Biased pathogenic assertions of loss of function variants challenge molecular diagnosis of admixed individuals

Bartter Syndrome-Related Variants Distribution: Brazilian Data and Its Comparison with Worldwide Cohorts

BACKGROUND

Genetic testing is recommended for accurate diagnosis of Bartter syndrome (BS) and serves as a basis for implementing specific target therapies. However, populations other than Europeans and North Americans are underrepresented in most databases and there are uncertainties in the genotype-phenotype correlation. We studied Brazilian BS patients, an admixed population with diverse ancestry.

METHODS

We evaluated the clinical and mutational profile of this cohort and performed a systematic review of BS mutations from worldwide cohorts.

RESULTS

Twenty-two patients were included; Gitelman syndrome was diagnosed in 2 siblings with antenatal BS and congenital chloride diarrhea in 1 girl. BS was confirmed in 19 patients: BS type 1 in 1 boy (antenatal BS); BS type 4a in 1 girl and BS type 4b in 1 girl, both of them with antenatal BS and neurosensorial deafness; BS type 3 (CLCNKB mutations): 16 cases. The deletion of the entire CLCNKB (1-20 del) was the most frequent variant. Patients carrying the 1-20 del presented earlier manifestations than those with other CLCNKB-mutations and the presence of homozygous 1-20 del was correlated with progressive chronic kidney disease. The prevalence of the 1-20 del in this BS Brazilian cohort was similar to that of Chinese cohorts and individuals of African and Middle Eastern descent from other cohorts.

CONCLUSION

This study expands the genetic spectrum of BS patients with different ethnics, reveals some genotype/phenotype correlations, compares the findings with other cohorts, and provides a systematic review of the literature on the distribution of BS-related variants worldwide.

Clinical genomics and precision medicine

Precision Medicine emerges from the genomic paradigm of health and disease. For precise molecular diagnoses of genetic diseases, we must analyze the Whole Exome (WES) or the Whole Genome (WGS). By not needing exon capture, WGS is more powerful to detect single nucleotide variants and copy number variants. In healthy individuals, we can observe monogenic highly penetrant variants, which may be causally responsible for diseases, and also susceptibility variants, associated with common polygenic diseases. But there is the major problem of penetrance. Thus, there is the question of whether it is worthwhile to perform WGS in all healthy individuals as a step towards Precision Medicine. The genetic architecture of disease is consistent with the fact that they are all polygenic. Moreover, ancestry adds another layer of complexity. We are now capable of obtaining Polygenic Risk Scores for all complex diseases using only data from new generation sequencing. Yet, review of available evidence does not at present favor the idea that WGS analyses are sufficiently developed to allow reliable predictions of the risk components for monogenic and polygenic hereditary diseases in healthy individuals. Probably, it is still better for WGS to remain reserved for the diagnosis of pathogenic variants of Mendelian diseases.

Variant interpretation using population databases: Lessons from gnomAD

Reference population databases are an essential tool in variant and gene interpretation. Their use guides the identification of pathogenic variants amidst the sea of benign variation present in every human genome, and supports the discovery of new disease-gene relationships. The Genome Aggregation Database (gnomAD) is currently the largest and most widely used publicly available collection of population variation from harmonized sequencing data. The data is available through the online gnomAD browser (https://gnomad.broadinstitute.org/) that enables rapid and intuitive variant analysis. This review provides guidance on the content of the gnomAD browser, and its usage for variant and gene interpretation. We introduce key features including allele frequency, per-base expression levels, constraint scores, and variant co-occurrence, alongside guidance on how to use these in analysis, with a focus on the interpretation of candidate variants and novel genes in rare disease.

Transcriptomic analysis of elderly women with low muscle mass: association with immune system pathway

Despite the well-established association of gene expression deregulation with low muscle mass (LMM), the associated biological mechanisms remain unclear. Transcriptomic studies are capable to identify key mediators in complex diseases. We aimed to identify relevant mediators and biological mechanisms associated with age-related LMM. LMM-associated genes were detected by logistic regression using microarray data of 20 elderly women with LMM and 20 age and race-matched controls extracted from our SPAH Study (GSE152073). We performed weighted gene co-expression analysis (WGCNA) that correlated the identified gene modules with laboratorial characteristics. Gene enrichment analysis was performed and an LMM predictive model was constructed using Support Vector Machine (SVM). Overall, 821 discriminating transcripts clusters were identified (|beta coefficient| >1; p-value <0.01). From this list, 45 predictors of LMM were detected by SVM and validated with 0.7 of accuracy. Our results revealed that the well-described association of inflammation, immunity and metabolic alterations is also relevant at transcriptomic level. WGCNA highlighted a correlation of genes modules involved in immunity pathways with vitamin D level (R = 0.63, p = 0.004) and the Agatston score (R = 0.51, p = 0.02). Our study generated a predicted regulatory network and revealed significant metabolic pathways related to aging processes, showing key mediators that warrant further investigation.