How to smooth a signal?
When using a moving average filter, or rectangular convolution in the time domain, the time domain smoothing and so-called spectral leakage are nearly opposing effects.  The smoothing is due to removing high frequency content, and the leakage is the name given for portions of this frequency content that end up not being removed.  Since sharp peaks and transients can be partially composed of high frequency content, smoothing by this kind of convolution can diminish them.

Time-domain convolution windows other than rectangular may remove less of the very nearby frequencies, but better remove more of the far away frequency content (relative to some transition frequency, which is related approximately to the window width).

An adaptive polynomial regression will remove different spectral characteristics from a signal at different points in time, which could either expose or hide "important" elements of the signal, depending on the signal, and what you are looking for.