Gene-based association study reveals a distinct female genetic signal in primary hypertension

Zucker, Roei; Kovalerchik, Michael; Linial, Michal

doi:10.1007/s00439-023-02567-9

Cited by 9 publications

(8 citation statements)

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“…Thus, it can help to assess the risk prediction for autoimmunity that overlaps with hypothyroidism ( Eriksson et al, 2012 ). Importantly, for a large collection of common diseases ( Brandes et al, 2020 ; Brandes et al, 2021 ; Zucker et al, 2023 ), we found no evidence for associations within the Chr 6 MHC locus by PWAS or coding GWAS. Therefore, we argue that an immune-related signature is a genuine contributing signal for hypothyroidism with gene-specific interpretability.…”

Section: Discussioncontrasting

confidence: 68%

Revealing the genetic complexity of hypothyroidism: integrating complementary association methods

Zucker,

Kovalerchik,

Stern

et al. 2024

Front. Genet.

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Hypothyroidism is a common endocrine disorder whose prevalence increases with age. The disease manifests itself when the thyroid gland fails to produce sufficient thyroid hormones. The disorder includes cases of congenital hypothyroidism (CH), but most cases exhibit hormonal feedback dysregulation and destruction of the thyroid gland by autoantibodies. In this study, we sought to identify causal genes for hypothyroidism in large populations. The study used the UK-Biobank (UKB) database, reporting on 13,687 cases of European ancestry. We used GWAS compilation from Open Targets (OT) and tuned protocols focusing on genes and coding regions, along with complementary association methods of PWAS (proteome-based) and TWAS (transcriptome-based). Comparing summary statistics from numerous GWAS revealed a limited number of variants associated with thyroid development. The proteome-wide association study method identified 77 statistically significant genes, half of which are located within the Chr6-MHC locus and are enriched with autoimmunity-related genes. While coding GWAS and PWAS highlighted the centrality of immune-related genes, OT and transcriptome-wide association study mostly identified genes involved in thyroid developmental programs. We used independent populations from Finland (FinnGen) and the Taiwan cohort to validate the PWAS results. The higher prevalence in females relative to males is substantiated as the polygenic risk score prediction of hypothyroidism relied mostly from the female group genetics. Comparing results from OT, TWAS, and PWAS revealed the complementary facets of hypothyroidism’s etiology. This study underscores the significance of synthesizing gene-phenotype association methods for this common, intricate disease. We propose that the integration of established association methods enhances interpretability and clinical utility.

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Section: Discussioncontrasting

confidence: 68%

Revealing the genetic complexity of hypothyroidism: integrating complementary association methods

Zucker,

Kovalerchik,

Stern

et al. 2024

Front. Genet.

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“…In the current version of the PWAS Hub, we discuss diseases according to clinical diagnosis codes based on ICD-10 indices. The results presented in PWAS Hub address the major pitfalls and limitations of GWAS, as discussed in the case of primary hypertension (Zucker et al 2023) or predisposition to 10 cancer types in a large population (Brandes et al 2021). In the implementation discussed in the PWAS Hub, we observed a relatively low number of significant genes for the studied diseases (e.g., 27 genes for asthma and 29 unique genes for females, males, and both) (Fig.…”

Section: Discussionmentioning

confidence: 88%

“…In PWAS, positive values indicate a positive correlation with the gene effect scores, where higher effect scores represent less functional damage, thereby indicating the "protective" virtue of genes. To account for potential biases (e.g., batch effect in data collection, residual population structure, age), we included a collection of 172 covariates with: sex (binary), year of birth (numeric), 40 principal components of the genetic data that capture the ancestry stratification were provided by the UKB (numeric), the UKB genotyping batch (one-hot-encoding, 105 categories), and the UKB assessment centers associated with each sample (binary, 25 categories) (Zucker et al 2023).…”

Section: Effect Size Of Disease Associationsmentioning

confidence: 99%

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PWAS Hub: Exploring Gene-Based Associations of Common Complex Diseases

Kelman,

Zucker,

Brandes

et al. 2024

Preprint

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PWAS (Proteome-Wide Association Study) is an innovative genetic association approach that complements widely-used methods like GWAS (Genome-Wide Association Study). The PWAS platform involves consecutive phases. Initially, machine learning modeling and probabilistic considerations quantified the impact of genetic variants on protein-coding genes' biochemical functions. Secondly, aggregating the variants per gene for each individual determines a gene-damaging score. Finally, standard statistical tests are activated in the case-control setting to yield statistically significant genes per phenotype. The PWAS Hub offers a user-friendly interface for an in-depth exploration of gene-disease associations from the UK Biobank (UKB). Results from PWAS cover 99 common diseases and conditions, each with over 10,000 diagnosed individuals per phenotype. Users can explore genes associated with these diseases, with separate analyses conducted for males and females. The PWAS Hub lists statistically significant genes associated with common diseases. It also indicates whether the analyzed damaged gene is associated with an increased or decreased risk. For each phenotype, the analyses account for sex-based genetic effects, inheritance modes (dominant and recessive), and the pleiotropic nature of associated genes. The PWAS Hub showcases its usefulness by navigating through such proteomic-genetic application for asthma. Graphical tools facilitate comparing genetic effects between the results of PWAS and coding GWAS, aiding in understanding the sex-specific genetic impact on common diseases. This adaptable platform is attractive for clinicians, researchers, and individuals interested in delving into gene-disease associations and sex-specific genetic effects. The PWAS Hub is accessible at http://pwas.huji.ac.il.

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“…To improve reliability, we filtered out variants by minor allele counts (MAC <20). Coding GWAS allows greater interpretability of the gene results since the connection of variant and function is plainer (19).…”

Section: Methodsmentioning

confidence: 99%

The genetics of idiopathic intracranial hypertension (IIH): Integration of population studies and clinical data

Zucker,

Kovalerchik,

Davidovich

et al. 2023

Preprint

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Idiopathic intracranial hypertension (IIH) is a condition characterized by increased intracranial pressure without a known cause. It mainly affects overweight, reproductive-age women, and its genetic basis remains unknown. Previous GWAS failed to find significant associations. To address this, we analyzed a cohort of 173 IIH and papilledema (PAP) patients from the UK Biobank (UKB) using various genetic association methods. We activate a GWAS that covers only coding regions of genes for better interpretability. We also employed the complementary methods of SKAT and PWAS, which aggregate variants to determine gene-based association. We report on 10 overlapping genes by two methods, with FOXF1 and RGCC identified by all three methods. In a separate GWAS on a Finnish cohort, a rare variant in the LRRFIP1 gene was associated with IIH. Comparing findings from the Finnish, IIH, and PAP cohorts, we discovered the SHANK2 gene as a shared genetic factor. Genes related to the choroid plexus epithelium cluster (MAPK15, DCDC1, DNAH5, and SLC28A3) were found to be enriched, suggesting a role for microtubule cilia regulation in IIH etiology. Importantly, many GWAS-associated coding variants were predicted to be deleterious and rare in healthy populations. Comorbidities associated with IIH and PAP include pain, migraines, and psychological and mental disorders. This study highlights the strength of an integrative genetic approach, combining functional and clinical knowledge, to better understand IIH etiology. By identifying potential genetic factors and their biological relevance, this research provides insights into IIH's causes and paves the way for further investigation and potential therapeutic interventions.

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Gene-based association study reveals a distinct female genetic signal in primary hypertension

Cited by 9 publications

References 50 publications

Revealing the genetic complexity of hypothyroidism: integrating complementary association methods

Revealing the genetic complexity of hypothyroidism: integrating complementary association methods

PWAS Hub: Exploring Gene-Based Associations of Common Complex Diseases

The genetics of idiopathic intracranial hypertension (IIH): Integration of population studies and clinical data

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