Mapping quantitative trait loci (QTLs) for molecular traits from chromatin to metabolites (i.e., xQTLs) provides insight into the locations and effect modes of genetic variants that influence these molecular phenotypes and the propagation of functional consequences of each variant. xQTL studies indirectly interrogate the functional landscape of the molecular basis of complex diseases, including the impact of non‐coding regulatory variants, the tissue specificity of regulatory elements, and their contribution to disease by integrating with genome‐wide association studies (GWAS). We summarize a variety of molecular xQTL studies in human tissues and cells. In addition, using the Alzheimer's Disease Sequencing Project (ADSP) as an example, we describe the ADSP xQTL project, a collaborative effort across the ADSP Functional Genomics Consortium (ADSP‐FGC). The project's ultimate goal is a reference map of Alzheimer's‐related QTLs using existing datasets from multiple omics layers to help us study the consequences of genetic variants identified in the ADSP. xQTL studies enable the identification of the causal genes and pathways in GWAS loci, which will likely aid in the discovery of novel biomarkers and therapeutic targets for complex diseases. © 2022 Wiley Periodicals LLC.

BackgroundAlzheimer’s disease (AD) is characterized by cognitive deterioration and extracellular amyloid beta deposits and neurofibrillary tangles in the brain. These may occur in tandem with markers of Lewy body (LB) and vascular dementia (VaD). Studying bulk and single‐cell expression profiles for these disorders may identify factors shared between and unique to AD and other dementias.MethodBulk RNA‐sequencing was performed using 210 human postmortem hippocampal region samples obtained from brains donated to the BU Alzheimer Disease Research Center. After quality checks (QC), 191 samples classified as AD+LB (n=43), AD+VaD (n=54), AD alone (n=73), and controls (n=17) were included in the study. Analysis of expression differences between each of these AD groups and controls was performed using limma software with models including covariates for age, sex, RNA quality, plate, and two surrogate variables to adjust for unknown variation. Weighted gene co‐expression network analysis (WGCNA) was used to identify clusters of co‐expressed genes. Additionally, high quality single‐nuclei RNA sequencing data (snRNA‐seq) was obtained from 8 of the 210 hippocampal samples with an average of 6000 cells detected per sample and 1800 genes per cell after QC. This snRNA‐seq data was integrated with the bulk data using Scissor to identify cell populations positively and negatively associated with AD.Result481 genes were differentially expressed between AD cases and controls. Upregulated genes in AD subjects were enriched for cilia function and morphological development and downregulated genes in AD subjects were enriched for mitochondrial energy production. A WGCNA module strongly associated with ciliary function was found to be overrepresented in AD (and especially AD+VaD) samples compared to controls. Multiple brain cell types were detected from our snRNA‐seq data. Of these, a subpopulation of ependymal cells related to the ciliary WGCNA module was positively associated with AD status.ConclusionOur results suggest that different sets of co‐expressed genes in hippocampus distinguish AD brains with and without pathological hallmarks related to other forms of dementia, and brains without AD pathology. This study also provides preliminary evidence for the involvement of ependymal cell populations in AD