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The integration of proteomic, transcriptomic, and genetic variant annotation data will improve our understanding of genotype–phenotype associations. Due, in part, to challenges associated with accurate inter‐database mapping, such multi‐omic studies have not extended to chemoproteomics, a method that measures the intrinsic reactivity and potential “druggability” of nucleophilic amino acid side chains. Here, we evaluated mapping approaches to match chemoproteomic‐detected cysteine and lysine residues with their genetic coordinates. Our analysis revealed that database update cycles and reliance on stable identifiers can lead to pervasive misidentification of labeled residues. Enabled by this examination of mapping strategies, we then integrated our chemoproteomics data with computational methods for predicting genetic variant pathogenicity, which revealed that codons of highly reactive cysteines are enriched for genetic variants that are predicted to be more deleterious and allowed us to identify and functionally characterize a new damaging residue in the cysteine protease caspase‐8. Our study provides a roadmap for more precise inter‐database mapping and points to untapped opportunities to improve the predictive power of pathogenicity scores and to advance prioritization of putative druggable sites., Multi‐omic data integration maps Chemoproteomic Detected (CpD) amino acids to genomic‐level predictions of variant pathogenicity. Highly reactive cysteine and lysine residues are enriched for high pathogenicity (CADD) scores and disease‐causing pathogenic variants.

Background Sex differences in obesity and related diseases are well established. Gonadal hormones are a major determinant of these sex differences. However, sex differences in body size and composition are evident prior to exposure to gonadal hormones, providing evidence for gonadal-independent contributions attributable to the XX or XY sex chromosome complement. Large-scale genetic studies have revealed male/female differences in the genetic architecture of adipose tissue amount and anatomical distribution. However, these studies have typically neglected the X and Y chromosomes. Scope of the review Here we discuss how the sex chromosome complement may influence obesity, lipid levels, and inflammation. Human sex chromosome anomalies such as Klinefelter syndrome (XXY), as well as mouse models with engineered alterations in sex chromosome complement, support an important role for sex chromosomes in obesity and metabolism. In particular, the Four Core Genotypes mouse model—consisting of XX mice with either ovaries or testes, and XY mice with either ovaries or testes—has revealed an effect of X chromosome dosage on adiposity, hyperlipidemia, and inflammation irrespective of male or female gonads. Mechanisms may include enhanced expression of genes that escape X chromosome inactivation. Major conclusions Although less well studied than effects of gonadal hormones, sex chromosomes exert independent and interactive effects on adiposity, lipid metabolism, and inflammation. In particular, the presence of two X chromosomes has been associated with increased adiposity and dyslipidemia in mouse models and in XXY men. The enhanced expression of genes that escape X chromosome inactivation may contribute, but more work is required., Highlights • Sex differences are influenced by both gonadal type and sex chromosome complement. • Males and females differ in adipose tissue distribution and expansion. • X chromosome dosage may be one factor underlying sex differences in adiposity. • X inactivation escapee genes are expressed at higher levels in XX vs. XY cells.