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- Davies, G., et al.
(författare)
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Study of 300,486 individuals identifies 148 independent genetic loci influencing general cognitive function
- 2018
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Ingår i: Nature Communications. - : Nature Publishing Group. - 2041-1723. ; 9:1
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Tidskriftsartikel (refereegranskat)abstract
- General cognitive function is a prominent and relatively stable human trait that is associated with many important life outcomes. We combine cognitive and genetic data from the CHARGE and COGENT consortia, and UK Biobank (total N = 300,486; age 16-102) and find 148 genome-wide significant independent loci (P < 5 × 10-8) associated with general cognitive function. Within the novel genetic loci are variants associated with neurodegenerative and neurodevelopmental disorders, physical and psychiatric illnesses, and brain structure. Gene-based analyses find 709 genes associated with general cognitive function. Expression levels across the cortex are associated with general cognitive function. Using polygenic scores, up to 4.3% of variance in general cognitive function is predicted in independent samples. We detect significant genetic overlap between general cognitive function, reaction time, and many health variables including eyesight, hypertension, and longevity. In conclusion we identify novel genetic loci and pathways contributing to the heritability of general cognitive function.
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- Blach, S., et al.
(författare)
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Global change in hepatitis C virus prevalence and cascade of care between 2015 and 2020: a modelling study
- 2022
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Ingår i: Lancet Gastroenterology & Hepatology. - : Elsevier BV. - 2468-1253. ; 7:5, s. 396-415
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Tidskriftsartikel (refereegranskat)abstract
- Background Since the release of the first global hepatitis elimination targets in 2016, and until the COVID-19 pandemic started in early 2020, many countries and territories were making progress toward hepatitis C virus (HCV) elimination. This study aims to evaluate HCV burden in 2020, and forecast HCV burden by 2030 given current trends. Methods This analysis includes a literature review, Delphi process, and mathematical modelling to estimate HCV prevalence (viraemic infection, defined as HCV RNA-positive cases) and the cascade of care among people of all ages (age =0 years from birth) for the period between Jan 1, 2015, and Dec 31, 2030. Epidemiological data were collected from published sources and grey literature (including government reports and personal communications) and were validated among country and territory experts. A Markov model was used to forecast disease burden and cascade of care from 1950 to 2050 for countries and territories with data. Model outcomes were extracted from 2015 to 2030 to calculate population-weighted regional averages, which were used for countries or territories without data. Regional and global estimates of HCV prevalence, cascade of care, and disease burden were calculated based on 235 countries and territories. Findings Models were built for 110 countries or territories: 83 were approved by local experts and 27 were based on published data alone. Using data from these models, plus population-weighted regional averages for countries and territories without models (n=125), we estimated a global prevalence of viraemic HCV infection of 0.7% (95% UI 0.7-0.9), corresponding to 56.8 million (95% UI 55.2-67.8) infections, on Jan 1, 2020. This number represents a decrease of 6.8 million viraemic infections from a 2015 (beginning of year) prevalence estimate of 63.6 million (61.8-75.8) infections (0.9% [0.8-1.0] prevalence). By the end of 2020, an estimated 12.9 million (12.5-15.4) people were living with a diagnosed viraemic infection. In 2020, an estimated 641 000 (623 000-765 000) patients initiated treatment. Interpretation At the beginning of 2020, there were an estimated 56.8 million viraemic HCV infections globally. Although this number represents a decrease from 2015, our forecasts suggest we are not currently on track to achieve global elimination targets by 2030. As countries recover from COVID-19, these findings can help refocus efforts aimed at HCV elimination. Copyright (C) 2022 Elsevier Ltd. All rights reserved.
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| 20. |
- Chauhan, G., et al.
(författare)
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Genetic and lifestyle risk factors for MRI-defined brain infarcts in a population-based setting
- 2019
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Ingår i: Neurology. - : Ovid Technologies (Wolters Kluwer Health). - 0028-3878 .- 1526-632X. ; 92:5
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Tidskriftsartikel (refereegranskat)abstract
- ObjectiveTo explore genetic and lifestyle risk factors of MRI-defined brain infarcts (BI) in large population-based cohorts.MethodsWe performed meta-analyses of genome-wide association studies (GWAS) and examined associations of vascular risk factors and their genetic risk scores (GRS) with MRI-defined BI and a subset of BI, namely, small subcortical BI (SSBI), in 18 population-based cohorts (n = 20,949) from 5 ethnicities (3,726 with BI, 2,021 with SSBI). Top loci were followed up in 7 population-based cohorts (n = 6,862; 1,483 with BI, 630 with SBBI), and we tested associations with related phenotypes including ischemic stroke and pathologically defined BI.ResultsThe mean prevalence was 17.7% for BI and 10.5% for SSBI, steeply rising after age 65. Two loci showed genome-wide significant association with BI: FBN2, p = 1.77 x 10(-8); and LINC00539/ZDHHC20, p = 5.82 x 10(-9). Both have been associated with blood pressure (BP)-related phenotypes, but did not replicate in the smaller follow-up sample or show associations with related phenotypes. Age- and sex-adjusted associations with BI and SSBI were observed for BP traits (p value for BI, p([BI]) = 9.38 x 10(-25); p([SSBI]) = 5.23 x 10(-14) for hypertension), smoking (p([BI]) = 4.4 x 10(-10); p([SSBI]) = 1.2 x 10(-4)), diabetes (p([BI]) = 1.7 x 10(-8); p([SSBI]) = 2.8 x 10(-3)), previous cardiovascular disease (p([BI]) = 1.0 x 10(-18); p([SSBI]) = 2.3 x 10(-7)), stroke (p([BI]) = 3.9 x 10(-69); p([SSBI]) = 3.2 x 10(-24)), and MRI-defined white matter hyperintensity burden (p([BI]) = 1.43 x 10(-157); p([SSBI]) = 3.16 x 10(-106)), but not with body mass index or cholesterol. GRS of BP traits were associated with BI and SSBI (p 0.0022), without indication of directional pleiotropy.ConclusionIn this multiethnic GWAS meta-analysis, including over 20,000 population-based participants, we identified genetic risk loci for BI requiring validation once additional large datasets become available. High BP, including genetically determined, was the most significant modifiable, causal risk factor for BI.
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