Uniform Lp bound implies finite Lp norm with random index? Suppose that $\{X_N:N\in\mathbb N\}$ is a sequence of random variables uniformly bounded in $L^p$ norm for all $p>1$:
$$\sup_N\|X_N\|_{L^p}<C(p).$$
Let $\mathcal N$ be some random variable taking values in $\mathbb N$ that is independent of the sequence $\{X_N\}$,
and define $X_{\mathcal N}$ as the random variable
$$\omega\to X_{\mathcal N(\omega)}(\omega).$$
Is it then possible to prove that
$\|X_{\mathcal N}\|_{L^{p}}<\infty$?
It is easy to see that
$$\|X_{\mathcal N}\|_{L^{p}}=\left\|\sum_{N}X_N\cdot1_{\{N=\mathcal N\}}\right\|_{L^{p}},$$
and thus we get the result by Minkowski's and Hölder's inequalities
if
$$\sum_N\|1_{\{N=\mathcal N\}}\|_{L^{2p}}<\infty.$$
However,
it is possible to prove this with weaker (or ideally no) conditions on the distribution of $\mathcal N$?

My guess is that no this isn't true without an assumption on $\mathcal{N}$. Constructing an explicit counterexample may require more time than I have right now, but more or less the only thing you have for free is that 
$\sum_{n=1}^{\infty} \mathbb{P}(\mathcal{N} = n) = 1$.
However this series could go so slowly that $\sum_{n=1}^{\infty} \mathbb{P}(\mathcal{N} = n)^{\alpha} = \infty$ for every $\alpha < 1$. Which seems to rule out any Holder inequality-type bound working (unless you have a uniform $L^{\infty}$ bound on $|X_n|$). 
And if an easy Holder argument doesn't work then my guess is there is a genuine counterexample that exploits this. The tricky thing in constructing one is the independence. Admittedly this is on your side, but I don't think Holder can be effectively improved, even when the RVs are independent. I think that basically you can still come very close to being equality which is bad in this case.
