Improving power of association tests using multiple sets of imputed genotypes from distributed reference panels

The accuracy of genotype imputation depends upon two factors: the sample size of the reference panel and the genetic similarity between the reference panel and the target samples. When multiple reference panels are not consented to combine together, it is unclear how to combine the imputation results to optimize the power of genetic association studies. We compared the accuracy of 9,265 Norwegian genomes imputed from three reference panels—1000 Genomes phase 3 (1000G), Haplotype Reference Consortium (HRC), and a reference panel containing 2,201 Norwegian participants from the population‐based Nord Trøndelag Health Study (HUNT) from low‐pass genome sequencing. We observed that the population‐matched reference panel allowed for imputation of more population‐specific variants with lower frequency (minor allele frequency (MAF) between 0.05% and 0.5%). The overall imputation accuracy from the population‐specific panel was substantially higher than 1000G and was comparable with HRC, despite HRC being 15‐fold larger. These results recapitulate the value of population‐specific reference panels for genotype imputation. We also evaluated different strategies to utilize multiple sets of imputed genotypes to increase the power of association studies. We observed that testing association for all variants imputed from any panel results in higher power to detect association than the alternative strategy of including only one version of each genetic variant, selected for having the highest imputation quality metric. This was particularly true for lower frequency variants (MAF < 1%), even after adjusting for the additional multiple testing burden.Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/139954/1/gepi22067_am.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/139954/2/gepi22067.pd

Tight-binding parameters for charge transfer along DNA

We systematically examine all the tight-binding parameters pertinent to charge transfer along DNA. The $\pi$ molecular structure of the four DNA bases (adenine, thymine, cytosine, and guanine) is investigated by using the linear combination of atomic orbitals method with a recently introduced parametrization. The HOMO and LUMO wavefunctions and energies of DNA bases are discussed and then used for calculating the corresponding wavefunctions of the two B-DNA base-pairs (adenine-thymine and guanine-cytosine). The obtained HOMO and LUMO energies of the bases are in good agreement with available experimental values. Our results are then used for estimating the complete set of charge transfer parameters between neighboring bases and also between successive base-pairs, considering all possible combinations between them, for both electrons and holes. The calculated microscopic quantities can be used in mesoscopic theoretical models of electron or hole transfer along the DNA double helix, as they provide the necessary parameters for a tight-binding phenomenological description based on the $\pi$ molecular overlap. We find that usually the hopping parameters for holes are higher in magnitude compared to the ones for electrons, which probably indicates that hole transport along DNA is more favorable than electron transport. Our findings are also compared with existing calculations from first principles.Comment: 15 pages, 3 figures, 7 table

Modulation of β-Catenin Signaling by Glucagon Receptor Activation

The glucagon receptor (GCGR) is a member of the class B G protein–coupled receptor family. Activation of GCGR by glucagon leads to increased glucose production by the liver. Thus, glucagon is a key component of glucose homeostasis by counteracting the effect of insulin. In this report, we found that in addition to activation of the classic cAMP/protein kinase A (PKA) pathway, activation of GCGR also induced β-catenin stabilization and activated β-catenin–mediated transcription. Activation of β-catenin signaling was PKA-dependent, consistent with previous reports on the parathyroid hormone receptor type 1 (PTH1R) and glucagon-like peptide 1 (GLP-1R) receptors. Since low-density-lipoprotein receptor–related protein 5 (Lrp5) is an essential co-receptor required for Wnt protein mediated β-catenin signaling, we examined the role of Lrp5 in glucagon-induced β-catenin signaling. Cotransfection with Lrp5 enhanced the glucagon-induced β-catenin stabilization and TCF promoter–mediated transcription. Inhibiting Lrp5/6 function using Dickkopf-1(DKK1) or by expression of the Lrp5 extracellular domain blocked glucagon-induced β-catenin signaling. Furthermore, we showed that Lrp5 physically interacted with GCGR by immunoprecipitation and bioluminescence resonance energy transfer assays. Together, these results reveal an unexpected crosstalk between glucagon and β-catenin signaling, and may help to explain the metabolic phenotypes of Lrp5/6 mutations

Dissecting Molecular Differences between Wnt Coreceptors LRP5 and LRP6

Low-density lipoprotein receptor-related proteins 5 and 6 (LRP5 and LRP6) serve as Wnt co-receptors for the canonical β-catenin pathway. While LRP6 is essential for embryogenesis, both LRP5 and LRP6 play critical roles for skeletal remodeling, osteoporosis pathogenesis and cancer formation, making LRP5 and LRP6 key therapeutic targets for cancer and disease treatment. LRP5 and LRP6 each contain in the cytoplasmic domain five conserved PPPSPxS motifs that are pivotal for signaling and serve collectively as phosphorylation-dependent docking sites for the scaffolding protein Axin. However existing data suggest that LRP6 is more effective than LRP5 in transducing the Wnt signal. To understand the molecular basis that accounts for the different signaling activity of LRP5 and LRP6, we generated a series of chimeric receptors via swapping LRP5 and LRP6 cytoplasmic domains, LRP5C and LRP6C, and studied their Wnt signaling activity using biochemical and functional assays. We demonstrate that LRP6C exhibits strong signaling activity while LRP5C is much less active in cells. Recombinant LRP5C and LRP6C upon in vitro phosphorylation exhibit similar Axin-binding capability, suggesting that LRP5 and LRP6 differ in vivo at a step prior to Axin-binding, likely at receiving phosphorylation. We identified between the two most carboxyl PPPSPxS motifs an intervening “gap4” region that appears to account for much of the difference between LRP5C and LRP6C, and showed that alterations in this region are sufficient to enhance LRP5 PPPSPxS phosphorylation and signaling to levels comparable to LRP6 in cells. In addition we provide evidence that binding of phosphorylated LRP5 or LRP6 to Axin is likely direct and does not require the GSK3 kinase as a bridging intermediate as has been proposed. Our studies therefore uncover a new and important molecular tuning mechanism for differential regulation of LRP5 and LRP6 phosphorylation and signaling activity

Depression and anxiety in relation to catechol-O-methyltransferase Val158Met genotype in the general population: The Nord-Trøndelag Health Study (HUNT)

<p>Abstract</p> <p>Background</p> <p>The catechol-O-methyltransferase (COMT) gene contains a functional polymorphism, Val158Met, which has been linked to anxiety and depression, but previous results are not conclusive. The aim of the present study was to examine the relationship between the Val158Met COMT gene polymorphism and anxiety and depression measured by the Hospital Anxiety and Depression Scale (HADS) in the general adult population.</p> <p>Methods</p> <p>In the Nord-Trøndelag Health Study (HUNT) the association between the Val158Met polymorphism and anxiety and depression was evaluated in a random sample of 5531 individuals. Two different cut off scores (≥ 8 and ≥ 11) were used to identify cases with anxiety (HADS-A) and depression (HADS-D), whereas controls had HADS-A <8 and HADS-D <8.</p> <p>Results</p> <p>The COMT genotype distribution was similar between controls and individuals in the groups with anxiety and depression using cut-off scores of ≥ 8. When utilizing the alternative cut-off score HADS-D ≥ 11, Met/Met genotype and Met allele were less common among men with depression compared to the controls (genotype: p = 0.017, allele: p = 0.006). In the multivariate analysis, adjusting for age and heart disease, depression (HADS-D ≥ 11) was less likely among men with the Met/Met genotype than among men with the Val/Val genotype (OR = 0.37, 95% CI = 0.18–0.76).</p> <p>Conclusion</p> <p>In this population-based study, no clear association between the Val158Met polymorphism and depression and anxiety was revealed. The Met/Met genotype was less likely among men with depression defined as HADS-D ≥ 11, but this may be an incidental finding.</p