Hair and skin

Investigating hair and skin-related 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

Childhood sunburn occasions

d <- make_dat("ukb-b-13246", "ieu-b-4760")

## API: public: http://gwas-api.mrcieu.ac.uk/

## Extracting data for 81 SNP(s) from 1 GWAS(s)

## Finding proxies for 5 SNPs in outcome ieu-b-4760

## Extracting data for 5 SNP(s) from 1 GWAS(s)

## Harmonising Childhood sunburn occasions || id:ukb-b-13246 (ukb-b-13246) and Number of children || id:ieu-b-4760 (ieu-b-4760)

d_mr<-mr(d)

## Analysing 'ukb-b-13246' on 'ieu-b-4760'

d_mr

##   id.exposure id.outcome                             outcome
## 1 ukb-b-13246 ieu-b-4760 Number of children || id:ieu-b-4760
## 2 ukb-b-13246 ieu-b-4760 Number of children || id:ieu-b-4760
## 3 ukb-b-13246 ieu-b-4760 Number of children || id:ieu-b-4760
## 4 ukb-b-13246 ieu-b-4760 Number of children || id:ieu-b-4760
## 5 ukb-b-13246 ieu-b-4760 Number of children || id:ieu-b-4760
##                                        exposure                    method nsnp
## 1 Childhood sunburn occasions || id:ukb-b-13246                  MR Egger   80
## 2 Childhood sunburn occasions || id:ukb-b-13246           Weighted median   80
## 3 Childhood sunburn occasions || id:ukb-b-13246 Inverse variance weighted   80
## 4 Childhood sunburn occasions || id:ukb-b-13246               Simple mode   80
## 5 Childhood sunburn occasions || id:ukb-b-13246             Weighted mode   80
##             b         se         pval
## 1 -0.06324747 0.01638124 2.315967e-04
## 2 -0.07042265 0.01198914 4.257321e-09
## 3 -0.04656187 0.01250956 1.975712e-04
## 4 -0.01939169 0.02493121 4.390056e-01
## 5 -0.05850729 0.00993868 9.093840e-08

mr_scatter_plot(d_mr,d)

## $`ukb-b-13246.ieu-b-4760`

## 
## attr(,"split_type")
## [1] "data.frame"
## attr(,"split_labels")
##   id.exposure id.outcome
## 1 ukb-b-13246 ieu-b-4760

d <- make_dat("ieu-b-4760", "ukb-b-13246")

## Extracting data for 9 SNP(s) from 1 GWAS(s)

## Finding proxies for 1 SNPs in outcome ukb-b-13246

## Extracting data for 1 SNP(s) from 1 GWAS(s)

## Harmonising Number of children || id:ieu-b-4760 (ieu-b-4760) and Childhood sunburn occasions || id:ukb-b-13246 (ukb-b-13246)

d_mr<-mr(d)

## Analysing 'ieu-b-4760' on 'ukb-b-13246'

d_mr

##   id.exposure  id.outcome                                       outcome
## 1  ieu-b-4760 ukb-b-13246 Childhood sunburn occasions || id:ukb-b-13246
## 2  ieu-b-4760 ukb-b-13246 Childhood sunburn occasions || id:ukb-b-13246
## 3  ieu-b-4760 ukb-b-13246 Childhood sunburn occasions || id:ukb-b-13246
## 4  ieu-b-4760 ukb-b-13246 Childhood sunburn occasions || id:ukb-b-13246
## 5  ieu-b-4760 ukb-b-13246 Childhood sunburn occasions || id:ukb-b-13246
##                              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  2.15706543 5.44205750 0.7055448
## 2  0.02616255 0.09835878 0.7902462
## 3 -0.64153735 0.89371692 0.4728617
## 4  0.06667191 0.12714401 0.6162035
## 5  0.13437661 0.11219640 0.2700143

mr_scatter_plot(d_mr,d)

## $`ieu-b-4760.ukb-b-13246`

## 
## attr(,"split_type")
## [1] "data.frame"
## attr(,"split_labels")
##   id.exposure  id.outcome
## 1  ieu-b-4760 ukb-b-13246

Ease of skin tanning

d <- make_dat("ukb-b-533", "ieu-b-4760")

## Extracting data for 135 SNP(s) from 1 GWAS(s)

## Finding proxies for 10 SNPs in outcome ieu-b-4760

## Extracting data for 10 SNP(s) from 1 GWAS(s)

## Harmonising Ease of skin tanning || id:ukb-b-533 (ukb-b-533) and Number of children || id:ieu-b-4760 (ieu-b-4760)

d_mr<-mr(d)

## Analysing 'ukb-b-533' on 'ieu-b-4760'

d_mr

##   id.exposure id.outcome                             outcome
## 1   ukb-b-533 ieu-b-4760 Number of children || id:ieu-b-4760
## 2   ukb-b-533 ieu-b-4760 Number of children || id:ieu-b-4760
## 3   ukb-b-533 ieu-b-4760 Number of children || id:ieu-b-4760
## 4   ukb-b-533 ieu-b-4760 Number of children || id:ieu-b-4760
## 5   ukb-b-533 ieu-b-4760 Number of children || id:ieu-b-4760
##                               exposure                    method nsnp
## 1 Ease of skin tanning || id:ukb-b-533                  MR Egger  131
## 2 Ease of skin tanning || id:ukb-b-533           Weighted median  131
## 3 Ease of skin tanning || id:ukb-b-533 Inverse variance weighted  131
## 4 Ease of skin tanning || id:ukb-b-533               Simple mode  131
## 5 Ease of skin tanning || id:ukb-b-533             Weighted mode  131
##              b          se         pval
## 1 -0.027049699 0.005918539 1.125400e-05
## 2 -0.027325717 0.006192725 1.021596e-05
## 3 -0.027092871 0.005010909 6.416881e-08
## 4 -0.001418702 0.014241474 9.208014e-01
## 5 -0.024976886 0.004539945 1.924410e-07

mr_scatter_plot(d_mr,d)

## $`ukb-b-533.ieu-b-4760`

## 
## attr(,"split_type")
## [1] "data.frame"
## attr(,"split_labels")
##   id.exposure id.outcome
## 1   ukb-b-533 ieu-b-4760

d <- make_dat("ieu-b-4760", "ukb-b-533")

## Extracting data for 9 SNP(s) from 1 GWAS(s)

## Finding proxies for 1 SNPs in outcome ukb-b-533

## Extracting data for 1 SNP(s) from 1 GWAS(s)

## Harmonising Number of children || id:ieu-b-4760 (ieu-b-4760) and Ease of skin tanning || id:ukb-b-533 (ukb-b-533)

d_mr<-mr(d)

## Analysing 'ieu-b-4760' on 'ukb-b-533'

d_mr

##   id.exposure id.outcome                              outcome
## 1  ieu-b-4760  ukb-b-533 Ease of skin tanning || id:ukb-b-533
## 2  ieu-b-4760  ukb-b-533 Ease of skin tanning || id:ukb-b-533
## 3  ieu-b-4760  ukb-b-533 Ease of skin tanning || id:ukb-b-533
## 4  ieu-b-4760  ukb-b-533 Ease of skin tanning || id:ukb-b-533
## 5  ieu-b-4760  ukb-b-533 Ease of skin tanning || id:ukb-b-533
##                              exposure                    method nsnp          b
## 1 Number of children || id:ieu-b-4760                  MR Egger    8 -2.0394672
## 2 Number of children || id:ieu-b-4760           Weighted median    8 -0.2978966
## 3 Number of children || id:ieu-b-4760 Inverse variance weighted    8 -1.9147557
## 4 Number of children || id:ieu-b-4760               Simple mode    8 -0.3554459
## 5 Number of children || id:ieu-b-4760             Weighted mode    8 -0.2809582
##            se        pval
## 1 11.40245180 0.863932769
## 2  0.09587407 0.001888909
## 3  1.82792909 0.294869049
## 4  0.12135842 0.022058985
## 5  0.10962316 0.037390609

mr_scatter_plot(d_mr,d)

## $`ieu-b-4760.ukb-b-533`

## 
## attr(,"split_type")
## [1] "data.frame"
## attr(,"split_labels")
##   id.exposure id.outcome
## 1  ieu-b-4760  ukb-b-533

Use of sun/uv protection

d <- make_dat("ukb-b-7422", "ieu-b-4760")

## Extracting data for 51 SNP(s) from 1 GWAS(s)

## Finding proxies for 5 SNPs in outcome ieu-b-4760

## Extracting data for 5 SNP(s) from 1 GWAS(s)

## Harmonising Use of sun/uv protection || id:ukb-b-7422 (ukb-b-7422) and Number of children || id:ieu-b-4760 (ieu-b-4760)

d_mr<-mr(d)

## Analysing 'ukb-b-7422' on 'ieu-b-4760'

d_mr

##   id.exposure id.outcome                             outcome
## 1  ukb-b-7422 ieu-b-4760 Number of children || id:ieu-b-4760
## 2  ukb-b-7422 ieu-b-4760 Number of children || id:ieu-b-4760
## 3  ukb-b-7422 ieu-b-4760 Number of children || id:ieu-b-4760
## 4  ukb-b-7422 ieu-b-4760 Number of children || id:ieu-b-4760
## 5  ukb-b-7422 ieu-b-4760 Number of children || id:ieu-b-4760
##                                    exposure                    method nsnp
## 1 Use of sun/uv protection || id:ukb-b-7422                  MR Egger   50
## 2 Use of sun/uv protection || id:ukb-b-7422           Weighted median   50
## 3 Use of sun/uv protection || id:ukb-b-7422 Inverse variance weighted   50
## 4 Use of sun/uv protection || id:ukb-b-7422               Simple mode   50
## 5 Use of sun/uv protection || id:ukb-b-7422             Weighted mode   50
##             b         se         pval
## 1 -0.14228535 0.03168300 4.452622e-05
## 2 -0.10807761 0.02373921 5.296076e-06
## 3 -0.07374565 0.02380585 1.949659e-03
## 4 -0.05620306 0.04616644 2.292823e-01
## 5 -0.12040433 0.02141205 8.859627e-07

mr_scatter_plot(d_mr,d)

## $`ukb-b-7422.ieu-b-4760`

## 
## attr(,"split_type")
## [1] "data.frame"
## attr(,"split_labels")
##   id.exposure id.outcome
## 1  ukb-b-7422 ieu-b-4760

d <- make_dat("ieu-b-4760", "ukb-b-7422")

## Extracting data for 9 SNP(s) from 1 GWAS(s)

## Finding proxies for 1 SNPs in outcome ukb-b-7422

## Extracting data for 1 SNP(s) from 1 GWAS(s)

## Harmonising Number of children || id:ieu-b-4760 (ieu-b-4760) and Use of sun/uv protection || id:ukb-b-7422 (ukb-b-7422)

d_mr<-mr(d)

## Analysing 'ieu-b-4760' on 'ukb-b-7422'

d_mr

##   id.exposure id.outcome                                   outcome
## 1  ieu-b-4760 ukb-b-7422 Use of sun/uv protection || id:ukb-b-7422
## 2  ieu-b-4760 ukb-b-7422 Use of sun/uv protection || id:ukb-b-7422
## 3  ieu-b-4760 ukb-b-7422 Use of sun/uv protection || id:ukb-b-7422
## 4  ieu-b-4760 ukb-b-7422 Use of sun/uv protection || id:ukb-b-7422
## 5  ieu-b-4760 ukb-b-7422 Use of sun/uv protection || id:ukb-b-7422
##                              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 -1.63035451 2.85943304 0.58926125
## 2 -0.09050563 0.08678466 0.29700578
## 3 -0.29963036 0.46775019 0.52179706
## 4 -0.12062567 0.11462747 0.32761350
## 5 -0.15976922 0.07796146 0.07960838

mr_scatter_plot(d_mr,d)

## $`ieu-b-4760.ukb-b-7422`

## 
## attr(,"split_type")
## [1] "data.frame"
## attr(,"split_labels")
##   id.exposure id.outcome
## 1  ieu-b-4760 ukb-b-7422

Skin colour

d <- make_dat("ukb-b-19560", "ieu-b-4760")

## Extracting data for 154 SNP(s) from 1 GWAS(s)

## Finding proxies for 15 SNPs in outcome ieu-b-4760

## Extracting data for 15 SNP(s) from 1 GWAS(s)

## Harmonising Skin colour || id:ukb-b-19560 (ukb-b-19560) and Number of children || id:ieu-b-4760 (ieu-b-4760)

d_mr<-mr(d)

## Analysing 'ukb-b-19560' on 'ieu-b-4760'

d_mr

##   id.exposure id.outcome                             outcome
## 1 ukb-b-19560 ieu-b-4760 Number of children || id:ieu-b-4760
## 2 ukb-b-19560 ieu-b-4760 Number of children || id:ieu-b-4760
## 3 ukb-b-19560 ieu-b-4760 Number of children || id:ieu-b-4760
## 4 ukb-b-19560 ieu-b-4760 Number of children || id:ieu-b-4760
## 5 ukb-b-19560 ieu-b-4760 Number of children || id:ieu-b-4760
##                        exposure                    method nsnp          b
## 1 Skin colour || id:ukb-b-19560                  MR Egger  148 0.02752613
## 2 Skin colour || id:ukb-b-19560           Weighted median  148 0.01754620
## 3 Skin colour || id:ukb-b-19560 Inverse variance weighted  148 0.03473666
## 4 Skin colour || id:ukb-b-19560               Simple mode  148 0.03617901
## 5 Skin colour || id:ukb-b-19560             Weighted mode  148 0.02401310
##            se         pval
## 1 0.009712907 5.248739e-03
## 2 0.011900150 1.403599e-01
## 3 0.008363769 3.278135e-05
## 4 0.026160351 1.687708e-01
## 5 0.007304050 1.263929e-03

mr_scatter_plot(d_mr,d)

## $`ukb-b-19560.ieu-b-4760`

## 
## attr(,"split_type")
## [1] "data.frame"
## attr(,"split_labels")
##   id.exposure id.outcome
## 1 ukb-b-19560 ieu-b-4760

d <- make_dat("ieu-b-4760", "ukb-b-19560")

## Extracting data for 9 SNP(s) from 1 GWAS(s)

## Finding proxies for 1 SNPs in outcome ukb-b-19560

## Extracting data for 1 SNP(s) from 1 GWAS(s)

## Harmonising Number of children || id:ieu-b-4760 (ieu-b-4760) and Skin colour || id:ukb-b-19560 (ukb-b-19560)

d_mr<-mr(d)

## Analysing 'ieu-b-4760' on 'ukb-b-19560'

d_mr

##   id.exposure  id.outcome                       outcome
## 1  ieu-b-4760 ukb-b-19560 Skin colour || id:ukb-b-19560
## 2  ieu-b-4760 ukb-b-19560 Skin colour || id:ukb-b-19560
## 3  ieu-b-4760 ukb-b-19560 Skin colour || id:ukb-b-19560
## 4  ieu-b-4760 ukb-b-19560 Skin colour || id:ukb-b-19560
## 5  ieu-b-4760 ukb-b-19560 Skin colour || id:ukb-b-19560
##                              exposure                    method nsnp         b
## 1 Number of children || id:ieu-b-4760                  MR Egger    8 1.0198615
## 2 Number of children || id:ieu-b-4760           Weighted median    8 0.1370346
## 3 Number of children || id:ieu-b-4760 Inverse variance weighted    8 1.0146129
## 4 Number of children || id:ieu-b-4760               Simple mode    8 0.1757603
## 5 Number of children || id:ieu-b-4760             Weighted mode    8 0.1354648
##           se       pval
## 1 5.89231723 0.86827732
## 2 0.06013320 0.02267593
## 3 0.94556468 0.28326068
## 4 0.08841143 0.08715021
## 5 0.06123652 0.06259761

mr_scatter_plot(d_mr,d)

## $`ieu-b-4760.ukb-b-19560`

## 
## attr(,"split_type")
## [1] "data.frame"
## attr(,"split_labels")
##   id.exposure  id.outcome
## 1  ieu-b-4760 ukb-b-19560

Facial ageing

younger then you are - same - older

d <- make_dat("ukb-b-2148", "ieu-b-4760")

## Extracting data for 79 SNP(s) from 1 GWAS(s)

## Finding proxies for 5 SNPs in outcome ieu-b-4760

## Extracting data for 5 SNP(s) from 1 GWAS(s)

## Harmonising Facial ageing || id:ukb-b-2148 (ukb-b-2148) and Number of children || id:ieu-b-4760 (ieu-b-4760)

## Removing the following SNPs for incompatible alleles:
## rs7089911

d_mr<-mr(d)

## Analysing 'ukb-b-2148' on 'ieu-b-4760'

d_mr

##   id.exposure id.outcome                             outcome
## 1  ukb-b-2148 ieu-b-4760 Number of children || id:ieu-b-4760
## 2  ukb-b-2148 ieu-b-4760 Number of children || id:ieu-b-4760
## 3  ukb-b-2148 ieu-b-4760 Number of children || id:ieu-b-4760
## 4  ukb-b-2148 ieu-b-4760 Number of children || id:ieu-b-4760
## 5  ukb-b-2148 ieu-b-4760 Number of children || id:ieu-b-4760
##                         exposure                    method nsnp          b
## 1 Facial ageing || id:ukb-b-2148                  MR Egger   78 -0.2812919
## 2 Facial ageing || id:ukb-b-2148           Weighted median   78 -0.2275974
## 3 Facial ageing || id:ukb-b-2148 Inverse variance weighted   78 -0.1351042
## 4 Facial ageing || id:ukb-b-2148               Simple mode   78 -0.1462567
## 5 Facial ageing || id:ukb-b-2148             Weighted mode   78 -0.2306976
##           se         pval
## 1 0.06541842 5.014830e-05
## 2 0.04241333 8.042408e-08
## 3 0.03554099 1.439027e-04
## 4 0.10012848 1.481690e-01
## 5 0.03931525 1.048946e-07

mr_scatter_plot(d_mr,d)

## $`ukb-b-2148.ieu-b-4760`

## 
## attr(,"split_type")
## [1] "data.frame"
## attr(,"split_labels")
##   id.exposure id.outcome
## 1  ukb-b-2148 ieu-b-4760

d <- make_dat("ieu-b-4760", "ukb-b-2148")

## Extracting data for 9 SNP(s) from 1 GWAS(s)

## Finding proxies for 1 SNPs in outcome ukb-b-2148

## Extracting data for 1 SNP(s) from 1 GWAS(s)

## Harmonising Number of children || id:ieu-b-4760 (ieu-b-4760) and Facial ageing || id:ukb-b-2148 (ukb-b-2148)

d_mr<-mr(d)

## Analysing 'ieu-b-4760' on 'ukb-b-2148'

d_mr

##   id.exposure id.outcome                        outcome
## 1  ieu-b-4760 ukb-b-2148 Facial ageing || id:ukb-b-2148
## 2  ieu-b-4760 ukb-b-2148 Facial ageing || id:ukb-b-2148
## 3  ieu-b-4760 ukb-b-2148 Facial ageing || id:ukb-b-2148
## 4  ieu-b-4760 ukb-b-2148 Facial ageing || id:ukb-b-2148
## 5  ieu-b-4760 ukb-b-2148 Facial ageing || id:ukb-b-2148
##                              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  0.06088218 0.49021501 0.9052173
## 2  0.01738616 0.03914244 0.6569149
## 3 -0.08933583 0.07939424 0.2604966
## 4  0.01359156 0.05385145 0.8079903
## 5  0.02070383 0.04415797 0.6534221

mr_scatter_plot(d_mr,d)

## $`ieu-b-4760.ukb-b-2148`

## 
## attr(,"split_type")
## [1] "data.frame"
## attr(,"split_labels")
##   id.exposure id.outcome
## 1  ieu-b-4760 ukb-b-2148

Hair/balding pattern 1

Pattern 1 - full head of hair

d <- make_dat("ukb-d-2395_1", "ieu-b-4760")

## Extracting data for 202 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 Hair/balding pattern: Pattern 1 || id:ukb-d-2395_1 (ukb-d-2395_1) and Number of children || id:ieu-b-4760 (ieu-b-4760)

d_mr<-mr(d)

## Analysing 'ukb-d-2395_1' on 'ieu-b-4760'

d_mr

##    id.exposure id.outcome                             outcome
## 1 ukb-d-2395_1 ieu-b-4760 Number of children || id:ieu-b-4760
## 2 ukb-d-2395_1 ieu-b-4760 Number of children || id:ieu-b-4760
## 3 ukb-d-2395_1 ieu-b-4760 Number of children || id:ieu-b-4760
## 4 ukb-d-2395_1 ieu-b-4760 Number of children || id:ieu-b-4760
## 5 ukb-d-2395_1 ieu-b-4760 Number of children || id:ieu-b-4760
##                                             exposure                    method
## 1 Hair/balding pattern: Pattern 1 || id:ukb-d-2395_1                  MR Egger
## 2 Hair/balding pattern: Pattern 1 || id:ukb-d-2395_1           Weighted median
## 3 Hair/balding pattern: Pattern 1 || id:ukb-d-2395_1 Inverse variance weighted
## 4 Hair/balding pattern: Pattern 1 || id:ukb-d-2395_1               Simple mode
## 5 Hair/balding pattern: Pattern 1 || id:ukb-d-2395_1             Weighted mode
##   nsnp          b         se         pval
## 1  181 0.08882160 0.02853647 2.159494e-03
## 2  181 0.08082450 0.01777314 5.427024e-06
## 3  181 0.06661912 0.01274028 1.704143e-07
## 4  181 0.06827399 0.04563497 1.363817e-01
## 5  181 0.09464334 0.03092130 2.545628e-03

mr_scatter_plot(d_mr,d)

## $`ukb-d-2395_1.ieu-b-4760`

## 
## attr(,"split_type")
## [1] "data.frame"
## attr(,"split_labels")
##    id.exposure id.outcome
## 1 ukb-d-2395_1 ieu-b-4760

d <- make_dat("ieu-b-4760", "ukb-d-2395_1")

## Extracting data for 9 SNP(s) from 1 GWAS(s)

## Finding proxies for 1 SNPs in outcome ukb-d-2395_1

## Extracting data for 1 SNP(s) from 1 GWAS(s)

## Harmonising Number of children || id:ieu-b-4760 (ieu-b-4760) and Hair/balding pattern: Pattern 1 || id:ukb-d-2395_1 (ukb-d-2395_1)

d_mr<-mr(d)

## Analysing 'ieu-b-4760' on 'ukb-d-2395_1'

d_mr

##   id.exposure   id.outcome                                            outcome
## 1  ieu-b-4760 ukb-d-2395_1 Hair/balding pattern: Pattern 1 || id:ukb-d-2395_1
## 2  ieu-b-4760 ukb-d-2395_1 Hair/balding pattern: Pattern 1 || id:ukb-d-2395_1
## 3  ieu-b-4760 ukb-d-2395_1 Hair/balding pattern: Pattern 1 || id:ukb-d-2395_1
## 4  ieu-b-4760 ukb-d-2395_1 Hair/balding pattern: Pattern 1 || id:ukb-d-2395_1
## 5  ieu-b-4760 ukb-d-2395_1 Hair/balding pattern: Pattern 1 || id:ukb-d-2395_1
##                              exposure                    method nsnp          b
## 1 Number of children || id:ieu-b-4760                  MR Egger    8 0.03641879
## 2 Number of children || id:ieu-b-4760           Weighted median    8 0.15901950
## 3 Number of children || id:ieu-b-4760 Inverse variance weighted    8 0.39162906
## 4 Number of children || id:ieu-b-4760               Simple mode    8 0.14214492
## 5 Number of children || id:ieu-b-4760             Weighted mode    8 0.14214492
##           se       pval
## 1 1.61840117 0.98277647
## 2 0.07161054 0.02637699
## 3 0.26101350 0.13350645
## 4 0.07663484 0.10601231
## 5 0.06616157 0.06877070

mr_scatter_plot(d_mr,d)

## $`ieu-b-4760.ukb-d-2395_1`

## 
## attr(,"split_type")
## [1] "data.frame"
## attr(,"split_labels")
##   id.exposure   id.outcome
## 1  ieu-b-4760 ukb-d-2395_1

Hair/balding pattern 3

Pattern 3 - bald spot

d <- make_dat("ukb-a-302", "ieu-b-4760")

## Extracting data for 43 SNP(s) from 1 GWAS(s)

## Finding proxies for 4 SNPs in outcome ieu-b-4760

## Extracting data for 4 SNP(s) from 1 GWAS(s)

## Harmonising Hair/balding pattern: Pattern 3 || id:ukb-a-302 (ukb-a-302) and Number of children || id:ieu-b-4760 (ieu-b-4760)

d_mr<-mr(d)

## Analysing 'ukb-a-302' on 'ieu-b-4760'

d_mr

##   id.exposure id.outcome                             outcome
## 1   ukb-a-302 ieu-b-4760 Number of children || id:ieu-b-4760
## 2   ukb-a-302 ieu-b-4760 Number of children || id:ieu-b-4760
## 3   ukb-a-302 ieu-b-4760 Number of children || id:ieu-b-4760
## 4   ukb-a-302 ieu-b-4760 Number of children || id:ieu-b-4760
## 5   ukb-a-302 ieu-b-4760 Number of children || id:ieu-b-4760
##                                          exposure                    method
## 1 Hair/balding pattern: Pattern 3 || id:ukb-a-302                  MR Egger
## 2 Hair/balding pattern: Pattern 3 || id:ukb-a-302           Weighted median
## 3 Hair/balding pattern: Pattern 3 || id:ukb-a-302 Inverse variance weighted
## 4 Hair/balding pattern: Pattern 3 || id:ukb-a-302               Simple mode
## 5 Hair/balding pattern: Pattern 3 || id:ukb-a-302             Weighted mode
##   nsnp          b         se         pval
## 1   41 -0.2131590 0.10162702 0.0424840750
## 2   41 -0.1474867 0.03906515 0.0001597486
## 3   41 -0.1063871 0.03860814 0.0058591540
## 4   41 -0.1394994 0.09315058 0.1420957214
## 5   41 -0.1356496 0.04959618 0.0092507053

mr_scatter_plot(d_mr,d)

## $`ukb-a-302.ieu-b-4760`

## 
## attr(,"split_type")
## [1] "data.frame"
## attr(,"split_labels")
##   id.exposure id.outcome
## 1   ukb-a-302 ieu-b-4760

d <- make_dat("ieu-b-4760", "ukb-a-302")

## Extracting data for 9 SNP(s) from 1 GWAS(s)

## Finding proxies for 1 SNPs in outcome ukb-a-302

## Extracting data for 1 SNP(s) from 1 GWAS(s)

## Harmonising Number of children || id:ieu-b-4760 (ieu-b-4760) and Hair/balding pattern: Pattern 3 || id:ukb-a-302 (ukb-a-302)

d_mr<-mr(d)

## Analysing 'ieu-b-4760' on 'ukb-a-302'

d_mr

##   id.exposure id.outcome                                         outcome
## 1  ieu-b-4760  ukb-a-302 Hair/balding pattern: Pattern 3 || id:ukb-a-302
## 2  ieu-b-4760  ukb-a-302 Hair/balding pattern: Pattern 3 || id:ukb-a-302
## 3  ieu-b-4760  ukb-a-302 Hair/balding pattern: Pattern 3 || id:ukb-a-302
## 4  ieu-b-4760  ukb-a-302 Hair/balding pattern: Pattern 3 || id:ukb-a-302
## 5  ieu-b-4760  ukb-a-302 Hair/balding pattern: Pattern 3 || id:ukb-a-302
##                              exposure                    method nsnp          b
## 1 Number of children || id:ieu-b-4760                  MR Egger    8  0.3158449
## 2 Number of children || id:ieu-b-4760           Weighted median    8 -0.1707081
## 3 Number of children || id:ieu-b-4760 Inverse variance weighted    8 -0.2137883
## 4 Number of children || id:ieu-b-4760               Simple mode    8 -0.2074340
## 5 Number of children || id:ieu-b-4760             Weighted mode    8 -0.1875713
##           se        pval
## 1 0.80072675 0.706889153
## 2 0.06047765 0.004762646
## 3 0.13331124 0.108784986
## 4 0.08503273 0.044794390
## 5 0.07094433 0.033233613

mr_scatter_plot(d_mr,d)

## $`ieu-b-4760.ukb-a-302`

## 
## attr(,"split_type")
## [1] "data.frame"
## attr(,"split_labels")
##   id.exposure id.outcome
## 1  ieu-b-4760  ukb-a-302

Hair/balding pattern 4

Pattern 4 - totally bald

d <- make_dat("ukb-a-303", "ieu-b-4760")

## Extracting data for 153 SNP(s) from 1 GWAS(s)

## Finding proxies for 11 SNPs in outcome ieu-b-4760

## Extracting data for 11 SNP(s) from 1 GWAS(s)

## Harmonising Hair/balding pattern: Pattern 4 || id:ukb-a-303 (ukb-a-303) and Number of children || id:ieu-b-4760 (ieu-b-4760)

d_mr<-mr(d)

## Analysing 'ukb-a-303' on 'ieu-b-4760'

d_mr

##   id.exposure id.outcome                             outcome
## 1   ukb-a-303 ieu-b-4760 Number of children || id:ieu-b-4760
## 2   ukb-a-303 ieu-b-4760 Number of children || id:ieu-b-4760
## 3   ukb-a-303 ieu-b-4760 Number of children || id:ieu-b-4760
## 4   ukb-a-303 ieu-b-4760 Number of children || id:ieu-b-4760
## 5   ukb-a-303 ieu-b-4760 Number of children || id:ieu-b-4760
##                                          exposure                    method
## 1 Hair/balding pattern: Pattern 4 || id:ukb-a-303                  MR Egger
## 2 Hair/balding pattern: Pattern 4 || id:ukb-a-303           Weighted median
## 3 Hair/balding pattern: Pattern 4 || id:ukb-a-303 Inverse variance weighted
## 4 Hair/balding pattern: Pattern 4 || id:ukb-a-303               Simple mode
## 5 Hair/balding pattern: Pattern 4 || id:ukb-a-303             Weighted mode
##   nsnp           b         se         pval
## 1  148 -0.11303068 0.03702856 2.696937e-03
## 2  148 -0.10162328 0.02122566 1.686566e-06
## 3  148 -0.08182822 0.01592134 2.754236e-07
## 4  148 -0.10689175 0.06594179 1.071603e-01
## 5  148 -0.14740906 0.04898982 3.085243e-03

mr_scatter_plot(d_mr,d)

## $`ukb-a-303.ieu-b-4760`

## 
## attr(,"split_type")
## [1] "data.frame"
## attr(,"split_labels")
##   id.exposure id.outcome
## 1   ukb-a-303 ieu-b-4760

d <- make_dat("ieu-b-4760", "ukb-a-303")

## Extracting data for 9 SNP(s) from 1 GWAS(s)

## Finding proxies for 1 SNPs in outcome ukb-a-303

## Extracting data for 1 SNP(s) from 1 GWAS(s)

## Harmonising Number of children || id:ieu-b-4760 (ieu-b-4760) and Hair/balding pattern: Pattern 4 || id:ukb-a-303 (ukb-a-303)

d_mr<-mr(d)

## Analysing 'ieu-b-4760' on 'ukb-a-303'

d_mr

##   id.exposure id.outcome                                         outcome
## 1  ieu-b-4760  ukb-a-303 Hair/balding pattern: Pattern 4 || id:ukb-a-303
## 2  ieu-b-4760  ukb-a-303 Hair/balding pattern: Pattern 4 || id:ukb-a-303
## 3  ieu-b-4760  ukb-a-303 Hair/balding pattern: Pattern 4 || id:ukb-a-303
## 4  ieu-b-4760  ukb-a-303 Hair/balding pattern: Pattern 4 || id:ukb-a-303
## 5  ieu-b-4760  ukb-a-303 Hair/balding pattern: Pattern 4 || id:ukb-a-303
##                              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  0.08373771 1.28410474 0.95012449
## 2 -0.15594735 0.06079853 0.01031801
## 3 -0.29877554 0.20773355 0.15035937
## 4 -0.29824533 0.10252548 0.02269327
## 5 -0.17329427 0.08487987 0.08051758

mr_scatter_plot(d_mr,d)

## $`ieu-b-4760.ukb-a-303`

## 
## attr(,"split_type")
## [1] "data.frame"
## attr(,"split_labels")
##   id.exposure id.outcome
## 1  ieu-b-4760  ukb-a-303

Having a full head of hair has a positive effect on number of children, the opposite for other hair patterns.