Combining samples across ancestries has an advantage for fine-mapping: the LD patterns that differ across populations can improve the resolution, assuming that many causal variants are shared across populations, which has been shown true for some traits, including schizophrenia (Lam et al., 2018; Marigorta and Navarro, 2013; Wojcik et al., 2019). Non-causal variants tagging the causal variants have marginal different effects across populations if LD is different, thus allowing the causal variant to be distinguished from non-causal variants. Furthermore, in certain populations (e.g., African), LD blocks are generally smaller, so fewer non-causal variants will tag the causal variants, improving the resolution of fine-mapping (International HapMap Consortium, 2005; Schaid et al., 2018).
