Intra- and inter-day precision and accuracy of quality control samples for targeted TCA metabolites.

<p>Intra- and inter-day precision and accuracy of quality control samples for targeted TCA metabolites.</p

Body weight gain for mice fed HFD diet and control chow over 8 weeks.

<p>**** p < 0.0001.</p

The results of targeted TCA intermediates in serum and liver.

<p>The results of targeted TCA intermediates in serum and liver.</p

Representative single ion monitoring chromatograms of the energy metabolites.

<p>a) pyruvic acid, b) succinic acid, c) fumaric acid, d) malic acid, e) oxaloacetic acid, f) 2-oxoglutaric acid, g) <i>cis</i>-aconitic acid, h) citric acid, i) DL-norleucine (IS), j) lactic acid, k) glutamine, l) glutamic acid, m) isocitrate, and n) pantothenic acid at MQC (20.0 μM).</p

Changes for the serum energy metabolite/IS ratios for HFD (H)- and control chow diet (C)-fed mice (n = 5).

<p>A, pyruvic acid; B, citric acid; C, <i>cis</i>-aconitic acid; D, succinic acid; E, fumaric acid; F, malic acid; G, 2-oxoglutaric acid; H, glutamine; I, glutamic acid; J, lactic acid; K, isocitric acid; L, pantothenic acid. *p<0.05; **p<0.01.</p

Network Analysis of a <em>Pkd1</em>-Mouse Model of Autosomal Dominant Polycystic Kidney Disease Identifies HNF4α as a Disease Modifier

<div><p>Autosomal Dominant Polycystic Kidney Disease (ADPKD; MIM ID's 173900, 601313, 613095) leads to end-stage kidney disease, caused by mutations in <em>PKD1</em> or <em>PKD2</em>. Inactivation of <em>Pkd1</em> before or after P13 in mice results in distinct early- or late-onset disease. Using a mouse model of ADPKD carrying floxed <em>Pkd1</em> alleles and an inducible Cre recombinase, we intensively analyzed the relationship between renal maturation and cyst formation by applying transcriptomics and metabolomics to follow disease progression in a large number of animals induced before P10. Weighted gene co-expression network analysis suggests that <em>Pkd1</em>-cystogenesis does not cause developmental arrest and occurs in the context of gene networks similar to those that regulate/maintain normal kidney morphology/function. Knowledge-based Ingenuity Pathway Analysis (IPA) software identifies HNF4α as a likely network node. These results are further supported by a meta-analysis of 1,114 published gene expression arrays in <em>Pkd1</em> wild-type tissues. These analyses also predict that metabolic pathways are key elements in postnatal kidney maturation and early steps of cyst formation. Consistent with these findings, urinary metabolomic studies show that <em>Pkd1</em> cystic mutants have a distinct profile of excreted metabolites, with pathway analysis suggesting altered activity in several metabolic pathways. To evaluate their role in disease, metabolic networks were perturbed by inactivating <em>Hnf4α</em> and <em>Pkd1</em>. The <em>Pkd1/Hnf4α</em> double mutants have significantly more cystic kidneys, thus indicating that metabolic pathways could play a role in <em>Pkd1</em>-cystogenesis.</p> </div

Histology and gene expression patterns in early-onset model.

<p>A) Representative kidney histology (H&E stain; scale bar: 500 mm); B) PCA plot: genotype and age explain most of the clustering in the complete set of 70 kidneys in the early-onset model (control: red; mutant: blue; size of spheres: age). C and D) Heatmap plot of mutant-signature (genes in <a href="http://www.plosgenetics.org/article/info:doi/10.1371/journal.pgen.1003053#pgen.1003053.s002" target="_blank">Table S1</a>) in the test (C) and validation (D) groups. E) Heatmap plot of ME2 (genes in <a href="http://www.plosgenetics.org/article/info:doi/10.1371/journal.pgen.1003053#pgen.1003053.s004" target="_blank">Table S3</a>) cluster in the validation group.</p