Urinary sodium excretion, dietary sources of sodium intake and knowledge and practices around salt use in a group of healthy Australian women

Objective: Strategies that aim to facilitate reduction of the salt content of foods in Australia are hampered by sparse and outdated data on habitual salt intakes. This study assessed habitual sodium intake through urinary excretion analyses, and identified food sources of dietary sodium, as well as knowledge and practices related to salt use in healthy women. Methods: Cross-sectional, convenient sample of 76 women aged 20 to 55 years, Wollongong, NSW. Data included a 24 hour urine sample, three-day food diary and a self-administered questionnaire. Results: Mean Na excretion equated to a NaCl (salt) intake of 6.41 (SD=2.61) g/day; 43% had values /day. Food groups contributing to dietary sodium were: bread and cereals (27%); dressings/sauces (20%); meat/egg-based dishes (18%); snacks/desserts/extras (11%); and milk and dairy products (11%). Approximately half the sample reported using salt in cooking or at the table. Dietary practices reflected a high awareness of salt-related health issues and a good knowledge of food sources of sodium. Conclusion: These findings from a sample of healthy women in the Illawarra indicate that dietary sodium intakes are lower in this group than previously reported in Australia. However, personal food choices and high levels of awareness of the salt reduction messages are not enough to achieve more stringent dietary targets of foods

The influence of α-actinin-3 deficiency on bone remodelling markers in young men

There is a large individual variation in the bone remodelling markers (BRMs) osteocalcin (OC), procollagen 1 N-terminal propeptide (P1NP) and β-isomerized C-terminal telopeptide (β-CTx), as well as undercarboxylated osteocalcin (ucOC), at rest and in response to exercise. α-actinin-3 (ACTN3), a sarcomeric protein, is expressed in skeletal muscle and osteoblasts and may influence BRM levels and the cross-talk between muscle and bone. We tested the levels of serum BRMs in α-actinin-3 deficient humans (ACTN3 XX) at baseline, and following a single bout of exercise. Forty-three healthy Caucasian individuals were divided into three groups (ACTN3 XX, n = 13; ACTN3 RX, n = 16; ACTN3 RR, n = 14). Participants completed a single session of High Intensity Interval Exercise (HIIE) on a cycle ergometer (8 × 2-min intervals at 85% of maximal power). Blood samples were taken before, immediately after, and three hours post exercise to identify the peak changes in serum BRMs. There was a stepwise increase in resting serum BRMs across the ACTN3 genotypes (XX \u3e RX \u3e RR) with significantly higher levels of tOC ~ 26%, P1NP ~ 34%, and β-CTX (~ 33%) in those with ACTN3 XX compared to ACTN3 RR. Following exercise BRMs and ucOC were higher in all three ACTN3 genotypes, with no significant differences between groups. Serum levels of tOC, P1NP and β-CTX are higher in men with ACTN3 XX genotype (α-actinin-3 deficiency) compared to RR and RX. It appears that the response of BRMs and ucOC to exercise is not explained by the ACTN3 genotype

Telomerecat: A ploidy-agnostic method for estimating telomere length from whole genome sequencing data.

Telomere length is a risk factor in disease and the dynamics of telomere length are crucial to our understanding of cell replication and vitality. The proliferation of whole genome sequencing represents an unprecedented opportunity to glean new insights into telomere biology on a previously unimaginable scale. To this end, a number of approaches for estimating telomere length from whole-genome sequencing data have been proposed. Here we present Telomerecat, a novel approach to the estimation of telomere length. Previous methods have been dependent on the number of telomeres present in a cell being known, which may be problematic when analysing aneuploid cancer data and non-human samples. Telomerecat is designed to be agnostic to the number of telomeres present, making it suited for the purpose of estimating telomere length in cancer studies. Telomerecat also accounts for interstitial telomeric reads and presents a novel approach to dealing with sequencing errors. We show that Telomerecat performs well at telomere length estimation when compared to leading experimental and computational methods. Furthermore, we show that it detects expected patterns in longitudinal data, repeated measurements, and cross-species comparisons. We also apply the method to a cancer cell data, uncovering an interesting relationship with the underlying telomerase genotype

Biological heterogeneity in idiopathic pulmonary arterial hypertension identified through unsupervised transcriptomic profiling of whole blood

Idiopathic pulmonary arterial hypertension (IPAH) is a rare but fatal disease diagnosed by right heart catheterisation and the exclusion of other forms of pulmonary arterial hypertension, producing a heterogeneous population with varied treatment response. Here we show unsupervised machine learning identification of three major patient subgroups that account for 92% of the cohort, each with unique whole blood transcriptomic and clinical feature signatures. These subgroups are associated with poor, moderate, and good prognosis. The poor prognosis subgroup is associated with upregulation of the ALAS2 and downregulation of several immunoglobulin genes, while the good prognosis subgroup is defined by upregulation of the bone morphogenetic protein signalling regulator NOG, and the C/C variant of HLA-DPA1/DPB1 (independently associated with survival). These findings independently validated provide evidence for the existence of 3 major subgroups (endophenotypes) within the IPAH classification, could improve risk stratification and provide molecular insights into the pathogenesis of IPAH

Publisher Correction: Telomerecat: A ploidy-agnostic method for estimating telomere length from whole genome sequencing data.

A correction to this article has been published and is linked from the HTML and PDF versions of this paper. The error has been fixed in the paper

GWAS meta-analysis of intrahepatic cholestasis of pregnancy implicates multiple hepatic genes and regulatory elements

Intrahepatic cholestasis of pregnancy (ICP) is a pregnancy-specific liver disorder affecting 0.5–2% of pregnancies. The majority of cases present in the third trimester with pruritus, elevated serum bile acids and abnormal serum liver tests. ICP is associated with an increased risk of adverse outcomes, including spontaneous preterm birth and stillbirth. Whilst rare mutations affecting hepatobiliary transporters contribute to the aetiology of ICP, the role of common genetic variation in ICP has not been systematically characterised to date. Here, we perform genome-wide association studies (GWAS) and meta-analyses for ICP across three studies including 1138 cases and 153,642 controls. Eleven loci achieve genome-wide significance and have been further investigated and fine-mapped using functional genomics approaches. Our results pinpoint common sequence variation in liver-enriched genes and liver-specific cis-regulatory elements as contributing mechanisms to ICP susceptibility

Poor iodine status and knowledge related to iodine on the eve of mandatory iodine fortification in Australia

Background: Mandatory fortification of bread with iodised salt is proposed to address the re-emergence of iodine deficiency in Australia and New Zealand. The impacts of fortification require baseline data of iodine status among vulnerable sectors of the population. Objective: To assess the iodine status of healthy women and to investigate consumer understanding and attitudes related to the proposed mandatory iodine fortification programme. Design: Cross-sectional sample of 78 non-pregnant women aged 20-55 y was conveniently sampled in Wollongong, NSW. A single 24-hr urine sample was collected for urinary iodine concentration (UIC). A selfadministered questionnaire assessed consumer understanding, perceptions and attitudes related to iodine fortification. Outcomes: Median UIC = 56 μg/L (IQR = 41-68), indicating mild iodine deficiency. Knowledge about iodine was poor with less than half associating low iodine status with adverse pregnancy outcomes. Health education and supplementation, particularly at the medical practitioner interface, was considered the best strategy for improving low iodine levels. Conclusions: The iodine status of women in one region of New South Wales was low. These data add support to the need for a national approach to address iodine intake which includes an accompanying consumer education campaign

Poor knowledge and practices related to iodine nutrition during pregnancy and lactation in Australian women: pre-and post-iodine fortification

A before-after review was undertaken to assess whether knowledge and practices related to iodine nutrition, supplementation and fortification has improved in Australian women since the introduction of mandatory iodine fortification in 2009. Surveys of pregnant (n = 139) and non-pregnant (n = 75) women in 2007-2008 are compared with surveys of pregnant (n = 147) and lactating women (n = 60) one to two years post-fortification in a regional area of New South Wales, Australia. A self-administered questionnaire was completed and dietary intake of iodine was assessed using a validated food frequency questionnaire. A generally poor knowledge about the role and sources of iodine in the diet remained after fortification. Post-fortification, iodine-containing supplements were being taken by 60% (up from 20% pre-fortification) and 45% of pregnant and lactating women, respectively. Dairy foods were the highest contributors to dietary iodine intake (57%-62%). A low intake of fish and seafood resulted in this food group contributing only 3%-8% of total intake. A low level of public awareness regarding the role of iodine in health supports the need for public health strategies in addition to fortification, such as an accompanying consumer education campaign, increased uptake of supplementation, and on-going monitoring

Evidence Based Selection of Commonly Used RT-qPCR Reference Genes for the Analysis of Mouse Skeletal Muscle

<div><p>The ability to obtain accurate and reproducible data using quantitative real-time Polymerase Chain Reaction (RT-qPCR) is limited by the process of data normalization. The use of ‘housekeeping’ or ‘reference’ genes is the most common technique used to normalize RT-qPCR data. However, commonly used reference genes are often poorly validated and may change as a result of genetic background, environment and experimental intervention. Here we present an analysis of 10 reference genes in mouse skeletal muscle (<i>Actb, Aldoa, Gapdh, Hprt1, Ppia, Rer1, Rn18s, Rpl27, Rpl41 and Rpl7L1</i>), which were identified as stable either by microarray or in the literature. Using the MIQE guidelines we compared wild-type (WT) mice across three genetic backgrounds (R129, C57BL/6j and C57BL/10) as well as analyzing the α-actinin-3 knockout (<i>Actn3</i> KO) mouse, which is a model of the common null polymorphism (R577X) in human <i>ACTN3</i>. Comparing WT mice across three genetic backgrounds, we found that different genes were more tightly regulated in each strain. We have developed a ranked profile of the top performing reference genes in skeletal muscle across these common mouse strains. Interestingly the commonly used reference genes; <i>Gapdh, Rn18s</i>, <i>Hprt1</i> and <i>Actb</i> were not the most stable. Analysis of our experimental variant (<i>Actn3</i> KO) also resulted in an altered ranking of reference gene suitability. Furthermore we demonstrate that a poor reference gene results in increased variability in the normalized expression of a gene of interest, and can result in loss of significance. Our data demonstrate that reference genes need to be validated prior to use. For the most accurate normalization, it is important to test several genes and use the geometric mean of at least three of the most stably expressed genes. In the analysis of mouse skeletal muscle, strain and intervention played an important role in selecting the most stable reference genes.</p></div

RNA quality control.

<p>A) Bioanalyser output of total RNA extracted from mouse skeletal muscle. (L) Ladder, (1 – 3) representative muscle samples. B) Example of Bioanalyser electropherogram of RNA, (M) marker, 18S and 28S ribosomal RNA peaks.</p