Investigating BMI, weight, and fat measures in relation to number of live births

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 details

BMI

d <- make_dat("ukb-b-19953", "ukb-b-1209")
## API: public: http://gwas-api.mrcieu.ac.uk/
## Extracting data for 458 SNP(s) from 1 GWAS(s)
## Finding proxies for 1 SNPs in outcome ukb-b-1209
## Extracting data for 1 SNP(s) from 1 GWAS(s)
## Harmonising Body mass index (BMI) || id:ukb-b-19953 (ukb-b-19953) and Number of live births || id:ukb-b-1209 (ukb-b-1209)
## Removing the following SNPs for incompatible alleles:
## rs7928320
d_mr<-mr(d)
## Analysing 'ukb-b-19953' on 'ukb-b-1209'
d_mr
##   id.exposure id.outcome                                outcome
## 1 ukb-b-19953 ukb-b-1209 Number of live births || id:ukb-b-1209
## 2 ukb-b-19953 ukb-b-1209 Number of live births || id:ukb-b-1209
## 3 ukb-b-19953 ukb-b-1209 Number of live births || id:ukb-b-1209
## 4 ukb-b-19953 ukb-b-1209 Number of live births || id:ukb-b-1209
## 5 ukb-b-19953 ukb-b-1209 Number of live births || id:ukb-b-1209
##                                  exposure                    method nsnp
## 1 Body mass index (BMI) || id:ukb-b-19953                  MR Egger  457
## 2 Body mass index (BMI) || id:ukb-b-19953           Weighted median  457
## 3 Body mass index (BMI) || id:ukb-b-19953 Inverse variance weighted  457
## 4 Body mass index (BMI) || id:ukb-b-19953               Simple mode  457
## 5 Body mass index (BMI) || id:ukb-b-19953             Weighted mode  457
##              b         se         pval
## 1 -0.061185678 0.03657499 9.503771e-02
## 2  0.042679408 0.01803347 1.794857e-02
## 3  0.061367832 0.01362366 6.652810e-06
## 4  0.038288478 0.08282076 6.440829e-01
## 5 -0.002372019 0.06723482 9.718722e-01
mr_scatter_plot(d_mr,d)
## $`ukb-b-19953.ukb-b-1209`

## 
## attr(,"split_type")
## [1] "data.frame"
## attr(,"split_labels")
##   id.exposure id.outcome
## 1 ukb-b-19953 ukb-b-1209
d <- make_dat("ukb-b-1209", "ukb-b-19953")
## Extracting data for 11 SNP(s) from 1 GWAS(s)
## Harmonising Number of live births || id:ukb-b-1209 (ukb-b-1209) and Body mass index (BMI) || id:ukb-b-19953 (ukb-b-19953)
d_mr<-mr(d)
## Analysing 'ukb-b-1209' on 'ukb-b-19953'
d_mr
##   id.exposure  id.outcome                                 outcome
## 1  ukb-b-1209 ukb-b-19953 Body mass index (BMI) || id:ukb-b-19953
## 2  ukb-b-1209 ukb-b-19953 Body mass index (BMI) || id:ukb-b-19953
## 3  ukb-b-1209 ukb-b-19953 Body mass index (BMI) || id:ukb-b-19953
## 4  ukb-b-1209 ukb-b-19953 Body mass index (BMI) || id:ukb-b-19953
## 5  ukb-b-1209 ukb-b-19953 Body mass index (BMI) || id:ukb-b-19953
##                                 exposure                    method nsnp
## 1 Number of live births || id:ukb-b-1209                  MR Egger   11
## 2 Number of live births || id:ukb-b-1209           Weighted median   11
## 3 Number of live births || id:ukb-b-1209 Inverse variance weighted   11
## 4 Number of live births || id:ukb-b-1209               Simple mode   11
## 5 Number of live births || id:ukb-b-1209             Weighted mode   11
##             b         se      pval
## 1 -1.70967972 1.07982945 0.1478160
## 2  0.02316551 0.05231896 0.6579287
## 3  0.23789224 0.14420427 0.0990065
## 4 -0.02540440 0.05698466 0.6652305
## 5 -0.02003130 0.04867554 0.6893674
mr_scatter_plot(d_mr,d)
## $`ukb-b-1209.ukb-b-19953`

## 
## attr(,"split_type")
## [1] "data.frame"
## attr(,"split_labels")
##   id.exposure  id.outcome
## 1  ukb-b-1209 ukb-b-19953

BMI 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", "ukb-b-1209")
## Extracting data for 498 SNP(s) from 1 GWAS(s)
## Harmonising Weight || id:ukb-b-11842 (ukb-b-11842) and Number of live births || id:ukb-b-1209 (ukb-b-1209)
d_mr<-mr(d)
## Analysing 'ukb-b-11842' on 'ukb-b-1209'
d_mr
##   id.exposure id.outcome                                outcome
## 1 ukb-b-11842 ukb-b-1209 Number of live births || id:ukb-b-1209
## 2 ukb-b-11842 ukb-b-1209 Number of live births || id:ukb-b-1209
## 3 ukb-b-11842 ukb-b-1209 Number of live births || id:ukb-b-1209
## 4 ukb-b-11842 ukb-b-1209 Number of live births || id:ukb-b-1209
## 5 ukb-b-11842 ukb-b-1209 Number of live births || id:ukb-b-1209
##                   exposure                    method nsnp            b
## 1 Weight || id:ukb-b-11842                  MR Egger  498 -0.056721477
## 2 Weight || id:ukb-b-11842           Weighted median  498 -0.042899364
## 3 Weight || id:ukb-b-11842 Inverse variance weighted  498 -0.008754732
## 4 Weight || id:ukb-b-11842               Simple mode  498 -0.089468321
## 5 Weight || id:ukb-b-11842             Weighted mode  498 -0.115049099
##           se       pval
## 1 0.03635678 0.11936586
## 2 0.01820696 0.01846261
## 3 0.01428955 0.54009674
## 4 0.06697011 0.18217898
## 5 0.04495540 0.01078681
mr_scatter_plot(d_mr,d)
## $`ukb-b-11842.ukb-b-1209`

## 
## attr(,"split_type")
## [1] "data.frame"
## attr(,"split_labels")
##   id.exposure id.outcome
## 1 ukb-b-11842 ukb-b-1209
d <- make_dat("ukb-b-1209", "ukb-b-11842")
## Extracting data for 11 SNP(s) from 1 GWAS(s)
## Harmonising Number of live births || id:ukb-b-1209 (ukb-b-1209) and Weight || id:ukb-b-11842 (ukb-b-11842)
d_mr<-mr(d)
## Analysing 'ukb-b-1209' on 'ukb-b-11842'
d_mr
##   id.exposure  id.outcome                  outcome
## 1  ukb-b-1209 ukb-b-11842 Weight || id:ukb-b-11842
## 2  ukb-b-1209 ukb-b-11842 Weight || id:ukb-b-11842
## 3  ukb-b-1209 ukb-b-11842 Weight || id:ukb-b-11842
## 4  ukb-b-1209 ukb-b-11842 Weight || id:ukb-b-11842
## 5  ukb-b-1209 ukb-b-11842 Weight || id:ukb-b-11842
##                                 exposure                    method nsnp
## 1 Number of live births || id:ukb-b-1209                  MR Egger   11
## 2 Number of live births || id:ukb-b-1209           Weighted median   11
## 3 Number of live births || id:ukb-b-1209 Inverse variance weighted   11
## 4 Number of live births || id:ukb-b-1209               Simple mode   11
## 5 Number of live births || id:ukb-b-1209             Weighted mode   11
##              b         se       pval
## 1 -2.133395750 0.78651635 0.02390095
## 2 -0.004403109 0.04437244 0.92095508
## 3  0.158903158 0.12568796 0.20613416
## 4 -0.014992579 0.04132423 0.72430259
## 5 -0.024366032 0.04093768 0.56493618
mr_scatter_plot(d_mr,d)
## $`ukb-b-1209.ukb-b-11842`

## 
## attr(,"split_type")
## [1] "data.frame"
## attr(,"split_labels")
##   id.exposure  id.outcome
## 1  ukb-b-1209 ukb-b-11842

Weight does not seem to be related.

Waist circumference

d <- make_dat("ukb-b-9405", "ukb-b-1209")
## Extracting data for 374 SNP(s) from 1 GWAS(s)
## Harmonising Waist circumference || id:ukb-b-9405 (ukb-b-9405) and Number of live births || id:ukb-b-1209 (ukb-b-1209)
## Removing the following SNPs for incompatible alleles:
## rs156902
d_mr<-mr(d)
## Analysing 'ukb-b-9405' on 'ukb-b-1209'
d_mr
##   id.exposure id.outcome                                outcome
## 1  ukb-b-9405 ukb-b-1209 Number of live births || id:ukb-b-1209
## 2  ukb-b-9405 ukb-b-1209 Number of live births || id:ukb-b-1209
## 3  ukb-b-9405 ukb-b-1209 Number of live births || id:ukb-b-1209
## 4  ukb-b-9405 ukb-b-1209 Number of live births || id:ukb-b-1209
## 5  ukb-b-9405 ukb-b-1209 Number of live births || id:ukb-b-1209
##                               exposure                    method nsnp
## 1 Waist circumference || id:ukb-b-9405                  MR Egger  374
## 2 Waist circumference || id:ukb-b-9405           Weighted median  374
## 3 Waist circumference || id:ukb-b-9405 Inverse variance weighted  374
## 4 Waist circumference || id:ukb-b-9405               Simple mode  374
## 5 Waist circumference || id:ukb-b-9405             Weighted mode  374
##             b         se        pval
## 1 -0.10170445 0.05273411 0.054537716
## 2  0.03316409 0.02310912 0.151256335
## 3  0.05008059 0.01854598 0.006926704
## 4  0.10740485 0.09633401 0.265601944
## 5  0.07061706 0.07668333 0.357702061
mr_scatter_plot(d_mr,d)
## $`ukb-b-9405.ukb-b-1209`

## 
## attr(,"split_type")
## [1] "data.frame"
## attr(,"split_labels")
##   id.exposure id.outcome
## 1  ukb-b-9405 ukb-b-1209
d <- make_dat("ukb-b-1209", "ukb-b-9405")
## Extracting data for 11 SNP(s) from 1 GWAS(s)
## Harmonising Number of live births || id:ukb-b-1209 (ukb-b-1209) and Waist circumference || id:ukb-b-9405 (ukb-b-9405)
d_mr<-mr(d)
## Analysing 'ukb-b-1209' on 'ukb-b-9405'
d_mr
##   id.exposure id.outcome                              outcome
## 1  ukb-b-1209 ukb-b-9405 Waist circumference || id:ukb-b-9405
## 2  ukb-b-1209 ukb-b-9405 Waist circumference || id:ukb-b-9405
## 3  ukb-b-1209 ukb-b-9405 Waist circumference || id:ukb-b-9405
## 4  ukb-b-1209 ukb-b-9405 Waist circumference || id:ukb-b-9405
## 5  ukb-b-1209 ukb-b-9405 Waist circumference || id:ukb-b-9405
##                                 exposure                    method nsnp
## 1 Number of live births || id:ukb-b-1209                  MR Egger   11
## 2 Number of live births || id:ukb-b-1209           Weighted median   11
## 3 Number of live births || id:ukb-b-1209 Inverse variance weighted   11
## 4 Number of live births || id:ukb-b-1209               Simple mode   11
## 5 Number of live births || id:ukb-b-1209             Weighted mode   11
##             b         se       pval
## 1 -1.24194057 0.64659829 0.08695479
## 2  0.01812676 0.04398794 0.68027723
## 3  0.20672361 0.09244020 0.02533242
## 4  0.03657581 0.05344377 0.50928502
## 5  0.01850218 0.04185113 0.66782814
mr_scatter_plot(d_mr,d)
## $`ukb-b-1209.ukb-b-9405`

## 
## attr(,"split_type")
## [1] "data.frame"
## attr(,"split_labels")
##   id.exposure id.outcome
## 1  ukb-b-1209 ukb-b-9405
d <- mv_extract_exposures(c("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, 711 variants, using EUR population reference
## Removing 261 of 711 variants due to LD with other variants or absence from LD reference panel
## Extracting data for 450 SNP(s) from 2 GWAS(s)
## Warning in .fun(piece, ...): Duplicated SNPs present in exposure data for phenotype 'Waist circumference || id:ukb-b-9405. Just keeping the first instance:
## rs9674487
## Harmonising Waist circumference || id:ukb-b-9405 (ukb-b-9405) and Body mass index (BMI) || id:ukb-b-19953 (ukb-b-19953)
## Removing the following SNPs for incompatible alleles:
## rs9674487
## Removing the following SNPs for being palindromic with intermediate allele frequencies:
## rs10887578, rs11250094, rs11634851, rs12507026, rs13264909, rs1454687, rs1860750, rs2396625, rs347551, rs396755, rs59086897, rs6597975, rs7568228, rs765874, rs7704382, rs961498
o <- extract_outcome_data(d$SNP, "ukb-b-1209")
## Extracting data for 449 SNP(s) from 1 GWAS(s)
d <- mv_harmonise_data(d, o)
## Harmonising Waist circumference || id:ukb-b-9405 (ukb-b-9405) and Number of live births || id:ukb-b-1209 (ukb-b-1209)
## Removing the following SNPs for being palindromic with intermediate allele frequencies:
## rs10887578, rs11250094, rs11634851, rs12507026, rs13264909, rs1454687, rs1860750, rs2396625, rs347551, rs396755, rs59086897, rs6597975, rs7568228, rs765874, rs7704382, rs961498
mv_multiple(d)
## $result
##   id.exposure                                exposure id.outcome
## 1 ukb-b-19953 Body mass index (BMI) || id:ukb-b-19953 ukb-b-1209
## 2  ukb-b-9405    Waist circumference || id:ukb-b-9405 ukb-b-1209
##                                  outcome nsnp           b         se      pval
## 1 Number of live births || id:ukb-b-1209  399  0.09674718 0.06105449 0.1130564
## 2 Number of live births || id:ukb-b-1209  290 -0.05340697 0.07665621 0.4859857

Body fat

Body fat percentage

d <- make_dat("ukb-b-8909", "ukb-b-1209")
## Extracting data for 395 SNP(s) from 1 GWAS(s)
## Harmonising Body fat percentage || id:ukb-b-8909 (ukb-b-8909) and Number of live births || id:ukb-b-1209 (ukb-b-1209)
## Removing the following SNPs for incompatible alleles:
## rs2731238
d_mr<-mr(d)
## Analysing 'ukb-b-8909' on 'ukb-b-1209'
d_mr
##   id.exposure id.outcome                                outcome
## 1  ukb-b-8909 ukb-b-1209 Number of live births || id:ukb-b-1209
## 2  ukb-b-8909 ukb-b-1209 Number of live births || id:ukb-b-1209
## 3  ukb-b-8909 ukb-b-1209 Number of live births || id:ukb-b-1209
## 4  ukb-b-8909 ukb-b-1209 Number of live births || id:ukb-b-1209
## 5  ukb-b-8909 ukb-b-1209 Number of live births || id:ukb-b-1209
##                               exposure                    method nsnp
## 1 Body fat percentage || id:ukb-b-8909                  MR Egger  395
## 2 Body fat percentage || id:ukb-b-8909           Weighted median  395
## 3 Body fat percentage || id:ukb-b-8909 Inverse variance weighted  395
## 4 Body fat percentage || id:ukb-b-8909               Simple mode  395
## 5 Body fat percentage || id:ukb-b-8909             Weighted mode  395
##             b         se        pval
## 1 -0.09975435 0.06270489 0.112446353
## 2  0.06188934 0.02442535 0.011282816
## 3  0.05985233 0.01958351 0.002241155
## 4  0.19228328 0.11022514 0.081858790
## 5  0.16584293 0.12051270 0.169558445
mr_scatter_plot(d_mr,d)
## $`ukb-b-8909.ukb-b-1209`

## 
## attr(,"split_type")
## [1] "data.frame"
## attr(,"split_labels")
##   id.exposure id.outcome
## 1  ukb-b-8909 ukb-b-1209
d <- make_dat("ukb-b-1209", "ukb-b-8909")
## Extracting data for 11 SNP(s) from 1 GWAS(s)
## Harmonising Number of live births || id:ukb-b-1209 (ukb-b-1209) and Body fat percentage || id:ukb-b-8909 (ukb-b-8909)
d_mr<-mr(d)
## Analysing 'ukb-b-1209' on 'ukb-b-8909'
d_mr
##   id.exposure id.outcome                              outcome
## 1  ukb-b-1209 ukb-b-8909 Body fat percentage || id:ukb-b-8909
## 2  ukb-b-1209 ukb-b-8909 Body fat percentage || id:ukb-b-8909
## 3  ukb-b-1209 ukb-b-8909 Body fat percentage || id:ukb-b-8909
## 4  ukb-b-1209 ukb-b-8909 Body fat percentage || id:ukb-b-8909
## 5  ukb-b-1209 ukb-b-8909 Body fat percentage || id:ukb-b-8909
##                                 exposure                    method nsnp
## 1 Number of live births || id:ukb-b-1209                  MR Egger   11
## 2 Number of live births || id:ukb-b-1209           Weighted median   11
## 3 Number of live births || id:ukb-b-1209 Inverse variance weighted   11
## 4 Number of live births || id:ukb-b-1209               Simple mode   11
## 5 Number of live births || id:ukb-b-1209             Weighted mode   11
##              b         se       pval
## 1 -1.623428386 0.61039893 0.02606208
## 2  0.027602487 0.04672043 0.55465364
## 3  0.101218545 0.09611295 0.29228565
## 4 -0.002726588 0.07130492 0.97025019
## 5 -0.019269579 0.05048541 0.71067927
mr_scatter_plot(d_mr,d)
## $`ukb-b-1209.ukb-b-8909`

## 
## attr(,"split_type")
## [1] "data.frame"
## attr(,"split_labels")
##   id.exposure id.outcome
## 1  ukb-b-1209 ukb-b-8909

Impedance of whole body

d <- make_dat("ukb-b-19921", "ukb-b-1209")
## Extracting data for 528 SNP(s) from 1 GWAS(s)
## Harmonising Impedance of whole body || id:ukb-b-19921 (ukb-b-19921) and Number of live births || id:ukb-b-1209 (ukb-b-1209)
d_mr<-mr(d)
## Analysing 'ukb-b-19921' on 'ukb-b-1209'
d_mr
##   id.exposure id.outcome                                outcome
## 1 ukb-b-19921 ukb-b-1209 Number of live births || id:ukb-b-1209
## 2 ukb-b-19921 ukb-b-1209 Number of live births || id:ukb-b-1209
## 3 ukb-b-19921 ukb-b-1209 Number of live births || id:ukb-b-1209
## 4 ukb-b-19921 ukb-b-1209 Number of live births || id:ukb-b-1209
## 5 ukb-b-19921 ukb-b-1209 Number of live births || id:ukb-b-1209
##                                    exposure                    method nsnp
## 1 Impedance of whole body || id:ukb-b-19921                  MR Egger  528
## 2 Impedance of whole body || id:ukb-b-19921           Weighted median  528
## 3 Impedance of whole body || id:ukb-b-19921 Inverse variance weighted  528
## 4 Impedance of whole body || id:ukb-b-19921               Simple mode  528
## 5 Impedance of whole body || id:ukb-b-19921             Weighted mode  528
##             b         se        pval
## 1 -0.04216400 0.04103065 0.304599959
## 2 -0.03797467 0.01996754 0.057194643
## 3 -0.04607240 0.01544993 0.002863292
## 4 -0.08970075 0.07527381 0.233931113
## 5 -0.04231315 0.06218068 0.496494986
mr_scatter_plot(d_mr,d)
## $`ukb-b-19921.ukb-b-1209`

## 
## attr(,"split_type")
## [1] "data.frame"
## attr(,"split_labels")
##   id.exposure id.outcome
## 1 ukb-b-19921 ukb-b-1209
d <- make_dat("ukb-b-1209", "ukb-b-19921")
## Extracting data for 11 SNP(s) from 1 GWAS(s)
## Harmonising Number of live births || id:ukb-b-1209 (ukb-b-1209) and Impedance of whole body || id:ukb-b-19921 (ukb-b-19921)
d_mr<-mr(d)
## Analysing 'ukb-b-1209' on 'ukb-b-19921'
d_mr
##   id.exposure  id.outcome                                   outcome
## 1  ukb-b-1209 ukb-b-19921 Impedance of whole body || id:ukb-b-19921
## 2  ukb-b-1209 ukb-b-19921 Impedance of whole body || id:ukb-b-19921
## 3  ukb-b-1209 ukb-b-19921 Impedance of whole body || id:ukb-b-19921
## 4  ukb-b-1209 ukb-b-19921 Impedance of whole body || id:ukb-b-19921
## 5  ukb-b-1209 ukb-b-19921 Impedance of whole body || id:ukb-b-19921
##                                 exposure                    method nsnp
## 1 Number of live births || id:ukb-b-1209                  MR Egger   11
## 2 Number of live births || id:ukb-b-1209           Weighted median   11
## 3 Number of live births || id:ukb-b-1209 Inverse variance weighted   11
## 4 Number of live births || id:ukb-b-1209               Simple mode   11
## 5 Number of live births || id:ukb-b-1209             Weighted mode   11
##              b         se      pval
## 1  0.346376604 0.94557837 0.7225956
## 2 -0.003017522 0.03893588 0.9382260
## 3 -0.175042869 0.10983300 0.1109991
## 4  0.048486177 0.03971338 0.2501278
## 5  0.028448856 0.03575601 0.4447178
mr_scatter_plot(d_mr,d)
## $`ukb-b-1209.ukb-b-19921`

## 
## attr(,"split_type")
## [1] "data.frame"
## attr(,"split_labels")
##   id.exposure  id.outcome
## 1  ukb-b-1209 ukb-b-19921

Basal metabolic rate

d <- make_dat("ukb-b-16446", "ukb-b-1209")
## Warning in .fun(piece, ...): Duplicated SNPs present in exposure data for phenotype 'Basal metabolic rate || id:ukb-b-16446. Just keeping the first instance:
## rs3129962
## Extracting data for 546 SNP(s) from 1 GWAS(s)
## Finding proxies for 1 SNPs in outcome ukb-b-1209
## Extracting data for 1 SNP(s) from 1 GWAS(s)
## Harmonising Basal metabolic rate || id:ukb-b-16446 (ukb-b-16446) and Number of live births || id:ukb-b-1209 (ukb-b-1209)
## Removing the following SNPs for incompatible alleles:
## rs3129962
d_mr<-mr(d)
## Analysing 'ukb-b-16446' on 'ukb-b-1209'
d_mr
##   id.exposure id.outcome                                outcome
## 1 ukb-b-16446 ukb-b-1209 Number of live births || id:ukb-b-1209
## 2 ukb-b-16446 ukb-b-1209 Number of live births || id:ukb-b-1209
## 3 ukb-b-16446 ukb-b-1209 Number of live births || id:ukb-b-1209
## 4 ukb-b-16446 ukb-b-1209 Number of live births || id:ukb-b-1209
## 5 ukb-b-16446 ukb-b-1209 Number of live births || id:ukb-b-1209
##                                 exposure                    method nsnp
## 1 Basal metabolic rate || id:ukb-b-16446                  MR Egger  545
## 2 Basal metabolic rate || id:ukb-b-16446           Weighted median  545
## 3 Basal metabolic rate || id:ukb-b-16446 Inverse variance weighted  545
## 4 Basal metabolic rate || id:ukb-b-16446               Simple mode  545
## 5 Basal metabolic rate || id:ukb-b-16446             Weighted mode  545
##             b         se        pval
## 1 -0.04973501 0.04005463 0.214890975
## 2 -0.06524149 0.02124245 0.002131440
## 3 -0.03739293 0.01661852 0.024444150
## 4 -0.14021590 0.07217670 0.052571009
## 5 -0.13217811 0.04864259 0.006790733
mr_scatter_plot(d_mr,d)
## $`ukb-b-16446.ukb-b-1209`

## 
## attr(,"split_type")
## [1] "data.frame"
## attr(,"split_labels")
##   id.exposure id.outcome
## 1 ukb-b-16446 ukb-b-1209
d <- make_dat("ukb-b-1209", "ukb-b-16446")
## Extracting data for 11 SNP(s) from 1 GWAS(s)
## Harmonising Number of live births || id:ukb-b-1209 (ukb-b-1209) and Basal metabolic rate || id:ukb-b-16446 (ukb-b-16446)
d_mr<-mr(d)
## Analysing 'ukb-b-1209' on 'ukb-b-16446'
d_mr
##   id.exposure  id.outcome                                outcome
## 1  ukb-b-1209 ukb-b-16446 Basal metabolic rate || id:ukb-b-16446
## 2  ukb-b-1209 ukb-b-16446 Basal metabolic rate || id:ukb-b-16446
## 3  ukb-b-1209 ukb-b-16446 Basal metabolic rate || id:ukb-b-16446
## 4  ukb-b-1209 ukb-b-16446 Basal metabolic rate || id:ukb-b-16446
## 5  ukb-b-1209 ukb-b-16446 Basal metabolic rate || id:ukb-b-16446
##                                 exposure                    method nsnp
## 1 Number of live births || id:ukb-b-1209                  MR Egger   11
## 2 Number of live births || id:ukb-b-1209           Weighted median   11
## 3 Number of live births || id:ukb-b-1209 Inverse variance weighted   11
## 4 Number of live births || id:ukb-b-1209               Simple mode   11
## 5 Number of live births || id:ukb-b-1209             Weighted mode   11
##              b         se      pval
## 1 -1.472711453 0.64608449 0.0486069
## 2 -0.004048275 0.03842546 0.9160949
## 3  0.109988451 0.09553311 0.2496038
## 4 -0.039885142 0.04548770 0.4011506
## 5 -0.036396833 0.03777301 0.3579850
mr_scatter_plot(d_mr,d)
## $`ukb-b-1209.ukb-b-16446`

## 
## attr(,"split_type")
## [1] "data.frame"
## attr(,"split_labels")
##   id.exposure  id.outcome
## 1  ukb-b-1209 ukb-b-16446

Appendicular lean mass

d <- make_dat("ebi-a-GCST90000025", "ukb-b-1209")
## Extracting data for 690 SNP(s) from 1 GWAS(s)
## Finding proxies for 117 SNPs in outcome ukb-b-1209
## Extracting data for 117 SNP(s) from 1 GWAS(s)
## Harmonising Appendicular lean mass || id:ebi-a-GCST90000025 (ebi-a-GCST90000025) and Number of live births || id:ukb-b-1209 (ukb-b-1209)
## Removing the following SNPs for incompatible alleles:
## rs664317, rs7543202, rs9640283
d_mr<-mr(d)
## Analysing 'ebi-a-GCST90000025' on 'ukb-b-1209'
d_mr
##          id.exposure id.outcome                                outcome
## 1 ebi-a-GCST90000025 ukb-b-1209 Number of live births || id:ukb-b-1209
## 2 ebi-a-GCST90000025 ukb-b-1209 Number of live births || id:ukb-b-1209
## 3 ebi-a-GCST90000025 ukb-b-1209 Number of live births || id:ukb-b-1209
## 4 ebi-a-GCST90000025 ukb-b-1209 Number of live births || id:ukb-b-1209
## 5 ebi-a-GCST90000025 ukb-b-1209 Number of live births || id:ukb-b-1209
##                                          exposure                    method
## 1 Appendicular lean mass || id:ebi-a-GCST90000025                  MR Egger
## 2 Appendicular lean mass || id:ebi-a-GCST90000025           Weighted median
## 3 Appendicular lean mass || id:ebi-a-GCST90000025 Inverse variance weighted
## 4 Appendicular lean mass || id:ebi-a-GCST90000025               Simple mode
## 5 Appendicular lean mass || id:ebi-a-GCST90000025             Weighted mode
##   nsnp           b          se         pval
## 1  622 -0.01770167 0.020248373 3.823332e-01
## 2  622 -0.02597202 0.012320438 3.502722e-02
## 3  622 -0.03392393 0.008710689 9.839436e-05
## 4  622 -0.02118641 0.040335037 5.995895e-01
## 5  622 -0.02118641 0.025452355 4.055062e-01
mr_scatter_plot(d_mr,d)
## $`ebi-a-GCST90000025.ukb-b-1209`

## 
## attr(,"split_type")
## [1] "data.frame"
## attr(,"split_labels")
##          id.exposure id.outcome
## 1 ebi-a-GCST90000025 ukb-b-1209
d <- make_dat("ukb-b-1209", "ebi-a-GCST90000025")
## Extracting data for 11 SNP(s) from 1 GWAS(s)
## Harmonising Number of live births || id:ukb-b-1209 (ukb-b-1209) and Appendicular lean mass || id:ebi-a-GCST90000025 (ebi-a-GCST90000025)
d_mr<-mr(d)
## Analysing 'ukb-b-1209' on 'ebi-a-GCST90000025'
d_mr
##   id.exposure         id.outcome
## 1  ukb-b-1209 ebi-a-GCST90000025
## 2  ukb-b-1209 ebi-a-GCST90000025
## 3  ukb-b-1209 ebi-a-GCST90000025
## 4  ukb-b-1209 ebi-a-GCST90000025
## 5  ukb-b-1209 ebi-a-GCST90000025
##                                           outcome
## 1 Appendicular lean mass || id:ebi-a-GCST90000025
## 2 Appendicular lean mass || id:ebi-a-GCST90000025
## 3 Appendicular lean mass || id:ebi-a-GCST90000025
## 4 Appendicular lean mass || id:ebi-a-GCST90000025
## 5 Appendicular lean mass || id:ebi-a-GCST90000025
##                                 exposure                    method nsnp
## 1 Number of live births || id:ukb-b-1209                  MR Egger   11
## 2 Number of live births || id:ukb-b-1209           Weighted median   11
## 3 Number of live births || id:ukb-b-1209 Inverse variance weighted   11
## 4 Number of live births || id:ukb-b-1209               Simple mode   11
## 5 Number of live births || id:ukb-b-1209             Weighted mode   11
##              b         se      pval
## 1 -1.057539827 0.96500031 0.3015817
## 2  0.044182085 0.06383253 0.4888392
## 3  0.014950629 0.11735351 0.8986252
## 4 -0.062269564 0.10999777 0.5838063
## 5 -0.006200623 0.09137043 0.9472328
mr_scatter_plot(d_mr,d)
## $`ukb-b-1209.ebi-a-GCST90000025`

## 
## attr(,"split_type")
## [1] "data.frame"
## attr(,"split_labels")
##   id.exposure         id.outcome
## 1  ukb-b-1209 ebi-a-GCST90000025