Human Genomics最新文献

Background: Polygenic risk scores (PRS) derived from European individuals have reduced portability across global populations, limiting their clinical implementation at worldwide scale. Here, we investigate the performance of a wide range of PRS models across four ancestry groups (Africans, Europeans, East Asians, and South Asians) for 14 conditions of high-medical interest.

Methods: To select the best-performing model per trait, we first compared PRS performances for publicly available scores, and constructed new models using different methods (LDpred2, PRS-CSx and SNPnet). We used 285 K European individuals from the UK Biobank (UKBB) for training and 18 K, including diverse ancestries, for testing. We then evaluated PRS portability for the best models in Europeans and compared their accuracies with respect to the best PRS per ancestry. Finally, we validated the selected PRS models using an independent set of 8,417 individuals from Biobank of the Americas-Genomelink (BbofA-GL); and performed a PRS-Phewas.

Results: We confirmed a decay in PRS performances relative to Europeans when the evaluation was conducted using the best-PRS model for Europeans (51.3% for South Asians, 46.6% for East Asians and 39.4% for Africans). We observed an improvement in the PRS performances when specifically selecting ancestry specific PRS models (phenotype variance increase: 1.62 for Africans, 1.40 for South Asians and 0.96 for East Asians). Additionally, when we selected the optimal model conditional on ancestry for CAD, HDL-C and LDL-C, hypertension, hypothyroidism and T2D, PRS performance for studied populations was more comparable to what was observed in Europeans. Finally, we were able to independently validate tested models for Europeans, and conducted a PRS-Phewas, identifying cross-trait interplay between cardiometabolic conditions, and between immune-mediated components.

Conclusion: Our work comprehensively evaluated PRS accuracy across a wide range of phenotypes, reducing the uncertainty with respect to which PRS model to choose and in which ancestry group. This evaluation has let us identify specific conditions where implementing risk-prioritization strategies could have practical utility across diverse ancestral groups, contributing to democratizing the implementation of PRS.

Human papillomavirus (HPV) drives cervical cancer (CaCx) pathogenesis and viral oncoproteins jeopardize global gene expression in such cancers. In this study, our aim was to identify differentially expressed coding (DEcGs) and long noncoding RNA genes (DElncGs) specifically sense intronic and Natural Antisense Transcripts as they are located in the genic regions and may have a direct influence on the expression pattern of their neighbouring coding genes. We compared HPV16-positive CaCx patients (N = 44) with HPV-negative normal individuals (N = 34) by employing strand-specific RNA-seq and determined the relationships between DEcGs and DElncGs and their clinical implications. By performing Gene set enrichment and protein-protein interaction (PPI) analyses of DEcGs, we identified enrichment of processes crucial for abortive virus life cycle and cancer progression. The DEcGs formed 16 gene clusters which we identified through Molecular Complex Detection (MCODE) plugin of Cytoscape. All the gene clusters portrayed cancer-related functions. We recorded significantly correlated expression levels of 79 DElncGs with DEcGs at proximal genomic loci based on Pearson's Correlation coefficients. Of these gene pairs, 24 pairs portrayed significantly altered correlation coefficients among patients, compared to normal individuals. Of these, 6 DEcGs of 6 such gene pairs, belonged to 5 of the identified gene clusters, one of which was survival-associated. Out of the 24 correlated DEcG: DElncG pairs, we identified 3 pairs, where expression of both members was significantly associated with patient overall survival. The findings justify the cooperative roles of these gene pairs, in patient prognostication, thereby bearing immense potential for translation. Thus, elucidation of correlative strengths between paired DElncGs and DEcGs in patient and normal samples, could serve as a foundation for identification of therapeutic and prognostic targets of HPV16-positive CaCx.

Background: Variant interpretation is essential for identifying patients' disease-causing genetic variants amongst the millions detected in their genomes. Hundreds of Variant Impact Predictors (VIPs), also known as Variant Effect Predictors (VEPs), have been developed for this purpose, with a variety of methodologies and goals. To facilitate the exploration of available VIP options, we have created the Variant Impact Predictor database (VIPdb).

Results: The Variant Impact Predictor database (VIPdb) version 2 presents a collection of VIPs developed over the past three decades, summarizing their characteristics, ClinGen calibrated scores, CAGI assessment results, publication details, access information, and citation patterns. We previously summarized 217 VIPs and their features in VIPdb in 2019. Building upon this foundation, we identified and categorized an additional 190 VIPs, resulting in a total of 407 VIPs in VIPdb version 2. The majority of the VIPs have the capacity to predict the impacts of single nucleotide variants and nonsynonymous variants. More VIPs tailored to predict the impacts of insertions and deletions have been developed since the 2010s. In contrast, relatively few VIPs are dedicated to the prediction of splicing, structural, synonymous, and regulatory variants. The increasing rate of citations to VIPs reflects the ongoing growth in their use, and the evolving trends in citations reveal development in the field and individual methods.

Conclusions: VIPdb version 2 summarizes 407 VIPs and their features, potentially facilitating VIP exploration for various variant interpretation applications. VIPdb is available at  https://genomeinterpretation.org/vipdb.

We describe the machine learning tool that we applied in the CAGI 6 experiment to predict whether single residue mutations in proteins are deleterious or benign. This tool was trained using only single sequences, i.e., without multiple sequence alignments or structural information. Instead, we used global characterizations of the protein sequence. Training and testing data for human gene mutations was obtained from ClinVar (ncbi.nlm.nih.gov/pub/ClinVar/), and for non-human gene mutations from Uniprot (www.uniprot.org). Testing was done on post-training data from ClinVar. This testing yielded high AUC and Matthews correlation coefficient (MCC) for well trained examples but low generalizability. For genes with either sparse or unbalanced training data, the prediction accuracy is poor. The resulting prediction server is available online at http://www.mamiris.com/Shoni.cagi6.

The KidGen Collaborative's Policy Implementation Workshop 2023 celebrated the 10th anniversary of Australia's first kidney genetics clinic in Brisbane. This event marked the establishment of a national network now comprising 19 kidney genetics clinics across Australia, all dedicated to providing equitable access to genomic testing for families affected by genetic kidney diseases. The workshop reflected on past progress and outlined future objectives for kidney genetics in Australia, recognising the collaborative efforts of clinical teams, researchers, and patients. Key insights from the workshop are documented in the proceedings.

Background: Recent studies suggested that genetic variants associated with monogenic bone disorders were involved in the pathogenesis of atypical femoral fractures (AFF). Here, we aim to identify rare genetic variants by whole exome sequencing in genes involved in monogenic rare skeletal diseases in 12 women with AFF and 4 controls without any fracture.

Results: Out of 33 genetic variants identified in women with AFF, eleven (33.3%) were found in genes belonging to the Wnt pathway (LRP5, LRP6, DAAM2, WNT1, and WNT3A). One of them was rated as pathogenic (p.Pro582His in DAAM2), while all others were rated as variants of uncertain significance according to ClinVar and ACMG criteria.

Conclusions: Osteoporosis, rare bone diseases, and AFFs may share the same genes, thus making it even more difficult to identify unique risk factors.

Background: The international disclosure of Chinese human genetic data continues to be a contentious issue in China, generating public debates in both traditional and social media channels. Concerns have intensified after Chinese scientists' research on pangenome data was published in the prestigious journal Nature.

Methods: This study scrutinized microblogs posted on Weibo, a popular Chinese social media site, in the two months immediately following the publication (June 14, 2023-August 21, 2023). Content analysis was conducted to assess the nature of public responses, justifications for positive or negative attitudes, and the users' overall knowledge of how Chinese human genetic information is regulated and managed in China.

Results: Weibo users displayed contrasting attitudes towards the article's public disclose of pangenome research data, with 18% positive, 64% negative, and 18% neutral. Positive attitudes came primarily from verified government and media accounts, which praised the publication. In contrast, negative attitudes originated from individual users who were concerned about national security and health risks and often believed that the researchers have betrayed China. The benefits of data sharing highlighted in the commentaries included advancements in disease research and scientific progress. Approximately 16% of the microblogs indicated that Weibo users had misunderstood existing regulations and laws governing data sharing and stewardship.

Conclusions: Based on the predominantly negative public attitudes toward scientific data sharing established by our study, we recommend enhanced outreach by scientists and scientific institutions to increase the public understanding of developments in genetic research, international data sharing, and associated regulations. Additionally, governmental agencies can alleviate public fears and concerns by being more transparent about their security reviews of international collaborative research involving Chinese human genetic data and its cross-border transfer.

Sitosterolemia is a rare inherited disorder caused by mutations in the ABCG5/ABCG8 genes. These genes encode proteins involved in the transport of plant sterols. Mutations in these genes lead to decreased excretion of phytosterols, which can accumulate in the body and lead to a variety of health problems, including premature coronary artery disease. We conducted the first genome-wide association study (GWAS) in the Middle East/North Africa population to identify genetic determinants of plant sterol levels in Qatari people. GWAS was performed on serum levels of β-sitosterol and campesterol using the Metabolon platform from Qatar Biobank (QBB) and genome sequence data provided by Qatar Genome Program. A trans-ancestry meta-analysis of data from our Qatari cohort with summary statistics from a previously published large cohort (9758 subjects) of European ancestry was conducted. Using conditional analysis, we identified two independent single nucleotide polymorphisms associated with β-sitosterol (rs145164937 and rs4299376), and two others with campesterol (rs7598542 and rs75901165) in the Qatari population in addition to previously reported variants. All of them map to the ABCG5/8 locus except rs75901165 which is located within the Intraflagellar Transport 43 (IFT43) gene. The meta-analysis replicated most of the reported variants, and our study provided significant support for the association of variants in SCARB1 and ABO with sitosterolemia. Evaluation of a polygenic risk score devised from European GWAS data showed moderate performance when applied to QBB (adjusted-R² = 0.082). These findings provide new insights into the genetic architecture of phytosterol metabolism while showing the importance including under-represented populations in future GWAS studies.

Background: Isolated methylmalonic acidemia, an autosomal recessive disorder of propionate metabolism, is usually caused by mutations in the methylmalonyl-CoA mutase gene (mut-type). Because no universal consensus was made on whether mut-type methylmalonic acidemia should be included in newborn screening (NBS), we aimed to compare the outcome of this disorder detected by NBS with that detected clinically and investigate the influence of NBS on the disease course.

Design & methods: In this study, 168 patients with mut-type methylmalonic acidemia diagnosed by NBS were compared to 210 patients diagnosed after disease onset while NBS was not performed. Clinical data of these patients from 7 metabolic centers in China were analyzed retrospectively, including initial manifestations, biochemical metabolites, the responsiveness of vitamin B12 therapy, and gene variation, to explore different factors on the long-term outcome.

Results: By comparison of the clinically-diagnosed patients, NBS-detected patients showed younger age at diagnosis, less incidence of disease onset, better responsiveness of vitamin B12, younger age at start of treatment, lower levels of biochemical features before and after treatment, and better long-term prognosis (P < 0.01). Onset of disease, blood C3/C2 ratio and unresponsiveness of vitamin B12 were more positively associated with poor outcomes of patients whether identified by NBS. Moreover, the factors above as well as older age at start of treatment were positively associated with mortality.

Conclusions: This research highly demonstrated NBS could prevent major disease-related events and allow an earlier treatment initiation. As a key prognostic factor, NBS is beneficial for improving the overall survival of infants with mut-type methylmalonic acidemia.

Background: Pharmacogenomics (PGx) constitutes an important part of personalized medicine and has several clinical applications. PGx role in clinical practice is known, however, it has not been widely adopted yet. In this study, we aim to investigate the perspectives of Greek physicians regarding the implementation of PGx testing in clinical practice and the key issues associated with it.

Methods: Fourteen interviews were conducted with physicians of various specialties for which PGx applications are available. A semi-structured interview guide was utilized based on the Consolidated Framework for Implementation Research (CFIR) context and the Diffusion of Innovation model. Transcripts were coded independently and compared by two members of the research team. Descriptive statistics were generated using Microsoft Excel.

Results: Six main themes emerged: awareness and use of PGx testing; source of information; key stakeholders of the PGx supply chain, their interactions and change agents; clinical benefit and significance of PGx testing; barriers and lack of reimbursement; and recommendations to boost the PGx adoption rate. Most respondents were aware of PGx applications, but only three had already recommended PGx testing. Peer-reviewed journals along with clinical guidelines were regarded as the most used source of information while stakeholders of the PGx supply chain were discussed. PGx was considered that promote patient-centered care, enhance medication clinical effectiveness, decrease the risk of side effects, and reduce healthcare costs. Lack of reimbursement, scarcity of resources, and high PGx cost were the foremost barriers affecting PGx adoption.

Conclusions: It was concluded that if case PGx testing is reimbursed and physicians' training is reinforced, PGx implementation will be boosted and improved shortly.