BMI
Clare Horscroft
04/08/2021
Investigating BMI, weight, and fat measures in relation to number of children
library(TwoSampleMR)## TwoSampleMR version 0.5.6
## [>] New: Option to use non-European LD reference panels for clumping etc
## [>] Some studies temporarily quarantined to verify effect allele
## [>] See news(package='TwoSampleMR') and https://gwas.mrcieu.ac.uk for further detailsBMI
d <- make_dat("ukb-b-19953", "ieu-b-4760")## API: public: http://gwas-api.mrcieu.ac.uk/## Extracting data for 458 SNP(s) from 1 GWAS(s)## Finding proxies for 42 SNPs in outcome ieu-b-4760## Extracting data for 42 SNP(s) from 1 GWAS(s)## Harmonising Body mass index (BMI) || id:ukb-b-19953 (ukb-b-19953) and Number of children || id:ieu-b-4760 (ieu-b-4760)d_mr<-mr(d)## Analysing 'ukb-b-19953' on 'ieu-b-4760'd_mr## id.exposure id.outcome outcome
## 1 ukb-b-19953 ieu-b-4760 Number of children || id:ieu-b-4760
## 2 ukb-b-19953 ieu-b-4760 Number of children || id:ieu-b-4760
## 3 ukb-b-19953 ieu-b-4760 Number of children || id:ieu-b-4760
## 4 ukb-b-19953 ieu-b-4760 Number of children || id:ieu-b-4760
## 5 ukb-b-19953 ieu-b-4760 Number of children || id:ieu-b-4760
## exposure method nsnp
## 1 Body mass index (BMI) || id:ukb-b-19953 MR Egger 449
## 2 Body mass index (BMI) || id:ukb-b-19953 Weighted median 449
## 3 Body mass index (BMI) || id:ukb-b-19953 Inverse variance weighted 449
## 4 Body mass index (BMI) || id:ukb-b-19953 Simple mode 449
## 5 Body mass index (BMI) || id:ukb-b-19953 Weighted mode 449
## b se pval
## 1 -0.02613507 0.022955956 2.555268e-01
## 2 0.04966187 0.010896349 5.172628e-06
## 3 0.06229082 0.008634626 5.430263e-13
## 4 0.07827496 0.038074558 4.037747e-02
## 5 0.02077471 0.017994299 2.489040e-01mr_scatter_plot(d_mr,d)## $`ukb-b-19953.ieu-b-4760`
##
## attr(,"split_type")
## [1] "data.frame"
## attr(,"split_labels")
## id.exposure id.outcome
## 1 ukb-b-19953 ieu-b-4760d <- make_dat("ieu-b-4760", "ukb-b-19953")## Extracting data for 9 SNP(s) from 1 GWAS(s)## Finding proxies for 1 SNPs in outcome ukb-b-19953## Extracting data for 1 SNP(s) from 1 GWAS(s)## Harmonising Number of children || id:ieu-b-4760 (ieu-b-4760) and Body mass index (BMI) || id:ukb-b-19953 (ukb-b-19953)d_mr<-mr(d)## Analysing 'ieu-b-4760' on 'ukb-b-19953'd_mr## id.exposure id.outcome outcome
## 1 ieu-b-4760 ukb-b-19953 Body mass index (BMI) || id:ukb-b-19953
## 2 ieu-b-4760 ukb-b-19953 Body mass index (BMI) || id:ukb-b-19953
## 3 ieu-b-4760 ukb-b-19953 Body mass index (BMI) || id:ukb-b-19953
## 4 ieu-b-4760 ukb-b-19953 Body mass index (BMI) || id:ukb-b-19953
## 5 ieu-b-4760 ukb-b-19953 Body mass index (BMI) || id:ukb-b-19953
## exposure method nsnp
## 1 Number of children || id:ieu-b-4760 MR Egger 8
## 2 Number of children || id:ieu-b-4760 Weighted median 8
## 3 Number of children || id:ieu-b-4760 Inverse variance weighted 8
## 4 Number of children || id:ieu-b-4760 Simple mode 8
## 5 Number of children || id:ieu-b-4760 Weighted mode 8
## b se pval
## 1 0.286756116 1.76568581 0.8763184
## 2 0.076863309 0.09256887 0.4063486
## 3 0.317479862 0.28375554 0.2632042
## 4 -0.009193725 0.12209120 0.9420812
## 5 0.066392394 0.13087148 0.6275257mr_scatter_plot(d_mr,d)## $`ieu-b-4760.ukb-b-19953`
##
## attr(,"split_type")
## [1] "data.frame"
## attr(,"split_labels")
## id.exposure id.outcome
## 1 ieu-b-4760 ukb-b-19953BMI highly related with number of children, no evidence of reverse causality (i.e. more children does not cause higher BMI)
Weight
d <- make_dat("ukb-b-11842", "ieu-b-4760")## Extracting data for 498 SNP(s) from 1 GWAS(s)## Finding proxies for 52 SNPs in outcome ieu-b-4760## Extracting data for 52 SNP(s) from 1 GWAS(s)## Harmonising Weight || id:ukb-b-11842 (ukb-b-11842) and Number of children || id:ieu-b-4760 (ieu-b-4760)d_mr<-mr(d)## Analysing 'ukb-b-11842' on 'ieu-b-4760'd_mr## id.exposure id.outcome outcome
## 1 ukb-b-11842 ieu-b-4760 Number of children || id:ieu-b-4760
## 2 ukb-b-11842 ieu-b-4760 Number of children || id:ieu-b-4760
## 3 ukb-b-11842 ieu-b-4760 Number of children || id:ieu-b-4760
## 4 ukb-b-11842 ieu-b-4760 Number of children || id:ieu-b-4760
## 5 ukb-b-11842 ieu-b-4760 Number of children || id:ieu-b-4760
## exposure method nsnp b
## 1 Weight || id:ukb-b-11842 MR Egger 486 -0.04281938
## 2 Weight || id:ukb-b-11842 Weighted median 486 0.01096388
## 3 Weight || id:ukb-b-11842 Inverse variance weighted 486 0.03519694
## 4 Weight || id:ukb-b-11842 Simple mode 486 0.02203825
## 5 Weight || id:ukb-b-11842 Weighted mode 486 0.01101614
## se pval
## 1 0.022543833 5.810832e-02
## 2 0.011484019 3.397255e-01
## 3 0.008860199 7.112908e-05
## 4 0.034658507 5.251621e-01
## 5 0.019775875 5.777508e-01mr_scatter_plot(d_mr,d)## $`ukb-b-11842.ieu-b-4760`
##
## attr(,"split_type")
## [1] "data.frame"
## attr(,"split_labels")
## id.exposure id.outcome
## 1 ukb-b-11842 ieu-b-4760d <- make_dat("ieu-b-4760", "ukb-b-11842")## Extracting data for 9 SNP(s) from 1 GWAS(s)## Finding proxies for 1 SNPs in outcome ukb-b-11842## Extracting data for 1 SNP(s) from 1 GWAS(s)## Harmonising Number of children || id:ieu-b-4760 (ieu-b-4760) and Weight || id:ukb-b-11842 (ukb-b-11842)d_mr<-mr(d)## Analysing 'ieu-b-4760' on 'ukb-b-11842'd_mr## id.exposure id.outcome outcome
## 1 ieu-b-4760 ukb-b-11842 Weight || id:ukb-b-11842
## 2 ieu-b-4760 ukb-b-11842 Weight || id:ukb-b-11842
## 3 ieu-b-4760 ukb-b-11842 Weight || id:ukb-b-11842
## 4 ieu-b-4760 ukb-b-11842 Weight || id:ukb-b-11842
## 5 ieu-b-4760 ukb-b-11842 Weight || id:ukb-b-11842
## exposure method nsnp b
## 1 Number of children || id:ieu-b-4760 MR Egger 8 0.6291490
## 2 Number of children || id:ieu-b-4760 Weighted median 8 0.0268911
## 3 Number of children || id:ieu-b-4760 Inverse variance weighted 8 0.2270329
## 4 Number of children || id:ieu-b-4760 Simple mode 8 -0.2579796
## 5 Number of children || id:ieu-b-4760 Weighted mode 8 -0.1284952
## se pval
## 1 1.48454399 0.68648484
## 2 0.09701889 0.78164663
## 3 0.24004585 0.34425577
## 4 0.11220024 0.05504963
## 5 0.17223861 0.47994716mr_scatter_plot(d_mr,d)## $`ieu-b-4760.ukb-b-11842`
##
## attr(,"split_type")
## [1] "data.frame"
## attr(,"split_labels")
## id.exposure id.outcome
## 1 ieu-b-4760 ukb-b-11842d <- mv_extract_exposures(c("ukb-b-11842", "ukb-b-19953"))## Please look at vignettes for options on running this locally if you need to run many instances of this command.## Clumping 1, 874 variants, using EUR population reference## Removing 383 of 874 variants due to LD with other variants or absence from LD reference panel## Extracting data for 491 SNP(s) from 2 GWAS(s)## Harmonising Weight || id:ukb-b-11842 (ukb-b-11842) and Body mass index (BMI) || id:ukb-b-19953 (ukb-b-19953)## Removing the following SNPs for being palindromic with intermediate allele frequencies:
## rs11250094, rs12507026, rs13264909, rs1454687, rs1860750, rs2396625, rs3097851, rs59086897, rs6597975, rs7568228, rs7942152, rs9614090o <- extract_outcome_data(d$SNP, "ieu-b-4760")## Extracting data for 491 SNP(s) from 1 GWAS(s)## Finding proxies for 49 SNPs in outcome ieu-b-4760## Extracting data for 49 SNP(s) from 1 GWAS(s)d <- mv_harmonise_data(d, o)## Harmonising Weight || id:ukb-b-11842 (ukb-b-11842) and Number of children || id:ieu-b-4760 (ieu-b-4760)## Removing the following SNPs for being palindromic with intermediate allele frequencies:
## rs11250094, rs12507026, rs13264909, rs1454687, rs1860750, rs2396625, rs59086897, rs6597975, rs7568228, rs7942152, rs9614090mv_multiple(d)## $result
## id.exposure exposure id.outcome
## 1 ukb-b-11842 Weight || id:ukb-b-11842 ieu-b-4760
## 2 ukb-b-19953 Body mass index (BMI) || id:ukb-b-19953 ieu-b-4760
## outcome nsnp b se pval
## 1 Number of children || id:ieu-b-4760 403 -0.02470037 0.01966343 0.209058954
## 2 Number of children || id:ieu-b-4760 316 0.07686678 0.01976412 0.000100572Weight effect explained by BMI.
Hip circumference
d <- make_dat("ukb-b-15590", "ieu-b-4760")## Extracting data for 420 SNP(s) from 1 GWAS(s)## Finding proxies for 30 SNPs in outcome ieu-b-4760## Extracting data for 30 SNP(s) from 1 GWAS(s)## Harmonising Hip circumference || id:ukb-b-15590 (ukb-b-15590) and Number of children || id:ieu-b-4760 (ieu-b-4760)## Removing the following SNPs for incompatible alleles:
## rs1294438d_mr<-mr(d)## Analysing 'ukb-b-15590' on 'ieu-b-4760'd_mr## id.exposure id.outcome outcome
## 1 ukb-b-15590 ieu-b-4760 Number of children || id:ieu-b-4760
## 2 ukb-b-15590 ieu-b-4760 Number of children || id:ieu-b-4760
## 3 ukb-b-15590 ieu-b-4760 Number of children || id:ieu-b-4760
## 4 ukb-b-15590 ieu-b-4760 Number of children || id:ieu-b-4760
## 5 ukb-b-15590 ieu-b-4760 Number of children || id:ieu-b-4760
## exposure method nsnp
## 1 Hip circumference || id:ukb-b-15590 MR Egger 413
## 2 Hip circumference || id:ukb-b-15590 Weighted median 413
## 3 Hip circumference || id:ukb-b-15590 Inverse variance weighted 413
## 4 Hip circumference || id:ukb-b-15590 Simple mode 413
## 5 Hip circumference || id:ukb-b-15590 Weighted mode 413
## b se pval
## 1 -0.049995048 0.024199480 0.039458828
## 2 0.012970141 0.011207526 0.247161802
## 3 0.026656226 0.008857273 0.002616525
## 4 0.015156827 0.037193289 0.683841366
## 5 0.008716964 0.021455244 0.684743472mr_scatter_plot(d_mr,d)## $`ukb-b-15590.ieu-b-4760`
##
## attr(,"split_type")
## [1] "data.frame"
## attr(,"split_labels")
## id.exposure id.outcome
## 1 ukb-b-15590 ieu-b-4760d <- make_dat("ieu-b-4760", "ukb-b-15590")## Extracting data for 9 SNP(s) from 1 GWAS(s)## Finding proxies for 1 SNPs in outcome ukb-b-15590## Extracting data for 1 SNP(s) from 1 GWAS(s)## Harmonising Number of children || id:ieu-b-4760 (ieu-b-4760) and Hip circumference || id:ukb-b-15590 (ukb-b-15590)d_mr<-mr(d)## Analysing 'ieu-b-4760' on 'ukb-b-15590'd_mr## id.exposure id.outcome outcome
## 1 ieu-b-4760 ukb-b-15590 Hip circumference || id:ukb-b-15590
## 2 ieu-b-4760 ukb-b-15590 Hip circumference || id:ukb-b-15590
## 3 ieu-b-4760 ukb-b-15590 Hip circumference || id:ukb-b-15590
## 4 ieu-b-4760 ukb-b-15590 Hip circumference || id:ukb-b-15590
## 5 ieu-b-4760 ukb-b-15590 Hip circumference || id:ukb-b-15590
## exposure method nsnp
## 1 Number of children || id:ieu-b-4760 MR Egger 8
## 2 Number of children || id:ieu-b-4760 Weighted median 8
## 3 Number of children || id:ieu-b-4760 Inverse variance weighted 8
## 4 Number of children || id:ieu-b-4760 Simple mode 8
## 5 Number of children || id:ieu-b-4760 Weighted mode 8
## b se pval
## 1 0.53640444 1.3901975 0.7129196
## 2 0.08542397 0.1053875 0.4176126
## 3 0.14108010 0.2249019 0.5304651
## 4 -0.17775265 0.2262958 0.4579251
## 5 0.13008726 0.1356214 0.3694113mr_scatter_plot(d_mr,d)## $`ieu-b-4760.ukb-b-15590`
##
## attr(,"split_type")
## [1] "data.frame"
## attr(,"split_labels")
## id.exposure id.outcome
## 1 ieu-b-4760 ukb-b-15590Waist circumference
d <- make_dat("ukb-b-9405", "ieu-b-4760")## Extracting data for 374 SNP(s) from 1 GWAS(s)## Finding proxies for 33 SNPs in outcome ieu-b-4760## Extracting data for 33 SNP(s) from 1 GWAS(s)## Harmonising Waist circumference || id:ukb-b-9405 (ukb-b-9405) and Number of children || id:ieu-b-4760 (ieu-b-4760)## Removing the following SNPs for incompatible alleles:
## rs156902d_mr<-mr(d)## Analysing 'ukb-b-9405' on 'ieu-b-4760'd_mr## id.exposure id.outcome outcome
## 1 ukb-b-9405 ieu-b-4760 Number of children || id:ieu-b-4760
## 2 ukb-b-9405 ieu-b-4760 Number of children || id:ieu-b-4760
## 3 ukb-b-9405 ieu-b-4760 Number of children || id:ieu-b-4760
## 4 ukb-b-9405 ieu-b-4760 Number of children || id:ieu-b-4760
## 5 ukb-b-9405 ieu-b-4760 Number of children || id:ieu-b-4760
## exposure method nsnp
## 1 Waist circumference || id:ukb-b-9405 MR Egger 368
## 2 Waist circumference || id:ukb-b-9405 Weighted median 368
## 3 Waist circumference || id:ukb-b-9405 Inverse variance weighted 368
## 4 Waist circumference || id:ukb-b-9405 Simple mode 368
## 5 Waist circumference || id:ukb-b-9405 Weighted mode 368
## b se pval
## 1 -0.03728952 0.03301158 2.593892e-01
## 2 0.03207637 0.01437253 2.562933e-02
## 3 0.06069885 0.01164090 1.845376e-07
## 4 0.06148943 0.04752355 1.965230e-01
## 5 0.02317524 0.02546021 3.632863e-01mr_scatter_plot(d_mr,d)## $`ukb-b-9405.ieu-b-4760`
##
## attr(,"split_type")
## [1] "data.frame"
## attr(,"split_labels")
## id.exposure id.outcome
## 1 ukb-b-9405 ieu-b-4760d <- make_dat("ieu-b-4760", "ukb-b-9405")## Extracting data for 9 SNP(s) from 1 GWAS(s)## Finding proxies for 1 SNPs in outcome ukb-b-9405## Extracting data for 1 SNP(s) from 1 GWAS(s)## Harmonising Number of children || id:ieu-b-4760 (ieu-b-4760) and Waist circumference || id:ukb-b-9405 (ukb-b-9405)d_mr<-mr(d)## Analysing 'ieu-b-4760' on 'ukb-b-9405'd_mr## id.exposure id.outcome outcome
## 1 ieu-b-4760 ukb-b-9405 Waist circumference || id:ukb-b-9405
## 2 ieu-b-4760 ukb-b-9405 Waist circumference || id:ukb-b-9405
## 3 ieu-b-4760 ukb-b-9405 Waist circumference || id:ukb-b-9405
## 4 ieu-b-4760 ukb-b-9405 Waist circumference || id:ukb-b-9405
## 5 ieu-b-4760 ukb-b-9405 Waist circumference || id:ukb-b-9405
## exposure method nsnp b
## 1 Number of children || id:ieu-b-4760 MR Egger 8 0.30193653
## 2 Number of children || id:ieu-b-4760 Weighted median 8 0.09830001
## 3 Number of children || id:ieu-b-4760 Inverse variance weighted 8 0.19256952
## 4 Number of children || id:ieu-b-4760 Simple mode 8 0.15942995
## 5 Number of children || id:ieu-b-4760 Weighted mode 8 0.12193475
## se pval
## 1 1.20960300 0.8112103
## 2 0.08070603 0.2232237
## 3 0.19449046 0.3221139
## 4 0.22879766 0.5083899
## 5 0.14711190 0.4345337mr_scatter_plot(d_mr,d)## $`ieu-b-4760.ukb-b-9405`
##
## attr(,"split_type")
## [1] "data.frame"
## attr(,"split_labels")
## id.exposure id.outcome
## 1 ieu-b-4760 ukb-b-9405d <- mv_extract_exposures(c("ukb-b-15590", "ukb-b-9405", "ukb-b-19953"))## Please look at vignettes for options on running this locally if you need to run many instances of this command.## Clumping 1, 1021 variants, using EUR population reference## Removing 540 of 1021 variants due to LD with other variants or absence from LD reference panel## Extracting data for 481 SNP(s) from 3 GWAS(s)## Warning in .fun(piece, ...): Duplicated SNPs present in exposure data for phenotype 'Hip circumference || id:ukb-b-15590. Just keeping the first instance:
## rs1294438## Harmonising Hip circumference || id:ukb-b-15590 (ukb-b-15590) and Body mass index (BMI) || id:ukb-b-19953 (ukb-b-19953)## Removing the following SNPs for incompatible alleles:
## rs1294438## Removing the following SNPs for being palindromic with intermediate allele frequencies:
## rs10887578, rs10954284, rs11250094, rs11778934, rs12507026, rs13264909, rs1454687, rs1860750, rs2032251, rs2396625, rs59086897, rs6597975, rs7568228, rs765874, rs7695177, rs961498## Harmonising Hip circumference || id:ukb-b-15590 (ukb-b-15590) and Waist circumference || id:ukb-b-9405 (ukb-b-9405)## Removing the following SNPs for incompatible alleles:
## rs1294438## Removing the following SNPs for being palindromic with intermediate allele frequencies:
## rs10887578, rs10954284, rs11250094, rs11778934, rs12507026, rs13264909, rs1454687, rs1860750, rs2032251, rs2396625, rs59086897, rs6597975, rs7568228, rs765874, rs7695177, rs961498o <- extract_outcome_data(d$SNP, "ieu-b-4760")## Extracting data for 480 SNP(s) from 1 GWAS(s)## Finding proxies for 45 SNPs in outcome ieu-b-4760## Extracting data for 45 SNP(s) from 1 GWAS(s)d <- mv_harmonise_data(d, o)## Harmonising Hip circumference || id:ukb-b-15590 (ukb-b-15590) and Number of children || id:ieu-b-4760 (ieu-b-4760)## Removing the following SNPs for being palindromic with intermediate allele frequencies:
## rs10887578, rs10954284, rs11250094, rs11778934, rs12507026, rs13264909, rs1454687, rs1860750, rs2032251, rs2396625, rs59086897, rs6597975, rs7568228, rs765874, rs7695177mv_multiple(d)## $result
## id.exposure exposure id.outcome
## 1 ukb-b-15590 Hip circumference || id:ukb-b-15590 ieu-b-4760
## 2 ukb-b-19953 Body mass index (BMI) || id:ukb-b-19953 ieu-b-4760
## 3 ukb-b-9405 Waist circumference || id:ukb-b-9405 ieu-b-4760
## outcome nsnp b se pval
## 1 Number of children || id:ieu-b-4760 301 -0.03782310 0.02492603 1.291622e-01
## 2 Number of children || id:ieu-b-4760 349 0.13136366 0.03371335 9.759752e-05
## 3 Number of children || id:ieu-b-4760 267 -0.05735947 0.04344779 1.867705e-01Waist/hip circumference effect explained by BMI.
Body fat
Body fat percentage
d <- make_dat("ukb-b-8909", "ieu-b-4760")## Extracting data for 395 SNP(s) from 1 GWAS(s)## Finding proxies for 32 SNPs in outcome ieu-b-4760## Extracting data for 32 SNP(s) from 1 GWAS(s)## Harmonising Body fat percentage || id:ukb-b-8909 (ukb-b-8909) and Number of children || id:ieu-b-4760 (ieu-b-4760)## Removing the following SNPs for incompatible alleles:
## rs2731238d_mr<-mr(d)## Analysing 'ukb-b-8909' on 'ieu-b-4760'd_mr## id.exposure id.outcome outcome
## 1 ukb-b-8909 ieu-b-4760 Number of children || id:ieu-b-4760
## 2 ukb-b-8909 ieu-b-4760 Number of children || id:ieu-b-4760
## 3 ukb-b-8909 ieu-b-4760 Number of children || id:ieu-b-4760
## 4 ukb-b-8909 ieu-b-4760 Number of children || id:ieu-b-4760
## 5 ukb-b-8909 ieu-b-4760 Number of children || id:ieu-b-4760
## exposure method nsnp
## 1 Body fat percentage || id:ukb-b-8909 MR Egger 386
## 2 Body fat percentage || id:ukb-b-8909 Weighted median 386
## 3 Body fat percentage || id:ukb-b-8909 Inverse variance weighted 386
## 4 Body fat percentage || id:ukb-b-8909 Simple mode 386
## 5 Body fat percentage || id:ukb-b-8909 Weighted mode 386
## b se pval
## 1 -0.05927734 0.03766790 1.163843e-01
## 2 0.04322055 0.01516630 4.375017e-03
## 3 0.05495872 0.01189996 3.867197e-06
## 4 0.05975012 0.05267802 2.573948e-01
## 5 0.02745917 0.03688260 4.570270e-01mr_scatter_plot(d_mr,d)## $`ukb-b-8909.ieu-b-4760`
##
## attr(,"split_type")
## [1] "data.frame"
## attr(,"split_labels")
## id.exposure id.outcome
## 1 ukb-b-8909 ieu-b-4760d <- make_dat("ieu-b-4760", "ukb-b-8909")## Extracting data for 9 SNP(s) from 1 GWAS(s)## Finding proxies for 1 SNPs in outcome ukb-b-8909## Extracting data for 1 SNP(s) from 1 GWAS(s)## Harmonising Number of children || id:ieu-b-4760 (ieu-b-4760) and Body fat percentage || id:ukb-b-8909 (ukb-b-8909)d_mr<-mr(d)## Analysing 'ieu-b-4760' on 'ukb-b-8909'd_mr## id.exposure id.outcome outcome
## 1 ieu-b-4760 ukb-b-8909 Body fat percentage || id:ukb-b-8909
## 2 ieu-b-4760 ukb-b-8909 Body fat percentage || id:ukb-b-8909
## 3 ieu-b-4760 ukb-b-8909 Body fat percentage || id:ukb-b-8909
## 4 ieu-b-4760 ukb-b-8909 Body fat percentage || id:ukb-b-8909
## 5 ieu-b-4760 ukb-b-8909 Body fat percentage || id:ukb-b-8909
## exposure method nsnp b
## 1 Number of children || id:ieu-b-4760 MR Egger 8 0.16742012
## 2 Number of children || id:ieu-b-4760 Weighted median 8 0.03801151
## 3 Number of children || id:ieu-b-4760 Inverse variance weighted 8 0.01811580
## 4 Number of children || id:ieu-b-4760 Simple mode 8 0.03216785
## 5 Number of children || id:ieu-b-4760 Weighted mode 8 0.06578933
## se pval
## 1 0.97444415 0.8692346
## 2 0.06568611 0.5628024
## 3 0.15688090 0.9080687
## 4 0.08754393 0.7241427
## 5 0.05742480 0.2895880mr_scatter_plot(d_mr,d)## $`ieu-b-4760.ukb-b-8909`
##
## attr(,"split_type")
## [1] "data.frame"
## attr(,"split_labels")
## id.exposure id.outcome
## 1 ieu-b-4760 ukb-b-8909Whole body fat mass
d <- make_dat("ukb-b-19393", "ieu-b-4760")## Extracting data for 435 SNP(s) from 1 GWAS(s)## Finding proxies for 37 SNPs in outcome ieu-b-4760## Extracting data for 37 SNP(s) from 1 GWAS(s)## Harmonising Whole body fat mass || id:ukb-b-19393 (ukb-b-19393) and Number of children || id:ieu-b-4760 (ieu-b-4760)## Removing the following SNPs for incompatible alleles:
## rs2731238d_mr<-mr(d)## Analysing 'ukb-b-19393' on 'ieu-b-4760'd_mr## id.exposure id.outcome outcome
## 1 ukb-b-19393 ieu-b-4760 Number of children || id:ieu-b-4760
## 2 ukb-b-19393 ieu-b-4760 Number of children || id:ieu-b-4760
## 3 ukb-b-19393 ieu-b-4760 Number of children || id:ieu-b-4760
## 4 ukb-b-19393 ieu-b-4760 Number of children || id:ieu-b-4760
## 5 ukb-b-19393 ieu-b-4760 Number of children || id:ieu-b-4760
## exposure method nsnp
## 1 Whole body fat mass || id:ukb-b-19393 MR Egger 425
## 2 Whole body fat mass || id:ukb-b-19393 Weighted median 425
## 3 Whole body fat mass || id:ukb-b-19393 Inverse variance weighted 425
## 4 Whole body fat mass || id:ukb-b-19393 Simple mode 425
## 5 Whole body fat mass || id:ukb-b-19393 Weighted mode 425
## b se pval
## 1 -0.04430319 0.025820600 8.692943e-02
## 2 0.02020708 0.011366669 7.544511e-02
## 3 0.04096855 0.009276934 1.004633e-05
## 4 0.04151055 0.039265288 2.910306e-01
## 5 0.01726454 0.020649163 4.035758e-01mr_scatter_plot(d_mr,d)## $`ukb-b-19393.ieu-b-4760`
##
## attr(,"split_type")
## [1] "data.frame"
## attr(,"split_labels")
## id.exposure id.outcome
## 1 ukb-b-19393 ieu-b-4760d <- make_dat("ieu-b-4760", "ukb-b-19393")## Extracting data for 9 SNP(s) from 1 GWAS(s)## Finding proxies for 1 SNPs in outcome ukb-b-19393## Extracting data for 1 SNP(s) from 1 GWAS(s)## Harmonising Number of children || id:ieu-b-4760 (ieu-b-4760) and Whole body fat mass || id:ukb-b-19393 (ukb-b-19393)d_mr<-mr(d)## Analysing 'ieu-b-4760' on 'ukb-b-19393'd_mr## id.exposure id.outcome outcome
## 1 ieu-b-4760 ukb-b-19393 Whole body fat mass || id:ukb-b-19393
## 2 ieu-b-4760 ukb-b-19393 Whole body fat mass || id:ukb-b-19393
## 3 ieu-b-4760 ukb-b-19393 Whole body fat mass || id:ukb-b-19393
## 4 ieu-b-4760 ukb-b-19393 Whole body fat mass || id:ukb-b-19393
## 5 ieu-b-4760 ukb-b-19393 Whole body fat mass || id:ukb-b-19393
## exposure method nsnp
## 1 Number of children || id:ieu-b-4760 MR Egger 8
## 2 Number of children || id:ieu-b-4760 Weighted median 8
## 3 Number of children || id:ieu-b-4760 Inverse variance weighted 8
## 4 Number of children || id:ieu-b-4760 Simple mode 8
## 5 Number of children || id:ieu-b-4760 Weighted mode 8
## b se pval
## 1 0.50910700 1.4909637 0.7443970
## 2 0.06357546 0.1039365 0.5407522
## 3 0.13651930 0.2408567 0.5708453
## 4 -0.16560978 0.1733732 0.3712815
## 5 0.08392018 0.1312092 0.5427957mr_scatter_plot(d_mr,d)## $`ieu-b-4760.ukb-b-19393`
##
## attr(,"split_type")
## [1] "data.frame"
## attr(,"split_labels")
## id.exposure id.outcome
## 1 ieu-b-4760 ukb-b-19393Impedance of whole body
d <- make_dat("ukb-b-19921", "ieu-b-4760")## Extracting data for 528 SNP(s) from 1 GWAS(s)## Finding proxies for 41 SNPs in outcome ieu-b-4760## Extracting data for 41 SNP(s) from 1 GWAS(s)## Harmonising Impedance of whole body || id:ukb-b-19921 (ukb-b-19921) and Number of children || id:ieu-b-4760 (ieu-b-4760)d_mr<-mr(d)## Analysing 'ukb-b-19921' on 'ieu-b-4760'd_mr## id.exposure id.outcome outcome
## 1 ukb-b-19921 ieu-b-4760 Number of children || id:ieu-b-4760
## 2 ukb-b-19921 ieu-b-4760 Number of children || id:ieu-b-4760
## 3 ukb-b-19921 ieu-b-4760 Number of children || id:ieu-b-4760
## 4 ukb-b-19921 ieu-b-4760 Number of children || id:ieu-b-4760
## 5 ukb-b-19921 ieu-b-4760 Number of children || id:ieu-b-4760
## exposure method nsnp
## 1 Impedance of whole body || id:ukb-b-19921 MR Egger 515
## 2 Impedance of whole body || id:ukb-b-19921 Weighted median 515
## 3 Impedance of whole body || id:ukb-b-19921 Inverse variance weighted 515
## 4 Impedance of whole body || id:ukb-b-19921 Simple mode 515
## 5 Impedance of whole body || id:ukb-b-19921 Weighted mode 515
## b se pval
## 1 -0.056579013 0.025731147 2.833401e-02
## 2 -0.032310306 0.011577753 5.259040e-03
## 3 -0.055948094 0.009760714 9.927247e-09
## 4 0.010477601 0.044019679 8.119598e-01
## 5 -0.007534324 0.023350878 7.470862e-01mr_scatter_plot(d_mr,d)## $`ukb-b-19921.ieu-b-4760`
##
## attr(,"split_type")
## [1] "data.frame"
## attr(,"split_labels")
## id.exposure id.outcome
## 1 ukb-b-19921 ieu-b-4760d <- make_dat("ieu-b-4760", "ukb-b-19921")## Extracting data for 9 SNP(s) from 1 GWAS(s)## Finding proxies for 1 SNPs in outcome ukb-b-19921## Extracting data for 1 SNP(s) from 1 GWAS(s)## Harmonising Number of children || id:ieu-b-4760 (ieu-b-4760) and Impedance of whole body || id:ukb-b-19921 (ukb-b-19921)d_mr<-mr(d)## Analysing 'ieu-b-4760' on 'ukb-b-19921'd_mr## id.exposure id.outcome outcome
## 1 ieu-b-4760 ukb-b-19921 Impedance of whole body || id:ukb-b-19921
## 2 ieu-b-4760 ukb-b-19921 Impedance of whole body || id:ukb-b-19921
## 3 ieu-b-4760 ukb-b-19921 Impedance of whole body || id:ukb-b-19921
## 4 ieu-b-4760 ukb-b-19921 Impedance of whole body || id:ukb-b-19921
## 5 ieu-b-4760 ukb-b-19921 Impedance of whole body || id:ukb-b-19921
## exposure method nsnp
## 1 Number of children || id:ieu-b-4760 MR Egger 8
## 2 Number of children || id:ieu-b-4760 Weighted median 8
## 3 Number of children || id:ieu-b-4760 Inverse variance weighted 8
## 4 Number of children || id:ieu-b-4760 Simple mode 8
## 5 Number of children || id:ieu-b-4760 Weighted mode 8
## b se pval
## 1 -0.41137051 1.47490658 0.78967562
## 2 -0.05457304 0.07081880 0.44094342
## 3 -0.44486424 0.23696909 0.06047574
## 4 0.07840899 0.06770992 0.28483745
## 5 0.02715578 0.06279775 0.67843651mr_scatter_plot(d_mr,d)## $`ieu-b-4760.ukb-b-19921`
##
## attr(,"split_type")
## [1] "data.frame"
## attr(,"split_labels")
## id.exposure id.outcome
## 1 ieu-b-4760 ukb-b-19921