Hypertension, diabetes and obesity are cardiovascular risk factors closely associated to the development of renal and cardiovascular target organ damage. VAV2 and VAV3, members of the VAV family proto-oncogenes, are guanosine nucleotide exchange factors for the Rho and Rac GTPase family, which is related with cardiovascular homeostasis. We have analyzed the relationship between the presence of VAV2 rs602990 and VAV3 rs7528153 polymorphisms with cardiovascular risk factors and target organ damage  in 411 subjects. Our results show that being carrier of the T allele in VAV2 rs602990 polymorphism is associated with an increased risk of obesity, reduced levels of ankle-brachial index and diastolic blood pressure and reduced retinal artery caliber. In addition, being carrier of T allele is associated with increased risk of target organ damage in males. On the other hand, being carrier of the T allele in VAV3 rs7528153 polymorphism is associated with a decreased susceptibility of developing a pathologic state composed by the presence of hypertension, diabetes, obesity or cardiovascular damage, and with an increased risk of developing altered basal glycaemia. This is the first report showing an association between VAV2 and VAV3 polymorphisms with cardiovascular risk factors and target organ damage. Hypertension (HT), diabetes mellitus (DM) and obesity are the most common risk factors associated to the development of cardiovascular diseases16The guanine nucleotide exchange factors VAV2 and VAV3 are members of the VAV family of proto-oncogenes. Both are GDP-GTP dependent factors that stimulate Rho and Rac GTPases141518et al.−/− mice 20et al.−/− mice fed with chow diet developed metabolic syndrome, whereas these mice fed under fatty diets showed resistance against obesity and metabolic syndromeSauzeau Although several studies have observed that some single nucleotide polymorphisms (SNPs) in VAV genes are related to pathologies such as schizophrenia (VAV3 rs1410403)We analyzed 411 subjects. There are statistically significant differences in the genotypic distribution for VAV2 rs602990 or VAV3 rs7538153 polymorphisms in cardiovascular risk parameters such as the presence of cardiovascular risk factors, TOD, altered basal glycaemia or obesity.On the one hand, there are statistically significant differences in the VAV3 rs7538153 genotypic distribution between the patients group (n = 281) and controls (n = 130). Being carrier of the T allele is associated with a decreased susceptibility of developing hypertension, diabetes, obesity or cardiovascular damage in the dominant model . There aOn the other hand, there are statistically significant differences in the allelic distribution for VAV2 rs602990 polymorphism between males with TOD (n = 107) and controls (n = 93). Being carrier of the T allele is associated with an increased risk of TOD in the dominant model . There aSome polymorphic variants of genes involved in cardiovascular regulation seem to influence the risk or predisposition to developing cardiovascular disease. For example, a nitric oxide synthase 3 (NOS3) polymorphism is related to rapid progression of heart failure in patients with dilated cardiomyopathy−/− mice show cardiovascular alterations such as hypertension, tachycardia or cardiovascular remodelingOur study shows an association between VAV2 rs602990 and VAV3 rs7528153 polymorphisms with several cardiovascular risk factors and TOD  in a Spanish population. Hypertension, diabetes and obesity are the most common cardiovascular risk factors11202324We have found an association between VAV3 rs7528153 polymorphisms and altered basal glycaemia. Being carrier of the T allele is associated with increased risk of higher values of basal glycaemia. AMP-activated protein kinase (AMPK) acts as an upstream signal for VAV3 induction involving metformin-mediated signaling. Loss of VAV3 potentiates metformin-mediated glucose uptake, suggesting that VAV3 could become a molecular target for blood glucose regulation through AMPKet al. observed that VAV2−/− mice showed cardiovascular and renal alterations, such as remodeling in the cardiovascular system, LVH with fibrosis, interstitial renal fibrosis and lower glomerular filtration rate−/−, VAV3−/− and triple VAV1−/−, VAV2−/− and VAV3−/− mice showed defects in dendritic spine development, in axon transmission and synaptic plasticity in cortical, renal and hippocampal neurons due to deregulation of Rac activity37The SNP V594M VAV2 rs602990 is located in the first SH3 domain. We detected an association between VAV2 rs602990 polymorphisms and the presence of TOD. Being carrier of the T allele confers an increased risk of TOD in males . Sauzeau ABI index is an indicative parameter of peripheral arterial disease and a low ABI index is directly related with vascular damageet al. observed that VAV2−/− mice were hypertensive due to sympathetic excitation, some studies reported that Rac1 is involved in vasoconstriction41Although Sauzeau Overall, this study shows the association between some VAV2 and VAV3 polymorphisms with cardiovascular risk factors in a Spanish population. However, this study has some limitations. First, this is a retrospective study. Second, due to the number of analyzed patients, there is a limitation in the statistical power of the study. Thus, in order to confirm our results, studies should be done in a larger population.In conclusion, this is the first study showing the association between VAV2 and VAV3 polymorphisms with cardiovascular risk factors and TOD, possibly through their influence in Rho and Rac pathways. These polymorphisms are associated with indicators frequently used in the clinical practice to evaluate cardiovascular damage . Thus, our study suggests that the analysis of VAV2 and VAV3 polymorphisms might be a useful diagnostic and prognostic marker of susceptibility to cardiovascular damage.2 This is a cross-sectional study performed in patients with or without DM and HT. 411 subjects aged between 20–80 years were recruited in the Primary Care Research Unit of La Alamedilla Health Centre, Salamanca (Spain), covering a population of 46,000 inhabitants. HT was diagnosed when the mean of three different BP measurements was ≥120 mm Hg for systolic blood pressure (SBP) or ≥80 mm Hg for diastolic blood pressure (DBP) or when patients received antihypertensive drugs. DM was diagnosed following 2 criteria: basal plasma glucose ≥126 mg/dL, glycosylated hemoglobin (HbA1c) > 6,5% or when patients received antidiabetic drugs. Obesity was diagnosed by body mass index (BMI) ≥ 30 kg/mTOD is a variable composed of renal TOD  vascular TOD (assessed by carotid intima-media thickness (IMT), pulse wave velocity (PWV) and ankle-brachial index (ABI)) and cardiac TOD (assessed by left ventricular hypertrophy (LVH) and pulse pressure (PP)).The experimental protocol was in accordance with the Declaration of Helsinki (2008) of the World Medical Association, approved by the University Hospital of Salamanca Ethics Committee and complied with Spanish data protection law (LO 15/1999) and specifications (RD 1720/2007). An informed consent was obtained from all participants recruited in the study.2) measuring body weight using a homologated electronic scale , and height with a portable system (Seca 222).We calculated BMI -cholesterol, low-density lipoprotein (LDL)-cholesterol in plasma, and creatinine and microalbumin in urine using standard automatic techniques on a blind basis in the Biochemistry laboratory of the University Hospital, Salamanca (Spain).Office BP evaluation involved three measurements of SBP and DBP with a validated OMRON model M7 sphygmomanometer  following the recommendations of the European Society of Hypertension (ESH)We used the ankle–brachial index (ABI), in patients refrained from drinking coffee or smoking tobacco for at least 8 h before measurements and at 22–24 °C. With the patient lying in supine position and with the feet uncovered, we measured BP in the lower limbs after resting for 20 min using a portable Doppler system Minidop Es-100Vx . We calculated ABI automatically for each foot by dividing the higher of the two SBP in the ankle by the higher of the two SBP in the arm. An ankle–brachial index <0.9 is considered abnormalElectrocardiography (ECG) was performed with a General Electric MAC 3.500 ECG System  that automatically measures wave voltage and duration and estimates the criteria of the Cornell voltage duration product (VDP)We evaluated PWV with the SphygmoCor System . We analyzed the pulse waves of the carotid and femoral arteries with the patient in the supine position measuring the delay with respect to the ECG wave, and then calculating PWV. We obtained distance measurements with a measuring tape from the sternal notch to the carotid and femoral arteries at the sensor location.We used a Micromax ultrasound device  paired with a 5–10 MHz multifrequency high-resolution linear transducer with Sonocal software for performing automated measurements of carotid IMT in order to optimise reproducibility. We made measurements of the common carotid after examination of a 10 mm longitudinal section at a distance of 1 cm from the bifurcation. We took measurements in the proximal wall, and in the distal wall in the lateral, anterior and posterior projections, following an axis perpendicular to the artery to discriminate two lines: one for the intima-blood interface and the other for the media-adventitious interface. We took six measurements of both the right and left carotid arteries, using average values (average carotid IMT) and maximum values (maximum carotid IMT) automatically calculated by the software2 or microalbuminuria between 30–300 mg/24 h or albumin–creatinine ratio between 30–300 mg/g, 3.4–34 mg/mmol. We defined renal disease as a glomerular filtration rate <30 mL/min/1.73 m2, proteinuria >300 mg/24 h or albumin/creatinine ratio >300 mg/24 hWe assessed kidney damage measuring the estimated glomerular filtration rate using the Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI)We evaluated retinography with a Topcon TRC NW 200 non-mydriatic retinal camera , obtaining nasal and temporal images centered on the disk. Images were loaded into our own developed software, AV Index calculator , which automatically estimates the mean caliber of veins and arteries in millimetres as an arteriole– venule ratio, arteriovenous index (AVIx). An AVIx of 1.0 suggests that arteriolar diameters are on average the same as venular diameters in that eye, whereas a smaller AVR suggests narrower arterioles. The pairs of main vessels in the upper and lower temporal quadrants were used, rejecting all other vessels, to improve reliability and increase efficiency of the process, analysing measures for each quadrant separately and together to estimate the mean measure in each eye.We estimated cardiovascular risk (CVR) of morbidity and mortality using the 2013 guidelines of the ESHWe extracted genomic DNA from peripheral blood leukocytes by the phenol-chloroform methodX2test. The odds ratio (OR) and 95% confidence intervals were calculated by a logistic regression model to evaluate the association with the risk to develop the disease. We compared quantitative variables and the influence of polymorphism distribution by the ANOVA test in those cases that followed a parametric distribution . When data followed a non-parametric distribution, we applied a Mann Whitney U test. In order to consider confounding variables, we made a statistical adjustment by sex and the continuous variable of age. We considered statistically significant differences when P-value was <0.05.We used the statistical software SPSS v.21.0 . We tested control group subjects for conformity to the Hardy-Weinberg equilibrium using the chi-squared test for each polymorphism. We analysed the association between the different clinical and molecular qualitative variables by cross tabs and the Pearson How to cite this article: Perretta-Tejedor, N. et al. Association of VAV2 and VAV3 polymorphisms with cardiovascular risk factors. Sci. Rep.7, 41875; doi: 10.1038/srep41875 (2017).Publisher's note: Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.


RAS protein interactions have predominantly been studied in the context of the RAF and PI3kinase oncogenic pathways. Structural modeling and X-ray crystallography have demonstrated that RAS isoforms bind to canonical downstream effector proteins in these pathways using the highly conserved switch I and II regions. Other non-canonical RAS protein interactions have been experimentally identified, however it is not clear whether these proteins also interact with RAS via the switch regions.To address this question we constructed a RAS isoform-specific protein-protein interaction network and predicted 3D complexes involving RAS isoforms and interaction partners to identify the most probable interaction interfaces. The resulting models correctly captured the binding interfaces for well-studied effectors, and additionally implicated residues in the allosteric and hyper-variable regions of RAS proteins as the predominant binding site for non-canonical effectors. Several partners binding to this new interface  have been implicated as important regulators of oncogenic RAS signaling. We further used these models to investigate competitive binding and multi-protein complexes compatible with RAS surface occupancy and the putative effects of somatic mutations on RAS protein interactions.We discuss our findings in the context of RAS localization to the plasma membrane versus within the cytoplasm and provide a list of RAS protein interactions with possible cancer-related consequences, which could help guide future therapeutic strategies to target RAS proteins.The online version of this article (doi:10.1186/s13628-017-0037-6) contains supplementary material, which is available to authorized users. Tumor exome sequencing studies have uncovered RAS mutations in over 30% of solid tumors, yet to date no therapy has been discovered to effectively treat RAS driven cancers. RAS proteins themselves provide an attractive therapeutic target but efforts aimed at drugging RAS directly thus far have failed . More coRAS is a small GTPase that localizes to the plasma membrane (PM) and upon receiving extracellular stimuli, initiates multiple signaling cascades inside the cell . There aRAS signaling is deceptively complex. In contrast to their sequence similarity, different RAS isoforms have been associated with distinct functionality and show distinct patterns of expression in various cell lines and tissues , 6. ReceRecently, Chavan et al.  describeFrom a therapeutic perspective, RAS proteins have been perceived as “undruggable” due to a lack of effective inhibitors, even after more than three decades of research . HoweverRAS PPIs have predominantly been studied in the context of the RAF and PI3kinase oncogenic pathways  and struTo study RAS isoform specific PPIs, including partners with no well-defined RBrD, we predicted which residues on the surface of RAS interact with each binding partner. The resulting map of binding to RAS was used to model possible RAS complexes and identify possible competitive binding relationships. We then analyzed the putative effects of mutant alleles on RAS interactions with binding partners. Our analysis suggests a novel binding interface on the allosteric region/HVR of RAS proteins that is accessible when RAS is not localized to the plasma membrane. Interestingly, multiple interaction partners that bind via this new interface are putative cancer genes.In order to identify interaction interfaces on RAS proteins, we first curated an experimentally verified RAS isoform specific PPI network that consists of as many as 103 RAS protein interactions see . Of 77 RWe next built RAS 3D complex models using PRISM , a templMost studies of RAS signaling in cancer focus on effectors that bind the switch regions, with few studies addressing binding partners without RBrDs. Among these, one of the earlier studies addresses the involvement of the HVR in the KRAS – CALM interaction . This reInteraction partners that do not contain an RBrD  and are Rab5 GDP/GTP exchange factor (RABGEF1) acts as an E3 ligase for HRAS, and HRAS monoubiquitination promotes its localization to the endosome, thereby decreasing ERK signaling . RABGEF1LGALS1 is a cytosolic protein that has a dual role in RAS biology: it acts both as a chaperone that transports depalmitoylated HRAS to the Golgi and a critical scaffolding protein  that is The inhibitory interaction between retinoic acid receptor responder protein 3 (RARRES3) and HRAS occurs in the Golgi , 40. RARSRC is a proto-oncogene that acts upstream of RAS , and actCALM is thought to specifically bind KRAS-4B among RAS family proteins , 44, 45.Based on this evidence and our structural predictions, we propose that when RAS is not localized to the PM, the allosteric and the HVR regions of RAS proteins are involved in interactions with proteins that regulate RAS localization and PTMs. Interestingly, some of these partners are reported to suppress tumorigenic RAS signaling, including RARRES3  and RABGWe next compared PRISM’s interface to interface predictions made by similar algorithms including pyDock , ZDOCK  and COTH.Finally, we investigated the possibility that proteins binding to RAS isoforms outside of the switch region use a common structural motif. None of the proteins interacted with RAS using the same domain. We next used VAST to assess pairwise structural similarity of these interfaces using the PDB IDs listed in Table RAS mutations are most commonly observed at residues 12, 13, 59 and 61 in tumors and these mutants have all been reported to favor RAS’s GTP-bound state. For KRAS, 80% of mutations occur at the 12th amino acid, while for NRAS, 60% of mutations affect residue Q61. HRAS, on the other hand, displays a less biased distribution with 50% and 40% of mutations occurring at codons 12 and 61 respectively . In vitrWe used FoldX  to deterSeveral mutants were predicted to stabilize complexes that promote tumorigenesis. A59G and G12D mutations on HRAS and G13D mutations on both HRAS and KRAS are predicted to stabilize interactions with RALGDS. RALGDS is an activator of HRAS and KRAS, thus stabilization of this interaction should increase the amount of RAS protein in the active state, consistent with RAS pathway activation during tumorigenesis. Additionally, we observed that A146T is predicted to stabilize the HRAS – BCL2 interaction that inhibits RAS-induced apoptosis .Interestingly, interactions with FHOD1 were destabilized by some mutants, and stabilized by others. FoldX predicted that G12 and G13 mutations de-stabilize HRAS-FHOD1 binding, while Q61 mutations stabilize it. These conflicting predictions suggest that FHOD1 may promote oncogenic RAS signaling in some settings and interfere with it in others. To further investigate this possibility, we investigated FHOD1 expression in two settings: head and neck cancer and thyroid cancer and thyroid cancer. In head and neck cancer, HRAS mutations are biased toward G12 and G13, whereas in thyroid cancer, HRAS mutations are most commonly observed at Q61. We observed that expression of FHOD1 is generally higher in thyroid tumors than in head and neck cancers, suggesting that Q61 may be more advantageous in thyroid cancer in part because of tumor type specific FHOD1 activity  can directly bind HRAS  and diveFinally, we investigated the RAS CAAX motif modifier Farnesyltransferase (FNT), which is responsible for the attachment of RAS proteins to the PM . The FNTRAS mutations are found in almost 30% of tumors, making these proteins an attractive target for therapy. However, targeting RAS therapeutically has proven challenging, due in part to incomplete knowledge of RAS protein interactions. Most therapies have focused on targeting effector interactions with the switch regions , 69, 70,Understanding of RAS protein interaction interfaces is still largely restricted to common effectors and proteins with RBrDs, which comprise only ~40% of reported RAS binding proteins. Using structural modeling techniques, we were able to investigate protein complex formation between RAS proteins and the experimentally implicated RAS isoform-specific interaction network  , two werObserved patterns of somatic mutations in RAS isoforms across tumor types suggest that biological context determines the advantage of particular mutations. A compelling possible explanation for the specificity of somatic RAS mutations is that tissue level patterns of gene expression results in different ratios of RAS interaction partners, and these differences modify the functionality to RAS mutations. Studying the implications of 5 common RAS mutations for interactions, we found evidence that different RAS binding partners could be affected in different ways by the same mutations. For example, G12 and G13 mutations favored RGALS1 binding, but impaired FHOD1 binding. Interestingly, the HRAS-FHOD1 interaction is subject to both stabilizing (Q61) and destabilizing (G12 and G13) mutations, however these events were associated with distinct tumor types. This suggests that the prevalence of particular RAS mutations in a tumor type may reflect the protein interactions that best contribute to oncogenic RAS signaling in that tumor.We used structural modeling to map RAS binding interfaces and infer possible multi-protein complexes. Analysis of the resulting binding site map suggests that the allosteric region of RAS may play a more important role in RAS signaling than previously thought, and this role may go beyond RAS dimerization. Protein interactions utilizing the RAS allosteric region appear to be important for RAS localization, which is an important determinant of oncogenic RAS signaling. Further studies are needed to investigate the implications of this new aspect of RAS signaling in cancer.We gathered experimentally validated HRAS, KRAS and NRAS protein interactions available in the STRING and PDB databases as of October 2015. We considered PPIs from STRING with confidence score greater than or equal to 0.4 (medium confidence) and manually checked each article associated with the given interaction. We discarded PPIs that had vague implications of physical interaction  from our dataset. Our network consists of 103 RAS protein interactions with 77 unique proteins; including 68 HRAS, 19 KRAS and 16 NRAS interactors , GAP domain (such as RAS_GAP) or GEF domain  as having a RAS binding related domain (RBrD).Among the 81 proteins in our network (including the RAS proteins), 50 had some structural data in PDB. There were 7 RAS complexes in the PDB (HRAS - RAF1 (PDB ID: 3KUD), HRAS – PLCE (PDB ID: 2C5L), HRAS – RASA1 (PDB ID: 1WQ1), HRAS – PIK3CG (PDB ID: 1HE8), HRAS – SOS1 (PDB ID: 1NVV), HRAS – GRB14 (PDB ID: 4 K81) and KRAS-ARAF (PDB ID: 2MSE)). One PDB structure displayed a biological homodimer of HRAS  but no equivalent structure was found for KRAS or NRAS. We used PISA  to diffeWe aligned PDB structures to discard redundant PDB chains but retained distinct conformations/domains of a given protein. We used TM-align  for the We used PRISM  to identProtein complexes predicted by PRISM becomes more energetically favorable as the energy score decreases. The PRISM server reports only the models with energy score smaller than 0, and a threshold of −10 has been used previously in the PRISM literature , 86. PRIWe ran PRISM with multiple distinct KRAS and HRAS chains, but only two chains generated complex predictions: 6q21 (A chain for HRAS) and 4dso (A chain for KRAS). There was only one PDB chain available for NRAS (3con:A) and it was missing the residues between 60 and 72. We therefore generated a complete model for NRAS via Swiss-Model  server.For selected interfaces, PRISM predictions were compared to those of three other tools designed to predict protein complexes pyDock , ZDOCK  and COTHhttps://www.ncbi.nlm.nih.gov/structure).We used the consensus set of KFC2  and HotPTo determine whether RAS binding partners could bind RAS simultaneously, we used structural data to investigate whether simultaneous binding would create steric clashes. To do this we aligned 11 HRAS/4 KRAS complexes  predictions for HRAS (PDB ID: 6q21A) and RARRES3 (PDB ID: 2lktA) reported by ZDOCK, pyDock, COTH and PRISM. (PNG 147 kb)Additional file 2: Fig. S2.Map of predicted KRAS-CALM interface residues. We have used the most favorable (lowest binding energy score) predictions for KRAS (PDB ID: 4dsoA) and CALM (PDB ID: 1zuzA) reported by ZDOCK, pyDock, COTH and PRISM. (PNG 147 kb)Additional file 3: Fig. S3.Map of predicted HRAS-RAF1 interface residues. We have used the most favorable (lowest binding energy score) predictions for HRAS (PDB ID: 6q21A) and RAF1 (PDB ID: 4g0nB) reported by ZDOCK, pyDock, COTH and PRISM. (PNG 148 kb)Additional file 4: Fig. S4.Pancancer FHOD1 gene expression distribution. This graph was produced using the gene expression data available via cBioPortal .


Bos taurus and indicus breeds. These QTL have been attributed to two functional variants in the bidirectional promoter of PLAG1 and CHCHD7. Although PLAG1 is a good candidate for mediating these effects, its role remains uncertain given that these variants are also associated with expression of five additional genes at the broader locus. In the current study, we conducted expression QTL (eQTL) mapping of this region using a large, high depth mammary RNAseq dataset representing 375 lactating cows. Here we show that of the seven previously implicated genes, only PLAG1 and LYN are differentially expressed by QTL genotype, and only PLAG1 bears the same association signature of the growth and body weight QTLs. For the first time, we also report significant association of PLAG1 genotype with milk production traits, including milk fat, volume, and protein yield. Collectively, these data strongly suggest PLAG1 as the causative gene underlying this diverse range of traits, and demonstrate new effects for the locus on lactation phenotypes.A major pleiotropic quantitative trait locus (QTL) located at ~25 Mbp on bovine chromosome 14 affects a myriad of growth and developmental traits in  Bos taurus and indicus species. Of these, a QTL on chromosome 14 with a major effect on stature and body weight was reported by Karim et al. in 2011456Stature and body weight represent economically important traits in cattle. In beef animals, maximizing growth and development holds obvious importance for meat production. Despite modest positive correlations of body size with milk volume, protein, and fat yieldPLAG1 and CHCHD7 genes; rs209821678, a (CCG) repeat of 9 or 11 copies and rs210030313 an A to G nucleotide substitutionPLAG1, RPS20, and SDR16C5 were plausible biological candidates for these effects, with demonstrated roles in growth and oncogenesis89PLAG1 represented an obvious candidate given plag1 knockout mice suffer from slow growth rates and dwarfism1013In a detailed analysis of this chromosome 14 locusIn the current study, we have used a mammary RNAseq dataset (N = 375) to perform expression QTL (eQTL) mapping in a 2 Mbp interval encompassing the previously implicated chromosome 14 locus. We report genetic effects for a subset of the nine genes of interest, and further report investigation of milk composition and body weight effects in a separate population  of lactating cows.CHCHD7, IMPAD1, LYN, PLAG1 and RPS20. Of these, RPS20 was by far the most abundantly expressed (109.6 FPKM), and PLAG1 was relatively lowly expressed (0.8 FPKM).To quantify the expression levels of the nine genes of interest at the chromosome 14 body weight locus, high-depth, mammary RNAseq data from 375 lactating cows was assessed. Five of these nine genes were appreciably expressed (see Methods), consisting of PLAG1 and LYN were significantly differentially expressed by rs109815800 genotype. For PLAG1, rs109815800 was the most significant SNP  effects. The frequency of the body weight-increasing ‘G’ allele was 0.68 in the mostly Holstein-Friesian RNAseq population.Association analysis of these five genes was then conducted to test for eQTL effects. In these analyses, transformed read counts for each gene were tested in conjunction with 432 Illumina BovineHD SNPs located in a 2 megabase (Mbp) interval encompassing the previously published QTL interval. This region was centred on the BovineHD panel variant rs109815800 , selected as a tag-SNP of the two putative causative variants, since this SNP has been shown to be in complete LD with these polymorphisms in New Zealand Holstein-Friesians, Jerseys and their crossesn of LYN . This coPLAG1 and LYN by rs109815800 genotype, we wondered whether these eQTL might have phenotypic consequences in the mammary gland. To answer this question, we used a population of 39,391 lactating cows for which both milk production and body weight data were available, using association models similar to those used for eQTL analysis (see Methods). Given the major milk production effects attributed to another  chromosome 14 mutation, the DGAT1 K232A variantDGAT1 K232A genotypes as a fixed effect (see Methods). Targeting the same interval of BovineHD SNPs used previously, analysis of body weight confirmed a very large effect at this locus, with the causative mutation tag-SNP rs109815800 the most significant variant  first reported the presence of eQTLs underpinning the bovine stature locus on chromosome 14. They performed quantitative PCR using foetal brain, bone, muscle and liver samples representing 79 individuals and found significant associations with the expression of RPS20, MOS, PLAG1, CHCHD7, SDR16C5, SDR16C6 and PENK genes. While it is possible that all genes in this interval are affected by a single control element in foetal tissues, it is also plausible that these associations were due to the genotype tagging multiple independent eQTL, given that association testing was restricted to analysis of a single variant. Critically, of the seven candidates above, only PLAG1 was significantly differentially expressed by body weight QTL genotype in mammary tissue, with both eQTL and physiological trait QTL sharing the same top-associated SNP. Although we also observe an association with LYN expression, the rank order of associated SNPs suggests these QTLs may be driven by a different genetic element, and given that no eQTL was reported in foetal tissues, LYN can likely be discounted as a candidate for the stature and body weight effects. Taken together, these observations provide further evidence for PLAG1, likely under regulatory control of the rs209821678 and/or rs210030313 variants proposed be Karim et al. (2011), as the causative gene responsible for these effects. Since mammary tissue was used for eQTL mapping in the current study, this hypothesis assumes a shared regulatory architecture between this tissue and tissues of more direct relevance to growth and development processes. As such, an alternative hypothesis proposes the lactation effects being driven by PLAG1, and the previously reported stature and body weight QTLs being underpinned by one of the other candidate genes highlighted by Karim et al. (2011). Although technically conceivable, we contend the simplest and most plausible hypothesis is one that sees a single, major-effect pleiotropic PLAG1 eQTL underpinning all physiological effects.Karim PLAG1 might impact lactation traits directly. We analysed milk volume, milk fat percentage and yield, and milk protein percentage and yield, and found highly significant associations of rs109815800 with all traits except protein percentage. The body weight-increasing ‘G’ allele was associated with increased milk volume, fat, and protein yield, and decreased fat percentage. This opposing sign of effect between component yields and percentages could reflect these animals producing a higher volume of milk relative to the increases seen in the milk components, resulting in milk that is marginally more dilute. This phenomenon of milk component and yield effects being co-ordinately impacted is something that we17Given observation of the mammary eQTL effects, and the many other pleiotropic observations at this locus, we wondered whether differential expression of decreased yields, suggesting an efficiency advantage to the alternate allele. The apparent reduction in milk fat yield in animals carrying the allele normally associated with increased body weight was the most significant effect in these models and is of further note, since effects on reduced intramuscular fat and fat deposition have also been reported for this allele21PLAG1 genotype to further test this hypothesis.However, given the profound impact of this locus on animal stature and body weight, and the fact that larger cattle produce more milkPLAG1 signalling include molecules of the IGF2 and WNT pathways103plag1 in mammary tissue show differential expression of IGF2 and WNT signalling genes27PLAG1 in these pathways is relevant outside of a tumorigenic context, the effects demonstrated might derive from morphological differences between animals of different QTL genotype. It is also possible that the milk composition and yield effects may reflect secondary impacts of the QTL deriving from effects in other tissues. Given that PLAG1 is expressed during lactation and the eQTL is observed during this period, however, another appealing mechanism is one that acts through some as yet unidentified factors with direct, modulatory roles on milk synthesis and secretion.It is interesting to contemplate what mammary-specific pathways may be involved in the lactation effects proposed in our study. Two well-demonstrated targets of PLAG1 that bears the same genetic signal underpinning the previously described body weight and developmental effects at this locus. We additionally report new associations of PLAG1 genotype with milk composition and yield phenotypes. These data provide the first functional validation of an eQTL-mediated mechanism underpinning these QTLs, and further expand the list of pleiotropic effects attributed to PLAG1 in bovine species.In summary, we describe a strong mammary eQTL for All animal experiments were conducted in strict accordance with the rules and guidelines outlined in the New Zealand Animal Welfare Act 1999. For the mammary tissue biopsy experiment, samples were obtained in accordance with protocols approved by the Ruakura Animal Ethics Committee, Hamilton, New Zealand . All other data were generated as part of routine commercial activities outside the scope of that requiring formal committee assessment and ethical approval (as defined by the above guidelines). No animals were sacrificed for this study.Primary datasets consisting of relevant genotypes, and milk production and gene expression phenotypes have been deposited into the Dryad digital data repositoryAnimals used for RNAseq analysis comprised 375 mostly Holstein-Friesian NZ dairy cows, representing a subset of 406 sequenced animals described in detail previously17The animal population used for GWAS comprised 39,391 dairy cows, consisting of 8,086 Holstein-Friesians, 4,322 Jerseys, and 26,983 Holstein-Friesian x Jersey cross breeds, where Holstein-Friesians and Jerseys were considered pure with a breed proportion of 16/16ths. This population represents part of a larger phenotypic and genotypic database of animals used for evaluation of sire performance, similar to populations described previously17Milk composition phenotypes were derived from first lactation herd test data. Concentrations of major milk components were measured using Fourier transform infrared spectroscopy as part of standard herd testing procedures as described in refs DGAT1 K232A variant was imputed from whole genome sequence data using a reference population of 556 animals, in an approach similar to that described previouslyGenomic DNA extraction was conducted as previously described1717High-depth RNAseq was undertaken using mammary gland biopsies from lactating cows as described in detail previouslyRNA sequence reads were mapped to the UMD3.1 genome using Tophat2 (version 2.0.12)To derive gene expression phenotypes suitable for eQTL analysis, the read counts from the nine genes in this interval were also processed using the variance-stabilising transformation (VST) method in DESeq (version 1.18)p is the frequency of the highest frequency allele and For the 2 Mbp interval of Illumina BovineHD SNPs encompassing the rs109815800 variant, associations with gene expression, body weight, and milk composition phenotypes were quantified using pedigree-based mixed models in ASReml-R36DGAT1 K232A mutation. This variant is known to have profound impacts on milk compositionFor eQTL analysis, these models used VST-normalised read counts from the mapped RNA-seq data, representing the five nominally expressed genes in the QTL interval. These models also included a fixed effect for biopsy year to address batch variation between the different sequencing submissions. For milk composition and body weight analysis, models used the body weight and milk composition phenotypes described above. For the association analyses that considered body weight in the analysis, these models were conducted in the same way, with the addition of body weight as another covariate. Models also included a fixed effect to account for potentially confounding impacts of the −5. For milk composition and body weight analyses, a nominal significance value of P = 1.51 × 10−3 was used (33 tests).Associations were considered significant using an alpha value of 0.05 that incorporated Bonferroni corrections for multiple hypothesis testing across the different study populations. For eQTL analyses, a total of 2160 tests were conducted (five gene expression traits x 432 SNPs), yielding a nominal significance threshold of P = 2.31 × 10How to cite this article: Fink, T. et al. Functional confirmation of PLAG1 as the candidate causative gene underlying major pleiotropic effects on body weight and milk characteristics. Sci. Rep.7, 44793; doi: 10.1038/srep44793 (2017).Publisher's note: Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.


Chronic obstructive pulmonary disease (COPD) is the third-leading cause of death worldwide. Identifying COPD-associated DNA methylation marks in African-Americans may contribute to our understanding of racial disparities in COPD susceptibility. We determined differentially methylated genes and co-methylation network modules associated with COPD in African-Americans recruited during exacerbations of COPD and smoking controls from the Pennsylvania Study of Chronic Obstructive Pulmonary Exacerbations (PA-SCOPE) cohort.We assessed DNA methylation from whole blood samples in 362 African-American smokers in the PA-SCOPE cohort using the Illumina Infinium HumanMethylation27 BeadChip Array. Final analysis included 19302 CpG probes annotated to the nearest gene transcript after quality control. We tested methylation associations with COPD case-control status using mixed linear models. Weighted gene comethylation networks were constructed using weighted gene coexpression network analysis (WGCNA) and network modules were analyzed for association with COPD.MAML1, which has been shown to affect NOTCH-dependent angiogenesis in murine lung. Network modeling yielded the “yellow” and “blue” comethylation modules which were significantly associated with COPD . The yellow module was enriched for gene sets related to inflammatory pathways known to be relevant to COPD. The blue module contained the top ranked genes in the concurrent differential methylation analysis , and was significantly associated with lung development processes in Gene Ontology gene-set enrichment analysis.There were five differentially methylated CpG probes significantly associated with COPD among African-Americans at an FDR less than 5 %, and seven additional probes that approached significance at an FDR less than 10 %. The top ranked gene association was We identified 12 differentially methylated CpG sites associated with COPD that mapped to biologically plausible genes. Network module comethylation patterns have identified candidate genes that may be contributing to racial differences in COPD susceptibility and severity. COPD-associated comethylation modules contained genes previously associated with lung disease and inflammation and recapitulated known COPD-associated genes. The genes implicated by differential methylation and WGCNA analysis may provide mechanistic targets contributing to COPD susceptibility, exacerbations, and outcomes among African-Americans.NCT00774176, Registry: ClinicalTrials.gov, URL: www.clinicaltrials.gov, Date of Enrollment of First Participant: June 2004, Date Registered: 04 January 2008 (retrospectively registered).Trial Registration: The online version of this article (doi:10.1186/s12931-016-0459-8) contains supplementary material, which is available to authorized users. Chronic obstructive pulmonary disease (COPD) is an incurable lung disease characterized by progressive airflow obstruction involving emphysematous destruction of lung parenchyma and mucus hypersecretion with chronic bronchitis. Over 12 million Americans are affected by COPD, which is the third leading cause of death in the US, –5 and thRace is an important contributor to genetic  and epigin utero during imprinting, tissue-specific methylation during development, and changes in the methylation of genes in response to major environmental exposures. Differential methylation impacts gene regulation, which may lead to clinically relevant changes in disease-related phenotypes. Modules of genes with correlated comethylation profiles may identify groups of genes under similar regulation that are associated with COPD risk. Prior research has identified differential methylation signals related to tobacco smoke exposure that may influence risk for development of COPD [DNA methylation patterns are determined at multiple time points in the life of an individual,  includin of COPD –18. The After quality control, the PA-SCOPE dataset included methylation data on 19302 probes measured in 93 AA subjects with COPD defined by GOLD spirometry criteria (GOLD I-IV), as well as 269 smoking controls. A quality control schematic is provided in Fig. p-value 8.188 × 10-8, percent methylation change -7.8 %), which mapped to the MAML1 gene. Gene annotation for the remaining four differentially methylated CpG sites associated with COPD included RBFOX2, CD72, GRASP, and SH3TC1.We used linear mixed models to identify COPD-associated CpG sites, using the method of Benjamini and Hochberg to control type I error. Five differentially methylated CpG sites were associated with COPD Table  at FDR lFOLR3, ELOVL3, FAXDC2, FXYD1/LGI4, GABRR1, IFNGR2, and LPO) also exhibited relative hypomethylation in association with COPD. The mean difference in methylation between cases and controls ranged from 7.5 to 11.9 %. These differential methylation results are presented in a volcano plot , and the yellow module contained 1698 probes . The association of the blue and yellow module eigengenes remained statistically significant  in a logistic regression model of COPD affection status after controlling for age, gender, and pack-years of smoking history.Weighted Gene Coexpression Network Analysis software (WGCNA) was used to create a scale-free comethylation network  were part of the blue module. CpG sites marking the COPD- and lung function-associated genes NOTCH4, SERPINA1, FAM13A, TNS1, PPT2, CHRNA5, PPAP2B, CHRNA3, RARB, CHRNA4, ARMC2, CCDC38, MECOM, ADAMTS19, HHIP, and ZKSCAN3/ZSCAN31 were also all found within the blue module. We limited both the blue and yellow modules to those genes with a stringent module membership  cutoff of 0.85 for further analysis, [We investigated the two COPD-associated network modules for genes previously related to COPD. This investigation included genes from the differential methylation analysis results and genes found to be associated with COPD and lung function measurements in genome-wide association studies (GWAS) , branching morphogenesis of an epithelial tube , lung morphogenesis , lung lobe morphogenesis , lung development , and lung lobe development . The limited yellow module of 151 genes was enriched for immune/inflammatory gene sets, such as response to other organism , immune response , defense response to bacterium , and chemotaxis of natural killer cells, neutrophils, and eosinophils .Gene set enrichment analyses of the limited modules were performed using GO Biological Processes ontology, KEGG, and Reactome pathways. The limited blue module of 317 genes was enriched for developmental gene sets, with statistically significant enrichment found in GO pathways such as anatomical structure development  as well as FYXD1  [LGI4/FXYD1) was statistically significantly associated with COPD at an FDR of 5 % in an independent, larger WH COPD methylation dataset cleaned and processed in a comparable way. In addition, in a qualitative comparison of the difference in differential methylation of CpG sites between AA and WH, many of our results were statistically significant for differential hypomethylation only in AA.Within the PASCOPE AA cohort, we identified 5 differentially methylated CpG sites significantly associated with COPD using an FDR of 5 %, and 7 additional associations that approached significance using an FDR of 10 %. We used WGCNA to identify comethylation modules associated with COPD that were enriched for genes related to lung development and immune response and contained biologically relevant genes associated with COPD and lung function. Differentially methylated CpG sites associated with COPD mapped to genes that were biologically plausible candidates for COPD pathogenesis. Notable functions among these genes included nd COPD) , 22. OnlMAML1, RBFOX2, GRASP, FAXDC2, FXYD1/LGI4, IFNGR2) or whole blood (IFNGR2) based on GTEx data showing a median reads per kilobase of transcript per million reads (RPKM) >10 in these tissues, [The majority of our significantly associated (FDR less than 10 %) differential methylation CpG sites are located in genes that are biologically plausible genes for lung disease that may affect the pulmonary, immune, and vascular biology of COPD based on previously published data. Additionally, many of these genes are expressed in either lung  was found to be 15- to 20-fold upregulated during stable COPD and acute exacerbations of COPD in previous studies, [FXYD1) was shown to be associated with COPD in the ICGN cohort by Qiu et al, [Two of the disease-associated genes were associated with COPD in prior studies. Folate Receptor Gamma  is secreted by submucosal glands in human bronchi and plays a role in human airway host defense against bacteria [GABRR1) has been shown to affect alveolar fluid homeostasis in alveolar epithelial type II cells [ELOVL3) has been proposed to contribute to dysregulated lipid droplet formation in pulmonary surfactant in response to particulate exposure [GRASP) were previously associated with asthma in a Latino cohort [SH3TC1) has not been adequately described in the lung; however, it is implicated in networks related to bronchial airway epithelial cells and cigarette smoking [Five CpG sites were annotated to genes related to pulmonary and airway physiology. Lactoperoxidase (bacteria . Gamma-aII cells . Upregulexposure . Rare mio cohort . The fun smoking .CD72) is a CD5 co-ligand involved in hypersensitivity reactions and sarcoidosis, highly expressed in pulmonary alveolar macrophages [FAXDC2) is implicated in “steroid biosynthesis” through KEGG pathways [IFNGR2) plays a role in activation of macrophages and regulation of Th1 response to intracellular pathogens, with genetic variants previously associated with atopic asthma [An additional three CpG sites were annotated to genes related to immune response and steroid synthesis. Cluster of Differentiation 72 (rophages . Fatty Apathways . Interfec asthma  and pulmMAML1) effects angiogenesis during organ development through NOTCH-dependent signaling in murine lung [RBFOX2) is a splicing regulator implicated in differentiation of myofibroblasts to skeletal muscle, and diminished expression previously associated with pressure-overload-mediated progression of dilated cardiomyopathy/heart failure; [The final two CpG sites were related to cardiovascular processes. Mastermind-Like1 protein  while the blue module contained primarily negative measures of gene significance (indicating negative correlation of module comethylation in association with COPD).SERPINA1 is the gene responsible for alpha-1-antitrypsin deficiency, [SEPRINA1 mutations known to cause alpha-1 antitrypsin deficiency are uncommon in AA, one could hypothesize from this data that coregulation of the SERPINA1 gene through DNA methylation (and other genes related to lung development in the blue module) could contribute to COPD susceptibility in a disease module framework. However, this hypothesis would require further study with larger datasets including additional modalities such as gene expression. Many of the CpG sites found in the differential methylation analysis were also found in the blue module with high measures of module membership (indicating importance of the gene to the module) and high measures of gene significance to COPD. The recapitulation of these CpG sites in the same module as previously known COPD- and lung-function-related genes adds validation to our differential methylation results.Further investigation of the blue module showed a network with biological significance for obstructive lung disease. The module was statistically enriched for pathways related to lung development, and also contained multiple genes previously associated with COPD and lung function. iciency,  a known The yellow module, by comparison, contained genes enriched for immune response pathways. Chronic inflammation in response to airway damage from cigarette smoking as well as external pathogens are recognized as integral parts of the pathogenesis of COPD and exacerbations –39. EnriThe PA-SCOPE dataset was a retrospective case-control study and so no direct causation can be inferred from results, only associations of CpG sites with disease. DNA methylation in response to smoking is a dynamic process, and effects may be time-dependent; longitudinal profiling of methylomes and phenotypes is needed , 46. OurThe Illumina Infinium HumanMethylation27 BeadChip Array interrogates only a subset of CpG sites in the human epigenome, and additional unmeasured sites may be differentially methylated in association with COPD. Specifically, the HumanMethylation27 BeadChip’s design focused on CpG sites within transcription start sites of over 14,000 genes and additional coverage of around 200 cancer-related genes . AdditioWe assayed whole blood for DNA methylation signals associated with COPD, but not lung tissue samples. Prior studies have shown associations between smoking and DNA methylation in whole blood , 17, 46.In conclusion, we performed differential methylation analysis in African-American subjects and identified 12 CpG sites statistically significantly associated with COPD at an FDR less than 10 %, of which seven are not statistically significant in a WH cohort study of COPD. We also performed weighted gene comethylation network analysis and identified two comethylation modules associated with COPD in AA, one of which included multiple genes related to obstructive lung disease and COPD. This module was enriched for lung-specific gene sets and our results add to insights into molecular mechanisms that may contribute to lung disease disparities in African-Americans. Molecular mechanisms for COPD-related outcomes in AA smokers have not been adequately investigated. While further research is needed to understand the biological consequences of differential methylation of the genes we identified, they represent promising genes for mechanistic investigations of COPD in AA and for the consideration of epigenetic contributions to racial disparity in COPD susceptibility and severity.1 increase >15 %) were excluded. COPD cases were subject to additional inclusion criteria including inpatient hospitalization for an acute exacerbation of COPD at the time of study entry and a spirometric diagnosis of COPD without significant bronchodilator response. Acute exacerbations of COPD were defined using criteria of worsening dyspnea, increase sputum volume and sputum purulence [Researchers at Temple University and the Pennsylvania Department of Public Health designed the Pennsylvania Study of Chronic Obstructive Pulmonary Exacerbations  as a collaborative observational study to identify demographic and genetic factors that contributed to COPD exacerbations among AA smokers with COPD in urban and rural Pennsylvania. Subject recruitment and data gathering occurred between June 2004 and May 2008. Additional details of the PA-SCOPE study design can be found in Additional file urulence . ControlWe assessed DNA samples from 371 COPD cases (defined by FEV1/FVC ≤ 0.7 and FEV1 ≤ 80 % predicted) and smoking controls for genome wide differential methylation using the Illumina  Infinium HumanMethylation27 BeadChip (Illumina27K). The Illumina27K array assays 27,758 CpG dinucleotides  for quanp-value greater than 0.05. CpG sites with a beadcount of less than 3 in greater than 5 % of samples, and sites having greater than 1 % of samples with a detection p-value greater than 0.05 were also removed; 8 subjects’ demographic data were incomplete and were removed for the final analysis. Technical replicates for one male and one female were included to assess for within-subject correlation across arrays.The R programming language  and the Differential methylation signals arising primarily from cell type composition of whole blood can bias methylation analysis. Both smoking and COPD are associated with inflammation, and differences in methylation signals between cases and controls based purely on immune cell type proportion in whole blood could confound association analysis results. To control for this bias, we performed cell type deconvolution using the method and software provided by Houseman et al,  which usDifferential methylation analysis was performed on 362 samples after quality control using the limma package . For theAn analysis of differential DNA methylation sites associated with COPD was performed previously by our group using WH subjects in the ICGN. This dataset has been previously described,  and addiWGCNA is a network analysis tool that uses hierarchical clustering of correlated methylation states (transformed using the power adjacency function) between CpG probes to construct weighted comethylation modules . The eigt-test statistic for differential methylation between COPD cases and controls, and larger values of gene significance indicate more contribution of the gene’s comethylation pattern to the module’s association with COPD. Results were inspected for genes in the differential methylation top results, as well as for known obstructive lung disease associations from GWAS studies of lung function [Weighted gene comethylation networks were constructed using the quality controlled PA-SCOPE dataset as input to the WGCNA R-package by Langfelder and Horvath,  and netwfunction –67 and Cfunction –73. For function . Gene sefunction  to compa


Metabolic syndrome (MetS), the clustering of multiple leading risk factors, predisposes individuals to increased risk for developing type 2 diabetes and/or cardiovascular disease (CVD). Cardio-metabolic disease risk increases with greater remoteness where specialist services are scarce. Nurse-led interventions are effective for the management of chronic disease. The aim of this clinical trial is to determine whether a nurse-implemented health and lifestyle modification program is more beneficial than standard care to reduce cardio-metabolic abnormalities and future risk of CVD and diabetes in individuals with MetS.MODERN is a multi-centre, open, parallel group randomized controlled trial in regional Victoria, Australia. Participants were self-selected and individuals aged 40 to 70 years with MetS who had no evidence of CVD or other chronic disease were recruited. Those attending a screening visit with any 3 or more risk factors of central obesity, dyslipidemia (high triglycerides or low high density lipoprotein cholesterol) elevated blood pressure and dysglycemia were randomized to either nurse-led health and lifestyle modification (intervention) or standard care (control). The intervention included risk factor management, health education, care planning and scheduled follow-up commensurate with level of risk. The primary cardio-metabolic end-point was achievement of risk factor thresholds to eliminate MetS or minimal clinically meaningful changes for at least 3 risk factors that characterise MetS over 2 year follow-up. Pre-specified secondary endpoints to evaluate between group variations in cardio-metabolic risk, general health and lifestyle behaviours and new onset CVD and type 2 diabetes will be evaluated. Key outcomes will be measured at baseline, 12 and 24 months via questionnaires, physical examinations, pathology and other diagnostic tests. Health economic analyses will be undertaken to establish the cost-effectiveness of the intervention.The MODERN trial will provide evidence for the potential benefit of independent nurse-run clinics in the community and their cost-effectiveness in adults with MetS. Findings will enable more nurse-led clinics to be adopted outside of major cities and encompassing other chronic diseases as a key primary preventative initiative.ACTRN12616000229471) on 19 February 2016 (retrospectively registered).MODERN is registered with the Australian New Zealand Clinical Trials Registry  and was approved by the Australian Catholic University Human Research Ethics Committee (Project No: 2014 244 V) and the Department of Health Human Research Ethics Committee (Project No:38/2014) for the release of Medicare claims information. Metabolic syndrome (MetS), the constellation of central obesity, dyslipidemia, elevated blood pressure (BP) and dysglycemia , encapsuNotwithstanding the definition used to identify subjects with MetS, having multiple risk factors is detrimental to increased disease risk in a dose-response gradient with more components of the MetS , 8. CVD Therefore, our aim was to assess the effectiveness of a nurse-led clinic program that modulated health and lifestyle factors to reduce cardio-metabolic abnormalities and future risk of CVD and T2DM in individuals with MetS. It was hypothesised that there would be more adults with MetS in the nurse-facilitated health and lifestyle modification group compared to standard care who achieve the primary endpoint of meeting target risk factor thresholds or minimum changes that would be considered clinically significant for any 3 or more risk factors that characterise the MetS over 2 year follow-up.MODERN is a multi-centre, open, parallel group randomized controlled trial evaluating the effect of nurse-facilitated health and lifestyle modification (intervention group) vs. standard care (control group) on a primary cardio-metabolic end-point  in at risk regional residents aged between 40 and 70 years. The study flow diagram over 2 year follow up and extended 5 year longer-term follow-up is shown in Fig. Participants were self-selected from two regional locations in Shepparton, northern Victoria, and Colac, south-west Victoria . Census data were used to ensure that a representative sample of the age and sex distribution of each regional community between 40 and 70 years were recruited. The sampling strategy involved large scale promotion of the study to key local workplaces, community groups (e.g. Rotary) and Local Members of Parliament, community engagement at local markets and stalls, direct and indirect postal invitations, radio and newspaper advertising and social media (e.g. Facebook). Individuals responded to participate and a brief screening questionnaire administered via telephone or face-to-face was initially used to determine age and history of CVD or other chronic disease. Eligible participants made an appointment to undergo screening to identify MetS from 26 September 2014 and recruitment was completed on 1 April 2016. The study protocol conformed to SPIRIT guidelines and a full CONSORT diagram will be finalised upon trial completion.1C level for increased risk of diabetes was used as a substitute for fasting plasma glucose [Participants residing in, or in surrounding regions of Shepparton or Colac and aged between 40 and 70 years with any three or more risk factors for MetS  as shown glucose . ParticiParticipants who satisfied the selection criteria were randomized into one of two trial arms according to a 1:1 allocation ratio using a pre-determined computer generated sequentially numbered randomisation schedule centrally performed via SPSS Statistics 22.0  and transferred to the receptionist at each study clinic to assign group distribution. Group allocation was concealed from nurses to eliminate selection bias during recruitment. Block randomisation  occurred with block sizes of 20 and stratified according to MetS without T2DM or with a diagnosis of T2DM. Due to the nature of the intervention, blinding subjects and nurses was not possible.The primary endpoint was the between group difference in achievement of the target risk factor thresholds Table  or minim1C level ≥ 6.5% [Secondary endpoints included between group changes at 24 months in meeting the individual components of the primary endpoint ; resolution of MetS status; incidence of T2DM, as indicated by initiation of glucose-lowering medication following confirmation of a diagnosis of T2DM or a HbAl ≥ 6.5% ; incidensocio-demographic factors including marital and work status, primary language spoken, income, education and ethnicity; health behaviours including smoking, diet and alcohol via the Dietary Questionnaire for Epidemiological Studies (DQES v2) [general health including history of CVD, associated conditions or other serious conditions, family history of CVD or diabetes, prescribed medications and adherence via the Medication Adherence Questionnaire (MAQ) [A self-report questionnaire posted to participants in the week prior to their scheduled visit collected information regarding: DQES v2) , sleep aDQES v2)  and; genre (MAQ) , signs are (MAQ) , health re (MAQ) , perceivre (MAQ)  and locure (MAQ) .preferences for the attributes of a health and lifestyle management program they consider of greatest importance affecting their choice to participate in such programs.An on-line, discrete choice experiment during the week prior to their scheduled visit at baseline and at study end evaluated participant screening assessments were undertaken at a dedicated clinic or on-site at workplaces (for few organisations with large numbers of workers) by registered nurses according to a standardised protocol at baseline, prior to randomisation. The same registered nurse who conducted the screening assessment remained responsible for the follow-up assessments of each participant until study completion; due to standardising the management of participants and frequency of follow-up, a different nurse that managed participants from only one study group was not required to alleviate bias.The 2) was determined from height, measured using a portable stadiometer  and weight, using digital weighing scales , after the removal of shoes and heavy garments. Total cholesterol (TC), high- (HDL-C) and low- (LDL-C) density lipoprotein cholesterol, triglycerides and HbA1C in capillary/fingerstick whole blood were analysed by the reflectance photometry technique using a calibrated Afinion™ AS100 analyser . Sitting blood pressure (BP) was measured in the brachial artery with a suitable cuff size using a calibrated Omron HEM-907 automated monitor  after 5 min of rest; the average of two measurements separated by a one-minute interval were analysed provided BP did not vary by ≥ 10/≥ 5 mmHg, in which case another reading was taken and the closest two readings were analysed. Calculation of CVD risk via the Framingham Risk Equation [Waist and hip circumference were measured using a Figure Finder® Tape Measure  in accord with the World Health Organization (WHO) STEPwise approach to surveillance (STEPS) procedure  in the hEquation , and T2DEquation , was estEquation  and deveEquation , respectelectrocardiography (ECG) via a 12-lead Universal ECG™ in accordance with standard electrode placement and recorded using Office Medic™ Software ; biochemistry assessment from venous blood of creatinine to estimate glomerular filtration rate (eGFR) using the Modification of Diet in Renal Disease study equation, and high-sensitive C-reactive protein (hs-CRP) as an inflammatory marker of CVD risk; actigraphy for 7-day continuous quantitative measurement of sleep, physical activity and sedentary behaviour using GTX3 accelerometers  and; arterial stiffness from ankle brachial (ABI) and cardio ankle vascular pressure indexes (CAVI) using the VaSera™ VS-1500 N vascular device .If MetS was indicated and subjects agreed to be randomized into a study group, additional information was collected including: Qualitative evaluation of intervention fidelity  to asses2 or waist circumference < 80 cm (women) or < 94 cm (men). For physical activity, responses to the IPAQ were assessed and according to Australian Government Department of Health guidelines [1C. For BP, average clinic readings were classified in accord with National Heart Foundation guidelines [Cardio-metabolic risk factor management - to achieve ideal goal levels based on recommended guidelines and with consideration for the circumstances of unique individuals. For weight management, waist circumference, BMI measurements and responses to the DQES food frequency questionnaire were all evaluated followed by tailored advice on healthy eating in accord with Australian Dietary Guidelines  to strividelines , subjectidelines  of < 4.5idelines  of < 5.7idelines  with theidelines . For oveidelines , 29 with1C ≥ 6.5%, markedly elevated levels of individual risk factors or who were smokers. GARDIAN designated AMBER subjects were those with moderate absolute CVD risk scores 10–15% or with risk factors above recommended ranges. GARDIAN designated GREEN subjects (at 12 month review) were those identified by low absolute CVD risk scores < 10%, HbA1C < 5.7% or risk factor levels within recommended limits.The results of the baseline screening assessment were assessed in accord with the Green, Amber, Red Delineation of Risk and Need (GARDIAN) management system to determine the frequency of health care intervention over study follow up . Figure Health education – to put risk factor management in context, participants received education on CVD and T2DM including causes, risks, symptoms, treatment and management; interpretation of individualised test results in contrast to target goal levels and benefits of changing behaviour(s); understanding how to read food labels; managing portion serving sizes and comprehension and adherence to prescribed medication. All participants received a brief report containing their risk assessment results as well as a Health Passport to document before and after photographs, record appointment times and to maintain a “health identity” profile to track risk factor measurements over time and change to their GARDIAN (traffic light) risk colour code. Written education information and risk factor targets to aim for to remain healthy was consolidated within the Health Passport.Care planning – to help reduce identified risk factors, nurses trained in motivational interviewing  applied Scheduled follow-up - to assist subjects to adhere to the care plan and reinforce positive behaviour change, specified follow-up visits and supplemental telephone coaching was implemented in accord with GARDIAN status. The frequency of contact with participants was aligned with their level of risk. As shown in Fig. The nurse-facilitated intervention required that two nurses at each site actively deliver a health and lifestyle intervention and remain responsible for assessing participant progress in achieving their health goals until study completion. Nurses applied the intervention on an individual basis and acted within the scope of their nursing responsibilities and independent of the participant’s health care professionals. The aim of the intervention was to deliver coaching to support individuals to achieve health behaviour change for improved risk factor management. Intervention participants were permitted to seek any relevant concomitant care. Key components were:Participants allocated to the standard care arm of MODERN received screening assessments but diluted risk factor management which was limited to receiving a brief risk assessment report and Health Passport with less intensive CVD and T2DM education and dietary and lifestyle advice. Ideal risk factor targets were identical yet care plans were not developed. GARDIAN status was not used to direct management and follow-up contacts at set times; aside from baseline, 12 month (mid), and 24 month (end) study visits, all management and follow-up was at the discretion of their usual health care providers. As per intervention group participants, control group participants were permitted to seek any relevant concomitant care.For all participants randomized into a study group, self-report questionnaires posted 1 week prior to their scheduled visit collected updated information regarding health behaviours and general health at 12 and 24 month visits. Screening assessments, biochemistry, actigraphy and arterial stiffness tests were also repeated at 12 and 24 month visits for all participants. For intervention participants only, just screening assessments were conducted at all other (GARDIAN directed) clinic visits to help assess participant’s progress in achieving their health goals. Extended surveillance to 5 years post randomization of cardio-metabolic health and associated health care activity to determine the longer-term impact of the MODERN intervention is planned.A 15% difference  in the number of subjects who achieved target risk factor thresholds or clinically significant changes in any 3 MetS risk factors was derived from sub-group analyses  from a pilot intervention study  and a raInformation collected under unique study identification will be returned to an independent data management unit for double data entry, range checks for data values, data queries to be resolved by data lock and coding according to standard operating procedures. Storage of paper documents will be filed in a locked compactus controlled by proxy access to authorised personnel. Electronic files will be saved in a secure server storage system that is accessible by authorised personnel in accord with information technology security processes. Data sharing and use by organisations involved in the study is guaranteed by clinical trial research agreements between collaborating institutions. Upon study completion, participants will receive a summary of group results and study findings will be presented in publications and presentations.2 tests with calculation of odds ratios and 95% CI, whereas continuous variables will be assessed using mean (SD) or median (IQR) and group differences compared using independent t-tests or Mann-Whitney tests for variables with skewed distributions. For dichotomous variables, multiple logistic regression using 24 month results as dependent variables will evaluate the independent correlates of achieving the primary and secondary endpoints, after adjusting for baseline results and socio-demographic characteristics. For continuous variables, mixed-model ANOVA will be performed to asses within (pre-post) and between-group (control-intervention) differences over time and multiple linear regression used to evaluate important predictors of response.All analyses will be performed according to a statistical analysis plan and on an intention-to-treat basis. Tests will be two-sided at the nominal level α = 0.05. Data from each clinic will be pooled and summarised. Descriptive statistics will summarise the socio-demographic, clinical and overall health profile of the sample at baseline and 24 months follow-up; discrete variables will be assessed by frequencies and percentages and group differences tested using χThis study will be the first Australian-based trial to establish the evidence for the potential benefit of independent nurse-run clinics in the community and their cost-effectiveness in adults with common cardio-metabolic abnormalities. Findings will determine whether a nurse-implemented health and lifestyle modification program is more effective at improving MetS components and other major risk factors for the development of CVD and T2DM compared to standard care in adults who are in jeopardy the most by living away from urban areas where socioeconomic disadvantage is higher and specialist health care increasingly scarce , 39. ImpThe novelty of the MODERN study will establish the feasibility of nurses to safely and effectively screen for the presence of MetS and deliver cardio-metabolic management based on a written protocol that integrates a systematic approach to individual assessment of risk and tailored management . Nurse-lThe detailed health economic evaluation component of the MODERN trial has the distinct advantage to enhance the translation of research findings into sustainable improvements in routine clinical practice and patient outcomes. Supporting health economic analyses are lacking in the Australian context and evidence relating to the cost-effectiveness of nurse-led clinics remains an obstacle to overcome before next generation models of care can improve the quality of preventative health. At present, it is incontrovertible that components of the MetS cause risk for CVD and T2DM and the MetS is an ideal target for risk reduction programs, carried out by nurses with the competence and skill set that uphold cardio-metabolic disease prevention. The results of the MODERN trial will add to the evidence-base for the success or failure of a nurse-led health service delivery of care for combatting the likelihood of CVD and T2DM in individuals with the MetS.


Dyslexia is a developmental disorder in reading that exhibits varied patterns of expression across children. Here we examined the degree to which different kinds of reading disabilities (defined as profiles or patterns of reading problems) contribute to brain morphology results in Jacobian determinant images that represent local brain shape and volume. A matched-pair brain morphometry approach was used to control for confounding from brain size and research site effects in this retrospective multi-site study of 134 children from eight different research sites. Parietal operculum, corona radiata, and internal capsule differences between cases and controls were consistently observed across children with evidence of classic dyslexia, specific comprehension deficit, and language learning disability. Thus, there can be common brain morphology findings across children with quite varied reading disability profiles that we hypothesize compound the developmental difficulties of children with unique reading disability profiles and reasons for their reading disability. Children with reading disability can exhibit varied patterns of oral and written language problems5 that include: (1) a classic dyslexia pattern with word-level decoding and spelling problems6; (2) comprehension-specific reading disability9; (3) and reading disability that occurs with specific language impairment or language learning disability11. Neurobiologic studies of reading disability typically focus on one of these three behavioral profiles. In practice, children with quite varied language profiles based on clinical measures are included in reading disability samples12, which raises questions about the degree to which a particular reading disability profile (pattern of language skills) contributes to dyslexia findings.Dyslexia is a developmental reading disability that affects 5–15% of the U.S. population16. This neurobiologic heterogeneity can limit effect sizes or produce inconsistent effects across studies when samples include multiple reading disability profiles, particularly when sample sizes are small. Thus, it is unclear as to whether there are common neurobiologic findings across children with reading disability or whether findings are due to a specific reading disability profile.Different reading disability profiles have been mapped to different neurobiological features15 and low brain size appears to occur with lower superior temporal sulcus gray matter volume in children with reading disability compared to controls12. Variance in brain size can dominate voxel-based effects in multi-site samples12 because brain size strongly covaries with voxel-based measures17.This behavioral heterogeneity problem is compounded by effects due to brain size when testing hypotheses about effects in locally specific brain regions. For example, low brain size is characteristic of children with oral and written language impairmentsHere we performed a case-control analysis of a multi-site dyslexia dataset to deal with brain size  and research site variance that can confound voxel-based effects. Parietal operculum and subcortical morphology differences were observed across reading disability profiles using Jacobian determinant images that represent the volumetric displacement of images to a brain template.p < 0.05; Table Case-control pairs were optimally matched for sex and research site and to minimize case-control differences in age, total gray and white matter volume. One-sample t-tests of case-control Jacobian determinant difference images demonstrated that reading disability cases required more expansion of voxels to fit to a study-specific template  and 1000 randomly matched pairs (paired across brain size and research sites). We then performed t-tests to establish the distribution of case-control differences. Because the same 134 individuals were used to form both bootstrap statistic distributions, differences in the voxel-level results were reflective of the quality of case-control matches. While the well-matched samples yielded results that were similar to the optimally matched results show in Fig. 5 and the raters’ considerable clinical experience assessing and treating children with reading disability. Random Forest was then used to show that these profiles could be consistently classified as different from controls (94% accuracy) using a machine learning algorithm. These unique patterns (profiles) of reading disability are shown in Fig. F = 27.02, p < 0.001; Dimension 2: F = 90.13, p < 0.001). Post-hoc comparisons revealed that all three reading disability profiles exhibited significant differences between each other for both dimensions (ps = 0.01 to p < 0.001).Clinician expert-raters classified the reading disability cases according to the three reading disability profiles described above based on evidence of: (1) poor word and non-word phonological decoding (Poor Decoders); 2) relatively specific reading comprehension problems (Poor Comprehenders); and 3) relatively poor decoding, reading comprehension, and verbal comprehension [Generally Poor Readers;  = 0.13, ns). This observation is consistent with the results of controlling for Dimension 2 on the left SII/SMG case-control differences, but not the left CR/IC differences.Corona radiata findings have been reported in diffusion imaging studies of dyslexia24. Left secondary somatosensory cortex (SII), in particular, exhibits increased responsiveness when people attend to speech25. A similar parietal operculum region (SII to SMG) is thought to support phonological processing by providing a working memory mechanism to “clean up” noisy phonological representations26. These findings appear to be consistent with evidence that this region supports mapping orthographic to phonologic representations27. They also suggest that atypical orthographic development would limit the benefit from orthographic consistency on speech processing in children with reading disability, as demonstrated in refs The left parietal operculum has been observed to exhibit atypical activation in functional imaging studies of dyslexia27. SII is engaged during speech production tasks30 and also exhibits gray matter density changes that track with changes in Verbal IQ31. Longitudinal changes in left SII gray matter density appeared to predict changes in Verbal IQ because of reading experience31. In support of this experience explanation, parietal cortex morphology (Jacobian determinant) was related to individual differences in reading ability for ~8.4 year old children, but not in the same children when the data were collected a year earlier32. Moreover, adults acquiring literacy late in life had increased SMG gray matter volume compared to illiterate adults33. The parietal operculum effects in the current study were observed across reading disability cases from 7.33–12.67 years of age, but the differences appeared to be most pronounced among the younger children  = −0.32, p = 0.008).A role for SII and SMG cortex in mapping orthographic to phonologic representations predicts that these regions are engaged when people read aloud34. Children with reading disability may not be able to make efficient use of working memory to accumulate sensory evidence for mapping orthographic and phonologic information (Poor Readers and Poor Decoders) or for following the meaning of connected speech or text (Poor Readers and Poor Comprehenders). Working memory measures may have demonstrated impaired phonological working memory across all three reading disability profiles38.One way parietal cortex could “clean up” noisy representations is through accumulating evidence to aid in perceptual decision-making41, which again may relate to diffusion imaging findings linking the CR/IC to reading development40. Given that the CR/IC effects were particularly evident in the Generally Poor Readers . These existing data were collected from contributing sites where the human subject review boards provided approval to share de-identified data that were collected under the appropriate human subjects guidelines of those institutions and with informed consent. Data de-identification protected the privacy of subjects in accordance with HIPAA regulations51. Reception of these “non-human” de-identified data was approved by the Medical University of South Carolina (MUSC) Institutional Review Board (IRB) and the research described here was performed in accordance to MUSC IRB regulations and guidelines.The data included in this study were collected as part of a project to develop methods for retrospective analysis of multi-site data and are part of a Dyslexia Data Consortium database  the Wechsler Intelligence Scales for Children or the Wechsler Abbreviated Scales of Intelligence 55; and (3) the Comprehensive Test of Phonological Processing Rapid Automatized Naming or the Rapid Alternating Stimulus Tests57. A subset of these cases  was included in brain morphology analyses after identifying (1) cases who could be consistently classified as having unique reading disability profiles (39 inconsistently classified by expert raters) and (2) cases and controls that could be matched according to brain size and research site (57 without matches). Controls were included if they had Word Attack, Word Identification, and Passage Comprehension scores above the 25th percentile, while reading disability cases were selected if they scored below the 25th percentile for one of these measures.Data from 247 children  were selected from the multi-site dataset based on having T1-weighted images and standardized scores from the: (1) Woodcock-Johnson IIIR or Woodcock Reading Mastery Tests 58 and input from a Psychologist with extensive clinical experience with specific learning disabilities (SLDs) and 25 years of experience directing NIH-supported research on SLDs, Poor Decoders were classified based on: (1) Verbal Comprehension standard scores that were within the average to above-average range or above the 25th percentile; (2) Word Attack standard scores that were typically below the 25th percentile; (3) Word Identification and Passage Comprehension standard scores that were typically consistent with Word Attack scores; and (4) RAN standard scores that were typically below the 25th percentile. Poor Comprehenders were classified based on: (1) Verbal Comprehension scores that met the same criteria as Poor Decoders; (2) Word Attack scores that were above the 25th percentile; (3) Word Identification and Passage Comprehension scores that were typically at or below the 25th percentile; (4) RAN scores that were typically greater than the 16th percentile; and (5) children were typically older than 7–8 years to consider the effects of developmental and academic exposure on comprehension. Generally Poor Readers were classified based on Verbal Comprehension, Word Attack, Word Identification, and Passage Comprehension scores that were at or below the 25th percentile. Supplemental Table Two clinically certified Speech-Language Pathologists with considerable experience assessing children with reading disabilities examined the behavioral data to classify reading disability cases into classic dyslexia (Poor Decoders), comprehension-specific (Poor Comprehenders), and multiple language impairment profiles . Guided by the empirical literatureSupplementary Table 59 was developed using the consistently classified reading disability cases to demonstrate that the clinical expert classified profiles could be distinguished from each other and from controls based on their behavioral profiles using an automated approach. The analyses were carried out using the R statistics package . The Random Forest was tuned  with a five step parameter search, then classified groups within the training dataset based on a leave-one-out cross validation test (LOOCV). The LOOCV test iteratively trains the Random Forest algorithm using all but one case from the training dataset, then classifies the remaining case to approximate independent train and test data. Classification accuracy was determined by whether the LOOCV classification of each case matched its expert-based label.A Random Forest classifierRandom Forest predicted the expert-rater classifications of Poor Decoders, Poor Comprehenders, Generally Poor Readers, and controls with 94% accuracy using the same behavioral and age variables that were used by the expert-raters. Each variable, perhaps with the exception of age, contributed to classification accuracy . Random Forest misclassified cases were likely to have a Verbal Comprehension or Word Attack score, for example, at a boundary that distinguished the reading disability profiles. These results (1) provide insight into the behavioral variables that were most important for reading disability profile classification and (2) demonstrate that there were unique behavioral profiles in the dataset. As described below, the Random Forest classification probabilities for each reading disability profile and controls were used to perform multidimensional scaling for the 134 cases and controls. This analysis generated two spatial dimensions to confirm that the profiles were clearly different from each other and from controls . There also was no significant difference in propensity score between the reading disability cases and controls (t(132) = −0.33, ns) and no significant case-control differences in propensity scores between the reading disability profiles  = 0.01, ns).Case-control pairs were identified by (1) creating strata of cases and controls according to smaller or larger brain size  and research site, and then 2) selecting unique pairs of optimally matched cases and controls within each stratum. Specifically, coarsened exact matching  was used to create the strata for 176 participants that included participants with smaller or larger total brain sizes who were from the same research site. Propensity scores were estimated for each subject with a logistic regression that predicted case-control status using research site and total brain size. A nearest-neighbor algorithm  was used to identify the most similar case-control pairs within each stratum on the basis of the propensity score, the match-quality weight from CEM, and total brain size. Because each case-control pair was required to include participants that did not occur in any other pair, the matching procedure reduced the sample size to 134 subjects . Paired-sample t-tests were performed to determine that there were no significant differences in the resultant matched pairs with respect to age, total gray matter volume, total white matter volume, or total brain size . This approach further limited the impact of these potential nuisance variables on the results that can lead to bias amplification, particularly when their effect on a dependent variable is stronger than the predictor variable of interest64 for the unsmoothed Jacobian determinant images that can represent shape and gross volumetric effects65.Statistical analyses were performed using (1) an unpaired group difference approach that is typically used in neuroimaging studies of group differences and (2) the matched-pair case-control approach. The results demonstrated a statistical advantage of the matched-pair approach over the unpaired approach, at least for a sample size of 134 subjects. The FSL randomise function was used to perform these voxel-based comparisons with 10,000 permutations to control for multiple comparisons. Threshold free cluster enhancement (TFCE) was used to optimize sensitivity to focal large effects and spatially broader smaller effectsps > 0.26).To ensure that case-control results were not dependent on the sampling of one set of case-control pairs, voxel-based t-test comparisons were performed for 1000 well-matched case-control samples to establish confidence intervals Fig.  for the rd dimension was not necessary to differentiate these profiles, as further demonstrated in Fig. Finally, multi-dimensional scaling was performed in R with the Random Forest classification probabilities using the cmdscale function. This procedure provided a Euclidian distance estimate for each participant relative to the others based on their reading disability profile classification probabilities. Two dimensions provided a goodness of fit = 0.87. Inspection of the Random Forest probabilities that suggested Poor Decoders and Generally Poor Readers fell along a continuum of Poor Decoder to Poor Reader, suggesting that a 3The multi-dimensional distance variables for each dimension were subtracted between a case and control to obtain case-control distance differences for each dimension. These two variables were used to determine the extent to which case-control brain structure differences could be attributed to the magnitude of behavioral difference between each case and control for metrics that were sensitive to the distribution of reading disability profiles. This provided a quantitative variable to test profile effects that considered the behavioral profile of both the case and control. Permutation tests 10,000) with FSL randomise (TFCE) were performed to relate difference images to one of the dimension difference variables at a time, to determine the extent to which the effects shown in Fig. 0,000 witSupplementary Information