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Genes underneath signals from genome-wide association studies (GWAS) for kidney function are promising targets for functional studies, but prioritizing variants and genes is challenging. By GWAS meta-analysis for creatinine-based estimated glomerular filtration rate (eGFR) from the Chronic Kidney Disease Genetics Consortium and UK Biobank (n = 1,201,909), we expand the number of eGFRcrea loci (424 loci, 201 novel; 9.8% eGFRcrea variance explained by 634 independent signal variants). Our increased sample size in fine-mapping (n = 1,004,040, European) more than doubles the number of signals with resolved fine-mapping (99% credible sets down to 1 variant for 44 signals, ≤5 variants for 138 signals). Cystatin-based eGFR and/or blood urea nitrogen association support 348 loci (n = 460,826 and 852,678, respectively). Our customizable tool for Gene PrioritiSation reveals 23 compelling genes including mechanistic insights and enables navigation through genes and variants likely relevant for kidney function in human to help select targets for experimental follow-up. Identifying causal variants and genes in genome-wide association studies remains a challenge, an issue that is ameliorated with larger sample sizes. Here the authors meta-analyze kidney function genome-wide association studies to identify new loci and fine-map loci to home in on variants and genes involved in kidney function.

Regulation of LDLR gene expression plays an important role in the development of atherosclerotic diseases including heart attack and stroke. Although LDLR regulation by sterol response elements has been well characterized, the functional significance of other noncoding regions at the LDLR locus remains poorly defined. In this study, we developed and applied a high throughput CRISPR screen to test the functional importance of candidate LDLR cis -regulatory elements (CREs) in their native genomic context. In total, we found 25 discrete regions to exhibit a significant impact on LDLR expression. For one of these regions with particularly strong activity in the first intron, we validated the presence of an enhancer by confirming that its disruption reduced endogenous LDLR expression while its insertion upstream of a minimal promoter augmented reporter gene expression. We then applied a massively parallel reporter assay to fine map enhancer activity within this region to a 129 bp interval that is highly conserved among vertebrates, exhibits biochemical hallmarks of enhancer activity, is enriched for transcription factor binding motifs, and contains a common genetic variant (rs57217136) that has been associated with human LDL cholesterol levels by genome-wide association studies. Overall, these findings demonstrate the power of CRISPR screening to interrogate candidate CREs and clarify the functional landscape of noncoding sequences at the LDLR locus.

The current understanding of the genetic determinants of thoracic aortic aneurysms and dissections (TAAD) has largely been informed through studies of rare, Mendelian forms of disease. Here, we conducted a genome-wide association study (GWAS) of TAAD, testing ~25 million DNA sequence variants in 8,626 participants with and 453,043 participants without TAAD in the Million Veteran Program, with replication in an independent sample of 4,459 individuals with and 512,463 without TAAD from six cohorts. We identified 21 TAAD risk loci, 17 of which have not been previously reported. We leverage multiple downstream analytic methods to identify causal TAAD risk genes and cell types and provide human genetic evidence that TAAD is a non-atherosclerotic aortic disorder distinct from other forms of vascular disease. Our results demonstrate that the genetic architecture of TAAD mirrors that of other complex traits and that it is not solely inherited through protein-altering variants of large effect size. A genome-wide association study of thoracic aortic aneurysms and dissections (TAAD) in the Million Veteran Program identifies 17 new risk loci and demonstrates that the genetic architecture of TAAD mirrors that of other complex traits.

Chronic kidney disease (CKD) is a growing health burden currently affecting 10–15% of adults worldwide. Estimated glomerular filtration rate (eGFR) as a marker of kidney function is commonly used to diagnose CKD. We analyze eGFR data from the Nord-Trøndelag Health Study and Michigan Genomics Initiative and perform a GWAS meta-analysis with public summary statistics, more than doubling the sample size of previous meta-analyses. We identify 147 loci (53 novel) associated with eGFR, including genes involved in transcriptional regulation, kidney development, cellular signaling, metabolism, and solute transport. Additionally, sex-stratified analysis identifies one locus with more significant effects in women than men. Using genetic risk scores constructed from these eGFR meta-analysis results, we show that associated variants are generally predictive of CKD with only modest improvements in detection compared with other known clinical risk factors. Collectively, these results yield additional insight into the genetic factors underlying kidney function and progression to CKD. Estimated glomerular filtration rate (eGFR) is a measure of kidney function and used to characterize chronic kidney disease. Here, Graham et al. identify 53 novel loci for eGFR in a GWAS meta-analysis, a subset of which are associated with other common diseases, such as diabetes and hypertension, based on PheWAS.

Genetic associations for lipid traits have identified hundreds of variants with clear differences across European, Asian and African studies. Based on a sub-Saharan-African GWAS for lipid traits in the population cross-sectional AWI-Gen cohort ( N  = 10,603) we report a novel LDL-C association in the GATB region ( P -value=1.56 × 10 −8 ). Meta-analysis with four other African cohorts ( N  = 23,718) provides supporting evidence for the LDL-C association with the GATB/FHIP1A region and identifies a novel triglyceride association signal close to the FHIT gene ( P -value =2.66 × 10 −8 ). Our data enable fine-mapping of several well-known lipid-trait loci including LDLR, PMFBP1 and LPA . The transferability of signals detected in two large global studies (GLGC and PAGE) consistently improves with an increase in the size of the African replication cohort. Polygenic risk score analysis shows increased predictive accuracy for LDL-C levels with the narrowing of genetic distance between the discovery dataset and our cohort. Novel discovery is enhanced with the inclusion of African data. Genetic associations and polygenic scores for lipid traits have low transferability to African individuals. Here, the authors perform a large sub-Sarahan African lipid GWAS and find that larger datasets and better global representation in discovery GWAS help to bridge this gap.

Hypercholesterolemia is a causal and modifiable risk factor for atherosclerotic cardiovascular disease. A critical pathway regulating cholesterol homeostasis involves the receptor-mediated endocytosis of low-density lipoproteins into hepatocytes, mediated by the LDL receptor. We applied genome-scale CRISPR screening to query the genetic determinants of cellular LDL uptake in HuH7 cells cultured under either lipoprotein-rich or lipoprotein-starved conditions. Candidate LDL uptake regulators were validated through the synthesis and secondary screening of a customized library of gRNA at greater depth of coverage. This secondary screen yielded significantly improved performance relative to the primary genome-wide screen, with better discrimination of internal positive controls, no identification of negative controls, and improved concordance between screen hits at both the gene and gRNA level. We then applied our customized gRNA library to orthogonal screens that tested for the specificity of each candidate regulator for LDL versus transferrin endocytosis, the presence or absence of genetic epistasis with LDLR deletion, the impact of each perturbation on LDLR expression and trafficking, and the generalizability of LDL uptake modifiers across multiple cell types. These findings identified several previously unrecognized genes with putative roles in LDL uptake and suggest mechanisms for their functional interaction with LDLR.

Background Escherichia coli lineage ST131 predominates across various spectra of extra-intestinal infections, including urinary tract infection (UTI). The distinctive resistance profile, diverse armamentarium of virulence factors and rapid global dissemination of ST131 E. coli makes it an intriguing pathogen. However, not much is known about the prevalence and genetic attributes of ST131 lineage in Pakistan. Methods We estimated prevalence and genetic attributes of E. coli ST131 isolates causing UTI among 155 randomly selected samples. Samples were analyzed for phylogenetic grouping, O-typing and fum C/ fim H typing. Isolates were further tested for the ESBL and virulence factors using PCR. Results Overall, 59% of the UPEC isolates belonged to the phylogenetic group B2, followed by D = 28%, B1 = 8% and A = 5%. Among 18 different Sequence-types, ST131 was the dominant lineage ( n  = 71; 46%) out of which 72% of the isolates were assigned to the phylogenetic group B2, while 61% adhered to the serogroup O25b. Fum C/ fim H typing confirmed 49% of the ST131 as H30 sub-types. In this study, significant numbers of the identified ST131 isolates were MDR and 42% showed ESBL phenotypes, out of which 37% carried bla - CTX-M-15 . Moreover, different virulence factors were detected in following percentages: fim H,155(100%), iut A 86 (55%), feo B 76 (49%), pap C 75 (48%), papGII  70 (45%), kpsMTII 40 (26%), pap EF 37 (24%), fyu A 37 (24%), usp 22 (14%), pap A 20 (13%), sfa/foc 20 (13%),  hly A 18 (12%), afa 15 (10%),  cdt B 11 (7%), papGI 6 (4%), papGIII 6 (4%),  kpsMTIII 4 (3%) and bma E2 (1%). Conclusion Conclusively, this study provides important insight into the genetic and virulence attributes of pandemic MDR ST131 strains involved in UTIs. It also highlights higher prevalence of ST131-O25b-H30 UPEC isolates in patients, which was previously unreported from this part of globe.

SARS-CoV-2 infection is initiated by binding of the viral spike protein to its receptor, ACE2, on the surface of host cells. ACE2 expression is heterogeneous both in vivo and in immortalized cell lines, but the molecular pathways that govern ACE2 expression remain unclear. We now report high-throughput CRISPR screens for functional modifiers of ACE2 surface abundance. In liver-derived HuH7 cells, we identified 35 genes whose disruption was associated with a change in the surface abundance of ACE2. Enriched among these ACE2 regulators were established transcription factors, epigenetic regulators, and functional networks. We further characterized individual HuH7 cell lines with disruption of SMAD4 , EP300 , PIAS1 , or BAMBI and found these genes to regulate ACE2 at the mRNA level and to influence cellular susceptibility to SARS-CoV-2 infection. Orthogonal screening of lung-derived Calu-3 cells revealed a distinct set of ACE2 modifiers comprised of ACE2 , KDM6A , MOGS , GPAA1 , and UGP2 . Collectively, our findings clarify the host factors involved in SARS-CoV-2 entry, highlight the cell type specificity of ACE2 regulatory networks, and suggest potential targets for therapeutic development.

Background Within the United States Veterans Health Administration (VHA), the number of patients using healthcare services has increased over the past several decades. Females make up a small proportion of overall patients within the VHA; however, this proportion is growing rapidly. Previous studies have described rates of VHA chiropractic use; however, no prior study assessed differences in use or utilization rates between male and female veterans. The purpose of this study was to assess rates of use and utilization of chiropractic care by sex among VHA patients receiving care at VHA facilities with on-station chiropractic clinics. Methods A serial cross-sectional analysis of VHA national electronic health record data was conducted in Fall 2021 for fiscal year (FY) 2005–2021. The cohort population was defined as VHA facilities with on-station chiropractic clinics, and facilities were admitted to the cohort after the first FY with a minimum of 500 on-station chiropractic visits. Variables extracted included counts of unique users of any VHA on-station facility outpatient services, unique users of VHA on-station facility chiropractic services, number of chiropractic visits, and sex. To calculate use, we determined the proportion of patients of each sex who received chiropractic services to the total patients of the same sex receiving any outpatient care within each facility. To calculate utilization, we determined the number of chiropractic care visits per patient per fiscal year. A linear mixed effects model was applied to examine the difference in chiropractic care utilization by sex. Results The percentage of female VHA on-station chiropractic patients increased from 11.7 to 17.7% from FY2005–FY2021. Among VHA facilities with on-station chiropractic care, the percentage of female VHA healthcare users who used chiropractic care (mean = 2.3%) was greater than the percentage of male VHA healthcare users who used chiropractic care (mean = 1.1%). Rates of chiropractic utilization by sex among VHA facilities with on-station chiropractic clinics were slightly higher for females (median = 4.3 visits per year, mean = 4.9) compared to males (median = 4.1 visits per year, mean = 4.6). Conclusion We report higher use and utilization of VHA chiropractic care by females compared with males, yet for both sexes rates were lower than in the private US healthcare system. This highlights the need for further assessment of the determinants and outcomes of VHA chiropractic care.

Iron is essential for many biological processes, but iron levels must be tightly regulated to avoid harmful effects of both iron deficiency and overload. Here, we perform genome-wide association studies on four iron-related biomarkers (serum iron, serum ferritin, transferrin saturation, total iron-binding capacity) in the Trøndelag Health Study (HUNT), the Michigan Genomics Initiative (MGI), and the SardiNIA study, followed by their meta-analysis with publicly available summary statistics, analyzing up to 257,953 individuals. We identify 123 genetic loci associated with iron traits. Among 19 novel protein-altering variants, we observe a rare missense variant (rs367731784) in HUNT, which suggests a role for DNAJC13 in transferrin recycling. We further validate recently published results using genetic risk scores for each biomarker in HUNT (6% variance in serum iron explained) and present linear and non-linear Mendelian randomization analyses of the traits on all-cause mortality. We find evidence of a harmful effect of increased serum iron and transferrin saturation in linear analyses that estimate population-averaged effects. However, there was weak evidence of a protective effect of increasing serum iron at the very low end of its distribution. Our findings contribute to our understanding of the genes affecting iron status and its consequences on human health. A GWAS on the four major iron-related biomarkers is conducted using data from the Trøndelag Health Study (HUNT), Michigan Genomics Initiative (MGI), and SardiNIA study, to identify 123 loci associated with iron homeostasis and effect on all-cause mortality.