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At least 19 recordsLinked to original sources
PubMed2025

Gut fungi are associated with human genetic variation and disease risk.

Human genetic determinants of the gut mycobiome remain uninvestigated despite decades of research highlighting tripartite relationships between gut bacteria, genetic background, and disease. Here, we present the first genome-wide association study on the number and types of human genetic loci influencing gut fungi relative abundance. We detect 148 fungi-associated variants (FAVs) across 7 chromosomes that statistically associate with 9 fungal taxa. Of these FAVs, several occur in the protein-coding genes PTPRC, ANAPC10, NAV2, and CDH13. Additional FAVs link to tissue-specific gene expression as fungi-associated expression quantitative trait loci. Notably, the relative abundance of gut yeast Kazachstania associates with genetic variation in CDH13 encoding T-cadherin, a protein linked to cardiovascular disease. Kazachstania forms a causal relationship with cardiovascular disease risk in a mendelian two-sample randomization analysis. These findings establish previously unrecognized connections between human genetics, gut fungi, and chronic disease, broadening the paradigm of human-microbe interactions in the gut to the mycobiome.

Humans↗
PubMed2025

The potential impacts of human genetics on virus emergence.

Human monogenic traits can confer resistance to viral infection in exposed individuals or predisposition to severe disease in infected individuals. Enhanced susceptibility can be driven directly by mutations in genes essential for control of the virus or indirectly via the production of autoantibodies against components of host defense. While the impact of viruses on individuals carrying these genotypes permitted their identification and has been amply studied, little is known about the impact of these human genotypes on the natural history of viruses, including not only persisting but also emerging viruses. We envisage several scenarios, including the possibility that genetically susceptible individuals serve as patient zeros, superspreaders, or mutation incubators, or that genetically resistant individuals even permit the selection of new viral mutants. Viruses are continually shared between individuals and even host species, where they can benefit from adaption to new environments. Current human viruses, as well as novel viruses from animal reservoirs, will continue to threaten the human population. Improvements in the scale of human genomic sequencing and analysis will permit testing hypotheses about the impact of human genetics on the origin and trajectory of viral infections, including future pandemics, which may ultimately help to prevent or curtail impending outbreaks.

Humans↗
PubMed2026

Research on the genome of microorganisms: ethical considerations and recommendations regarding the incidental bystander sequencing of human genetic material.

In genomic research primarily targeting microorganisms (or pathogens), a substantial risk exists that the presence of human genetic bycatch is not sufficiently recognised, and that the potential harm of unwarranted analysis, access, or sharing of human genetic bystander data is also insufficiently acknowledged or mitigated. In this Personal View, we contend that mandatory risk mitigation measures are necessary, more so in view of the likely increase of sharing of materials and pathogen sequence information under the WHO Pandemic Agreement and the related Pathogen Access and Benefit Sharing framework. Based on a joint reflection of the Institutional Review Board and individual researchers at the Institute of Tropical Medicine in Antwerp, Belgium, we propose a four-step approach to mitigate such risks: prevention or early removal of human genetic sequences, secure storage of samples and data, adaptation of informed consent, and targeted ethics review. This approach should contribute to maintaining ethical integrity, protect the rights of individuals and communities, and bolster public trust in the expanding use of untargeted sequencing in global health research.

Humans↗
PubMed2025

Computational modeling of human genetic variants in mice.

Mouse models represent a powerful platform to study genes and variants associated with human diseases. While genome editing technologies have increased the rate and precision of model development, predicting and installing specific types of mutations in mice that mimic the native human genetic context is complicated. Computational tools can identify and align orthologous wild-type genetic sequences from different species; however, predictive modeling and engineering of equivalent mouse variants that mirror the nucleotide and/or polypeptide change effects of human variants remains challenging. Here, we present H2M (human-to-mouse), a computational pipeline to analyze human genetic variation data to systematically model and predict the functional consequences of equivalent mouse variants. We show that H2M can integrate mouse-to-human and paralog-to-paralog variant mapping analyses with precision genome editing pipelines to devise strategies tailored to model specific variants in mice. We leveraged these analyses to establish a database containing > 3 million human-mouse equivalent mutation pairs, as well as in silico-designed base and prime editing libraries to engineer 4,944 recurrent variant pairs. Using H2M, we also found that predicted pathogenicity and immunogenicity scores were highly correlated between human-mouse variant pairs, suggesting that variants with similar sequence change effects may also exhibit broad interspecies functional conservation. Overall, H2M fills a gap in the field by establishing a robust and versatile computational framework to identify and model homologous variants across species while providing key experimental resources to augment functional genetics and precision medicine applications. The H2M database (including software package and documentation) can be accessed at https://human2mouse.com.

Journal Article↗
PubMed2026

Human genetic variation associates with infection by derived Ugandan M. tuberculosis lineage.

BACKGROUND: Several studies have examined host and pathogen genetic influences on tuberculosis (TB) susceptibility separately, but relatively few studied their combined effects. However, host-pathogen interactions or co-evolution may explain the inability to replicate many reported human genetic effects across global populations and provide additional insight into TB risk. In this study, we address such possible interactions by focusing on the outcome of infection with the L4-Uganda M. tuberculosis sub-lineage and human genetic variants as independent variables. This is possible because the L4-Uganda sub-lineage is both restricted to Uganda and nearby locations and is recent there, compared to other more ancestral L4 lineages. METHODS: Our study consisted of 276 culture-confirmed adult TB cases from a long-standing household contact study. We conducted a genome-wide association study, with infection with L4-Uganda versus L4-NonUganda as the outcome. RESULTS: Multiple loci with results suggestive of association (p<10-5) also demonstrated convergent relevant evidence for strain specific infection via: evidence of gene expression in relevant cells and lung tissue, signatures of natural selection, eQTL expression, and CRISPR screens for immunity-related genes. We also replicated previously published host-pathogen interaction effects, demonstrating that effects seen for other sub-lineages were also present for L4-Uganda. CONCLUSIONS: These results provide evidence for host-pathogen co-evolution in TB, consistent with our previous work, and indicate these interactions involve genes highly relevant to the host immune response to Mycobacterium infection.

GWAS↗
PubMed2025

Human genetic variation reveals FCRL3 is a lymphocyte receptor for Yersinia pestis.

Yersinia pestis is the bacterium responsible for plague, one of the deadliest diseases in history. To discover human genetic determinants of Y. pestis infection, we utilized nearly 1,000 genetically diverse lymphoblastoid cell lines in a cellular genome-wide association study. A nonsynonymous SNP, rs2282284 (N721S), in Fc receptor-like 3 (FCRL3) was associated with bacterial invasion of host cells (p = 9 &#xd7; 10-8). Overexpressed FCRL3 facilitated attachment and invasion of Y. pestis and colocalized with Y. pestis at attachment sites. These properties were variably conserved across the FCRL family, revealing an immunoglobulin-like domain and signaling motifs shared by FCRL3 and FCRL5 to be necessary for attachment and invasion. Direct binding to FCRL5 extracellular domain was confirmed, and B cells (the primary cells that express FCRLs) were preferentially invaded by Y. pestis. Thus, Y. pestis hijacks FCRL proteins, possibly taking advantage of an immune receptor to create a lymphocyte niche during infection.

Yersinia pestis↗
PubMed2025

HCSeeker: A classification tool for human genetic variant hot and cold spots designed for PM1 and benign criteria in the ACMG-AMP guideline.

PURPOSE: The PM1 criterion, which states that a variant is located in a mutational hot spot and/or critical and well-established functional domain without benign variation (such as the active site of an enzyme), is considered moderate evidence for assessing its pathogenicity. Although guidelines from the American College of Medical Genetics and Genomics and the Association for Molecular Pathology are widely adopted, the PM1 criterion remains limited from lacking a reliable database of variant hot spots. Compared with hot spots, cold spots are neglected by the guidelines. To improve variant classification, we suggest including cold spots for supporting benign classifications. Consequently, we have developed the HCSeeker to provide data support for PM1 and the "Benign" criteria. METHODS: HCSeeker uses the Kernel Density Estimation and the Expectation-Maximization algorithm to identify hot- and cold-spot regions. RESULTS: Through HCSeeker, we identified 988 hot spots and 682 cold spots across 889 genes and provided a public database (http://www.genemed.tech/hcseeker/) for researchers and clinicians to query variant locations, facilitating the application of American College of Medical Genetics and Genomics and the Association for Molecular Pathology PM1 or "Benign" criteria. CONCLUSION: We developed the HCSeeker tool, which can effectively identify variant hot and cold spots within genes to enhance the interpretability of gene variants.

Humans↗
PubMed2026

Robust human genetic evidence supporting causal effects of FGF21 on reducing alcohol consuming behaviours.

BACKGROUND: Alcohol use disorder (AUD) represents a tremendous societal burden, yet few efficacious therapies are available and widely used. Pre-clinical and human observational data support fibroblast growth factor 21 (FGF21) as a promising therapeutic target for the treatment of AUD. The objective of this study is to identify a robust genetic instrument for FGF21 agonism and leverage it to explore the effects of FGF21 agonism on AUD and related traits, as well as metabolic outcomes more widely. METHODS: We first compared associations with the positive control outcomes of liver fat and liver cirrhosis risk for the FGF21 cis-protein quantitative trait locus (cis-pQTL) (rs838131) to those for the common allele FGF21 L174P missense variant (rs739320). Having identified the L174P missense variant as a plausible genetic instrument, we subsequently performed association analyses investigating effects on AUD, related traits, and metabolic outcomes more widely. Finally, we performed colocalisation analyses to test whether observed association results reflect a causal mechanism that overlaps with the clinical effects of FGF21 on liver fat and liver cirrhosis. RESULTS: Consistent association and colocalisation evidence support a protective association between genetically predicted FGF21 agonism and alcohol consumption (association p&#x2009;=&#x2009;1&#x2009;&#xd7;&#x2009;10-18, colocalisation posterior probability&#x2009;=&#x2009;0.90), problematic alcohol use (association p&#x2009;=&#x2009;0.02, posterior probability&#x2009;=&#x2009;0.64), and AUD (association p&#x2009;=&#x2009;9&#x2009;&#xd7;&#x2009;10-8, posterior probability&#x2009;=&#x2009;0.97). Similar evidence was also observed for favourable effects of FGF21 on improving kidney function, lowering triglyceride levels, lowering proportional energy intake from carbohydrates, increasing proportional energy intake from protein and fat, increasing body weight and lowering waist-to-hip ratio. CONCLUSIONS: This study identifies a genetic instrument for FGF21 effects to provide causal human evidence supporting favourable effects of FGF21 analogues for the treatment of AUD and related traits, as well as on metabolic outcomes more broadly. Further clinical study is duly warranted.

Humans↗
PubMed2026

Genetic trade-offs in fertility and longevity explain the maintenance of disease-associated alleles in humans.

Genetic variants that increase the risk for complex diseases persist in human populations, despite adverse effects on health and longevity. Life-history theory predicts that such alleles can be maintained by trade-offs arising from pleiotropy, yet direct genomic evidence has been limited. We asked whether disease-associated variants persist because they enhance reproduction, despite costs to health and lifespan. By analysing genome-wide data across 62 diseases, longevity and fertility, we show that disease-risk alleles are, on average, associated with reduced longevity and increased fertility. Moreover, the subset of alleles that increase both fertility and disease risk appear to have been favoured by natural selection over the past 50,000 years. Using Mendelian randomization, we detect a causal effect of genetic liability to disease on longevity, but no robust evidence for a causal effect on fertility; importantly, these estimates remain stable after adjusting for socioeconomic factors. At the individual level, we compared offspring numbers between affected and unaffected individuals with high polygenic disease risk. For most diseases, affected individuals had more children than unaffected ones. But for early-onset diseases, the pattern reverses, indicating reproductive costs of early morbidity. Together, these results support antagonistic pleiotropy and help explain the persistence of disease-risk alleles in human populations.

Humans↗
PubMed2025

Generating synthetic genotypes using diffusion models.

SUMMARY: In this paper, we introduce the first diffusion model designed to generate complete synthetic human genotypes, which, by standard protocols, one can straightforwardly expand into full-length, DNA-level genomes. The synthetic genotypes mimic real human genotypes without just reproducing known genotypes, in terms of approved metrics. When training biomedically relevant classifiers with synthetic genotypes, accuracy is near-identical to the accuracy achieved when training classifiers with real data. We further demonstrate that augmenting small amounts of real with synthetically generated genotypes drastically improves performance rates. This addresses a significant challenge in translational human genetics: real human genotypes, although emerging in large volumes from genome wide association studies, are sensitive private data, which limits their public availability. Therefore, the integration of additional, insensitive data when striving for rapid sharing of biomedical knowledge of public interest appears imperative. AVAILABILITY AND IMPLEMENTATION: All non proprietary data and the code to replicate the experiments is available on Github.

Humans↗
PubMed2026

The Genomics and Genetics of Rare Disease Illuminate Human Biology.

Richard Gibbs interviews James (Jim) Lupski about his training in New York and work in Houston to elucidate the role of complex genomic rearrangements in human genetic diseases. The challenges and excitement of developing human personalized genomics and the advantages of clinical translation of genome methods for both patients and researchers are discussed.

Humans↗
PubMed2022

Genetics for all: Tri-directional research engagement as an equitable framework for international partnerships.

Over the past 5 years, human genetics and genomics research has placed a greater emphasis on increasing diversity among research participants and study researchers as a means of expanding the reach of human genetics and the knowledge accrued by it. Within this context, international collaborations between investigators in well-resourced research-funded countries (RFCs) and those in research-underfunded countries (RUCs) have flourished, with the goal of recruiting more geographically diverse participant pools. Past harms to communities engaged in genetics research have underscored the importance of bi-directional relational engagements, in which researchers and communities work together to ensure ethical research practices and participant involvement. Successful collaborations in the global genomics space, however, are often dependent upon RUC stakeholder investigators and physicians, whose needs are frequently either excluded from existing models of bi-directional community engagement or conflated with that of the study community. Here, we advocate for building more equitable international partnerships through the empowerment of RUC stakeholder investigators-a tri-directional engagement model-that includes supporting, building, and validating the efforts of RUC investigators through training, access, and authorship. We highlight existing initiatives that serve as exemplars in this effort and offer a framework for the broader genetics community to support equitable models of international research partnerships while being mindful of practical challenges. The core concepts embodied augment ongoing efforts to diversify the field of human genetics and complement the long-term goal of genetics for all.

Journal Article↗
PubMed2022

Destabilizing heterochromatin by APOE mediates senescence.

Apolipoprotein E (APOE) is a component of lipoprotein particles that function in the homeostasis of cholesterol and other lipids. Although APOE is genetically associated with human longevity and Alzheimer's disease, its mechanistic role in aging is largely unknown. Here, we used human genetic, stress-induced and physiological cellular aging models to explore APOE-driven processes in stem cell homeostasis and aging. We report that in aged human mesenchymal progenitor cells (MPCs), APOE accumulation is a driver for cellular senescence. By contrast, CRISPR-Cas9-mediated deletion of APOE endows human MPCs with resistance to cellular senescence. Mechanistically, we discovered that APOE functions as a destabilizer for heterochromatin. Specifically, increased APOE leads to the degradation of nuclear lamina proteins and a heterochromatin-associated protein KRAB-associated protein 1 via the autophagy-lysosomal pathway, thereby disrupting heterochromatin and causing senescence. Altogether, our findings uncover a role of APOE as an epigenetic mediator of senescence and provide potential targets to ameliorate aging-related diseases.

Humans↗
PubMed2025

Unique signatures of highly constrained genes across publicly available genomic databases.

PURPOSE: Publicly available genomic databases are critical in understanding human genetic variation. They also provide unique insights into patterns of genetic constraints and their relationship with human disease. METHODS: We utilized one of the largest publicly available databases, Genome Aggregate Database, to determine genes that are highly constrained for only loss-of-function, only missense, and both loss-of-function/missense variants. We identified their unique signatures and explored their causal relationship with human diseases. Those genes were also evaluated for chromosomal location, tissue-level expression, Gene Ontology analysis, and gene family categorization using multiple publicly available databases. RESULTS: We identified unique patterns of inheritance, protein size, and enrichment in distinct molecular pathways for those constrained genes associated with human disease. In addition, we identified genes that are currently not known to cause human disease, which may be excellent gene discovery candidates. CONCLUSION: We elucidate biological pathways of highly constrained genes that expand our understanding of critical cellular proteins. The findings can also advance research in rare diseases.

Humans↗
PubMed2026

Potential mitochondria-associated pathogenic genes in sepsis: a multi-omics Mendelian randomization study.

BACKGROUND: Mitochondrial dysfunction has been implicated in the pathophysiology of sepsis. However, human genetic evidence linking mitochondria-related genes to sepsis susceptibility remains limited. This study aimed to identify mitochondria-related genes associated with sepsis risk using a multi-omics Mendelian randomization framework. METHODS: Summary-data-based Mendelian randomization (SMR) was applied using sepsis genome-wide association study (GWAS) summary statistics from the UK Biobank and FinnGen databases. Expression, methylation, single-cell, and protein quantitative trait loci (QTLs) were used as genetic instruments. Colocalization analyses were conducted to evaluate whether SMR associations were driven by shared genetic variants. Expression of prioritized candidate genes was further examined in clinical septic samples, and correlations with disease severity (SOFA scores) were assessed. RESULTS: SMR analysis prioritized 13 mitochondria-related genes associated with sepsis risk. Immune cell-specific eQTL analysis suggested that genetically predicted SURF1 expression in memory B cells and na&#xef;ve T cells was associated with sepsis risk. Differential expression of 12 candidate genes was confirmed in septic patients by qPCR, and PPOX expression showed a negative correlation with SOFA scores. Integration of mQTL and eQTL data supported a regulatory relationship between methylation at cg06661924 and AK4 expression. Increased genetically predicted AK4 expression was associated with higher sepsis risk (OR&#xa0;=&#xa0;1.21, 95% CI 1.02-1.42). Protein-level analysis identified DUT as a potential sepsis-associated candidate, with consistent evidence across streptococcal and pneumococcal septicemia subtypes. Subtype analyses also suggested heterogeneous genetic signals across different sepsis subtypes. CONCLUSION: This study prioritized several mitochondria-related genes associated with sepsis susceptibility based on human genetic evidence. These findings provide candidate targets for further mechanistic and translational investigation.

Humans↗
PubMed2026

An encyclopedia of human enhancer-gene regulatory interactions.

Identifying transcriptional enhancers and their target genes is essential for understanding gene regulation and the effect of human genetic variation on disease1-6. Here we create and evaluate a resource of more than 92&#x2009;million enhancer-gene regulatory interactions across 1,458 biosamples covering 369 cell types and tissues, by integrating predictive models, chromatin states, three-dimensional contacts and large-scale genetic perturbations generated by the ENCODE Consortium7. We first create a systematic benchmarking pipeline to compare predictive models, assembling a dataset of 10,356 element-gene pairs measured in CRISPR perturbation experiments, more than 30,000 fine-mapped expression quantitative trait loci and 569 fine-mapped genome-wide association study&#xa0;(GWAS) variants linked to a probable causal gene. Using this framework, we develop ENCODE-rE2G, a predictive model achieving state-of-the-art performance across several prediction tasks, demonstrating that iterative perturbations and supervised machine learning can build increasingly accurate predictive models of enhancer regulation. Using ENCODE-rE2G, we build an encyclopedia of enhancer-gene regulatory interactions in the human genome, revealing global properties of enhancer networks, identifying differences in regulatory complexity across genes and improving analyses linking noncoding variants to target genes and cell types for common complex diseases. By interpreting the model, we find that beyond enhancer activity and three-dimensional enhancer-promoter contacts, additional features that&#xa0;guide enhancer-promoter communication include promoter class and enhancer-enhancer synergy. These genome-wide maps of enhancer-gene regulatory interactions, benchmarking software, predictive models and insights about enhancer function provide a valuable resource for future studies of gene regulation and human genetics.

Humans↗