Investigating smoking and alcohol consumption 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

Average weekly beer plus cider intake

d <- make_dat("ukb-b-5174", "ukb-b-1209")
## API: public: http://gwas-api.mrcieu.ac.uk/
## Extracting data for 22 SNP(s) from 1 GWAS(s)
## Harmonising Average weekly beer plus cider intake || id:ukb-b-5174 (ukb-b-5174) and Number of live births || id:ukb-b-1209 (ukb-b-1209)
d_mr<-mr(d)
## Analysing 'ukb-b-5174' on 'ukb-b-1209'
d_mr
##   id.exposure id.outcome                                outcome
## 1  ukb-b-5174 ukb-b-1209 Number of live births || id:ukb-b-1209
## 2  ukb-b-5174 ukb-b-1209 Number of live births || id:ukb-b-1209
## 3  ukb-b-5174 ukb-b-1209 Number of live births || id:ukb-b-1209
## 4  ukb-b-5174 ukb-b-1209 Number of live births || id:ukb-b-1209
## 5  ukb-b-5174 ukb-b-1209 Number of live births || id:ukb-b-1209
##                                                 exposure
## 1 Average weekly beer plus cider intake || id:ukb-b-5174
## 2 Average weekly beer plus cider intake || id:ukb-b-5174
## 3 Average weekly beer plus cider intake || id:ukb-b-5174
## 4 Average weekly beer plus cider intake || id:ukb-b-5174
## 5 Average weekly beer plus cider intake || id:ukb-b-5174
##                      method nsnp         b        se       pval
## 1                  MR Egger   22 0.1886616 0.4231316 0.66048054
## 2           Weighted median   22 0.2007403 0.1039127 0.05338208
## 3 Inverse variance weighted   22 0.2516405 0.1198807 0.03580880
## 4               Simple mode   22 0.2971580 0.2019737 0.15604517
## 5             Weighted mode   22 0.2182339 0.1832856 0.24706622
mr_scatter_plot(d_mr,d)
## $`ukb-b-5174.ukb-b-1209`

## 
## attr(,"split_type")
## [1] "data.frame"
## attr(,"split_labels")
##   id.exposure id.outcome
## 1  ukb-b-5174 ukb-b-1209
d <- make_dat("ukb-b-1209", "ukb-b-5174")
## Extracting data for 11 SNP(s) from 1 GWAS(s)
## Harmonising Number of live births || id:ukb-b-1209 (ukb-b-1209) and Average weekly beer plus cider intake || id:ukb-b-5174 (ukb-b-5174)
d_mr<-mr(d)
## Analysing 'ukb-b-1209' on 'ukb-b-5174'
d_mr
##   id.exposure id.outcome                                                outcome
## 1  ukb-b-1209 ukb-b-5174 Average weekly beer plus cider intake || id:ukb-b-5174
## 2  ukb-b-1209 ukb-b-5174 Average weekly beer plus cider intake || id:ukb-b-5174
## 3  ukb-b-1209 ukb-b-5174 Average weekly beer plus cider intake || id:ukb-b-5174
## 4  ukb-b-1209 ukb-b-5174 Average weekly beer plus cider intake || id:ukb-b-5174
## 5  ukb-b-1209 ukb-b-5174 Average weekly beer plus cider intake || id:ukb-b-5174
##                                 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 -0.63360027 0.53036949 0.26276004
## 2  0.04747594 0.04507297 0.29219769
## 3  0.11236229 0.06700797 0.09357192
## 4  0.02212228 0.07058266 0.76039852
## 5  0.03296988 0.07374009 0.66432423
mr_scatter_plot(d_mr,d)
## $`ukb-b-1209.ukb-b-5174`

## 
## attr(,"split_type")
## [1] "data.frame"
## attr(,"split_labels")
##   id.exposure id.outcome
## 1  ukb-b-1209 ukb-b-5174

No large effect.

Past tobacco smoking

Note this is coded from 1=Smoke most or all days through to 4=Never smoked

d <- make_dat("ukb-b-2134", "ukb-b-1209")
## Extracting data for 101 SNP(s) from 1 GWAS(s)
## Harmonising Past tobacco smoking || id:ukb-b-2134 (ukb-b-2134) and Number of live births || id:ukb-b-1209 (ukb-b-1209)
d_mr<-mr(d)
## Analysing 'ukb-b-2134' on 'ukb-b-1209'
d_mr
##   id.exposure id.outcome                                outcome
## 1  ukb-b-2134 ukb-b-1209 Number of live births || id:ukb-b-1209
## 2  ukb-b-2134 ukb-b-1209 Number of live births || id:ukb-b-1209
## 3  ukb-b-2134 ukb-b-1209 Number of live births || id:ukb-b-1209
## 4  ukb-b-2134 ukb-b-1209 Number of live births || id:ukb-b-1209
## 5  ukb-b-2134 ukb-b-1209 Number of live births || id:ukb-b-1209
##                                exposure                    method nsnp
## 1 Past tobacco smoking || id:ukb-b-2134                  MR Egger  101
## 2 Past tobacco smoking || id:ukb-b-2134           Weighted median  101
## 3 Past tobacco smoking || id:ukb-b-2134 Inverse variance weighted  101
## 4 Past tobacco smoking || id:ukb-b-2134               Simple mode  101
## 5 Past tobacco smoking || id:ukb-b-2134             Weighted mode  101
##             b         se        pval
## 1 -0.09428328 0.11456010 0.412484454
## 2 -0.06454117 0.03124220 0.038844221
## 3 -0.08435097 0.02663786 0.001542419
## 4 -0.07493338 0.08263781 0.366708925
## 5 -0.05909452 0.06564811 0.370191952
mr_scatter_plot(d_mr,d)
## $`ukb-b-2134.ukb-b-1209`

## 
## attr(,"split_type")
## [1] "data.frame"
## attr(,"split_labels")
##   id.exposure id.outcome
## 1  ukb-b-2134 ukb-b-1209
d <- make_dat("ukb-b-1209", "ukb-b-2134")
## Extracting data for 11 SNP(s) from 1 GWAS(s)
## Harmonising Number of live births || id:ukb-b-1209 (ukb-b-1209) and Past tobacco smoking || id:ukb-b-2134 (ukb-b-2134)
d_mr<-mr(d)
## Analysing 'ukb-b-1209' on 'ukb-b-2134'
d_mr
##   id.exposure id.outcome                               outcome
## 1  ukb-b-1209 ukb-b-2134 Past tobacco smoking || id:ukb-b-2134
## 2  ukb-b-1209 ukb-b-2134 Past tobacco smoking || id:ukb-b-2134
## 3  ukb-b-1209 ukb-b-2134 Past tobacco smoking || id:ukb-b-2134
## 4  ukb-b-1209 ukb-b-2134 Past tobacco smoking || id:ukb-b-2134
## 5  ukb-b-1209 ukb-b-2134 Past tobacco smoking || id:ukb-b-2134
##                                 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  1.858986664 1.04747198 0.1096838
## 2 -0.026850842 0.07322298 0.7138431
## 3 -0.107145807 0.14151489 0.4489693
## 4 -0.009129525 0.11490939 0.9382423
## 5  0.034121655 0.08350462 0.6914315
mr_scatter_plot(d_mr,d)
## $`ukb-b-1209.ukb-b-2134`

## 
## attr(,"split_type")
## [1] "data.frame"
## attr(,"split_labels")
##   id.exposure id.outcome
## 1  ukb-b-1209 ukb-b-2134

Never smoked

d <- make_dat("ukb-d-20116_0", "ukb-b-1209")
## Extracting data for 84 SNP(s) from 1 GWAS(s)
## Finding proxies for 12 SNPs in outcome ukb-b-1209
## Extracting data for 12 SNP(s) from 1 GWAS(s)
## Harmonising Smoking status: Never || id:ukb-d-20116_0 (ukb-d-20116_0) and Number of live births || id:ukb-b-1209 (ukb-b-1209)
d_mr<-mr(d)
## Analysing 'ukb-d-20116_0' on 'ukb-b-1209'
d_mr
##     id.exposure id.outcome                                outcome
## 1 ukb-d-20116_0 ukb-b-1209 Number of live births || id:ukb-b-1209
## 2 ukb-d-20116_0 ukb-b-1209 Number of live births || id:ukb-b-1209
## 3 ukb-d-20116_0 ukb-b-1209 Number of live births || id:ukb-b-1209
## 4 ukb-d-20116_0 ukb-b-1209 Number of live births || id:ukb-b-1209
## 5 ukb-d-20116_0 ukb-b-1209 Number of live births || id:ukb-b-1209
##                                    exposure                    method nsnp
## 1 Smoking status: Never || id:ukb-d-20116_0                  MR Egger   79
## 2 Smoking status: Never || id:ukb-d-20116_0           Weighted median   79
## 3 Smoking status: Never || id:ukb-d-20116_0 Inverse variance weighted   79
## 4 Smoking status: Never || id:ukb-d-20116_0               Simple mode   79
## 5 Smoking status: Never || id:ukb-d-20116_0             Weighted mode   79
##             b         se         pval
## 1 -0.06112112 0.28157427 8.287285e-01
## 2 -0.20427199 0.08019270 1.085712e-02
## 3 -0.24495532 0.06188901 7.558702e-05
## 4 -0.13044578 0.19390577 5.031087e-01
## 5 -0.12192074 0.16761572 4.691693e-01
mr_scatter_plot(d_mr,d)
## $`ukb-d-20116_0.ukb-b-1209`

## 
## attr(,"split_type")
## [1] "data.frame"
## attr(,"split_labels")
##     id.exposure id.outcome
## 1 ukb-d-20116_0 ukb-b-1209
d <- make_dat("ukb-b-1209", "ukb-d-20116_0")
## Extracting data for 11 SNP(s) from 1 GWAS(s)
## Harmonising Number of live births || id:ukb-b-1209 (ukb-b-1209) and Smoking status: Never || id:ukb-d-20116_0 (ukb-d-20116_0)
d_mr<-mr(d)
## Analysing 'ukb-b-1209' on 'ukb-d-20116_0'
d_mr
##   id.exposure    id.outcome                                   outcome
## 1  ukb-b-1209 ukb-d-20116_0 Smoking status: Never || id:ukb-d-20116_0
## 2  ukb-b-1209 ukb-d-20116_0 Smoking status: Never || id:ukb-d-20116_0
## 3  ukb-b-1209 ukb-d-20116_0 Smoking status: Never || id:ukb-d-20116_0
## 4  ukb-b-1209 ukb-d-20116_0 Smoking status: Never || id:ukb-d-20116_0
## 5  ukb-b-1209 ukb-d-20116_0 Smoking status: Never || id:ukb-d-20116_0
##                                 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  0.78243583 0.46227253 0.1247851
## 2 -0.03977059 0.03392792 0.2411134
## 3 -0.06788731 0.06210440 0.2743429
## 4 -0.09998796 0.05528526 0.1006347
## 5 -0.04500277 0.04768510 0.3675402
mr_scatter_plot(d_mr,d)
## $`ukb-b-1209.ukb-d-20116_0`

## 
## attr(,"split_type")
## [1] "data.frame"
## attr(,"split_labels")
##   id.exposure    id.outcome
## 1  ukb-b-1209 ukb-d-20116_0

Never smoked shows evidence of a negative effect on the number of live births.