. A new melt extent record occurred on 11-12 July on the Greenland ice sheet; 97% of the ice sheet showed some form of melt, four times greater than the average melt for this time of year. The climate in Antarctica was relatively stable overall. The largest maximum sea ice extent since records begain in 1978 was observed in September 2012. In the stratosphere, warm air led to the second smallest ozone hole in the past two decades. Even so, the springtime ozone layer above Antarctica likely will not return to its early 1980s state until about 2060. Following a slight decline associated with the global 2 emissions from fossil fuel combustion and cement production reached a record 9.5 +/- 0.5 Pg C in 2011 and a new record of 9.7 +/- 0.5 Pg C is estimated for 2012. Atmospheric CO2 concentrations increased by 2.1 ppm in 2012, to 392.6 ppm. In spring 2012, 2 concentration exceeded 400 ppm at 7 of the 13 Arctic observation sites. Globally, other greenhouse gases including methane and nitrous oxide also continued to rise in concentration and the combined effect now represents a 32% increase in radiative forcing over a 1990 baseline. Concentrations of most ozone depleting substances continued to fall.
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| 5. |
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- 2019
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Journal article (peer-reviewed)
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| 6. |
- Fresard, Laure, et al.
(author)
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Identification of rare-disease genes using blood transcriptome sequencing and large control cohorts
- 2019
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In: Nature Medicine. - : NATURE PUBLISHING GROUP. - 1078-8956 .- 1546-170X. ; 25:6, s. 911-919
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Journal article (peer-reviewed)abstract
- It is estimated that 350 million individuals worldwide suffer from rare diseases, which are predominantly caused by mutation in a single gene(1). The current molecular diagnostic rate is estimated at 50%, with whole-exome sequencing (WES) among the most successful approaches(2-5). For patients in whom WES is uninformative, RNA sequencing (RNA-seq) has shown diagnostic utility in specific tissues and diseases(6-8). This includes muscle biopsies from patients with undiagnosed rare muscle disorders(6,9), and cultured fibroblasts from patients with mitochondrial disorders(7). However, for many individuals, biopsies are not performed for clinical care, and tissues are difficult to access. We sought to assess the utility of RNA-seq from blood as a diagnostic tool for rare diseases of different pathophysiologies. We generated whole-blood RNA-seq from 94 individuals with undiagnosed rare diseases spanning 16 diverse disease categories. We developed a robust approach to compare data from these individuals with large sets of RNA-seq data for controls (n = 1,594 unrelated controls and n = 49 family members) and demonstrated the impacts of expression, splicing, gene and variant filtering strategies on disease gene identification. Across our cohort, we observed that RNA-seq yields a 7.5% diagnostic rate, and an additional 16.7% with improved candidate gene resolution.
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| 7. |
- 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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| 8. |
- Myers-Smith, Isla H., et al.
(author)
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Complexity revealed in the greening of the Arctic
- 2020
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In: Nature Climate Change. - : Springer Science and Business Media LLC. - 1758-678X .- 1758-6798. ; 10:2, s. 106-117
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Journal article (peer-reviewed)abstract
- As the Arctic warms, vegetation is responding, and satellite measures indicate widespread greening at high latitudes. This ‘greening of the Arctic’ is among the world’s most important large-scale ecological responses to global climate change. However, a consensus is emerging that the underlying causes and future dynamics of so-called Arctic greening and browning trends are more complex, variable and inherently scale-dependent than previously thought. Here we summarize the complexities of observing and interpreting high-latitude greening to identify priorities for future research. Incorporating satellite and proximal remote sensing with in-situ data, while accounting for uncertainties and scale issues, will advance the study of past, present and future Arctic vegetation change.
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| 9. |
- Watson, Hunna J., et al.
(author)
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Common Genetic Variation and Age of Onset of Anorexia Nervosa
- 2022
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In: BIOLOGICAL PSYCHIATRY: GLOBAL OPEN SCIENCE. - : Elsevier BV. - 2667-1743. ; 2:4, s. 368-378
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Journal article (peer-reviewed)abstract
- BACKGROUND: Genetics and biology may influence the age of onset of anorexia nervosa (AN). The aims of this study were to determine whether common genetic variation contributes to age of onset of AN and to investigate the genetic associations between age of onset of AN and age at menarche.METHODS: A secondary analysis of the Psychiatric Genomics Consortium genome-wide association study (GWAS) of AN was performed, which included 9335 cases and 31,981 screened controls, all from European ancestries. We conducted GWASs of age of onset, early-onset AN (,13 years), and typical-onset AN, and genetic correlation, genetic risk score, and Mendelian randomization analyses.RESULTS: Two loci were genome-wide significant in the typical-onset AN GWAS. Heritability estimates (single nucleotide polymorphism-h2) were 0.01-0.04 for age of onset, 0.16-0.25 for early-onset AN, and 0.17-0.25 for typical-onset AN. Early-and typical-onset AN showed distinct genetic correlation patterns with putative risk factors for AN. Specifically, early-onset AN was significantly genetically correlated with younger age at menarche, and typical-onset AN was significantly negatively genetically correlated with anthropometric traits. Genetic risk scores for age of onset and early-onset AN estimated from independent GWASs significantly predicted age of onset. Mendelian randomization analysis suggested a causal link between younger age at menarche and early -onset AN.CONCLUSIONS: Our results provide evidence consistent with a common variant genetic basis for age of onset and implicate biological pathways regulating menarche and reproduction.
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| 10. |
- 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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