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- 2019
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Tidskriftsartikel (refereegranskat)
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| 2. |
- Hibar, Derrek P., et al.
(författare)
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Novel genetic loci associated with hippocampal volume
- 2017
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Ingår i: Nature Communications. - : Springer Science and Business Media LLC. - 2041-1723. ; 8
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Tidskriftsartikel (refereegranskat)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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- Sandholm, Niina, et al.
(författare)
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New susceptibility loci associated with kidney disease in type 1 diabetes
- 2012
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Ingår i: PLOS Genetics. - San Francisco, USA : Public Library of Science, PLOS. - 1553-7390 .- 1553-7404. ; 8:9, s. e1002921-
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Tidskriftsartikel (refereegranskat)abstract
- Diabetic kidney disease, or diabetic nephropathy (DN), is a major complication of diabetes and the leading cause of end-stage renal disease (ESRD) that requires dialysis treatment or kidney transplantation. In addition to the decrease in the quality of life, DN accounts for a large proportion of the excess mortality associated with type 1 diabetes (T1D). Whereas the degree of glycemia plays a pivotal role in DN, a subset of individuals with poorly controlled T1D do not develop DN. Furthermore, strong familial aggregation supports genetic susceptibility to DN. However, the genes and the molecular mechanisms behind the disease remain poorly understood, and current therapeutic strategies rarely result in reversal of DN. In the GEnetics of Nephropathy: an International Effort (GENIE) consortium, we have undertaken a meta-analysis of genomewide association studies (GWAS) of T1D DN comprising similar to 2.4 million single nucleotide polymorphisms (SNPs) imputed in 6,691 individuals. After additional genotyping of 41 top ranked SNPs representing 24 independent signals in 5,873 individuals, combined meta-analysis revealed association of two SNPs with ESRD: rs7583877 in the AFF3 gene (P = 1.2 x 10(-8)) and an intergenic SNP on chromosome 15q26 between the genes RGMA and MCTP2, rs12437854 (P = 2.0 x 10(-9)). Functional data suggest that AFF3 influences renal tubule fibrosis via the transforming growth factor-beta (TGF-beta 1) pathway. The strongest association with DN as a primary phenotype was seen for an intronic SNP in the ERBB4 gene (rs7588550, P = 2.1 x 10(-7)), a gene with type 2 diabetes DN differential expression and in the same intron as a variant with cis-eQTL expression of ERBB4. All these detected associations represent new signals in the pathogenesis of DN.
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| 4. |
- Sandholm, Niina, et al.
(författare)
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Genome-wide meta-analysis and omics integration identifies novel genes associated with diabetic kidney disease
- 2022
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Ingår i: Diabetologia. - : Springer Science and Business Media LLC. - 0012-186X .- 1432-0428. ; 65:9, s. 1495-1509
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Tidskriftsartikel (refereegranskat)abstract
- Aims/hypothesis: Diabetic kidney disease (DKD) is the leading cause of kidney failure and has a substantial genetic component. Our aim was to identify novel genetic factors and genes contributing to DKD by performing meta-analysis of previous genome-wide association studies (GWAS) on DKD and by integrating the results with renal transcriptomics datasets. Methods: We performed GWAS meta-analyses using ten phenotypic definitions of DKD, including nearly 27,000 individuals with diabetes. Meta-analysis results were integrated with estimated quantitative trait locus data from human glomerular (N=119) and tubular (N=121) samples to perform transcriptome-wide association study. We also performed gene aggregate tests to jointly test all available common genetic markers within a gene, and combined the results with various kidney omics datasets. Results: The meta-analysis identified a novel intronic variant (rs72831309) in the TENM2 gene associated with a lower risk of the combined chronic kidney disease (eGFR<60 ml/min per 1.73 m2) and DKD (microalbuminuria or worse) phenotype (p=9.8×10−9; although not withstanding correction for multiple testing, p>9.3×10−9). Gene-level analysis identified ten genes associated with DKD (COL20A1, DCLK1, EIF4E, PTPRN–RESP18, GPR158, INIP–SNX30, LSM14A and MFF; p<2.7×10−6). Integration of GWAS with human glomerular and tubular expression data demonstrated higher tubular AKIRIN2 gene expression in individuals with vs without DKD (p=1.1×10−6). The lead SNPs within six loci significantly altered DNA methylation of a nearby CpG site in kidneys (p<1.5×10−11). Expression of lead genes in kidney tubules or glomeruli correlated with relevant pathological phenotypes (e.g. TENM2 expression correlated positively with eGFR [p=1.6×10−8] and negatively with tubulointerstitial fibrosis [p=2.0×10−9], tubular DCLK1 expression correlated positively with fibrosis [p=7.4×10−16], and SNX30 expression correlated positively with eGFR [p=5.8×10−14] and negatively with fibrosis [p<2.0×10−16]). Conclusions/interpretation: Altogether, the results point to novel genes contributing to the pathogenesis of DKD. Data availability: The GWAS meta-analysis results can be accessed via the type 1 and type 2 diabetes (T1D and T2D, respectively) and Common Metabolic Diseases (CMD) Knowledge Portals, and downloaded on their respective download pages (https://t1d.hugeamp.org/downloads.html; https://t2d.hugeamp.org/downloads.html; https://hugeamp.org/downloads.html). Graphical abstract: [Figure not available: see fulltext.]
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