What Are the Consequences of Using Least Squares When Heteroskedasticity

What are the consequences of using least squares when heteroskedasticity is present?

A) no consequences,coefficient estimates are still unbiased
B) confidence intervals and hypothesis testing are inaccurate due to inflated standard errors
C) all coefficient estimates are biased for variables correlated with the error term
D) it requires very large sample sizes to get efficient estimates