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.
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.
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.
l.krause@uq.edu.au.
Supplementary data are available at Bioinformatics online.
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.
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.
We sought to examine the association of gestational weight gain (GWG) and prepregnancy weight with offspring adiposity and cardiovascular risk factors.
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.
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.
BACKGROUND: High maternal dietary intakes in pregnancy may lead to increased fetal growth and program neuroendocrine pathways that result in greater appetite, energy intake, and adiposity in ...offspring later in life. Few prospective dietary studies have explored this relation. OBJECTIVE: The objective was to assess associations of maternal dietary intake in pregnancy and maternal and paternal dietary intake postnatally with child dietary intake and adiposity. DESIGN: Dietary intakes of energy, protein, total fat, and carbohydrate were assessed prospectively in mothers during pregnancy, in mothers and their partners at 47 mo postnatally, and in children at 10 y (n = 5717 mother-child pairs prenatally, 5593 mother-child pairs postnatally, and 3009 father-child pairs). Child body composition was assessed at 9 and 11 y (n = 5725). RESULTS: Maternal dietary intakes of protein, fat (when adjusted for energy intake), and carbohydrate in pregnancy were positively associated with child dietary intakes of the same nutrients, and these associations were greater than those observed for paternal dietary intake, which was not strongly associated with offspring diet. Associations of maternal prenatal-offspring intakes were stronger than those of maternal postnatal-offspring intakes for protein and fat. Greater child energy and macronutrient intakes were only associated with greater adiposity in children when adjusted for potential energy underreporting. Maternal diet during pregnancy was not associated with offspring adiposity or lean mass. CONCLUSION: The stronger prenatal maternal associations with child dietary intake, particularly protein and fat, compared with both paternal intake associations and maternal postnatal intake associations provide some evidence for in utero programming of offspring appetite by maternal intake during pregnancy.
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CMK, GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
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.
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.
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EMUNI, FIS, FZAB, GEOZS, GIS, IJS, IMTLJ, KILJ, KISLJ, MFDPS, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, SBMB, SBNM, UKNU, UL, UM, UPUK, VKSCE, ZAGLJ
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