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The initiation and progression of autoimmune disorders such as multiple sclerosis (MS) is linked to aberrant cholesterol metabolism and overt inflammation. Liver X receptors (LXR) are nuclear receptors that function at the crossroads of cholesterol metabolism and immunity, and their activation is considered a promising therapeutic strategy to attenuate autoimmunity. However, despite clear functional heterogeneity and cell-specific expression profiles, the impact of the individual LXR isoforms on autoimmunity remains poorly understood. Here, we show that LXR alpha and LXR beta have an opposite impact on immune cell function and disease severity in the experimental autoimmune encephalomyelitis model, an experimental MS model. While Lxr alpha deficiency aggravated disease pathology and severity, absence of Lxr beta was protective. Guided by flow cytometry and by using cell-specific knockout models, reduced disease severity in Lxr beta-deficient mice was primarily attributed to changes in peripheral T cell physiology and occurred independent from alterations in microglia function. Collectively, our findings indicate that LXR isoforms play functionally non-redundant roles in autoimmunity, potentially having broad implications for the development of LXR-based therapeutic strategies aimed at dampening autoimmunity and neuroinflammation.

Genome-wide association studies (GWAs) have identifed thousands of loci associated with complex traits, but it is challenging to pinpoint causal genes in these loci and to exploit subtle association signals. We used tissue-specifc quantitative interaction proteomics to map a network of fve genes involved in the mendelian disorder long Qt syndrome (lQts). We integrated the lQts network with GWAs loci from the corresponding common complex trait, Qt-interval variation, to identify candidate genes that were subsequently confrmed in Xenopus laevis oocytes and zebrafsh. We used the lQts protein network to flter weak GWAs signals by identifying single-nucleotide polymorphisms (snPs) in proximity to genes in the network supported by strong proteomic evidence. three snPs passing this flter reached genome-wide signifcance after replication genotyping. overall, we present a general strategy to propose candidates in GWAs loci for functional studies and to systematically flter subtle association signals using tissue-specifc quantitative interaction proteomics.

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