| 1. |
- Hibar, Derrek P., et al.
(author)
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Novel genetic loci associated with hippocampal volume
- 2017
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In: Nature Communications. - : Springer Science and Business Media LLC. - 2041-1723. ; 8
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Journal article (peer-reviewed)abstract
- The hippocampal formation is a brain structure integrally involved in episodic memory, spatial navigation, cognition and stress responsiveness. Structural abnormalities in hippocampal volume and shape are found in several common neuropsychiatric disorders. To identify the genetic underpinnings of hippocampal structure here we perform a genome-wide association study (GWAS) of 33,536 individuals and discover six independent loci significantly associated with hippocampal volume, four of them novel. Of the novel loci, three lie within genes (ASTN2, DPP4 and MAST4) and one is found 200 kb upstream of SHH. A hippocampal subfield analysis shows that a locus within the MSRB3 gene shows evidence of a localized effect along the dentate gyrus, subiculum, CA1 and fissure. Further, we show that genetic variants associated with decreased hippocampal volume are also associated with increased risk for Alzheimer's disease (r(g) = -0.155). Our findings suggest novel biological pathways through which human genetic variation influences hippocampal volume and risk for neuropsychiatric illness.
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| 2. |
- de Vries, Paul S., et al.
(author)
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Comparison of HapMap and 1000 Genomes Reference Panels in a Large-Scale Genome-Wide Association Study
- 2017
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In: PLOS ONE. - : Public Library of Science (PLoS). - 1932-6203. ; 12:1
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Journal article (peer-reviewed)abstract
- An increasing number of genome-wide association (GWA) studies are now using the higher resolution 1000 Genomes Project reference panel (1000G) for imputation, with the expectation that 1000G imputation will lead to the discovery of additional associated loci when compared to HapMap imputation. In order to assess the improvement of 1000G over HapMap imputation in identifying associated loci, we compared the results of GWA studies of circulating fibrinogen based on the two reference panels. Using both HapMap and 1000G imputation we performed a meta-analysis of 22 studies comprising the same 91,953 individuals. We identified six additional signals using 1000G imputation, while 29 loci were associated using both HapMap and 1000G imputation. One locus identified using HapMap imputation was not significant using 1000G imputation. The genome-wide significance threshold of 5x10(-8) is based on the number of independent statistical tests using HapMap imputation, and 1000G imputation may lead to further independent tests that should be corrected for. When using a stricter Bonferroni correction for the 1000G GWA study (P-value < 2.5x10(-8)), the number of loci significant only using HapMap imputation increased to 4 while the number of loci significant only using 1000G decreased to 5. In conclusion, 1000G imputation enabled the identification of 20% more loci than HapMap imputation, although the advantage of 1000G imputation became less clear when a stricter Bonferroni correction was used. More generally, our results provide insights that are applicable to the implementation of other dense reference panels that are under development.
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| 3. |
- Wahl, Simone, et al.
(author)
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Epigenome-wide association study of body mass index, and the adverse outcomes of adiposity
- 2017
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In: Nature. - : NATURE PUBLISHING GROUP. - 0028-0836 .- 1476-4687. ; 541:7635, s. 81-
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Journal article (peer-reviewed)abstract
- Approximately 1.5 billion people worldwide are overweight or affected by obesity, and are at risk of developing type (2) diabetes, cardiovascular disease and related metabolic and inflammatory disturbances(1,2). Although the mechanisms linking adiposity to associated clinical conditions are poorly understood, recent studies suggest that adiposity may influence DNA methylation(3-6), a key regulator of gene expression and molecular phenotype(7). Here we use epigenome-wide association to show that body mass index (BMI; a key measure of adiposity) is associated with widespread changes in DNA methylation (187 genetic loci with P < 1 x 10(-7), range P = 9.2 x 10(-8) to 6.0 x 10(-46); n = 10,261 samples). Genetic association analyses demonstrate that the alterations in DNA methylation are predominantly the consequence of adiposity, rather than the cause. We find that methylation loci are enriched for functional genomic features in multiple tissues (P < 0.05), and show that sentinel methylation markers identify gene expression signatures at 38 loci (P < 9.0 x 10(-6), range P = 5.5 x 10(-6) to 6.1 x 10(-35), n = 1,785 samples). The methylation loci identify genes involved in lipid and lipoprotein metabolism, substrate transport and inflammatory pathways. Finally, we show that the disturbances in DNA methylation predict future development of type 2 diabetes (relative risk per 1 standard deviation increase in methylation risk score: 2.3 (2.07-2.56); P = 1.1 x 10(-54)). Our results provide new insights into the biologic pathways influenced by adiposity, and may enable development of new strategies for prediction and prevention of type 2 diabetes and other adverse clinical consequences of obesity.
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