Integrating a multiple regression equation (including covariates) into ggplot2 graph

Question

I am currently generating simple linear regression plots in ggplot2 with the following code (toy example)

library(ggplot2)

Data<-data.frame(Age=c(40,41,42,43,44,45,46,47,48,49),
                 Height=c(185,184,183,182,181,186,187,188,189,190),
                 Sex=c("Male","Male","Male","Male","Male","Female","Female","Female","Female","Female"),
                 Weight=c(84,83,82,81,80,85,86,87,88,89),
                 BMI=c(20,21,22,23,24,25,26,27,28,29))

points<-c("#FF9999","turquoise")
lines<-c("dark red","blue")
linetypes<-c(1,1)

x<-ggplot(Data,aes(x=Age,y=Weight))+
  geom_point(aes(fill=factor(Sex)),size=4,alpha=1,shape=21,color="transparent")+
  geom_smooth(aes(color=Sex,linetype=Sex),method="lm",formula=y~x,lwd=1,se=F)+
  scale_fill_manual(values=points,labels=c("Female","Male"))+
  scale_colour_manual(values=lines)+
  scale_linetype_manual(values=linetypes)+
  theme_classic(base_size=15)+
  theme(legend.position="top",legend.direction="horizontal")+
  labs(fill="Points",colour="Lines",x='Age',y='Weight')+
  guides(fill=guide_legend(override.aes=list(shape=c(16,16),alpha=1,size=4,color=c("#FF9999","turquoise"))))+
  guides(colour=guide_legend(override.aes=list(linetype=c(1,1),alpha=1,size=1,color=c("dark red","blue"))))+
  guides(linetype="none")
x

I am stuck as how to add one-or-more covariates, in order to transform the plots from simple to multiple linear regression, e.g., from Weight~Age to Weight~Age+Height+BMI

I am sure that it must have something to do with the method="lm" and formula=y~x commands, but I am not clear on exactly what changes need to be made.

Any help would be very much appreciated. Thank you.