Australian Genomics: Outcomes of a 5-year national program to accelerate the integration of genomics in healthcare.

Australian Genomics is a national collaborative partnership of more than 100 organizations piloting a whole-of-system approach to integrating genomics into healthcare, based on federation principles. In the first five years of operation, Australian Genomics has evaluated the outcomes of genomic testing in more than 5,200 individuals across 19 rare disease and cancer flagship studies. Comprehensive analyses of the health economic, policy, ethical, legal, implementation and workforce implications of incorporating genomics in the Australian context have informed evidence-based change in policy and practice, resulting in national government funding and equity of access for a range of genomic tests. Simultaneously, Australian Genomics has built national skills, infrastructure, policy, and data resources to enable effective data sharing to drive discovery research and support improvements in clinical genomic delivery.

The Effect of Plasma Lipids and Lipid-Lowering Interventions on Bone Mineral Density: A Mendelian Randomization Study.

Several epidemiological studies have reported a relationship between statin treatment and increased bone mineral density (BMD) and reduced fracture risk, but the mechanism underlying the purported relationship is unclear. We used Mendelian randomization (MR) to assess whether this relationship is explained by a specific effect in response to statin use or by a general effect of lipid lowering. We utilized 400 single-nucleotide polymorphisms (SNPs) robustly associated with plasma lipid levels as exposure. The outcome results were obtained from a heel estimated BMD (eBMD) genomewide association study (GWAS) from the UK Biobank and dual-energy X-ray absorptiometry (DXA) BMD at four body sites and fracture GWAS from the GEFOS consortium. We performed univariate and multivariable MR analyses of low-density lipoprotein cholesterol (LDL-C), high-density lipoprotein cholesterol (HDL-C), and triglyceride levels on BMD and fracture. Univariate MR analyses suggested a causal effect of LDL-C on eBMD (ß = -0.06; standard deviation change in eBMD per standard deviation change in LDL-C, 95% confidence interval [CI] = -0.08 to -0.04; p = 4 × 10-6 ), total body BMD (ß = -0.05, 95% CI = -0.08 to -0.01, p = 6 × 10-3 ) and potentially on lumbar spine BMD. Multivariable MR suggested that the effects of LDL-C on eBMD and total body BMD were independent of HDL-C and triglycerides. Sensitivity MR analyses suggested that the LDL-C results were robust to pleiotropy. MR analyses of LDL-C restricted to SNPs in the HMGCR region showed similar effects on eBMD (ß = -0.083; -0.132 to -0.034; p = .001) to those excluding these SNPs (ß = -0.063; -0.090 to -0.036; p = 8 × 10-6 ). Bidirectional MR analyses provided some evidence for a causal effect of eBMD on plasma LDL-C levels. Our results suggest that effects of statins on eBMD and total body BMD are at least partly due to their LDL-C lowering effect. Further studies are required to examine the potential role of modifying plasma lipid levels in treating osteoporosis. © 2020 American Society for Bone and Mineral Research.

The Medical Genome Reference Bank contains whole genome and phenotype data of 2570 healthy elderly.

Population health research is increasingly focused on the genetic determinants of healthy ageing, but there is no public resource of whole genome sequences and phenotype data from healthy elderly individuals. Here we describe the first release of the Medical Genome Reference Bank (MGRB), comprising whole genome sequence and phenotype of 2570 elderly Australians depleted for cancer, cardiovascular disease, and dementia. We analyse the MGRB for single-nucleotide, indel and structural variation in the nuclear and mitochondrial genomes. MGRB individuals have fewer disease-associated common and rare germline variants, relative to both cancer cases and the gnomAD and UK Biobank cohorts, consistent with risk depletion. Age-related somatic changes are correlated with grip strength in men, suggesting blood-derived whole genomes may also provide a biologic measure of age-related functional deterioration. The MGRB provides a broadly applicable reference cohort for clinical genetics and genomic association studies, and for understanding the genetics of healthy ageing.

The Medical Genome Reference Bank: a whole-genome data resource of 4000 healthy elderly individuals. Rationale and cohort design.

Allele frequency data from human reference populations is of increasing value for the filtering, interpretation, and assignment of pathogenicity to genetic variants. Aged and healthy populations are more likely to be selectively depleted of pathogenic alleles and therefore particularly suitable as a reference population for the major diseases of clinical and public health importance. However, reference studies of confirmed healthy elderly individuals have remained under-represented in human genetics. Here we describe the Medical Genome Reference Bank (MGRB), a large-scale comprehensive whole-genome data set of healthy elderly individuals. The MGRB provides an accessible data resource for health-related research and clinical genetics and a powerful platform for studying the genetics of healthy ageing. The MGRB is comprised of 4000 healthy, older individuals, mostly of European descent, recruited from two Australian community-based cohorts. Each participant lived ≥70 years with no reported history of cancer, cardiovascular disease, or dementia. DNA derived from blood samples has been subject to whole-genome sequencing. The MGRB has committed to a policy of data sharing, employing a hierarchical data management system to maintain participant privacy and confidentiality, while maximising research and clinical usage of the database. The MGRB represents a resource of international significance, which will be made broadly accessible to the clinical and genetic research community.

Calypso: a user-friendly web-server for mining and visualizing microbiome-environment interactions.

Calypso is an easy-to-use online software suite that allows non-expert users to mine, interpret and compare taxonomic information from metagenomic or 16S rDNA datasets. Calypso has a focus on multivariate statistical approaches that can identify complex environment-microbiome associations. The software enables quantitative visualizations, statistical testing, multivariate analysis, supervised learning, factor analysis, multivariable regression, network analysis and diversity estimates. Comprehensive help pages, tutorials and videos are provided via a wiki page. Availability and Implementation: The web-interface is accessible via http://cgenome.net/calypso/ . The software is programmed in Java, PERL and R and the source code is available from Zenodo ( https://zenodo.org/record/50931 ). The software is freely available for non-commercial users. Contact: l.krause@uq.edu.au. Supplementary information: Supplementary data are available at Bioinformatics online.

Mining, visualizing and comparing multidimensional biomolecular data using the Genomics Data Miner (GMine) Web-Server.

Genomics Data Miner (GMine) is a user-friendly online software that allows non-experts to mine, cluster and compare multidimensional biomolecular datasets. Various powerful visualization techniques are provided, generating high quality figures that can be directly incorporated into scientific publications. Robust and comprehensive analyses are provided via a broad range of data-mining techniques, including univariate and multivariate statistical analysis, supervised learning, correlation networks, clustering and multivariable regression. The software has a focus on multivariate techniques, which can attribute variance in the measurements to multiple explanatory variables and confounders. Various normalization methods are provided. Extensive help pages and a tutorial are available via a wiki server. Using GMine we reanalyzed proteome microarray data of host antibody response against Plasmodium falciparum. Our results support the hypothesis that immunity to malaria is a higher-order phenomenon related to a pattern of responses and not attributable to any single antigen. We also analyzed gene expression across resting and activated T cells, identifying many immune-related genes with differential expression. This highlights both the plasticity of T cells and the operation of a hardwired activation program. These application examples demonstrate that GMine facilitates an accurate and in-depth analysis of complex molecular datasets, including genomics, transcriptomics and proteomics data.

Estimation and partitioning of (co)heritability of inflammatory bowel disease from GWAS and immunochip data.

As custom arrays are cheaper than generic GWAS arrays, larger sample size is achievable for gene discovery. Custom arrays can tag more variants through denser genotyping of SNPs at associated loci, but at the cost of losing genome-wide coverage. Balancing this trade-off is important for maximizing experimental designs. We quantified both the gain in captured SNP-heritability at known candidate regions and the loss due to imperfect genome-wide coverage for inflammatory bowel disease using immunochip (iChip) and imputed GWAS data on 61,251 and 38.550 samples, respectively. For Crohn's disease (CD), the iChip and GWAS data explained 19 and 26% of variation in liability, respectively, and SNPs in the densely genotyped iChip regions explained 13% of the SNP-heritability for both the iChip and GWAS data. For ulcerative colitis (UC), the iChip and GWAS data explained 15 and 19% of variation in liability, respectively, and the dense iChip regions explained 10 and 9% of the SNP-heritability in the iChip and the GWAS data. From bivariate analyses, estimates of the genetic correlation in risk between CD and UC were 0.75 (SE 0.017) and 0.62 (SE 0.042) for the iChip and GWAS data, respectively. We also quantified the SNP-heritability of genomic regions that did or did not contain the previous 163 GWAS hits for CD and UC, and SNP-heritability of the overlapping loci between the densely genotyped iChip regions and the 163 GWAS hits. For both diseases, over different genomic partitioning, the densely genotyped regions on the iChip tagged at least as much variation in liability as in the corresponding regions in the GWAS data, however a certain amount of tagged SNP-heritability in the GWAS data was lost using the iChip due to the low coverage at unselected regions. These results imply that custom arrays with a GWAS backbone will facilitate more gene discovery, both at associated and novel loci.

Mining the human phenome using allelic scores that index biological intermediates.

It is common practice in genome-wide association studies (GWAS) to focus on the relationship between disease risk and genetic variants one marker at a time. When relevant genes are identified it is often possible to implicate biological intermediates and pathways likely to be involved in disease aetiology. However, single genetic variants typically explain small amounts of disease risk. Our idea is to construct allelic scores that explain greater proportions of the variance in biological intermediates, and subsequently use these scores to data mine GWAS. To investigate the approach's properties, we indexed three biological intermediates where the results of large GWAS meta-analyses were available: body mass index, C-reactive protein and low density lipoprotein levels. We generated allelic scores in the Avon Longitudinal Study of Parents and Children, and in publicly available data from the first Wellcome Trust Case Control Consortium. We compared the explanatory ability of allelic scores in terms of their capacity to proxy for the intermediate of interest, and the extent to which they associated with disease. We found that allelic scores derived from known variants and allelic scores derived from hundreds of thousands of genetic markers explained significant portions of the variance in biological intermediates of interest, and many of these scores showed expected correlations with disease. Genome-wide allelic scores however tended to lack specificity suggesting that they should be used with caution and perhaps only to proxy biological intermediates for which there are no known individual variants. Power calculations confirm the feasibility of extending our strategy to the analysis of tens of thousands of molecular phenotypes in large genome-wide meta-analyses. We conclude that our method represents a simple way in which potentially tens of thousands of molecular phenotypes could be screened for causal relationships with disease without having to expensively measure these variables in individual disease collections.

Calculating statistical power in Mendelian randomization studies.

In Mendelian randomization (MR) studies, where genetic variants are used as proxy measures for an exposure trait of interest, obtaining adequate statistical power is frequently a concern due to the small amount of variation in a phenotypic trait that is typically explained by genetic variants. A range of power estimates based on simulations and specific parameters for two-stage least squares (2SLS) MR analyses based on continuous variables has previously been published. However there are presently no specific equations or software tools one can implement for calculating power of a given MR study. Using asymptotic theory, we show that in the case of continuous variables and a single instrument, for example a single-nucleotide polymorphism (SNP) or multiple SNP predictor, statistical power for a fixed sample size is a function of two parameters: the proportion of variation in the exposure variable explained by the genetic predictor and the true causal association between the exposure and outcome variable. We demonstrate that power for 2SLS MR can be derived using the non-centrality parameter (NCP) of the statistical test that is employed to test whether the 2SLS regression coefficient is zero. We show that the previously published power estimates from simulations can be represented theoretically using this NCP-based approach, with similar estimates observed when the simulation-based estimates are compared with our NCP-based approach. General equations for calculating statistical power for 2SLS MR using the NCP are provided in this note, and we implement the calculations in a web-based application.

Lack of emergence of associations between selected maternal exposures and offspring blood pressure at age 15 years.

BACKGROUND: A recent review found little evidence for substantial effects of modifiable maternal exposures on offspring blood pressure (BP), but this may have been because almost all the studies reported on BP in early and mid-childhood. METHODS: This study uses data on 4723 mother-child pairs, collected as part of the Avon Longitudinal Study of Parents and Children, Bristol, England between 1991 and 1997; associations between three maternal variables (smoking during pregnancy, age at childbirth and prenatal diet) and offspring BP at approximately 15 years were assessed. Comparisons of maternal and paternal associations with offspring BP were carried out as a way of evaluating whether prenatal exposures exerted an influence through intrauterine effects. RESULTS: The selected maternal exposures were not associated with offspring BP, after minimal or full adjustment for potential confounders. Maternal and paternal associations with offspring BP for each exposure were found to be similar. CONCLUSIONS: The findings of this study suggest that associations between the selected maternal exposures and offspring BP do not emerge with age up to adolescence.

Vitamin B-12 status during pregnancy and child's IQ at age 8: a Mendelian randomization study in the Avon longitudinal study of parents and children.

Vitamin B-12 is essential for the development and maintenance of a healthy nervous system. Brain development occurs primarily in utero and early infancy, but the role of maternal vitamin B-12 status during pregnancy on offspring cognitive function is unclear. In this study we assessed the effect of vitamin B-12 status in well-nourished pregnant women on the cognitive ability of their offspring in a UK birth cohort (ALSPAC). We then examined the association of SNPs in maternal genes FUT2 (rs492602) and TCN2 (rs1801198, rs9606756) that are related to plasma vitamin B-12, with offspring IQ. Observationally, there was a positive association between maternal vitamin B-12 intake and child's IQ that was markedly attenuated after adjustment for potential confounders (mean difference in offspring IQ score per doubling of maternal B-12 intake, before adjustment: 2.0 (95% CI 1.3, 2.8); after adjustment: 0.7 (95% CI -0.04, 1.4)). Maternal FUT2 was weakly associated with offspring IQ: mean difference in IQ per allele was 0.9 (95% CI 0.1, 1.6). The expected effect of maternal vitamin B-12 on offspring IQ, given the relationships between SNPs and vitamin B-12, and SNPs and IQ was consistent with the observational result. Our findings suggest that maternal vitamin B-12 may not have an important effect on offspring cognitive ability. However, further examination of this issue is warranted.

Genetic variation in the 15q25 nicotinic acetylcholine receptor gene cluster (CHRNA5-CHRNA3-CHRNB4) interacts with maternal self-reported smoking status during pregnancy to influence birth weight.

Maternal smoking during pregnancy is associated with low birth weight. Common variation at rs1051730 is robustly associated with smoking quantity and was recently shown to influence smoking cessation during pregnancy, but its influence on birth weight is not clear. We aimed to investigate the association between this variant and birth weight of term, singleton offspring in a well-powered meta-analysis. We stratified 26 241 European origin study participants by smoking status (women who smoked during pregnancy versus women who did not smoke during pregnancy) and, in each stratum, analysed the association between maternal rs1051730 genotype and offspring birth weight. There was evidence of interaction between genotype and smoking (P = 0.007). In women who smoked during pregnancy, each additional smoking-related T-allele was associated with a 20 g [95% confidence interval (95% CI): 4-36 g] lower birth weight (P = 0.014). However, in women who did not smoke during pregnancy, the effect size estimate was 5 g per T-allele (95% CI: -4 to 14 g; P = 0.268). To conclude, smoking status during pregnancy modifies the association between maternal rs1051730 genotype and offspring birth weight. This strengthens the evidence that smoking during pregnancy is causally related to lower offspring birth weight and suggests that population interventions that effectively reduce smoking in pregnant women would result in a reduced prevalence of low birth weight.

Maternal smoking during pregnancy and offspring trajectories of height and adiposity: comparing maternal and paternal associations.

BACKGROUND: Maternal smoking during pregnancy is associated with reduced offspring birth length and has been postulated as a risk factor for obesity. Causality for obesity is not established. Causality is well-supported for birth length, but evidence on persistence of height deficits is inconsistent. METHODS: We examined the association between maternal smoking during pregnancy and trajectories of offspring height (0-10 years, N = 9424), ponderal index (PI) (0-2 years, N = 9321) and body mass index (BMI) (2-10 years, N = 8887) in the Avon Longitudinal Study of Parents and Children. To strengthen inference, measured confounders were controlled for, maternal and partner smoking associations were compared, dose-response and associations with post-natal smoking were examined. RESULTS: Maternal smoking during pregnancy was associated with shorter birth length, faster height growth in infancy and slower growth in later childhood. By 10 years, daughters of women who smoke during pregnancy are on average 1.11 cm (SE = 0.27) shorter after adjustment for confounders and partner smoking; the difference is 0.22 cm (SE = 0.22) for partner's smoking. Maternal smoking was associated with lower PI at birth, faster PI increase in infancy, but not with BMI changes 2-10 years. Associations were stronger for maternal than partner smoking for PI at birth and PI changes in infancy, but not for BMI changes after 2 years. A similar dose-response in both maternal and partner smoking was seen for BMI change 2-10 years. CONCLUSION: Maternal smoking during pregnancy has an intrauterine effect on birth length, and possibly on adiposity at birth and changes in height and adiposity in infancy. We do not find evidence of a specific intrauterine effect on height or adiposity changes after the age of 2 years.

Maternal smoking during pregnancy and offspring growth in childhood: 1993 and 2004 Pelotas cohort studies.

OBJECTIVE: To explore the effects of maternal smoking during pregnancy on offspring growth using three approaches: (1) multiple adjustments for socioeconomic and parental factors, (2) maternal-paternal comparisons as a test of putative intrauterine effects and (3) comparisons between two birth cohort studies. METHODS: Population-based birth cohort studies were carried out in Pelotas, Brazil, in 1993 and 2004. Cohort members were followed up at 3, 12, 24 and 48 months. Multiple linear regression analysis was used to examine the relationships between maternal and paternal prenatal smoking and offspring anthropometric indices. In the 2004 cohort, the association of smoking with trunk length, leg length and leg-to-sitting-height ratio at 48 months was also explored. RESULTS: Maternal smoking during pregnancy was associated with reduced z scores of length/height-for-age at each follow-up in both cohorts and reduced leg length at 48 months in the 2004 cohort. Children older than 3 months born to smoking women showed a higher body mass index-for-age z score than children of non-smoking women. CONCLUSIONS: The results of this study strongly support the hypothesis that maternal smoking during pregnancy impairs linear growth and promotes overweight in childhood.

What are the causal effects of breastfeeding on IQ, obesity and blood pressure? Evidence from comparing high-income with middle-income cohorts.

BACKGROUND: A novel approach is explored for improving causal inference in observational studies by comparing cohorts from high-income with low- or middle-income countries (LMIC), where confounding structures differ. This is applied to assessing causal effects of breastfeeding on child blood pressure (BP), body mass index (BMI) and intelligence quotient (IQ). METHODS: Standardized approaches for assessing the confounding structure of breastfeeding by socio-economic position were applied to the British Avon Longitudinal Study of Parents and Children (ALSPAC) (N ≃ 5000) and Brazilian Pelotas 1993 cohorts (N ≃ 1000). This was used to improve causal inference regarding associations of breastfeeding with child BP, BMI and IQ. Analyses were extended to include results from a meta-analysis of five LMICs (N ≃ 10 000) and compared with a randomized trial of breastfeeding promotion. Findings Although higher socio-economic position was strongly associated with breastfeeding in ALSPAC, there was little such patterning in Pelotas. In ALSPAC, breastfeeding was associated with lower BP, lower BMI and higher IQ, adjusted for confounders, but in the directions expected if due to socioeconomic patterning. In contrast, in Pelotas, breastfeeding was not strongly associated with BP or BMI but was associated with higher IQ. Differences in associations observed between ALSPAC and the LMIC meta-analysis were in line with those observed between ALSPAC and Pelotas, but with robust evidence of heterogeneity detected between ALSPAC and the LMIC meta-analysis associations. Trial data supported the conclusions inferred by the cross-cohort comparisons, which provided evidence for causal effects on IQ but not for BP or BMI. CONCLUSION: While reported associations of breastfeeding with child BP and BMI are likely to reflect residual confounding, breastfeeding may have causal effects on IQ. Comparing associations between populations with differing confounding structures can be used to improve causal inference in observational studies.

Intrauterine effects of maternal prepregnancy overweight on child cognition and behavior in 2 cohorts.

OBJECTIVE: Greater maternal prepregnancy adiposity has been associated with behavioral problems, such as attention-deficit/hyperactivity disorder, and lower intellectual function in offspring. However, few studies of humans have explored this, and it is unclear if intrauterine mechanisms or confounding factors drive these associations. PATIENTS AND METHODS: Parental adiposity and offspring verbal skills, nonverbal skills, and behavioral problems were assessed in the British Avon Longitudinal Study of Parents and Children (N = ∼5000) and Dutch Generation R (N = ∼2500) cohorts. We aimed to determine the plausibility of intrauterine effects by (1) adjusting for multiple confounders, (2) comparing associations between maternal and paternal overweight with offspring cognition/behaviors, and (3) searching for cross-cohort consistency. RESULTS: Maternal prepregnancy overweight was associated with reduced child verbal skills (unadjusted). However, after adjusting for confounders, this result was not consistently observed in both cohorts. Maternal overweight was also associated with child total behavior problems and externalizing problems even after adjusting for confounders. However, this was observed in Generation R only and was not replicated in the British Avon Longitudinal Study of Parents and Children. No associations of maternal overweight with child attention problems, emotional/internalizing problems, or nonverbal skills were observed in either cohort. Paternal overweight was not associated with any of the child outcomes but was also less strongly related to potential confounding factors than was maternal overweight. CONCLUSIONS: Overall, we found little consistent evidence of intrauterine effects of maternal prepregnancy overweight on child cognition and behavior. Some associations initially observed were not consistently replicated across cohorts or robust to adjustment for confounding factors and, thus, are likely to reflect confounding by socioeconomic or postnatal factors.

Maternal smoking and child psychological problems: disentangling causal and noncausal effects.

OBJECTIVE: To explore associations of maternal prenatal smoking and child psychological problems and determine the role of causal intrauterine mechanisms. PATIENTS AND METHODS: Maternal smoking and child psychological problems were explored in 2 birth cohorts in Pelotas, Brazil (n = 509, random subsample), and the Avon Longitudinal Study of Parents and Children (ALSPAC) in Britain (n = 6735). Four approaches for exploring causal mechanisms were applied: (1) cross-population comparisons between a high-income and a middle-income country; (2) multiple adjustment for socioeconomic and parental psychological factors; (3) maternal-paternal comparisons as a test of putative intrauterine effects; and (4) searching for specific effects on different behavioral subscales. RESULTS: Socioeconomic patterning of maternal prenatal smoking was stronger in the ALSPAC compared with the Pelotas cohort. Despite this difference in a key confounder, consistency in observed associations was found between these cohorts. In both cohorts, unadjusted maternal smoking was associated with greater offspring hyperactivity, conduct/externalizing problems, and peer problems but not with emotional/internalizing problems. After adjusting for confounders and paternal prenatal smoking, only the association with conduct/externalizing problems persisted in both cohorts (conduct problems in the ALSPAC cohort, odds ratio [OR]: 1.24 [95% confidence interval (CI): 1.07-1.46], P = .005; externalizing problems in the Pelotas cohort, OR: 1.82 [95% CI: 1.19-2.78], P = .005; ORs reflect ordinal odds ratios of maternal smokers having offspring with higher scores). Maternal smoking associations were stronger than paternal smoking associations, although statistical evidence that these associations differed was weak in 1 cohort. CONCLUSION: Evidence from 4 approaches suggests a possible intrauterine effect of maternal smoking on offspring conduct/externalizing problems.

Association of maternal weight gain in pregnancy with offspring obesity and metabolic and vascular traits in childhood.

BACKGROUND: We sought to examine the association of gestational weight gain (GWG) and prepregnancy weight with offspring adiposity and cardiovascular risk factors. METHODS AND RESULTS: Data from 5154 (for adiposity and blood pressure) and 3457 (for blood assays) mother-offspring pairs from a UK prospective pregnancy cohort were used. Random-effects multilevel models were used to assess incremental GWG (median and range of repeat weight measures per woman: 10 [1, 17]). Women who exceeded the 2009 Institute of Medicine-recommended GWG were more likely to have offspring with greater body mass index, waist, fat mass, leptin, systolic blood pressure, C-reactive protein, and interleukin-6 levels and lower high-density lipoprotein cholesterol and apolipoprotein A1 levels. Children of women who gained less than the recommended amounts had lower levels of adiposity, but other cardiovascular risk factors tended to be similar in this group to those of offspring of women gaining recommended amounts. When examined in more detail, greater prepregnancy weight was associated with greater offspring adiposity and more adverse cardiovascular risk factors at age 9 years. GWG in early pregnancy (0 to 14 weeks) was positively associated with offspring adiposity across the entire distribution but strengthened in women gaining >500 g/wk. By contrast, between 14 and 36 weeks, GWG was only associated with offspring adiposity in women gaining >500 g/wk. GWG between 14 and 36 weeks was positively and linearly associated with adverse lipid and inflammatory profiles, with these associations largely mediated by the associations with offspring adiposity. CONCLUSIONS: Greater maternal prepregnancy weight and GWG up to 36 weeks of gestation are associated with greater offspring adiposity and adverse cardiovascular risk factors. Before any GWG recommendations are implemented, the balance of risks and benefits of attempts to control GWG for short- and long-term outcomes in mother and child should be ascertained.

Genetic variation at the SLC23A1 locus is associated with circulating concentrations of L-ascorbic acid (vitamin C): evidence from 5 independent studies with >15,000 participants.

BACKGROUND: L-ascorbic acid is an essential part of the human diet and has been associated with a wide range of chronic complex diseases, including cardiovascular outcomes. To date, there are no confirmed genetic correlates of circulating concentrations of L-ascorbic acid. OBJECTIVE: We aimed to confirm the existence of an association between common variation at the SLC23A1 gene locus and circulating concentrations of L-ascorbic acid. DESIGN: We used a 2-stage design, which included a discovery cohort (the British Women's Heart and Health Study), a series of follow-up cohorts, and meta-analysis (totaling 15,087 participants) to assess the relation between variation at SLC23A1 and circulating concentrations of L-ascorbic acid. RESULTS: In the discovery cohort, variation at rs33972313 was associated with a reduction in circulating concentrations of L-ascorbic acid (-4.15 micromol/L; 95% CI: -0.49, -7.81 micromol/L; P = 0.03 reduction per minor allele). Pooled analysis of the relation between rs33972313 and circulating L-ascorbic acid across all studies confirmed this and showed that each additional rare allele was associated with a reduction in circulating concentrations of L-ascorbic acid of -5.98 micromol/L (95% CI: -8.23, -3.73 micromol/L; P = 2.0 x 10(-7) per minor allele). CONCLUSIONS: A genetic variant (rs33972313) in the SLC23A1 vitamin C active transporter locus was identified that is reliably associated with circulating concentrations of L-ascorbic acid in the general population. This finding has implications more generally for the epidemiologic investigation of relations between circulating L-ascorbic acid and health outcomes.