A genome-wide association study of chemotherapy-induced alopecia in breast cancer patients

Cancer-Related Alopecia: From Etiologies to Global Management

Simple Summary

Although it does not represent a condition that threatens the life of patients, alopecia nevertheless has an essential impact on the quality of life of patients, particularly in terms of the psychological and social aspects. Indeed, while it has long been considered an acceptable side effect in the management of patients, the progressive emergence of a patient-centered approach coupled with a better knowledge of the pathophysiological processes involved has led to a better consideration of alopecia, both on the preventive and palliative sides. Thus, cancerous alopecia can be multifactorial: iatrogenic (in particular via conventional chemotherapy), induced by a vitamin/nutritional deficiency, or even caused by the disease itself. In this state-of-the-art review, we therefore cover alopecia in an exhaustive manner by considering the different mechanisms involved and their frequency as well as the various therapies offered.

Abstract

Alopecia represents a multifaceted challenge with distinct etiologies and consequences. Transposed to the world of oncology, different types of alopecia and molecular pathways have been characterized, allowing a better understanding of the underlying mechanisms. In patients with cancer, alopecia can be iatrogenic (i.e., due to conventional chemotherapies, endocrine therapies, targeted therapies, immunotherapies, radiotherapy and surgery) or a direct consequence of the disease itself (e.g., malnutrition, scalp metastases and paraneoplastic syndromes). Identification of the actual incriminated mechanism(s) is therefore essential in order to deliver appropriate supportive care, whether preventive or curative. On the preventive side, the last few years have seen the advent of the automated cooling cap, a prophylactic approach supported by several randomized clinical trials. On the curative side, although the treatments currently available are limited, several promising therapeutic approaches are under development. Appropriate alopecia management is essential, particularly regarding its psychological repercussions with significant consequences on the quality of life of patients and their family and with a potential impact on treatment compliance.

[Alopecia and cancers: From basics to clinical practice]

Alopecia, although long considered an unavoidable consequence of cancer therapy, currently presents a multifaceted challenge. The knowledge of the physiology of the hair and consequently of the pathophysiology of alopecia has led to show that there is not one but several types of alopecia. Transposed to the world of oncology, different types of alopecia and subsequently molecular pathways have been characterized, allowing a better understanding of the underlying mechanisms. Thus, in patients with cancer, alopecia can be iatrogenic (chemotherapies, endocrine therapies, targeted therapies, immunotherapies, radiotherapy, surgery) or directly the consequence of the disease itself (malnutrition, scalp metastases, paraneoplastic syndromes). Knowledge of the incriminated mechanism(s) could thus make it possible to deploy an appropriate care component, whether on the preventive or curative sides or in terms of supportive care. These are particularly essential regarding the psychological repercussions caused by alopecia, with significant consequences on the quality of life of patients and with a potential impact on treatment compliance. On the preventive side, the last few years have seen the advent of the automated scalp cooling therapy, supported by several randomized clinical trials. On the curative side, several therapeutic proposals are currently deployed or under development in order to provide relevant treatments.

Association Between ABCB1 Genetic Variants and Persistent Chemotherapy-Induced Alopecia in Women With Breast Cancer

Importance

Persistent chemotherapy-induced alopecia (pCIA) has been recently described in patients with breast cancer and in its most severe form occurs in up to 10% of these patients. Genetic risk factors associated with pCIA have not been adequately explored.

Objective

To identify genetic variants associated with pCIA.

Design, Setting, and Participants

In this genetic association study, 215 women with breast cancer treated with docetaxel-based chemotherapy with a follow-up of 1.5 to 10 years after the end of the treatment were recruited retrospectively through 3 hospital oncology units across Spain between 2005 and 2018. Severe pCIA was defined as lack of scalp hair recovery (Common Terminology Criteria for Adverse Events, version 3.0, grade 2) 18 months or more after the end of treatment. Patients with grade 2 pCIA were selected as cases, and those with no sign of residual alopecia 12 months after the end of docetaxel treatment were selected as controls. A genome-wide association study in a discovery phase was conducted, and logistic regression was used to identify variants associated with the risk to develop this adverse effect. The validity of the association was addressed through a replication phase.

Exposures

Docetaxel-based chemotherapy.

Main Outcomes and Measures

Genotypes of single-nucleotide variants associated with pCIA.

Results

In total, 215 women with breast cancer (median age, 51.6 years; interquartile range, 44-60 years) were recruited (173 patients for the discovery phase and 42 patients for the replication phase). In the discovery phase, ABCB1 genetic variants were associated with risk to develop pCIA. In particular, single-nucleotide variation rs1202179, a regulatory variant located in an enhancer element that interacts with the ABCB1 promoter, was associated with the occurrence of pCIA. This finding was validated in the replication cohort (combined odds ratio, 4.05; 95% CI, 2.46-6.67; P = 3.946 × 10-8). This variant is associated with ABCB1 mRNA expression, and the risk allele was associated with decreased ABCB1 expression levels (P = 1.64 × 10-20).

Conclusions and Relevance

This is the first study, to our knowledge, that identifies an association between a regulatory variant in the ABCB1 gene and the occurrence of pCIA in patients with breast cancer who were treated with docetaxel-based therapies. This finding suggests an important insight into the biological mechanisms underlying pCIA and opens the opportunity to explore personalized treatment of these patients.

Amlodipine and Verapamil, Voltage-Gated Ca2+ Channel Inhibitors, Suppressed the Growth of Gastric Cancer Stem Cells

BACKGROUND

The membrane transporters activated in cancer stem cells (CSCs) are the target of novel cancer therapies for gastric cancer. The present study investigated ion channel expression profiles in gastric CSCs (GCSCs).

METHODS

Cells strongly expressing CD44 were separated from MKN74 cells, a human gastric cancer cell line, by fluorescence-activated cell sorting (FACS), and GCSCs were identified based on tumorsphere formation. Gene expression profiles in GCSCs were examined by a microarray analysis.

RESULTS

Among MKN74 cells, CD44 messenger RNA levels were higher in CSCs than in non-CSCs. These CSCs also exhibited resistance to cisplatin. The microarray analysis revealed that the expression of several genes related to voltage-gated Ca²⁺ channels (VGCCs), including CACNA2D1 and CACNB4, was upregulated. The cytotoxicities of the CACNA2D1 inhibitor amlodipine and the CACNB4 inhibitor verapamil were greater at lower concentrations in CSCs than in non-CSCs, and markedly reduced tumorsphere numbers. Tumor volumes were significantly smaller in a xenograft nude mouse model treated with amlodipine or verapamil in combination with cisplatin than in that treated with cisplatin alone.

CONCLUSIONS

The present results indicate that VGCCs play a role in maintaining CSCs, and demonstrated the potential of their specific inhibitors, amlodipine and verapamil, as targeted therapeutic agents against gastric cancer.

Drug response in association with pharmacogenomics and pharmacomicrobiomics: towards a better personalized medicine

Researchers have long been presented with the challenge imposed by the role of genetic heterogeneity in drug response. For many years, Pharmacogenomics and pharmacomicrobiomics has been investigating the influence of an individual's genetic background to drug response and disposition. More recently, the human gut microbiome has proven to play a crucial role in the way patients respond to different therapeutic drugs and it has been shown that by understanding the composition of the human microbiome, we can improve the drug efficacy and effectively identify drug targets. However, our knowledge on the effect of host genetics on specific gut microbes related to variation in drug metabolizing enzymes, the drug remains limited and therefore limits the application of joint host-microbiome genome-wide association studies. In this paper, we provide a historical overview of the complex interactions between the host, human microbiome and drugs. While discussing applications, challenges and opportunities of these studies, we draw attention to the critical need for inclusion of diverse populations and the development of an innovative and combined pharmacogenomics and pharmacomicrobiomics approach, that may provide an important basis in personalized medicine.

The physical, psychological and social experiences of alopecia among women receiving chemotherapy: An integrative literature review

PURPOSE

To conduct an integrative scoping review of the physical, psychological and social experiences of women who have experienced chemotherapy-induced alopecia (CIA).

METHOD

An integrative review was undertaken. A systematic search of MEDLINE, CINAHL and PsycInfo identified 23 studies meeting the inclusion criteria. Data relating to women's experiences of alopecia was extracted and synthesized thematically.

RESULTS

Four analytical themes were formed; 'the physical and psychological effect of alopecia', 'more than the loss of hair', 'the complexities of a visual cancer identity' and 'coping with new internal and external relationships'. CIA involves a public and private representation of illness which disrupts women's identity and their acceptance in public, yet this is a highly individualised experience. There is disparity in current evidence regarding the experience of CIA for women among older age groups, with rarer forms of cancer, haematological malignancies and those receiving palliative care or targeted treatment modalities.

CONCLUSIONS

This review highlights the continued pervasive psychosocial implications arising from CIA, however this is not exclusive to scalp hair as alopecia from the face and body has also been found to require adaptation and effective coping. Limited knowledge exists on the experience of alopecia induced by treatment for haematological cancers and rarer-tumour groups and emerging systemic anti-cancer treatment modalities. Healthcare professionals must endeavour to support and discuss the potential risks of alopecia, and provide patients with an opportunity to voice their fears, concerns, and experiences of CIA. Future research should incorporate the identified underserved populations and the experience of newer therapies.

CDK4/6 inhibition mitigates stem cell damage in a novel model for taxane-induced alopecia

Taxanes are a leading cause of severe and often permanent chemotherapy‐induced alopecia. As the underlying pathobiology of taxane chemotherapy‐induced alopecia remains poorly understood, we investigated how paclitaxel and docetaxel damage human scalp hair follicles in a clinically relevant ex vivo organ culture model. Paclitaxel and docetaxel induced massive mitotic defects and apoptosis in transit amplifying hair matrix keratinocytes and within epithelial stem/progenitor cell‐rich outer root sheath compartments, including within Keratin 15+ cell populations, thus implicating direct damage to stem/progenitor cells as an explanation for the severity and permanence of taxane chemotherapy‐induced alopecia. Moreover, by administering the CDK4/6 inhibitor palbociclib, we show that transit amplifying and stem/progenitor cells can be protected from paclitaxel cytotoxicity through G1 arrest, without premature catagen induction and additional hair follicle damage. Thus, the current study elucidates the pathobiology of taxane chemotherapy‐induced alopecia, highlights the paramount importance of epithelial stem/progenitor cell‐protective therapy in taxane‐based oncotherapy, and provides preclinical proof‐of‐principle in a healthy human (mini‐) organ that G1 arrest therapy can limit taxane‐induced tissue damage.

Use of big data in drug development for precision medicine: an update

INTRODUCTION

Big-data-driven drug development resources and methodologies have been evolving with ever-expanding data from large-scale biological experiments, clinical trials, and medical records from participants in data collection initiatives. The enrichment of biological- and clinical-context-specific large-scale data has enabled computational inference more relevant to real-world biomedical research, particularly identification of therapeutic targets and drugs for specific diseases and clinical scenarios.

AREAS COVERED

Here we overview recent progresses made in the fields: new big-data-driven approach to therapeutic target discovery, candidate drug prioritization, inference of clinical toxicity, and machine-learning methods in drug discovery.

EXPERT OPINION

In the near future, much larger volumes and complex datasets for precision medicine will be generated, e.g., individual and longitudinal multi-omic, and direct-to-consumer datasets. Closer collaborations between experts with different backgrounds would also be required to better translate analytic results into prognosis and treatment in the clinical practice. Meanwhile, cloud computing with protected patient privacy would become more routine analytic practice to fill the gaps within data integration along with the advent of big-data. To conclude, integration of multitudes of data generated for each individual along with techniques tailored for big-data analytics may eventually enable us to achieve precision medicine.

A Pharmacogenetic Prediction Model of Progression-Free Survival in Breast Cancer using Genome-Wide Genotyping Data from CALGB 40502 (Alliance)

Genome-wide genotyping data are increasingly available for pharmacogenetic association studies, but application of these data for development of prediction models is limited. Prediction methods, such as elastic net regularization, have recently been applied to genetic studies but only limitedly to pharmacogenetic outcomes. An elastic net was applied to a pharmacogenetic study of progression-free survival (PFS) of 468 patients with advanced breast cancer in a clinical trial of paclitaxel, nab-paclitaxel, and ixabepilone. A final model included 13 single nucleotide polymorphisms (SNPs) in addition to clinical covariates (prior taxane status, hormone receptor status, disease-free interval, and presence of visceral metastases) with an area under the curve (AUC) integrated over time of 0.81, an increase compared to an AUC of 0.64 for a model with clinical covariates alone. This model may be of value in predicting PFS with microtubule targeting agents and may inform reverse translational studies to understand differential response to these drugs.

Prediction for Intravenous Immunoglobulin Resistance by Using Weighted Genetic Risk Score Identified From Genome-Wide Association Study in Kawasaki Disease

Supplemental Digital Content is available in the text.

Background—

Intravenous immunoglobulin (IVIG) is the treatment of choice in Kawasaki disease (KD). IVIG is used to prevent cardiovascular complications related to KD. However, a proportion of KD patients have persistent fever after IVIG treatment and are defined as IVIG resistant.

Methods and Results—

To develop a risk scoring system based on genetic markers to predict IVIG responsiveness in KD patients, a total of 150 KD patients (126 IVIG responders and 24 IVIG nonresponders) were recruited for this study. A genome-wide association analysis was performed to compare the 2 groups and identified risk alleles for IVIG resistance. A weighted genetic risk score was calculated by the natural log of the odds ratio multiplied by the number of risk alleles. Eleven single-nucleotide polymorphisms were identified by genome-wide association study. The KD patients were categorized into 3 groups based on their calculated weighted genetic risk score. Results indicated a significant association between weighted genetic risk score (groups 3 and 4 versus group 1) and the response to IVIG (Fisher’s exact P value 4.518×10⁻⁰³ and 8.224×10⁻¹⁰, respectively).

Conclusions—

This is the first weighted genetic risk score study based on a genome-wide association study in KD. The predictive model integrated the additive effects of all 11 single-nucleotide polymorphisms to provide a prediction of the responsiveness to IVIG.

Breast cancer: The translation of big genomic data to cancer precision medicine

Cancer is a complex genetic disease that develops from the accumulation of genomic alterations in which germline variations predispose individuals to cancer and somatic alterations initiate and trigger the progression of cancer. For the past 2 decades, genomic research has advanced remarkably, evolving from single-gene to whole-genome screening by using genome-wide association study and next-generation sequencing that contributes to big genomic data. International collaborative efforts have contributed to curating these data to identify clinically significant alterations that could be used in clinical settings. Focusing on breast cancer, the present review summarizes the identification of genomic alterations with high-throughput screening as well as the use of genomic information in clinical trials that match cancer patients to therapies, which further leads to cancer precision medicine. Furthermore, cancer screening and monitoring were enhanced greatly by the use of liquid biopsies. With the growing data complexity and size, there is much anticipation in exploiting deep machine learning and artificial intelligence to curate integrative "-omics" data to refine the current medical practice to be applied in the near future.

Anagen Effluvium in Association With Extracorporeal Membrane Oxygenation

Anagen effluvium (AE) is a type of alopecia with hair loss during the growth phase of a hair follicle and is most often associated with cytotoxic chemotherapy. This report describes a case of AE in a critically ill 2-year-old boy who developed cardiorespiratory failure requiring extracorporeal membranous oxygenation. We postulate that the combination of hypotension and hypoxia with subsequent reperfusion triggered an apoptotic cascade in the hair matrix, resulting in AE.

Improving the detection of pathways in genome-wide association studies by combined effects of SNPs from Linkage Disequilibrium blocks

Genome-wide association studies (GWAS) have successfully identified single variants associated with diseases. To increase the power of GWAS, gene-based and pathway-based tests are commonly employed to detect more risk factors. However, the gene- and pathway-based association tests may be biased towards genes or pathways containing a large number of single-nucleotide polymorphisms (SNPs) with small P-values caused by high linkage disequilibrium (LD) correlations. To address such bias, numerous pathway-based methods have been developed. Here we propose a novel method, DGAT-path, to divide all SNPs assigned to genes in each pathway into LD blocks, and to sum the chi-square statistics of LD blocks for assessing the significance of the pathway by permutation tests. The method was proven robust with the type I error rate >1.6 times lower than other methods. Meanwhile, the method displays a higher power and is not biased by the pathway size. The applications to the GWAS summary statistics for schizophrenia and breast cancer indicate that the detected top pathways contain more genes close to associated SNPs than other methods. As a result, the method identified 17 and 12 significant pathways containing 20 and 21 novel associated genes, respectively for two diseases. The method is available online by http://sparks-lab.org/server/DGAT-path.

A genome-wide association study identifies WT1 variant with better response to 5-fluorouracil, pirarubicin and cyclophosphamide neoadjuvant chemotherapy in breast cancer patients

Breast cancer is believed to result from the interplay of genetic and non-genetic risk factors, and individual genetic variation may influence the efficacy of chemotherapy. Here we conducted a genome-wide association study to identify single nucleotide polymorphisms (SNPs) associated with response to anthracycline- and taxane-based neoadjuvant chemotherapy in breast cancer patients. In the discovery stage, we divided 92 patients who received anthracycline-based neoadjuvant chemotherapy into 2 groups according to pathologic response and performed a genome-wide study using Affymetrix SNP6.0 genechip. Of 389,795 SNPs associated with pathologic complete response (pCR), we identified 2 SNPs, rs6044100 and rs1799937, that were significantly associated with pCR after neoadjuvant chemotherapy. In the validation stage, genotype analysis of samples from an independent cohort of 401 patients who received anthracycline-based neoadjuvant regimens and 467 patients who received taxane-based regimens was performed using sequencing analysis. We found that only SNP rs1799937, located in the WT1 gene, was associated with pCR after anthracycline-based neoadjuvant therapy (AA vs GG; odds ratio [OR], 2.81; 95% confidence interval [CI], 1.13-6.98; P < 0.05) but not after taxane-based neoadjuvant therapy (AA vs GG; OR, 0.85; 95% CI, 0.36-2.04; P = 0.72). These results suggest that WT1 may be a potential target of anthracycline-based neoadjuvant therapy for breast cancer.

The use of scalp cooling for chemotherapy-induced hair loss

Chemotherapy-induced hair loss is a common and distressing side effect of cancer therapy and is one of the major unmet challenges in cancer management. Scalp cooling can prevent chemotherapy-induced hair loss in some cancer patients with solid tumours receiving certain chemotherapy regimens. Recent evidence indicates that this technique does not increase the risk of scalp metastasis. A reduction in post-chemotherapy infusion duration of scalp cooling and the advancement in cool cap technology may assist clinicians in promoting scalp cooling to cancer patients. This article discusses recent research, scalp cooling guidelines, products available and implications for nurses and their organisations in providing scalp cooling. It also considers recent advancements in identifying genes associated with chemotherapy-induced hair loss and international research collaborations including a registry and a 'chemotherapy-induced hair loss action group'--all striving to improve the patient experience of chemotherapy-induced hair loss.

Clinical association between pharmacogenomics and adverse drug reactions

Adverse drug reactions (ADRs) are a major public health concern and cause significant patient morbidity and mortality. Pharmacogenomics is the study of how genetic polymorphisms affect an individual's response to pharmacotherapy at the level of a whole genome. This article updates our knowledge on how genetic polymorphisms of important genes alter the risk of ADR occurrence after an extensive literature search. To date, at least 244 pharmacogenes identified have been associated with ADRs of 176 clinically used drugs based on PharmGKB. At least 28 genes associated with the risk of ADRs have been listed by the Food and Drug Administration as pharmacogenomic biomarkers. With the availability of affordable and reliable testing tools, pharmacogenomics looks promising to predict, reduce, and minimize ADRs in selected populations.

Progress in understanding the genomic basis for adverse drug reactions: a comprehensive review and focus on the role of ethnicity

A major goal of the field of pharmacogenomics is to identify the genomic causes of serious adverse drug reactions (ADRs). Increasingly, genome-wide association studies (GWAS) have been used to achieve this goal. In this article, we review recent progress in the identification of genetic variants associated with ADRs using GWAS and discuss emerging themes from these studies. We also compare aspects of GWAS for ADRs to GWAS for common diseases. In the second part of the article, we review progress in performing pharmacogenomic research in multi-ethnic populations and discuss the challenges and opportunities of investigating genetic causes of ADRs in ethnically diverse patient populations.

Prediction of breast cancer survival using clinical and genetic markers by tumor subtypes

PURPOSE

To identify the genetic variants associated with breast cancer survival, a genome-wide association study (GWAS) was conducted of Korean breast cancer patients.

METHODS

From the Seoul Breast Cancer Study (SEBCS), 3,226 patients with breast cancer (1,732 in the discovery and 1,494 in the replication set) were included in a two-stage GWAS on disease-free survival (DFS) by tumor subtypes based on hormone receptor (HR) and human epidermal growth factor receptor 2 (HER2). The associations of the re-classified combined prognostic markers through recursive partitioning analysis (RPA) of DFS for breast cancer were assessed with the Cox proportional hazard model. The prognostic predictive values of the clinical and genetic models were evaluated by Harrell's C.

RESULTS

In the two-stage GWAS stratified by tumor subtypes, rs166870 and rs10825036 were consistently associated with DFS in the HR+ HER2- and HR- HER2- breast cancer subtypes, respectively (Prs166870 = 2.88 × 10(-7) and Prs10825036 = 3.54 × 10(-7) in the combined set). When patients were classified by the RPA in each subtype, genetic factors contributed significantly to differentiating the high risk group associated with DFS inbreast cancer, specifically the HR+ HER2- (P discovery=1.18 × 10(-8) and P replication = 2.08 × 10(-5)) and HR- HRE2- subtypes (P discovery = 2.35 × 10(-4) and P replication = 2.60 × 10(-2)). The inclusion of the SNPs tended to improve the performance of the prognostic models consisting of age, TNM stage and tumor subtypes based on ER, PR, and HER2 status.

CONCLUSION

Combined prognostic markers that include clinical and genetic factors by tumor subtypes could improve the prediction of survival in breast cancer.

Genome-wide association study: a useful tool to identify common genetic variants associated with drug toxicity and efficacy in cancer pharmacogenomics

In recent years, the utilization of genome-wide association study (GWAS) has proved to be a beneficial method to identify novel common genetic variations not only for disease susceptibility but also for drug efficacy and drug-induced toxicity, creating a field of pharmacogenomics studies. In addition, the findings from GWAS also generate new biologic hypotheses that could improve the understanding of pathophysiology for disease or the mechanism of drug-induced toxicity. This review highlights the implications of GWAS that have been published to date and discusses the successes as well as challenges of using GWAS in cancer pharmacogenomics. The aim of pharmacogenomics is to realize the vision of personalized medicine; it is hoped that through GWAS, novel common genetic variations could be identified to predict clinical outcome and/or toxicity in cancer therapies that subsequently could be implemented to improve the quality of lives of patients with cancer. Nevertheless, given the complexity of cancer therapies, underpowered studies, and large heterogeneity of study designs, collaborative efforts are needed to validate these findings and overcome the limitations of GWA studies before clinical implementation. See all articles in this ccr focus section, "Progress in pharmacodynamic endpoints."

Familiarity, opinions, experiences and knowledge about scalp cooling: a Dutch survey among breast cancer patients and oncological professionals

Objective:

Scalp cooling (SC) is applied to reduce chemotherapy-induced alopecia (CIA). The aim of this study was to investigate patients’ familiarity and opinions and oncological professionals’ attitude and knowledge about SC in the Netherlands.

Methods:

Ex breast cancer patients, nurses and medical oncologists (MDs) from SC and non-SC hospitals filled out questionnaires.

Results:

The majority of MDs and nurses were satisfied with the results of SC, as were SC patients. Over 33% of MDs and nurses perceived their knowledge level insufficient to inform patients about effectiveness, which was over 43% for information about safety. MDs main reason to not apply SC was doubt about effectiveness and safety. Nurses generally offered SC to a minority of eligible patients. Patients were frequently unfamiliar with SC before diagnosis. Seventy percent of SC patients with insufficient results (20/52) reported to mind it very much. With expected success rates of 35% and 50%, respectively, 36% and 54% of patients would use SC again.

Conclusion:

Room for improvement has been shown for both patients’ familiarity and oncological professionals’ knowledge about SC. Sharing knowledge about results, safety and patients’ experiences will improve patient counseling and SC availability. The results of this survey led to the development of a national standard on CIA and SC.

Quality control metrics improve repeatability and reproducibility of single-nucleotide variants derived from whole-genome sequencing

Although many quality control (QC) methods have been developed to improve the quality of single-nucleotide variants (SNVs) in SNV-calling, QC methods for use subsequent to single-nucleotide polymorphism-calling have not been reported. We developed five QC metrics to improve the quality of SNVs using the whole-genome-sequencing data of a monozygotic twin pair from the Korean Personal Genome Project. The QC metrics improved both repeatability between the monozygotic twin pair and reproducibility between SNV-calling pipelines. We demonstrated the QC metrics improve reproducibility of SNVs derived from not only whole-genome-sequencing data but also whole-exome-sequencing data. The QC metrics are calculated based on the reference genome used in the alignment without accessing the raw and intermediate data or knowing the SNV-calling details. Therefore, the QC metrics can be easily adopted in downstream association analysis.