Rare Variant Association Research Articles

Weighted Selection Probability to Prioritize Susceptible Rare Variants in Multi-Phenotype Association Studies with Application to a Soybean Genetic Data Set.

Rare variant association studies with multiple traits or diseases have drawn a lot of attention since association signals of rare variants can be boosted if more than one phenotype outcome is associated with the same rare variants. Most of the existing statistical methods to identify rare variants associated with multiple phenotypes are based on a group test, where a pre-specified genetic region is tested one at a time. However, these methods are not designed to locate susceptible rare variants within the genetic region. In this article, we propose new statistical methods to prioritize rare variants within a genetic region when a group test for the genetic region identifies a statistical association with multiple phenotypes. It computes the weighted selection probability (WSP) of individual rare variants and ranks them from largest to smallest according to their WSP. In simulation studies, we demonstrated that the proposed method outperforms other statistical methods in terms of true positive selection, when multiple phenotypes are correlated with each other. We also applied it to our soybean single nucleotide polymorphism (SNP) data with 13 highly correlated amino acids, where we identified some potentially susceptible rare variants in chromosome 19.

Variations in gender identity and sexual orientation of university students

Abstract Background Previous studies have shown that a small percentage of people in the general population have atypical gender identity and/or sexual orientation. Aim This study aimed to explore variations in gender identity and sexual orientation in university students and determine genetic factors associated with these variations. Methods Deviations from complete gender congruence and exclusive heterosexual orientation in 736 Japanese university students were quantitatively assessed with self-assessment questionnaires. Next, we conducted genetic tests for 80 participants who showed relatively low gender identity scores and/or atypical sexual orientation. These genetic tests consisted of repeat number analysis of the androgen receptor gene (AR) and a SKAT-O: an optimal unified sequence kernel association test, which is an exome-based rare variant association study. The results of the genetic tests were compared with the Japanese reference data and the results of our 637 control samples. Outcomes We calculated the gender identity and sexual orientation scores of all participants and analyzed the molecular data of 80 selected participants. Results The gender identity scores of 736 participants were broadly distributed: only ~15% of natal males and ~5% of natal females had the maximum score that corresponds to complete gender congruence. The sexual orientation scores also varied: ~80% of natal males and ~60% of natal females showed exclusive heterosexual orientation. We found no association between gender characteristics and AR repeat numbers. The SKAT-O showed that rare damaging variants of TDRP and 3 other genes were more common in the 80 participants than in the control group. Clinical Implications Our data support the view that gender is a phenotypic continuum rather than a binary trait. Strength and Limitations This study quantitatively assessed the gender characteristics of a large cohort of university students. Moreover, we conducted systematic screening for genetic factors associated with gender variations. The weaknesses of the study were the limited analytic power of the questionnaires, the relatively small sample for molecular analyses, and incomplete clinical information and relatively advanced ages of the control group. Conclusion This study revealed significant variations in gender identity and sexual orientation in university students, which may be partly associated with variants in TDRP or other genes.

Excalibur: A new ensemble method based on an optimal combination of aggregation tests for rare-variant association testing for sequencing data.

The development of high-throughput next-generation sequencing technologies and large-scale genetic association studies produced numerous advances in the biostatistics field. Various aggregation tests, i.e. statistical methods that analyze associations of a trait with multiple markers within a genomic region, have produced a variety of novel discoveries. Notwithstanding their usefulness, there is no single test that fits all needs, each suffering from specific drawbacks. Selecting the right aggregation test, while considering an unknown underlying genetic model of the disease, remains an important challenge. Here we propose a new ensemble method, called Excalibur, based on an optimal combination of 36 aggregation tests created after an in-depth study of the limitations of each test and their impact on the quality of result. Our findings demonstrate the ability of our method to control type I error and illustrate that it offers the best average power across all scenarios. The proposed method allows for novel advances in Whole Exome/Genome sequencing association studies, able to handle a wide range of association models, providing researchers with an optimal aggregation analysis for the genetic regions of interest.

Gene-based burden scores identify rare variant associations for 28 blood biomarkers

BackgroundA relevant part of the genetic architecture of complex traits is still unknown; despite the discovery of many disease-associated common variants. Polygenic risk score (PRS) models are based on the evaluation of the additive effects attributable to common variants and have been successfully implemented to assess the genetic susceptibility for many phenotypes. In contrast, burden tests are often used to identify an enrichment of rare deleterious variants in specific genes. Both kinds of genetic contributions are typically analyzed independently. Many studies suggest that complex phenotypes are influenced by both low effect common variants and high effect rare deleterious variants. The aim of this paper is to integrate the effect of both common and rare functional variants for a more comprehensive genetic risk modeling.MethodsWe developed a framework combining gene-based scores based on the enrichment of rare functionally relevant variants with genome-wide PRS based on common variants for association analysis and prediction models. We applied our framework on UK Biobank dataset with genotyping and exome data and considered 28 blood biomarkers levels as target phenotypes. For each biomarker, an association analysis was performed on full cohort using gene-based scores (GBS). The cohort was then split into 3 subsets for PRS construction and feature selection, predictive model training, and independent evaluation, respectively. Prediction models were generated including either PRS, GBS or both (combined).ResultsAssociation analyses of the cohort were able to detect significant genes that were previously known to be associated with different biomarkers. Interestingly, the analyses also revealed heterogeneous effect sizes and directionality highlighting the complexity of the blood biomarkers regulation. However, the combined models for many biomarkers show little or no improvement in prediction accuracy compared to the PRS models.ConclusionThis study shows that rare variants play an important role in the genetic architecture of complex multifactorial traits such as blood biomarkers. However, while rare deleterious variants play a strong role at an individual level, our results indicate that classical common variant based PRS might be more informative to predict the genetic susceptibility at the population level.

Family studies: A useful tool to better understand spondyloarthritis.

Spondyloarthritis (SpA) is an immune-mediated disease characterized by a high heritability, reflected by strong familial aggregation. Therefore, family studies are a powerful tool for elucidating the genetic basis of SpA. First, they helped to assess the relative importance of genetic and environmental factors and established the polygenic character of the disease. Family-based designs were also historically used to identify genetic factors of susceptibility through linkage analyses. In SpA, three whole-genome linkage studies were published in the 1990's, unfortunately with few consistent results. After having been put aside for several years in favour of case-control GWAS, there is a renewed interest in family-based designs in particular to detect rare variant associations. This review aims at summarizing what family studies have brought to the field of SpA genetics, from genetic epidemiology studies to the most recent rare variant analyses. It also highlights the potential interest of family history of SpA to help diagnosis and detection of patients at high risk to develop the disease.

An allelic-series rare-variant association test for candidate-gene discovery

Allelic series are of candidate therapeutic interest because of the existence of a dose-response relationship between the functionality of a gene and the degree or severity of a phenotype. We define an allelic series as a collection of variants in which increasingly deleterious mutations lead to increasingly large phenotypic effects, and we have developed a gene-based rare-variant association test specifically targeted to identifying genes containing allelic series. Building on the well-known burden test and sequence kernel association test (SKAT), we specify a variety of association models covering different genetic architectures and integrate these into a Coding-Variant Allelic-Series Test (COAST). Through extensive simulations, we confirm that COAST maintains the type I error and improves the power when the pattern of coding-variant effect sizes increases monotonically with mutational severity. We applied COAST to identify allelic-series genes for four circulating-lipid traits and five cell-count traits among 145,735 subjects with available whole-exome sequencing data from the UK Biobank. Compared with optimal SKAT (SKAT-O), COAST identified 29% more Bonferroni-significant associations with circulating-lipid traits, on average, and 82% more with cell-count traits. All of the gene-trait associations identified by COAST have corroborating evidence either from rare-variant associations in the full cohort (Genebass, n= 400,000) or from common-variant associations in the GWAS Catalog. In addition to detecting many gene-trait associations present in Genebass by using only a fraction (36.9%) of the sample, COAST detects associations, such as that between ANGPTL4 and triglycerides, that are absent from Genebass but that have clear common-variant support.

Association of Rare Variants in ARSA with Parkinson's Disease.

Several lysosomal genes are associated with Parkinson's disease (PD), yet the association between PD and ARSA remains unclear. To study rare ARSA variants in PD. To study rare ARSA variants (minor allele frequency < 0.01) in PD, we performed burden analyses in six independent cohorts with 5801 PD patients and 20,475 controls, followed by a meta-analysis. We found evidence for associations between functional ARSA variants and PD in four cohorts (P ≤ 0.05 in each) and in the meta-analysis (P = 0.042). We also found an association between loss-of-function variants and PD in the United Kingdom Biobank cohort (P = 0.005) and in the meta-analysis (P = 0.049). These results should be interpreted with caution as no association survived multiple comparisons correction. Additionally, we describe two families with potential co-segregation of ARSA p.E382K and PD. Rare functional and loss-of-function ARSA variants may be associated with PD. Further replications in large case-control/familial cohorts are required. © 2023 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.

234-LB: Cell-State Dependent Regulation of PPARg Signaling by Zbtb9 in Adipocytes

The discovery of new genes involved in adipocyte development and function can shed light on the pathophysiology of obesity and T2D and provide new therapeutic targets for these disorders. Towards this end, GWAS and rare variant association studies in the T2D Knowledge Portal revealed associations between ZBTB9 and T2D, BMI, and hip circumference. However, the function of ZBTB9 in organismal physiology was not known. We found that Zbtb9 plays a key role in adipocyte biology and differentiation via cell-state dependent regulation of PPARγ signaling. Zbtb9 directly interacts with the PPARγ/RXRα complex as shown by co-IP, and acts as a positive regulator of PPARγ transcriptional activity as shown by a PPARγ reporter assay, together establishing Zbtb9 as a new PPARγ cofactor. In line with these findings, endogenous PPARγ target gene expression was decreased in the context of Zbtb9 deficiency in adipocytes. Given the central role of PPARγ in adipogenesis, we also sought to investigate the role of Zbtb9 in this process. Surprisingly, loss of Zbtb9 in preadipocytes increased adipogenesis and the expression of adipogenic genes, including PPARγ. Transcriptome analysis prior to and during adipogenesis revealed enhanced expression of E2F target genes prior to the initiation of differentiation and later induction of adipogenic gene expression. Treatment of Zbtb9 deficient preadipocytes with an E2F1 inhibitor (HLM006474) blocked the effects of Zbtb9 deficiency on adipogenic gene expression and adipogenesis. Collectively, these results demonstrate that Zbtb9 inhibits adipogenesis as a negative regulator of PPARγ expression via altered E2F1 signaling. We further demonstrated that E2F1 activation by Zbtb9 is associated with increased phosphorylation of Rb, which is known to cause dissociation of the Rb/E2F complex, and activation of E2F. Our findings revealed cell-state dependent roles of Zbtb9 in adipocytes, identifying a new molecule that may be important in the pathogenesis and treatment of obesity and T2D. Disclosure X. Xu: None. D. Buchner: None. Funding National Institutes of Health (DK119305)

Rare genetic variants impact muscle strength

Muscle strength is highly heritable and predictive for multiple adverse health outcomes including mortality. Here, we present a rare protein-coding variant association study in 340,319 individuals for hand grip strength, a proxy measure of muscle strength. We show that the exome-wide burden of rare protein-truncating and damaging missense variants is associated with a reduction in hand grip strength. We identify six significant hand grip strength genes, KDM5B, OBSCN, GIGYF1, TTN, RB1CC1, and EIF3J. In the example of the titin (TTN) locus we demonstrate a convergence of rare with common variant association signals and uncover genetic relationships between reduced hand grip strength and disease. Finally, we identify shared mechanisms between brain and muscle function and uncover additive effects between rare and common genetic variation on muscle strength.

Toward Identification of Functional Sequences and Variants in Noncoding DNA.

Understanding the noncoding part of the genome, which encodes gene regulation, is necessary to identify genetic mechanisms of disease and translate findings from genome-wide association studies into actionable results for treatments and personalized care. Here we provide an overview of the computational analysis of noncoding regions, starting from gene-regulatory mechanisms and their representation in data. Deep learning methods, when applied to these data, highlight important regulatory sequence elements and predict the functional effects of genetic variants. These and other algorithms are used to predict damaging sequence variants. Finally, we introduce rare-variant association tests that incorporate functional annotations and predictions in order to increase interpretability and statistical power.

0031 Whole genome sequence analyses for Excessive Daytime Sleepiness in the NHLBI TOPMed Program

Abstract Introduction Excessive daytime sleepiness is associated with multiple sleep, cardiometabolic, and neuropsychiatric disorders. Previous genome-wide association studies (GWAS) of daytime sleepiness using a single question in European population revealed associations for multiple genes in central nervous pathways. However, findings are still limited and may not be generalizable to other populations. In this study, we performed the first whole-genome sequence (WGS) analyses for Epworth Sleepiness Scale (ESS) in the NHLBI Trans-Omics for Precision Medicine (TOPMed) program. Methods This study includes 15,201 individuals of diverse race and ethnic backgrounds from seven cohorts in the TOPMed. We performed GWAS of single common variants (MAF&amp;gt;0.01) and gene-based burden tests of low-frequency and rare functional variants (loss of function and missense; MAF&amp;lt; 0.05). We adjusted for age, sex, body mass index (BMI), study, race/ethnicity, and genetic relatedness using linear mixed effects models implemented in the GENESIS R package. Results This sample included 43.8% males with a mean age of 54.9 years and BMI 29.6kg/m2, of whom 21.3% were classified with excessive daytime sleepiness (ESS&amp;gt;=10). In single variant test, we identified one novel genomic locus at rs60249969 (on CELF2) significantly associated with ESS (p-value=3.91x10-8). Suggestive significant associations were observed at 5 novel loci that overlapped with PDE7A/DNAJC5B, AHI1/PDE7B, KCNH7, F5, and FBXL17 (p&amp;lt; 1x10-7). In gene-based burden test, we did not identify any gene significantly associated with the ESS after correcting for multiple comparisons (p&amp;lt; 2x10-6). Suggestive significant evidence was observed at OR1A2 (consisting of 41 missense variants; p-value=1.65x10-5), an olfactory receptor gene differentially expressed in choroid plexus in the brain implicated in neurodegenerative diseases. Conclusion In our investigation of common and rare variant associations with excessive daytime sleepiness as assessed by the ESS, we identified one significant and several suggestive novel loci that mapped to genes highly expressed in brain tissues, which may have implications on sleep wake control system. Our next step will include replication analyses using independent imputed samples. Support (if any) R01HL153814 (to H.W.), NHLBI R35HL135818 (to S.R.).

Ravages: An R package for the simulation and analysis of rare variants in multicategory phenotypes.

Current software packages for the analysis and the simulations of rare variants are only available for binary and continuous traits. Ravages provides solutions in a single R package to perform rare variant association tests for multicategory, binary and continuous phenotypes, to simulate datasets under different scenarios and to compute statistical power. Association tests can be run in the whole genome thanks to C++ implementation of most of the functions, using either RAVA-FIRST, a recently developed strategy to filter and analyse genome-wide rare variants, or user-defined candidate regions. Ravages also includes a simulation module that generates genetic data for cases who can be stratified into several subgroups and for controls. Through comparisons with existing programmes, we show that Ravages complements existing tools and will be useful to study the genetic architecture of complex diseases. Ravages is available on the CRAN at https://cran.r-project.org/web/packages/Ravages/ and maintained on Github at https://github.com/genostats/Ravages.

Family-base rare variant association analysis in Saudi Arabian hydrocephalus subjects using whole exome sequencing.

Hydrocephalus is a highly heterogeneous multifactorial disease that arises from genetic and environmental factors. Familial genetic studies of hydrocephalus have elucidated four robustly associated hydrocephalus associated loci. This study aims to identify potential genetic causation in cases of hydrocephalus, with or without spina bifida and Dandy Walker Syndrome (DWS), using family-based rare variant association analysis of whole exome sequencing. We performed whole exome sequencing in 143 individuals across 48 families where at least one offspring was affected with hydrocephalus (N.=27), with hydrocephalus with spina bifida (N.=21) and with DWS (N.=3), using Illumina HiSeq 2500 instrument. No pathogenic or putative pathogenic single-nucleotide variants were evident in the four known hydrocephalus loci in our subjects. However, after examining 73 known hydrocephalus genes previously identified from literature, we identified three potentially impactful variants from the cohort. Using a gene panel comprising variants in known neural tube defects loci, we identified a total of 1024 potentially deleterious variants, of which 797 were missense variants and 191 were frameshift variants, 36 were stop gain/loss variants. A small portion of our family pedigree analyses yielded putative genetic signals which may be responsible for hydrocephaly elated phenotypes, however the low diagnostic yield may be due to lack of capture of genetic variants in the exonic regions i.e. structural variants may only be evident from whole genome sequencing. We identified three potentially impactful variants from our cohort in 73 known hydrocephalus genes previously identified in literature.

Rare TMEM230 Variants are Potentially Associated With Early Onset Parkinson’s Disease (P3-11.013)

Rare TMEM230 Variants are Potentially Associated With Early Onset Parkinson’s Disease (P3-11.013)

Scalable mixed model methods for set-based association studies on large-scale categorical data analysis and its application to exome-sequencing data in UK Biobank

The ongoing release of large-scale sequencing data in the UK Biobank allows for the identification of associations between rare variants and complex traits. SAIGE-GENE+ is a valid approach to conducting set-based association tests for quantitative and binary traits. However, for ordinal categorical phenotypes, applying SAIGE-GENE+ with treating the trait as quantitative or binarizing the trait can cause inflated type I error rates or power loss. In this study, we propose a scalable and accurate method for rare-variant association tests, POLMM-GENE, in which we used a proportional odds logistic mixed model to characterize ordinal categorical phenotypes while adjusting for sample relatedness. POLMM-GENE fully utilizes the categorical nature of phenotypes and thus can well control type I error rates while remaining powerful. In the analyses of UK Biobank 450k whole-exome-sequencing data for five ordinal categorical traits, POLMM-GENE identified 54 gene-phenotype associations.

Correlation Analysis of CTSB Promoter Polymorphism and Function in Patients with Dilated Cardiomyopathy

Dilated cardiomyopathy (DCM) is caused by a combination of genetic susceptibility and environmental factors. Cathepsin B affects the pathogenesis of DCM; however, its molecular mechanism is still unclear. In this study, we examined the association of rare CTSB variants with the occurrence of DCM. This case-control study involved 394 participants: 142 patients with DCM and 252 healthy controls. DNA was extracted from the peripheral leukocytes of all participants, and CTSB variants were analyzed and identified using polymerase chain reaction amplification. Functional analysis was performed using the dual-luciferase reporter assay, and the ability of genetic CTSB variants to bind to transcription factors (TFs) was analyzed and validated using the electrophoretic mobility shift assay (EMSA). Two single-nucleotide polymorphisms (SNPs) were identified in the study population. One SNP, g.4803 T > C (rs1293312), was more common in patients with DCM. A second SNP, g.4954 T > A (rs942670850), was identified in two patients with DCM. Both SNPs significantly enhanced the transcriptional activity of CTSB promoters. An analysis using the TRANSFAC database revealed that these SNPs affect TF binding, which was confirmed using the EMSA. Our results demonstrate that within the CTSB promoter, the genetic variants g.4803T>C (rs1293312) and g.4954 T > A (rs942670850) are rare risk factors for DCM development.

Adjusting for common variant polygenic scores improves yield in rare variant association analyses.

With the emergence of large-scale sequencing data, methods for improving power in rare variant association tests are needed. Here we show that adjusting for common variant polygenic scores improves yield in gene-based rare variant association tests across 65 quantitative traits in the UK Biobank (up to 20% increase at α = 2.6 × 10-6), without marked increases in false-positive rates or genomic inflation. Benefits were seen for various models, with the largest improvements seen for efficient sparse mixed-effects models. Our results illustrate how polygenic score adjustment can efficiently improve power in rare variant association discovery.

Whole exome sequencing and rare variant association study to identify genetic modifiers, KLF1 mutations, and a novel double mutation in Thai patients with hemoglobin E/beta-thalassemia

ABSTRACTObjectivesClinical manifestations of patients with Hemoglobin E/beta-thalassemia vary from mild to severe phenotypes despite exhibiting the same genotype. Studies have partially identified genetic modifiers. We aimed to study the association between rare variants in protein-coding regions and clinical severity in Thai patients.MethodsFrom April to November 2018, a case–control study was conducted based on clinical information and DNA samples collected from Thai patients with hemoglobin E/beta-thalassemia over the age of four years. Cases were patients with severe symptoms, while patients with mild symptoms acted as controls. Whole exome sequencing and rare variant association study were used to analyze the data.ResultsAll 338 unrelated patients were classified into 165 severe and 173 mild cases. Genotypes comprised 81.4% of hemoglobin E/beta-thalassemia, 2.7% of homozygous or compound heterozygous beta-thalassemia, and 0.3% of (δβ)0 thalassemia Hb E while 15.7% of samples were not classified as beta-thalassemia. A novel cis heterozygotes of IVS I-7 (A > T) and codon 26 (G > A) was identified. Six genes (COL4A3, DLK1, FAM186A, PZP, THPO, and TRIM51) showed the strongest associations with severity (observed p-values of <0.05; significance lost after correction for multiplicity). Among known modifiers, KLF1 variants were found in four mild patients and one severe patient.ConclusionNo rare variants were identified as contributors to the clinical heterogeneity of hemoglobin E/beta-thalassemia. KLF1 mutations are potential genetic modifiers. Studies to identify genetic factors are still important and helpful for predicting severity and developing targeted therapy.

CRELD1 variants are associated with bicuspid aortic valve in Turner syndrome

Turner syndrome (TS) is a chromosomal disorder caused by complete or partial loss of the second sex chromosome and exhibits phenotypic heterogeneity, even after accounting for mosaicism and karyotypic variation. Congenital heart defects (CHD) are found in up to 45 percent of girls with TS and span a phenotypic continuum of obstructive left-sided lesions, with bicuspid aortic valve (BAV) being the most common. Several recent studies have demonstrated a genome-wide impact of X chromosome haploinsufficiency, including global hypomethylation and altered RNA expression. The presence of such broad changes to the TS epigenome and transcriptome led others to hypothesize that X chromosome haploinsufficiency sensitizes the TS genome, and several studies have demonstrated that a second genetic hit can modify disease susceptibility in TS. The objective of this study was to determine whether genetic variants in known heart developmental pathways act synergistically in this setting to increase the risk for CHD, specifically BAV, in TS. We analyzed 208 whole exomes from girls and women with TS and performed gene-based variant enrichment analysis and rare-variant association testing to identify variants associated with BAV in TS. Notably, rare variants in CRELD1 were significantly enriched in individuals with TS who had BAV compared to those with structurally normal hearts. CRELD1 is a protein that functions as a regulator of calcineurin/NFAT signaling, and rare variants in CRELD1 have been associated with both syndromic and non-syndromic CHD. This observation supports the hypothesis that genetic modifiers outside the X chromosome that lie in known heart development pathways may influence CHD risk in TS.

The impact of coding germline variants on contralateral breast cancer risk and survival

Evidence linking coding germline variants in breast cancer (BC)-susceptibility genes other than BRCA1, BRCA2, and CHEK2 with contralateral breast cancer (CBC) risk and breast cancer-specific survival (BCSS) is scarce. The aim of this study was to assess the association of protein-truncating variants (PTVs) and rare missense variants (MSVs) in nine known (ATM, BARD1, BRCA1, BRCA2, CHEK2, PALB2, RAD51C, RAD51D, and TP53) and 25 suspected BC-susceptibility genes with CBC risk and BCSS. Hazard ratios (HRs) and 95% confidence intervals (CIs) were estimated with Cox regression models. Analyses included 34,401 women of European ancestry diagnosed with BC, including 676 CBCs and 3,449 BC deaths; the median follow-up was 10.9 years. Subtype analyses were based on estrogen receptor (ER) status of the first BC. Combined PTVs and pathogenic/likely pathogenic MSVs in BRCA1, BRCA2, and TP53 and PTVs in CHEK2 and PALB2 were associated with increased CBC risk [HRs (95% CIs): 2.88 (1.70-4.87), 2.31 (1.39-3.85), 8.29 (2.53-27.21), 2.25 (1.55-3.27), and 2.67 (1.33-5.35), respectively]. The strongest evidence of association with BCSS was for PTVs and pathogenic/likely pathogenic MSVs in BRCA2 (ER-positive BC) and TP53 and PTVs in CHEK2 [HRs (95% CIs): 1.53 (1.13-2.07), 2.08 (0.95-4.57), and 1.39 (1.13-1.72), respectively, after adjusting for tumor characteristics and treatment]. HRs were essentially unchanged when censoring for CBC, suggesting that these associations are not completely explained by increased CBC risk, tumor characteristics, or treatment. There was limited evidence of associations of PTVs and/or rare MSVs with CBC risk or BCSS for the 25 suspected BC genes. The CBC findings are relevant to treatment decisions, follow-up, and screening after BC diagnosis.