Human Genome Research Research Articles

APOL1 Bi- and Monoallelic Variants and Chronic Kidney Disease in West Africans.

Apolipoprotein L1 gene (APOL1) variants are risk factors for chronic kidney disease (CKD) among Black Americans. Data are sparse on the genetic epidemiology of CKD and the clinical association of APOL1 variants with CKD in West Africans, a major group in the Black population. We conducted a case-control study involving participants from Ghana and Nigeria who had CKD stages 2 through 5, biopsy-proven glomerular disease, or no kidney disease. We analyzed the association of CKD with APOL1 variants among participants with high-risk genotypes (two APOL1 risk alleles) and those with low-risk genotypes (fewer than two APOL1 risk alleles) by fitting logistic-regression models that controlled for covariates, including clinical site, age, and sex. Among 8355 participants (4712 with CKD stages 2 through 5, 866 with glomerular diseases, and 2777 with no kidney disease), the prevalence of monoallelic APOL1 variants was 43.0% and that of biallelic APOL1 variants was 29.7%. Participants with two APOL1 risk alleles had higher odds of having CKD than those with one risk allele or no risk alleles (adjusted odds ratio, 1.25; 95% confidence interval [CI], 1.11 to 1.40), as well as higher odds of focal segmental glomerulosclerosis (adjusted odds ratio, 1.84; 95% CI, 1.30 to 2.61). Participants with one APOL1 risk allele had higher odds of having CKD than those with no risk alleles (adjusted odds ratio, 1.18; 95% CI, 1.04 to 1.33), as well as higher odds of focal segmental glomerulosclerosis (adjusted odds ratio, 1.61; 95% CI, 1.04 to 2.48). The inclusion of covariates did not modify the association of monoallelic and biallelic APOL1 variants with CKD or focal segmental glomerulosclerosis. In this study, monoallelic APOL1 variants were associated with 18% higher odds of CKD and 61% higher odds of focal segmental glomerulosclerosis; biallelic APOL1 variants were associated with 25% higher odds of CKD and 84% higher odds of focal segmental glomerulosclerosis. (Funded by the National Human Genome Research Institute and others.).

Neurodevelopmental Disorder Caused by Deletion of CHASERR, a lncRNA Gene

SummaryCHASERR encodes a human long noncoding RNA (lncRNA) adjacent to CHD2, a coding gene in which de novo loss-of-function variants cause developmental and epileptic encephalopathy. Here, we report our findings in three unrelated children with a syndromic, early-onset neurodevelopmental disorder, each of whom had a de novo deletion in the CHASERR locus. The children had severe encephalopathy, shared facial dysmorphisms, cortical atrophy, and cerebral hypomyelination — a phenotype that is distinct from the phenotypes of patients with CHD2 haploinsufficiency. We found that the CHASERR deletion results in increased CHD2 protein abundance in patient-derived cell lines and increased expression of the CHD2 transcript in cis. These findings indicate that CHD2 has bidirectional dosage sensitivity in human disease, and we recommend that other lncRNA-encoding genes be evaluated, particularly those upstream of genes associated with mendelian disorders. (Funded by the National Human Genome Research Institute and others.)

Identifying Gene Variants That Are Pathogenic In Osteoporosis Using An Omics Data And Bioinformatics Approach

Introduction. The biological cause of osteoporosis, a metabolic bone disease, is osteoclastic bone resorption that is not offset by osteoblastic bone synthesis. Fractures become more likely as a result of the bones being brittle and weak. Common genetic variants that indicate hereditary susceptibility factors to osteoporosis in the general population, as well as mutations affecting specific genes that cause uncommon monogenic causes of osteoporosis, are the two main types of osteoporosis. Bone defects can now be caused by numerous additional genes. In this study, we aimed to identify variants of this pathogen across continents using genome-based and bioinformatics methodologies. Methods. We integrated osteoporosis-associated variants into this study using various bioinformatics-based techniques by using GWAS data from the National Human Genome Research Institute (NHGRI). Results. We found that the variant rs3742909 is likely to cause osteoporosis. SMOC1 gene expression in whole blood tissue also appears to be affected by this variant. We found that this genomic variant requires additional research to validate functional and clinical studies in patients with osteoporosis. Conclusions. We suggest that better understanding of disease susceptibility, including osteoporosis, can be achieved through the merging of genome-based databases and bioinformatics. Our goal is to validate the findings of this study both in vitro and in vivo during the preclinical stage.

Indigenous Peoples' human genomic sovereignty: Lessons for Africa.

Human genomics research with indigenous peoples has often been characterised by tension between the 'western' science ideologies and indigenous peoples' cultural beliefs in relation to their human genetic resources and data. This article explores this tension from the lens of the concept of indigenous peoples' human genomic sovereignty and tests the applicability of the concept in Africa. The article achieves this by first highlighting the tension between 'western' science and indigenous peoples through three case studies from Canada, the USA, and South Africa. It then analyses indigenous peoples' human genomic sovereignty in the USA and Canada and compares it with the notion of indigenous peoples' sovereignty in Africa. The article concludes by highlighting lessons that indigenous groups in Africa can draw from the USA and Canada in their quest for human genomic sovereignty.

Genotype imputation in human genomic studies.

Imputation is a method that supplies missing information about genetic variants that could not be directly genotyped with DNA microarrays or low-coverage sequencing. Imputation plays a critical role in genome-wide association studies (GWAS). It leads to a significant increase in the number of studied variants, which improves the resolution of the method and enhances the comparability of data obtained in different cohorts and/or by using different technologies, which is important for conducting meta-analyses. When performing imputation, genotype information from the study sample, in which only part of the genetic variants are known, is complemented using the standard (reference) sample, which has more complete genotype data (most often the results of whole-genome sequencing). Imputation has become an integral part of human genomic research due to the benefits it provides and the increasing availability of imputation tools and reference sample data. This review focuses on imputation in human genomic research. The first section of the review provides a description of technologies for obtaining information about human genotypes and characteristics of these types of data. The second section describes the imputation methodology, lists the stages of its implementation and the corresponding programs, provides a description of the most popular reference panels and methods for assessing the quality of imputation. The review concludes with examples of the use of imputation in genomic studies of samples from Russia. This review shows the importance of imputation, provides information on how to carry it out, and systematizes the results of its application using Russian samples.

Ethical, Legal, and Social Implications of Gene-Environment Interaction Research.

Many complex disorders are impacted by the interplay of genetic and environmental factors. In gene-environment interactions (GxE), an individual's genetic and epigenetic makeup impacts the response to environmental exposures. Understanding GxE can impact health at the individual, community, and population levels. The rapid expansion of GxE research in biomedical studies for complex diseases raises many unique ethical, legal, and social implications (ELSIs) that have not been extensively explored and addressed. This review article builds on discussions originating from a workshop held by the National Institute of Environmental Health Sciences (NIEHS) and the National Human Genome Research Institute (NHGRI) in January 2022, entitled: "Ethical, Legal, and Social Implications of Gene-Environment Interaction Research." We expand upon multiple key themes to inform broad recommendations and general guidance for addressing some of the most unique and challenging ELSI in GxE research. Key takeaways include strategies and approaches for establishing sustainable community partnerships, incorporating social determinants of health and environmental justice considerations into GxE research, effectively communicating and translating GxE findings, and addressing privacy and discrimination concerns in all GxE research going forward. Additional guidelines, resources, approaches, training, and capacity building are required to further support innovative GxE research and multidisciplinary GxE research teams.

Abstract B167: Genomics and cancer clinical trials navigator training: Results from a systematic review of the literature

Abstract Introduction: Trained cancer navigators have demonstrated success in improving outcomes for cancer patients. Trainings provided by the American Cancer Society and other organizations equip navigators with the knowledge, skills and experience to support patients and address barriers to cancer-related care and survivorship. Racial/ethnic minorities continue to be underrepresented in cancer clinical trials and are less likely to receive genomic counseling and testing. There is a notable gap in the availability of cancer navigator training in genomic and clinical trials. This study used a systematic review of the literature and consultations with Genomics and Cancer Clinical Trial (CCT) experts to inform the development of cancer navigation training curriculum. Methods: Two reviewers searched the PubMed database for peer-reviewed studies published through October 2022. Key MeSH terms included cancer, genetics, and training. An ancestor search of relevant articles was also conducted. Following title screening, eleven articles were selected for abstract and full-text review. Eight articles met all the inclusion criteria from which we extracted the 1) trainee population, 2) theoretical frameworks used, 3) program design and format, 4) curricular components, and 5) outcomes. New Data: Only seven articles on the topic of navigator training in genomics within the context of CCT were identified in the search. Training participants were diverse and were located within the United States and abroad. One training program was developed for bilingual (English/Spanish) navigators, one was tailored for cancer survivors who became navigators and two programs trained navigators for specific cancer types (e.g., colorectal cancer). Social cognitive theory (SCT) was used in two of the training programs. Other adult learning theories and intervention mapping for program development were also used in training development. The process for designing navigator trainings included: conducting discussion groups; interviews and surveys; engaging advisory boards; and adapting the National Human Genomics Research Institute modules and other resources. The curricula components included in-person and web-based; single semester or year-long sessions; formal coursework; lectures; role-playing; video viewing; tours of facilities; demonstrations; short writing assignments; action plans; case studies; story- telling; discussion and networking; assessment/evaluation; and refresher sessions. Modules addressed attitudes, barrier assessment and resolution, knowledge, self-efficacy, and communication. Conclusion: The peer-reviewed literature on navigator training describes some curricular elements that measure and address knowledge about genomics and CCT as well as the skills needed to increase self-efficacy to navigate for genetic studies and cancer clinical trials. However, the field of CCT lacks a consistent and widely used program aimed at training navigators in the integral role of genetics in precision medicine. These findings informed the design of our ACS-funded curriculum. Citation Format: Desiree Rivers, Robina Josiah Willock, Victoria Churchill. Genomics and cancer clinical trials navigator training: Results from a systematic review of the literature [abstract]. In: Proceedings of the 17th AACR Conference on the Science of Cancer Health Disparities in Racial/Ethnic Minorities and the Medically Underserved; 2024 Sep 21-24; Los Angeles, CA. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2024;33(9 Suppl):Abstract nr B167.

Ethical Aspects of Human Genome Research in Sports-A Narrative Review.

Human genome research in sports raises complex ethical considerations regarding the intersection of genetics and athletic performance. Pursuing genetic enhancements must uphold fairness, equality, and respect for human dignity. This narrative review explores the ethical dimensions of human genome research in sports, its potential implications on athletes, and the integrity of sports. As a narrative review, this study synthesizes the existing literature and expert insights to examine the ethical aspects of human genome research in sports. This study extensively examined the current literature on genetics, sports performance, ethical concerns, human rights, and legal regulations within the European context. The literature was searched using the SPORTDiscus, Scopus, Google Scholar, and PubMed databases. Exploring human genome research in sports reveals significant ethical implications, including potential genetic discrimination, impacts on human rights, and creating a genetic underclass of athletes. There are also definite benefits surrounding genetic testing. In conclusion, this review contends that integrating ethical considerations into developing and applying genetic technologies in sports is crucial to upholding fundamental principles of fairness, equality, and respect for human dignity. It stresses the importance of open and inclusive dialogue about the potential consequences of genetic advancements on athletic performance, future generations, and the integrity of sports.

Semi-supervised machine learning method for predicting homogeneous ancestry groups to assess Hardy-Weinberg equilibrium in diverse whole-genome sequencing studies

Large-scale, multi-ethnic whole-genome sequencing (WGS) studies, such as the National Human Genome Research Institute Genome Sequencing Program's Centers for Common Disease Genomics (CCDG), play an important role in increasing diversity for genetic research. Before performing association analyses, assessing Hardy-Weinberg equilibrium (HWE) is a crucial step in quality control procedures to remove low quality variants and ensure valid downstream analyses. Diverse WGS studies contain ancestrally heterogeneous samples; however, commonly used HWE methods assume that the samples are homogeneous. Therefore, directly applying these to the whole dataset can yield statistically invalid results. To account for this heterogeneity, HWE can be tested on subsets of samples that have genetically homogeneous ancestries and the results aggregated at each variant. To facilitate valid HWE subset testing, we developed a semi-supervised learning approach that predicts homogeneous ancestries based on the genotype. This method provides a convenient tool for estimating HWE in the presence of population structure and missing self-reported race and ethnicities in diverse WGS studies. In addition, assessing HWE within the homogeneous ancestries provides reliable HWE estimates that will directly benefit downstream analyses, including association analyses in WGS studies. We applied our proposed method on the CCDG dataset, predicting homogeneous genetic ancestry groups for 60,545 multi-ethnic WGS samples to assess HWE within each group.

The Role of Host Genetics and Intestinal Microbiota and Metabolome as a New Insight into IBD Pathogenesis.

Inflammatory bowel disease (IBD) is an incurable, chronic disorder of the gastrointestinal tract whose incidence increases every year. Scientific research constantly delivers new information about the disease and its multivariate, complex etiology. Nevertheless, full discovery and understanding of the complete mechanism of IBD pathogenesis still pose a significant challenge to today's science. Recent studies have unanimously confirmed the association of gut microbial dysbiosis with IBD and its contribution to the regulation of the inflammatory process. It transpires that the altered composition of pathogenic and commensal bacteria is not only characteristic of disturbed intestinal homeostasis in IBD, but also of viruses, parasites, and fungi, which are active in the intestine. The crucial function of the microbial metabolome in the human body is altered, which causes a wide range of effects on the host, thus providing a basis for the disease. On the other hand, human genomic and functional research has revealed more loci that play an essential role in gut homeostasis regulation, the immune response, and intestinal epithelial function. This review aims to organize and summarize the currently available knowledge concerning the role and interaction of crucial factors associated with IBD pathogenesis, notably, host genetic composition, intestinal microbiota and metabolome, and immune regulation.

Beyond the Beat: Understanding Inherited Risk and Therapeutic Opportunities in Cardiovascular Diseases with Emphasis on Inherited Cardiomyopathies and Inherited Arrhythmic Syndromes

Over the past three decades, significant progress has been made in elucidating the intricate connection between genetic predispositions and cardiovascular diseases (CVDs). Through extensive investigation, numerous genetic variants linked to various cardiovascular conditions have been discovered, shedding crucial light on the underlying biological mechanisms and pathways. These discoveries have not only revolutionized risk assessment for patients but have also paved the way for personalized treatment strategies, allowing healthcare providers to tailor interventions according to individual genetic profiles. Furthermore, genetic testing has facilitated cascade screening, enabling the early identification and intervention of potential cardiovascular issues among at-risk biological family members. This review aims to comprehensively summarize the current state of knowledge regarding inherited risk and novel insights from human genome and epigenome research, as well as therapeutic opportunities in CVDs with special emphasis on inherited cardiomyopathies and inherited arrhythmic syndromes. The newest translational trials for CVDs and pharmaceutical approaches are discussed, including gene therapy options for heart failure and cardiomyopathies.

Benefit-Sharing by Design: A Call to Action for Human Genomics Research.

The ethical standards for the responsible conduct of human research have come a long way; however, concerns surrounding equity remain in human genetics and genomics research. Addressing these concerns will help society realize the full potential of human genomics research. One outstanding concern is the fair and equitable sharing of benefits from research on human participants. Several international bodies have recognized that benefit-sharing can be an effective tool for ethical research conduct, but international laws, including the Convention on Biological Diversity and its Nagoya Protocol on Access and Benefit-Sharing, explicitly exclude human genetic and genomic resources. These agreements face significant challenges that must be considered and anticipated if similar principles are applied in human genomics research. We propose that benefit-sharing from human genomics research can be a bottom-up effort and embedded into the existing research process. We propose the development of a "benefit-sharing by design" framework to address concerns of fairness and equity in the use of human genomic resources and samples and to learn from the aspirations and decade of implementation of the Nagoya Protocol.

Mid-pass whole-genome sequencing in a Malagasy cohort uncovers body composition associations

The majority of human genomic research studies have been conducted in European-ancestry cohorts, reducing the likelihood of detecting potentially novel and globally impactful findings. Here, we present mid-pass whole-genome sequencing data and a genome-wide association study in a cohort of 264 self-reported Malagasy individuals from three locations on the island of Madagascar. We describe genetic variation in this Malagasy cohort, providing insight into the shared and unique patterns of genetic variation across the island. We observe phenotypic variation by location and find high rates of hypertension, particularly in the Southern Highlands sampling site, as well as elevated self-reported malaria prevalence in the West Coast site relative to other sites. After filtering to a subset of 214minimally related individuals, we find a number of genetic associations with body composition traits, including many variants that are only observed in African populations or populations with admixed African ancestry from the 1000 Genomes Project. This study highlights the importance of including diverse populations in genomic research for the potential to gain novel insights, even with small cohort sizes. This project was conducted in partnership and consultation with local stakeholders in Madagascar and serves as an example of genomic research that prioritizes community engagement and potentially impacts our understanding of human health and disease.

Beyond Meta-Omics: Functional Genomics in Future Marine Microbiome Research.

When President Bill Clinton and Francis Collins, then the director of the National Human Genome Research Institute, celebrated the near completion of the human genome sequence at the White House in the summer of 2000, it is unlikely that they or anyone else could have predicted the blossoming of meta-omics in the following two decades and their applications in modern human microbiome and environmental microbiome research. This transformation was enabled by the development of high-throughput sequencing technologies and sophisticated computational biology tools and bioinformatics software packages. Today, environmental meta-omics has undoubtedly revolutionized our understanding of ocean ecosystems, providing the genetic blueprint of oceanic microscopic organisms. In this review, I discuss the importance of functional genomics in future marine microbiome research and advocate a position for a gene-centric, bottom-up approach in modern oceanography. I propose that a synthesis of multidimensional approaches is required for a better understanding of the true functionality of the marine microbiome.

Genome Sequencing for Diagnosing Rare Diseases

BackgroundGenetic variants that cause rare disorders may remain elusive even after expansive testing, such as exome sequencing. The diagnostic yield of genome sequencing, particularly after a negative evaluation, remains poorly defined.MethodsWe sequenced and analyzed the genomes of families with diverse phenotypes who were suspected to have a rare monogenic disease and for whom genetic testing had not revealed a diagnosis, as well as the genomes of a replication cohort at an independent clinical center.ResultsWe sequenced the genomes of 822 families (744 in the initial cohort and 78 in the replication cohort) and made a molecular diagnosis in 218 of 744 families (29.3%). Of the 218 families, 61 (28.0%) — 8.2% of families in the initial cohort — had variants that required genome sequencing for identification, including coding variants, intronic variants, small structural variants, copy-neutral inversions, complex rearrangements, and tandem repeat expansions. Most families in which a molecular diagnosis was made after previous nondiagnostic exome sequencing (63.5%) had variants that could be detected by reanalysis of the exome-sequence data (53.4%) or by additional analytic methods, such as copy-number variant calling, to exome-sequence data (10.8%). We obtained similar results in the replication cohort: in 33% of the families in which a molecular diagnosis was made, or 8% of the cohort, genome sequencing was required, which showed the applicability of these findings to both research and clinical environments.ConclusionsThe diagnostic yield of genome sequencing in a large, diverse research cohort and in a small clinical cohort of persons who had previously undergone genetic testing was approximately 8% and included several types of pathogenic variation that had not previously been detected by means of exome sequencing or other techniques. (Funded by the National Human Genome Research Institute and others.)

ACMGA: a reference-free multiple-genome alignment pipeline for plant species

BackgroundThe short-read whole-genome sequencing (WGS) approach has been widely applied to investigate the genomic variation in the natural populations of many plant species. With the rapid advancements in long-read sequencing and genome assembly technologies, high-quality genome sequences are available for a group of varieties for many plant species. These genome sequences are expected to help researchers comprehensively investigate any type of genomic variants that are missed by the WGS technology. However, multiple genome alignment (MGA) tools designed by the human genome research community might be unsuitable for plant genomes.ResultsTo fill this gap, we developed the AnchorWave-Cactus Multiple Genome Alignment (ACMGA) pipeline, which improved the alignment of repeat elements and could identify long (> 50 bp) deletions or insertions (INDELs). We conducted MGA using ACMGA and Cactus for 8 Arabidopsis (Arabidopsis thaliana) and 26 Maize (Zea mays) de novo assembled genome sequences and compared them with the previously published short-read variant calling results. MGA identified more single nucleotide variants (SNVs) and long INDELs than did previously published WGS variant callings. Additionally, ACMGA detected significantly more SNVs and long INDELs in repetitive regions and the whole genome than did Cactus. Compared with the results of Cactus, the results of ACMGA were more similar to the previously published variants called using short-read. These two MGA pipelines identified numerous multi-allelic variants that were missed by the WGS variant calling pipeline.ConclusionsAligning denovo assembled genome sequences could identify more SNVs and INDELs than mapping short-read. ACMGA combines the advantages of AnchorWave and Cactus and offers a practical solution for plant MGA by integrating global alignment, a 2-piece-affine-gap cost strategy, and the progressive MGA algorithm.

Advancing genomics to improve health equity.

Health equity is the state in which everyone has fair and just opportunities to attain their highest level of health. The field of human genomics has fallen short in increasing health equity, largely because the diversity of the human population has been inadequately reflected among participants of genomics research. This lack of diversity leads to disparities that can have scientific and clinical consequences. Achieving health equity related to genomics will require greater effort in addressing inequities within the field. As part of the commitment of the National Human Genome Research Institute (NHGRI) to advancing health equity, it convened experts in genomics and health equity research to make recommendations and performed a review of current literature to identify the landscape of gaps and opportunities at the interface between human genomics and health equity research. This Perspective describes these findings and examines health equity within the context of human genomics and genomic medicine.

Understanding the Gap: A Cross-Sectional Survey of ELSI Scholars’ Dissemination Practices and Translation Goals

Background Researchers engaged in the study of the ethical, legal, and social implications (ELSI) of genetics and genomics are often publicly funded and intend their work to be in the public interest. These features of U.S. ELSI research create an imperative for these scholars to demonstrate the public utility of their work and the expectation that they engage in research that has potential to inform policy or practice outcomes. In support of the fulfillment of this “translational mandate,” the Center for ELSI Resources and Analysis (CERA), funded by the National Human Genome Research Institute (NHGRI), aims to facilitate community-informed, ELSI research results synthesis and dissemination. However, little is known about how ELSI research scholars define the goals of translation and imagine the intended users of their research findings. Methodology We distributed a Qualtrics survey to ELSI scholars that aimed to determine: (1) researchers’ expectations for their research findings in relation to policy or practice outcomes, (2) the stakeholder groups researchers believe could benefit from their research findings, and (3) the methods researchers use to foster the uptake of their findings by those stakeholders. Results Most ELSI researchers surveyed thought there were stakeholders that could benefit from their research findings, including health care professionals, at-risk individuals, patients, and their family members, policy-makers, and researchers/scientists, and expected their research findings to inform the creation or revision of laws, policies, or practice guidelines. Most researchers planned to disseminate findings directly to relevant stakeholders, with fewer expecting dissemination support from research funders, universities, or other entities. Conclusion The broad range of research topics, disciplines, and set of potential end users represented in ELSI reseach complicate the work of a knowledge broker. Nonetheless, the CERA can play an important role in disseminating ELSI results to relevant stakeholders. Further research should explore outreach mechanisms.

Optimized verifiable delegated private set intersection on outsourced private datasets

Private Set Intersection (PSI) has been applied in various fields, such as human genome research, advertising conversion rate analysis, etc. Traditional PSI has the drawback of requiring local devices to be constantly online and needing high storage capacity of the devices. To overcome these issues, many researchers have focused on delegating PSI computation to cloud servers. However, third-party clouds may bring many new challenges. One of the primary concerns is ensuring that the cloud server does not obtain sensitive data when the client outsources their dataset. Additionally, ensuring clients verify the correctness of the results is also a critical issue. In this paper, we propose the optimized verifiable delegated private set intersection protocol on outsourced private datasets (VO-PSI). Our protocol enables clients to verify the correctness of intersection with a negligible probability of incorrect results while being able to guarantee data privacy. Compared with previous research, the verifiability of the protocol has been dramatically improved. We analyze the security of the protocol under the malicious model and conduct experiments to evaluate its efficiency and feasibility.

Causal effect of gut microbiota on pancreatic cancer: A Mendelian randomization and colocalization study.

The causal relationship between gut microbiota (GM) and pancreatic cancer (PC) remains unclear. This study aimed to investigate the potential genes underlying this mechanism. GM Genome-wide association study (GWAS) summary data were from the MiBioGen consortium. PC GWAS data were from the National Human Genome Research Institute-European Bioinformatics Institute (NHGRI-EBI) GWAS Catalogue. To detect the causal relationship between GM and PC, we implemented three complementary Mendelian randomization (MR) methods: Inverse Variance Weighting (IVW), MR-Egger and Weighted Median, followed by sensitivity analyses. Furthermore, we integrated GM GWAS data with blood cis-expression quantitative trait loci (eQTLs) and blood cis-DNA methylation QTL (mQTLs) using Summary data-based Mendelian Randomization (SMR) methods. This integration aimed to prioritize potential GM-affecting genes through SMR analysis of two molecular traits. PC cis-eQTLs and cis-mQTLs were summarized from The Cancer Genome Atlas (TCGA) data. Through colocalization analysis of GM cis-QTLs and PC cis-QTLs data, we identified common genes that influence both GM and PC. Our study found a causal association between GM and PC, including four protective and five risk-associated GM [Inverse Variance Weighted (IVW), p < 0.05]. No significant heterogeneity of instrumental variables (IVs) or horizontal pleiotropy was found. The gene SVBP was identified as a GM-affecting gene using SMR analysis of two molecular traits (FDR<0.05, P_HEIDI>0.05). Additionally, two genes, MCM6 and RPS26, were implicated in the interaction between GM and PC based on colocalization analysis (PPH4>0.5). In summary, this study provides evidence for future research aimed at developing suitable therapeutic interventions and disease prevention.