In a recent study published in the journal Nature Communications, researchers performed a meta-analysis of 908,697 samples to investigate the genetic, sex-dependent basis of kidney traits.
Study: X-chromosome and kidney function: evidence from a multi-trait genetic analysis of 908,697 individuals reveals sex-specific and sex-differential findings in genes regulated by androgen response elements. Image Credit: Peakstock/Shutterstock.com
Background
Their sex-stratified cross-ancestry study focused on seven kidney traits and identified 23 loci significantly associated with two of these traits. Notably, they discovered four novel estimated glomerular filtration rate (eGFR) loci contained by three male- and one female-specific gene.
Their findings further revealed the role of androgen response elements (AREs) in sex-differential gene expressions and identified five such AREs. Together, this study provides novel knowledge into the sexual dimorphism of kidney traits and identifies critical gene targets for future work.
CKD and the role of the X-chromosome
Chronic kidney disease (CKD) is a kidney disease characterized by excess fluid and waste buildup due to damaged kidneys. It is an alarming condition with comorbidities, including renal failure, stroke, and heart disease.
Research has estimated that CKD affects one in every ten adults worldwide, with prevalence increasing so rapidly that current predictions estimate CKD to be the fifth cause of death by 2040.
The clinical and behavioral risks associated with CKD are well-classified, as are loci associated with kidney function traits.
Genome-wide association studies (GWAS) have uncovered hundreds of such loci and have revealed a peculiar characteristic of the disease – it is sexually dimorphic, observed more frequently in women, but with faster progression in their male counterparts.
Unfortunately, clinical interventions aimed at preventing or treating CKD, along with randomized clinical trials of patients suffering from the condition, remain lacking.
“Investigating the genetic basis of CKD defining traits and kidney function markers accounting for its sexual dimorphism is important to identify molecular targets for tailored pharmaceutical and non-pharmaceutical solutions.”
Furthermore, most GWAS have focused on loci identification, largely ignoring sex-differential effects.
About the study
In the present study, researchers carried out a cross-ancestry X-chromosome-wide association meta-analysis comprising 40 publications with a total sample size of 908,697 individuals.
Four quantitative and three binary kidney traits, namely estimated glomerular filtration rate (eGFR), serum uric acid (UA) levels, urine Albumin-to-Creatinine ratio (UACR), blood urea nitrogen (BUN), CKD, gout, and microalbuminuria (MA).
Data from the CKDGen consortium included 1,032,701 single-nucleotide polymorphisms (SNPs).
Quantitative phenotypes were measured using proxies where required, such as serum creatinine for eGFR and BUN estimates from blood urea (BUN = blood urea/2.14 mg/dL). CKD was defined and measured as eGFR <60 (cases) and eGRF >60 ml/min/1.73 m2 (controls). Similarly, MA cases and controls were identified using UACR = 30 mg/g as the cutoff.
“eGFR, UACR and BUN were logarithmized (natural logarithm) and residualized with respect to age, and untransformed values of UA were residualized with respect to age prior to association analysis. Moreover, UACR residuals were inverse normal transformed prior to genetic association analysis.”
Study analyses began with quality control (QC) and harmonization of the 40 studies included. Fixed inverse variance estimates were then used to combine sex-specific summary statistics. The meta-analysis was segregated into three groups: females and males.
To ensure accuracy in loci discovery and identification, a loci was only considered for analysis if included in 10 or more publications. Between-study heterogeneity was screened and measured using I2 statistics.
For trait analyses, every trait had a corresponding locus, with the SNP having the lowest P value (called the ‘index SNP’) comprising this locus.
These index SNPs then formed the basis for genetic sec-interaction analyses by computing male-female differences in meta-effect estimates, standardized by standard error.
“Since escape from X-inactivation could bias interaction analyses towards larger effect sizes in females, we also performed a sensitivity analysis assuming the extreme case of no inactivation. For that purpose, beta estimates and standard errors of female effects were halved prior to interaction analysis. We also performed colocalization analyses of male and female statistics for all loci to test for a shared underlying causal variant.”
The associations between kidney traits and their corresponding loci were investigated via cross-phenotype genetic association analysis.
Study findings
Demographic analyses of study individuals revealed that more than 80% of participants were of European descent, limiting the generalizability of results. Twenty-three loci were identified in the present study for UA (n = 7) and eGFG (n = 16).
Since the 40 included publications only contained statistically significant genome-wide results for these two traits, the other five were discarded from cross-phenotype genetic association analysis. Surprisingly, most UA and eGFR loci overlap observed, with Xq13.1 being a notable exception.
Of the 16 eGFR loci identified, four were novel to science and were found to be associated with ACSL4, CLDN2, TSPAN6, and DRP2 genes, the last of which is female-specific.
Additionally, five novel sex interactions (for previously identified loci) were described, of which FAM9B and AR/EDA2R were found to be male-specific.
The study highlights three sex-differential findings explaining sexual dimorphisms in human kidney function – DCAF12L1 and MST4 have stronger genetic effects in men, and HPRT1 has more potent effects in women. Androgen response elements (ARE) were contained in all these loci, suggesting functional explanations.
“Several lines of evidence suggest that sex hormones may play a role in kidney function and may contribute to sexual dimorphism of CKD. Higher levels of the sex hormone binding globulin (SHBG), a modulator of several sex hormones, have been causally associated with lower CKD risk35 and gout36 in men but not in women.”
Due to their small size (14 bp), overlaps between AREs and data sets from the study. However, results highlight that more candidate genes with AREs were found more often than expected by chance. This suggests that AREs may have a pronounced role in sex-differential gene expression.
Conclusions
The present study comprised a meta-analysis of 40 GWAS publications, including more than 900,000 participants and 1,000,000 SNPs, to evaluate the role of the X-chromosome in kidney disease outcomes.
Genetic association analyses comprehensively evaluated four quantitative and three binary (diseases) kidney traits. Four novel loci were discovered alongside six with previously unknown genetic sex interactions.
Candidate genes of loci presenting sex interactions were found to be associated with AREs, a plausible explanation for the observed sexual dimorphisms in kidney function.
“These findings contribute new insights into sex-dimorphisms and hormone dependance of kidney traits along with new prioritized gene targets for further molecular research.”
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