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Genome-wide association studies (GWAS) have identified loci for kidney disease, but the causal variants, genes, and pathways remain unknown. Here we identify two kidney disease genes Dipeptidase 1 ( DPEP1 ) and Charged Multivesicular Body Protein 1 A ( CHMP1A ) via the triangulation of kidney function GWAS, human kidney expression, and methylation quantitative trait loci. Using single-cell chromatin accessibility and genome editing, we fine map the region that controls the expression of both genes. Mouse genetic models demonstrate the causal roles of both genes in kidney disease. Cellular studies indicate that both Dpep1 and Chmp1a are important regulators of a single pathway, ferroptosis and lead to kidney disease development via altering cellular iron trafficking. Identifying causal variants and genes is an essential step in interpreting GWAS loci. Here, the authors investigate a kidney disease GWAS locus with functional genomics data, CRISPR editing and mouse experiments to identify DPEP1 and CHMP1A as putative kidney disease genes via ferroptosis.

The functional interpretation of genome-wide association studies (GWAS) is challenging due to the cell-type-dependent influences of genetic variants. Here, we generated comprehensive maps of expression quantitative trait loci (eQTLs) for 659 microdissected human kidney samples and identified cell-type-eQTLs by mapping interactions between cell type abundances and genotypes. By partitioning heritability using stratified linkage disequilibrium score regression to integrate GWAS with single-cell RNA sequencing and single-nucleus assay for transposase-accessible chromatin with high-throughput sequencing data, we prioritized proximal tubules for kidney function and endothelial cells and distal tubule segments for blood pressure pathogenesis. Bayesian colocalization analysis nominated more than 200 genes for kidney function and hypertension. Our study clarifies the mechanism of commonly used antihypertensive and renal-protective drugs and identifies drug repurposing opportunities for kidney disease. Cell-type-specific eQTL maps in the human kidney generated from the analysis of over 600 microdissected kidney samples, together with single-cell RNA sequencing and single-nucleus ATAC-seq, prioritize cell types influencing kidney function, hypertension and other traits.

Keloids are raised scars that grow beyond original wound boundaries, resulting in pain and disfigurement. Reasons for keloid development are not well-understood, and current treatment options are limited. Keloids are more likely to occur in darker-skinned individuals of African and Asian descent than in Europeans. We performed a genome-wide association study (GWAS) examining keloid risk across and within continental ancestry groups, incorporating 7837 cases and 1,593,009 controls. We detected 26 loci in the multi-ancestry analysis, 12 of which replicated in an independent dataset. Heritability estimates were 6%, 21%, and 34% for the European, East Asian, and African ancestry analyses, respectively. Genetically predicted gene expression and colocalization analyses identified 27 gene-tissue pairs, nine in skin and fibroblasts. Pathway analyses implicated integrin signaling and upstream regulators involved in cancer, fibrosis, and sex hormone signaling. This investigation nearly quintuples the number of keloid-associated risk loci, illuminating biological processes in keloid pathology. Keloids are fibroproliferative scars with higher prevalence in individuals of African and Asian ancestry. Here, the authors perform a multi-ancestry GWAS identifying 26 loci and pathways linked to fibrosis, integrin signalling, and hormone regulation.

Uterine leiomyomata or fibroids are highly heritable, common, and benign tumors of the uterus with poorly understood etiology. Previous GWAS have reported 72 associated genes but included limited numbers of non-European individuals. Here, we identify 11 novel genes associated with fibroids across multi-ancestry and ancestry-stratified GWAS analyses. We replicate a known fibroid GWAS gene in African ancestry individuals and estimate the SNP-based heritability of fibroids in African ancestry populations as 15.9%. Using genetically predicted gene expression and colocalization analyses, we identify 46 novel genes associated with fibroids. These genes are significantly enriched in cancer, cell death and survival, reproductive system disease, and cellular growth and proliferation networks. We also find that increased predicted expression of HEATR3 in uterine tissue is associated with fibroids across ancestry strata. Overall, we report genetic variants associated with fibroids coupled with functional and gene pathway enrichment analyses. Here, the authors present multi-ancestry genome-wide meta-analyses of uterine fibroids, identifying 11 new gene associations, and demonstrating that heritability is higher in African ancestries.

Fibroproliferative diseases are common complex traits featuring scarring and overgrowth of connective tissue which vary widely in presentation because they affect many organ systems. Most fibroproliferative diseases are more prevalent in African-derived populations than in European populations, leading to pronounced health disparities. It is hypothesized that the increased prevalence of these diseases in African-derived populations is due to selection for pro-fibrotic alleles that are protective against helminth infections. We constructed a genetic risk score (GRS) of fibroproliferative disease risk-increasing alleles using 147 linkage disequilibrium-pruned variants identified through genome-wide association studies of seven fibroproliferative diseases with large African-European prevalence disparities. A comparison of the fibroproliferative disease GRS between 1000 Genomes Phase 3 populations detected a higher mean GRS in AFR (mean = 148 risk alleles) than EUR (mean = 136 risk alleles; T-test p-value = 1.75x10-123). To test whether differences in GRS burden are systematic and may be due to selection, we employed the quantitative trait loci (QTL) sign test. The QTL sign test result indicates that population differences in risk-increasing allele burdens at these fibroproliferative disease variants are systematic and support a model featuring selective pressure (p-value = 0.011). These observations were replicated in an independent sample and were more statistically significant (T-test p-value = 7.26x10-237, sign test p-value = 0.015). This evidence supports the role of selective pressure acting to increase frequency of fibroproliferative alleles in populations of African relative to European ancestry populations.

The placenta is critical to human growth and development and has been implicated in health outcomes. Understanding the mechanisms through which the placenta influences perinatal and later-life outcomes requires further investigation. We evaluated the relationships between birthweight and adult body mass index (BMI) and genetically-predicted gene expression in human placenta. Birthweight genome-wide association summary statistics were obtained from the Early Growth Genetics Consortium (N = 298,142). Adult BMI summary statistics were obtained from the GIANT consortium (N = 681,275). We used S-PrediXcan to evaluate associations between the outcomes and predicted gene expression in placental tissue and, to identify genes where placental expression was exclusively associated with the outcomes, compared to 48 other tissues (GTEx v7). We identified 24 genes where predicted placental expression was significantly associated with birthweight, 15 of which were not associated with birthweight in any other tissue. One of these genes has been previously linked to birthweight. Analyses identified 182 genes where placental expression was associated with adult BMI, 110 were not associated with BMI in any other tissue. Eleven genes that had placental gene expression levels exclusively associated with BMI have been previously associated with BMI. Expression of a single gene, PAX4 , was associated with both outcomes exclusively in the placenta. Inter-individual variation of gene expression in placental tissue may contribute to observed variation in birthweight and adult BMI, supporting developmental origins hypothesis.

Preeclampsia, a pregnancy complication characterized by hypertension after 20 gestational weeks, is a major cause of maternal and neonatal morbidity and mortality. Mechanisms leading to preeclampsia are unclear; however, there is evidence of high heritability. We evaluated the association of polygenic scores (PGS) for blood pressure traits and preeclampsia to assess whether there is shared genetic architecture. Non-Hispanic Black and White reproductive age females with pregnancy indications and genotypes were obtained from Vanderbilt University’s BioVU, Electronic Medical Records and Genomics network, and Penn Medicine Biobank. Preeclampsia was defined by ICD codes. Summary statistics for diastolic blood pressure (DBP), systolic blood pressure (SBP), and pulse pressure (PP) PGS were acquired from Giri et al. Associations between preeclampsia and each PGS were evaluated separately by race and data source before subsequent meta-analysis. Ten-fold cross validation was used for prediction modeling. In 3504 Black and 5009 White included individuals, the rate of preeclampsia was 15.49%. In cross-ancestry meta-analysis, all PGSs were associated with preeclampsia (OR DBP  = 1.10, 95% CI 1.02–1.17, p  = 7.68 × 10 −3 ; OR SBP  = 1.16, 95% CI 1.09–1.23, p  = 2.23 × 10 −6 ; OR PP  = 1.14, 95% CI 1.07–1.27, p  = 9.86 × 10 −5 ). Addition of PGSs to clinical prediction models did not improve predictive performance. Genetic factors contributing to blood pressure regulation in the general population also predispose to preeclampsia.

Objectives/Goals: Identify genetic variants associated with the development of diabetic retinopathy (DR) and its advanced complication, diabetic macular edema (DME). Despite DME being a leading cause of vision loss among people with diabetes, genetic findings have been limited by small sample size, underrepresentation of diverse populations, and poor study design. Methods/Study Population: Genome-wide association studies (GWAS) were conducted to identify genetic variants linked to DME. GWAS were conducted separately by ancestry (African, European, and Admixed American) in the Million Veteran Program and All of Us cohorts, adjusted for age, sex, BMI, diabetes duration, mean HbA1c, and 10 principal components. We then combined population groups to perform a multi-ancestry meta-analysis (Multi) using a software called METAL. Analyses included autosomes and chromosome X for DME versus DR controls (14,211 cases and 47,005 controls). Gene expression analyses were performed using S-PrediXcan across 49 tissues to identify genes whose predicted expression is associated with DME risk. APOL1 variant and haplotype analyses were conducted to assess ancestry-specific associations with DME and type 2 diabetes. Results/Anticipated Results: Genome-wide significant loci included G6PD (Multi and African), previously reported to influence diabetes diagnosis, and APOL1 (Multi and European), previously linked to kidney disease in African ancestry. Gene expression analyses revealed 32 significant gene–tissue pairs (Multi 18 and African 18), corresponding to 9 unique genes. In APOL1, E150K was strongly associated with DME in Europeans (OR=1.22, P=2.9×10 −8 ) and modestly in Africans (OR=1.18, P=5.3×10 −4 ). N264K also showed significant effects in Europeans (OR=1.42, P=9.8×10 −4 ) and weaker but consistent effects in Africans (OR=1.04, P=0.025). The high-risk G1/G2 haplotype demonstrated a modest association in African ancestry (OR=1.15, P=0.048). Discussion/Significance of Impact: This is the largest genetic study of DME, uncovering genetic risk factors that could potentially be driving risk, such as APOL1, a gene historically tied to kidney disease among individuals of African ancestry. Our results indicate its involvement may extend to diabetic complications more generally.

Objectives/Goals: We aimed to discover treatment candidates for uterine fibroids, a common benign tumor with adverse impacts on quality of life. Repurposing already approved medications for fibroids can expedite treatment option expansion. Using genetic proxies, we identified novel fibroid drug candidates and estimated their effect on risk of fibroid diagnosis. Methods/Study Population: We performed a genetically predicted gene expression (GPGE) analysis using S-PrediXcan and GTEx tissue models with multi-ancestry genome-wide association study (GWAS) summary statistics of fibroids (cases  =  74,294, controls  =  465). There were 81 genes significantly associated with fibroid risk. Querying drug–gene interaction databases identified 56 approved medications that target these genes, including two antihypertensives, hydralazine, and spironolactone. Using independent multi-ancestry GWAS summary statistics (N  =  635,969) for systolic (SBP) and diastolic blood pressure (DBP), we conducted GPGE analyses. Blood pressure (exposure) and fibroids (outcome) GPGE summary statistics in the same tissues were used for two-sample Mendelian randomization (MR) analyses to proxy medication effects. Results/Anticipated Results: GPGE analyses identified hydralazine/tumor protein P53 (TP53) activity and spironolactone/thyroid hormone receptor beta (THRB) activity as drug-gene candidate pairs. Both drugs increase gene activity of their paired gene. Increased TP53 expression was associated with SBP in four tissues (exposure). The MR results indicated hydralazine use, proxied by increased TP53 expression, may reduce fibroid risk by 42% per standard deviation of gene expression (odds ratio [OR]  =  0.58, p  =  1.43E-12). Increased THRB expression was associated with DBP in eight tissues and were included in the MR (exposure). The MR results suggest spironolactone use, proxied by increased THRB expression, may reduce fibroid risk by 23% per standard deviation of gene expression (OR  =  0.77, p  = 5.94E-6). Discussion/Significance of Impact: We provide biologically plausible evidence for repurposing hydralazine and spironolactone for reducing risk of fibroid diagnosis. Repurposing these hypertension medications could provide novel preventative treatments for fibroids, particularly for individuals disproportionately affected by both conditions.

Background The burden of comorbidities in those with uterine fibroids compared to those without fibroids is understudied. We performed a phenome-wide association study to systematically assess the association between fibroids and other conditions. Methods Vanderbilt University Medical Center’s Synthetic Derivative and Geisinger Health System Database, two electronic health record databases, were used for discovery and validation. Non-Hispanic Black and White females were included. Fibroid cases were identified through a previously validated algorithm. Race-stratified and multi-population phenome-wide association analyses, adjusting for age and body mass index, were performed before statistically significant, validated results were meta-analyzed. Results There were 52,295 and 26,918 (9022 and 10,232 fibroid cases) females included in discovery and validation analyses. In multi-population meta-analysis, 389 conditions were associated with fibroid risk, with evidence of enrichment of circulatory, dermatologic, genitourinary, musculoskeletal, and sense organ conditions. The strongest associations within and across racial groups included conditions previously associated with fibroids. Numerous novel diagnoses, including cancers in female genital organs, were tied to fibroid status. Conclusions Overall, individuals with fibroids have a marked increase in comorbidities compared to those without fibroids. This approach to evaluate the health context of fibroids highlights the potential to understand fibroid etiology through studying the common biology of comorbid diagnoses and through disease networks. Plain language summary Though many females have uterine fibroids, not enough is known about how fibroids affect people’s health compared to those who do not have them. We explored fibroids’ connection to many other health conditions using information from electronic health records and groups of people from different races. Across all groups, we found over 380 conditions were associated with fibroids. Many of these health issues were circulatory, skin, genital and urinary, musculoskeletal, and sense organ conditions. In addition to strong known associations, we also found many diagnoses that have not been associated with fibroids, like cancers in female genitals. Overall, individuals with fibroids have more health conditions compared to those without fibroids. Our approach can help us to understand causes and consequences of fibroids. Jasper and Mautz et al. systematically assess associations between uterine fibroids and hundreds of conditions using electronic health record databases. They identify numerous associations, both known and novel, and find that individuals with fibroids have more comorbidities compared to those without fibroids.