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Träfflista för sökning "WFRF:(Lehtovirta Mikko) "

Sökning: WFRF:(Lehtovirta Mikko)

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1.
  • Dwivedi, Om Prakash, et al. (författare)
  • Loss of ZnT8 function protects against diabetes by enhanced insulin secretion
  • 2019
  • Ingår i: Nature Genetics. - : Nature Publishing Group. - 1061-4036. ; , s. 1-22
  • Tidskriftsartikel (refereegranskat)abstract
    • A rare loss-of-function allele p.Arg138* in SLC30A8 encoding the zinc transporter 8 (ZnT8), which is enriched in Western Finland, protects against type 2 diabetes (T2D). We recruited relatives of the identified carriers and showed that protection was associated with better insulin secretion due to enhanced glucose responsiveness and proinsulin conversion, particularly when compared with individuals matched for the genotype of a common T2D-risk allele in SLC30A8, p.Arg325. In genome-edited human induced pluripotent stem cell (iPSC)-derived β-like cells, we establish that the p.Arg138* allele results in reduced SLC30A8 expression due to haploinsufficiency. In human β cells, loss of SLC30A8 leads to increased glucose responsiveness and reduced KATP channel function similar to isolated islets from carriers of the T2D-protective allele p.Trp325. These data position ZnT8 as an appealing target for treatment aimed at maintaining insulin secretion capacity in T2D.
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2.
  • Oskolkov, Nikolay, et al. (författare)
  • High-throughput muscle fiber typing from RNA sequencing data
  • 2022
  • Ingår i: Skeletal Muscle. - 2044-5040. ; 12:1
  • Tidskriftsartikel (refereegranskat)abstract
    • Background: Skeletal muscle fiber type distribution has implications for human health, muscle function, and performance. This knowledge has been gathered using labor-intensive and costly methodology that limited these studies. Here, we present a method based on muscle tissue RNA sequencing data (totRNAseq) to estimate the distribution of skeletal muscle fiber types from frozen human samples, allowing for a larger number of individuals to be tested. Methods: By using single-nuclei RNA sequencing (snRNAseq) data as a reference, cluster expression signatures were produced by averaging gene expression of cluster gene markers and then applying these to totRNAseq data and inferring muscle fiber nuclei type via linear matrix decomposition. This estimate was then compared with fiber type distribution measured by ATPase staining or myosin heavy chain protein isoform distribution of 62 muscle samples in two independent cohorts (n = 39 and 22). Results: The correlation between the sequencing-based method and the other two were r(ATpas) = 0.44 [0.13-0.67], [95% CI], and r(myosin) = 0.83 [0.61-0.93], with p = 5.70 x 10(-3) and 2.00 x 10(-6), respectively. The deconvolution inference of fiber type composition was accurate even for very low totRNAseq sequencing depths, i.e., down to an average of similar to 10,000 paired-end reads. Conclusions: This new method (https://github.com/OlaHanssonLab/PredictFiberType) consequently allows for measurement of fiber type distribution of a larger number of samples using totRNAseq in a cost and labor-efficient way. It is now feasible to study the association between fiber type distribution and e.g. health outcomes in large well-powered studies.
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3.
  • Parker, Alex, et al. (författare)
  • A gene conferring susceptibility to type 2 diabetes in conjunction with obesity is located on chromosome 18p11
  • 2001
  • Ingår i: Diabetes. - : American Diabetes Association Inc.. - 1939-327X. ; 50:3, s. 675-680
  • Tidskriftsartikel (refereegranskat)abstract
    • Genome-wide nonparametric linkage analysis of 480 sib-pairs affected with type 2 diabetes revealed linkage to a previously unreported susceptibility locus on chromosome 18p11. This result improved with stringent subphenotyping using age- and sex-adjusted BMI, ultimately reaching a logarithm of odds of 3.82 (allele sharing 0.6654) at a point between markers D18S976 and D18S391 when the most obese 20% of the sample was analyzed. Several genes on chromosome 18 have been suggested as metabolic disease candidates, but none of these colocalize with our linkage result. We conclude that our results provide support for the presence of a currently uncharacterized gene on chromosome 18p, certain alleles of which confer increased susceptibility to type 2 diabetes in conjunction with obesity. We additionally observed moderate evidence for linkage to chromosome 1, near marker D1S3462; chromosome 4, near marker D4S2361; chromosome 5, near marker D5S1505; and chromosome 17, near marker D17S1301.
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