Investigating intelligence 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 details

Cognitive performance

d <- make_dat("ebi-a-GCST006572", "ukb-b-1209")
## API: public: http://gwas-api.mrcieu.ac.uk/
## Extracting data for 147 SNP(s) from 1 GWAS(s)
## Harmonising Cognitive performance || id:ebi-a-GCST006572 (ebi-a-GCST006572) and Number of live births || id:ukb-b-1209 (ukb-b-1209)
d_mr<-mr(d)
## Analysing 'ebi-a-GCST006572' on 'ukb-b-1209'
d_mr
##        id.exposure id.outcome                                outcome
## 1 ebi-a-GCST006572 ukb-b-1209 Number of live births || id:ukb-b-1209
## 2 ebi-a-GCST006572 ukb-b-1209 Number of live births || id:ukb-b-1209
## 3 ebi-a-GCST006572 ukb-b-1209 Number of live births || id:ukb-b-1209
## 4 ebi-a-GCST006572 ukb-b-1209 Number of live births || id:ukb-b-1209
## 5 ebi-a-GCST006572 ukb-b-1209 Number of live births || id:ukb-b-1209
##                                       exposure                    method nsnp
## 1 Cognitive performance || id:ebi-a-GCST006572                  MR Egger  147
## 2 Cognitive performance || id:ebi-a-GCST006572           Weighted median  147
## 3 Cognitive performance || id:ebi-a-GCST006572 Inverse variance weighted  147
## 4 Cognitive performance || id:ebi-a-GCST006572               Simple mode  147
## 5 Cognitive performance || id:ebi-a-GCST006572             Weighted mode  147
##              b         se         pval
## 1 -0.212541899 0.09451768 2.603916e-02
## 2 -0.101989572 0.02455570 3.275753e-05
## 3 -0.116969157 0.02121750 3.530457e-08
## 4 -0.009784325 0.07802220 9.003759e-01
## 5  0.006189646 0.08603890 9.427480e-01
mr_scatter_plot(d_mr,d)
## $`ebi-a-GCST006572.ukb-b-1209`

## 
## attr(,"split_type")
## [1] "data.frame"
## attr(,"split_labels")
##        id.exposure id.outcome
## 1 ebi-a-GCST006572 ukb-b-1209
d <- make_dat("ukb-b-1209", "ebi-a-GCST006572")
## Extracting data for 11 SNP(s) from 1 GWAS(s)
## Finding proxies for 1 SNPs in outcome ebi-a-GCST006572
## Extracting data for 1 SNP(s) from 1 GWAS(s)
## Harmonising Number of live births || id:ukb-b-1209 (ukb-b-1209) and Cognitive performance || id:ebi-a-GCST006572 (ebi-a-GCST006572)
d_mr<-mr(d)
## Analysing 'ukb-b-1209' on 'ebi-a-GCST006572'
d_mr
##   id.exposure       id.outcome                                      outcome
## 1  ukb-b-1209 ebi-a-GCST006572 Cognitive performance || id:ebi-a-GCST006572
## 2  ukb-b-1209 ebi-a-GCST006572 Cognitive performance || id:ebi-a-GCST006572
## 3  ukb-b-1209 ebi-a-GCST006572 Cognitive performance || id:ebi-a-GCST006572
## 4  ukb-b-1209 ebi-a-GCST006572 Cognitive performance || id:ebi-a-GCST006572
## 5  ukb-b-1209 ebi-a-GCST006572 Cognitive performance || id:ebi-a-GCST006572
##                                 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  1.0323612 1.16243572 3.975995e-01
## 2 -0.3409697 0.07919614 1.666977e-05
## 3 -0.3782699 0.14527258 9.217959e-03
## 4 -0.4245654 0.12021660 5.431659e-03
## 5 -0.3862501 0.14536695 2.401981e-02
mr_scatter_plot(d_mr,d)
## $`ukb-b-1209.ebi-a-GCST006572`

## 
## attr(,"split_type")
## [1] "data.frame"
## attr(,"split_labels")
##   id.exposure       id.outcome
## 1  ukb-b-1209 ebi-a-GCST006572

Fluid intelligence score

d <- make_dat("ukb-b-5238", "ukb-b-1209")
## Extracting data for 79 SNP(s) from 1 GWAS(s)
## Harmonising Fluid intelligence score || id:ukb-b-5238 (ukb-b-5238) and Number of live births || id:ukb-b-1209 (ukb-b-1209)
d_mr<-mr(d)
## Analysing 'ukb-b-5238' on 'ukb-b-1209'
d_mr
##   id.exposure id.outcome                                outcome
## 1  ukb-b-5238 ukb-b-1209 Number of live births || id:ukb-b-1209
## 2  ukb-b-5238 ukb-b-1209 Number of live births || id:ukb-b-1209
## 3  ukb-b-5238 ukb-b-1209 Number of live births || id:ukb-b-1209
## 4  ukb-b-5238 ukb-b-1209 Number of live births || id:ukb-b-1209
## 5  ukb-b-5238 ukb-b-1209 Number of live births || id:ukb-b-1209
##                                    exposure                    method nsnp
## 1 Fluid intelligence score || id:ukb-b-5238                  MR Egger   79
## 2 Fluid intelligence score || id:ukb-b-5238           Weighted median   79
## 3 Fluid intelligence score || id:ukb-b-5238 Inverse variance weighted   79
## 4 Fluid intelligence score || id:ukb-b-5238               Simple mode   79
## 5 Fluid intelligence score || id:ukb-b-5238             Weighted mode   79
##             b         se         pval
## 1 -0.07865612 0.05403467 1.495518e-01
## 2 -0.05747523 0.01249954 4.261835e-06
## 3 -0.06127680 0.01171632 1.694758e-07
## 4 -0.06997607 0.03337902 3.928778e-02
## 5 -0.07303584 0.03417717 3.573373e-02
mr_scatter_plot(d_mr,d)
## $`ukb-b-5238.ukb-b-1209`

## 
## attr(,"split_type")
## [1] "data.frame"
## attr(,"split_labels")
##   id.exposure id.outcome
## 1  ukb-b-5238 ukb-b-1209
d <- make_dat("ukb-b-1209", "ukb-b-5238")
## Extracting data for 11 SNP(s) from 1 GWAS(s)
## Harmonising Number of live births || id:ukb-b-1209 (ukb-b-1209) and Fluid intelligence score || id:ukb-b-5238 (ukb-b-5238)
d_mr<-mr(d)
## Analysing 'ukb-b-1209' on 'ukb-b-5238'
d_mr
##   id.exposure id.outcome                                   outcome
## 1  ukb-b-1209 ukb-b-5238 Fluid intelligence score || id:ukb-b-5238
## 2  ukb-b-1209 ukb-b-5238 Fluid intelligence score || id:ukb-b-5238
## 3  ukb-b-1209 ukb-b-5238 Fluid intelligence score || id:ukb-b-5238
## 4  ukb-b-1209 ukb-b-5238 Fluid intelligence score || id:ukb-b-5238
## 5  ukb-b-1209 ukb-b-5238 Fluid intelligence score || id:ukb-b-5238
##                                 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  2.4745365 2.0510419 0.2583885855
## 2 -0.6585283 0.1801301 0.0002563322
## 3 -0.8645836 0.2670947 0.0012079644
## 4 -0.6733159 0.3064306 0.0526824643
## 5 -0.5534807 0.2421448 0.0453408211
mr_scatter_plot(d_mr,d)
## $`ukb-b-1209.ukb-b-5238`

## 
## attr(,"split_type")
## [1] "data.frame"
## attr(,"split_labels")
##   id.exposure id.outcome
## 1  ukb-b-1209 ukb-b-5238

Intelligence

d <- make_dat("ebi-a-GCST006250", "ukb-b-1209")
## Extracting data for 165 SNP(s) from 1 GWAS(s)
## Harmonising Intelligence || id:ebi-a-GCST006250 (ebi-a-GCST006250) and Number of live births || id:ukb-b-1209 (ukb-b-1209)
d_mr<-mr(d)
## Analysing 'ebi-a-GCST006250' on 'ukb-b-1209'
d_mr
##        id.exposure id.outcome                                outcome
## 1 ebi-a-GCST006250 ukb-b-1209 Number of live births || id:ukb-b-1209
## 2 ebi-a-GCST006250 ukb-b-1209 Number of live births || id:ukb-b-1209
## 3 ebi-a-GCST006250 ukb-b-1209 Number of live births || id:ukb-b-1209
## 4 ebi-a-GCST006250 ukb-b-1209 Number of live births || id:ukb-b-1209
## 5 ebi-a-GCST006250 ukb-b-1209 Number of live births || id:ukb-b-1209
##                              exposure                    method nsnp          b
## 1 Intelligence || id:ebi-a-GCST006250                  MR Egger  165 -0.1461753
## 2 Intelligence || id:ebi-a-GCST006250           Weighted median  165 -0.1188004
## 3 Intelligence || id:ebi-a-GCST006250 Inverse variance weighted  165 -0.1091967
## 4 Intelligence || id:ebi-a-GCST006250               Simple mode  165 -0.2032403
## 5 Intelligence || id:ebi-a-GCST006250             Weighted mode  165 -0.1994294
##           se         pval
## 1 0.09751364 1.358017e-01
## 2 0.02369386 5.331688e-07
## 3 0.02085754 1.646633e-07
## 4 0.08964672 2.468872e-02
## 5 0.09240521 3.236642e-02
mr_scatter_plot(d_mr,d)
## $`ebi-a-GCST006250.ukb-b-1209`

## 
## attr(,"split_type")
## [1] "data.frame"
## attr(,"split_labels")
##        id.exposure id.outcome
## 1 ebi-a-GCST006250 ukb-b-1209
d <- make_dat("ukb-b-1209", "ebi-a-GCST006250")
## Extracting data for 11 SNP(s) from 1 GWAS(s)
## Finding proxies for 1 SNPs in outcome ebi-a-GCST006250
## Extracting data for 1 SNP(s) from 1 GWAS(s)
## Harmonising Number of live births || id:ukb-b-1209 (ukb-b-1209) and Intelligence || id:ebi-a-GCST006250 (ebi-a-GCST006250)
d_mr<-mr(d)
## Analysing 'ukb-b-1209' on 'ebi-a-GCST006250'
d_mr
##   id.exposure       id.outcome                             outcome
## 1  ukb-b-1209 ebi-a-GCST006250 Intelligence || id:ebi-a-GCST006250
## 2  ukb-b-1209 ebi-a-GCST006250 Intelligence || id:ebi-a-GCST006250
## 3  ukb-b-1209 ebi-a-GCST006250 Intelligence || id:ebi-a-GCST006250
## 4  ukb-b-1209 ebi-a-GCST006250 Intelligence || id:ebi-a-GCST006250
## 5  ukb-b-1209 ebi-a-GCST006250 Intelligence || id:ebi-a-GCST006250
##                                 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  1.4468198 1.01270303 1.868713e-01
## 2 -0.3011661 0.07129858 2.399906e-05
## 3 -0.3351126 0.12651526 8.078000e-03
## 4 -0.2648211 0.10295838 2.778953e-02
## 5 -0.2432114 0.10690159 4.616900e-02
mr_scatter_plot(d_mr,d)
## $`ukb-b-1209.ebi-a-GCST006250`

## 
## attr(,"split_type")
## [1] "data.frame"
## attr(,"split_labels")
##   id.exposure       id.outcome
## 1  ukb-b-1209 ebi-a-GCST006250

For all intelligence measures there is a negative effect on number of children.