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Review of genetics in the United States with emphasis on the prenatal, metabolic, genetic counseling, and training aspects of the field.
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BACKGROUND: While employing change agents is a widely used strategy to support implementation of evidence-based practices in healthcare, the perspectives of the target users of this intervention are under-explored. Within a genomic care setting in Australia, we examined non-genetic clinicians' views of and experience with embedded genetic counsellors employed as external change agents to support the adoption of genomics in clinical care. METHODS: We conducted qualitative interviews with 16 non-genetic healthcare professionals involved in different models of genomic care, all of which employed genetic counsellors as external change agents to provide embedded genetic expertise and support in non-genetic specialty clinics. The Diffusion of Innovations (DOI) theory and the Theoretical Domains Framework (TDF) were drawn upon to guide the study design and data analysis to explore the enablers/barriers to non-genetic clinicians' use of genetic expertise and the wider implementation context of the change agent approach. RESULTS: The TDF domain 'Belief about Consequences' was a positive influence on non-genetic specialists' view of the embedded change agents, when they believed that the change agents positively impacted patient outcomes and the clinicians' knowledge and practice of using genomics in routine care. Meanwhile, major barriers were related to 'Environmental Context & Resources,' e.g. time constraints and logistic hurdles of involving change agents. Perceived attributes related to 'complexity' and 'observability' of genetic expertise were critical factors influencing the decision to put the support to actual use, impacting the diffusion of the genomic innovation. CONCLUSIONS: Our study offers insights into behavioural influences and contextual conditions shaping clinicians' decisions to interact with genetic counsellor change agents and incorporate (or not) their expertise into their routine care. Such understandings can inform future design and implementation of interventions that use change agents to support the adoption of innovations, such as genomics, effectively and sustainably.
Alzheimer's disease (AD) and Parkinson's disease (PD) are the most prevalent late-onset neurodegenerative diseases worldwide. Both are influenced in part by genetic factors and are currently incurable. Tobacco and alcohol, the two most common substances used among the general adult population, are potential AD/PD risk factors and are also heritable. Although important progress has been made, most existing research on the genetics of AD and PD has been carried out in individuals of European genetic ancestry. Investigations in a broad range of groups are crucial to understand disease mechanisms. Given the current availability of ancestry-specific tobacco and alcohol use as well as AD and PD genome-wide association study summary statistics, we performed global and local genetic correlation analyses using East Asian datasets. Genes within the correlated genetic regions were subsequently used to identify potentially enriched biological pathways between substance use and neurodegenerative diseases. We identified a global genetic correlation between smoking cessation and PD, which we confirmed in complementary European genetic ancestry data. Gene set enrichment analyses highlighted potentially shared genetic mechanisms between breast cancer and AD, which warrants further exploration. This work aims to promote further analyses across genetic ancestry groups.
Clinical genetic services address diverse genetic testing needs, but there is no comprehensive digital solution to meet this variety. We aimed to develop and test the usability of the Genetics Navigator (GN), a platform designed to enhance genetic services for paediatric and adult patients. The GN prototype was created with input from a patient and clinician advisory board, informed by prior research. Usability testing involved genetics patients (N = 14), parents of paediatric patients (N = 4), and the general public (N = 10). Participants provided feedback using the 'think aloud' method when using the platform. We used the System Usability Scale (SUS) for quantitative evaluation. Qualitative data were coded by platform section, item, and identified key areas for improvement. Building on the Genetics Adviser platform, we added video and written content for various genetic conditions and patient groups, including pre-test education, counselling, decision support, history collection, post-test result disclosure, and management. Key feedback during rounds of usability testing emphasized the need for a supportive design, seamless workflow, and engaging experience of the tool. The tool was modified to reflect the feedback, and the GN achieved an average SUS score of 87.7 ± 10.9 (N = 28), indicating above-average usability. Future research will evaluate its clinical and cost-effectiveness in a randomized trial.
BACKGROUND: Heart failure (HF) and body mass index (BMI) share substantial genetic architecture, which may lead genetically informed target discovery to preferentially identify adiposity-related pathways. We sought to identify circulating proteins associated with HF beyond this shared genetic component. METHODS: We applied GWAS-by-subtraction to overall HF, nonischemic HF, and nonischemic HF with reduced or preserved ejection fraction to derive BMI-related and BMI-subtracted HF components. We then performed proteome-wide cis-pQTL Mendelian randomization and colocalization using four independent proteomic cohorts, followed by tissue-specific eQTL colocalization, cardiac transcriptomic annotation, and druggability assessment. RESULTS: Compared with the original HF phenotypes, the BMI-subtracted components showed attenuated genetic correlations with BMI (0.045-0.147) while retaining 28 independent loci for overall HF and nine for nonischemic HF. Across 19,930 protein-HF tests, 11 associations involving nine proteins were prioritized by the Mendelian randomization and colocalization analyses. For example, a 1-SD increase in genetically predicted CELSR2 abundance was associated with lower overall HF risk (odds ratio, 0.96 [95% CI, 0.94-0.98]; P=8.6×10-7), whereas a 1-SD increase in genetically predicted CSF3 abundance was associated with higher nonischemic HF risk (odds ratio, 1.32 [95% CI, 1.18-1.48]; P=2.0×10-6). CELSR2 and TMEM106B colocalized with cis-eQTLs in failing left ventricular myocardium, and DAG1 showed cardiomyocyte enrichment with concordant downregulation in failing hearts. CONCLUSIONS: We identified nine circulating proteins associated with HF beyond the genetic component shared with BMI. These findings extend the range of genetically supported pathways implicated in HF and nominate candidate proteins for further mechanistic and therapeutic investigation.
Latin Americans are underrepresented in genetic studies, increasing disparities in personalized genomic medicine. Despite available genetic data from thousands of Latin Americans, accessing and navigating the bureaucratic hurdles for consent or access remains challenging. To address this, we introduce the Genetics of Latin American Diversity (GLAD) Project, compiling genome-wide information from 53,738 Latin Americans across 39 studies representing 46 geographical regions. Through GLAD, we identified heterogeneous ancestry composition and recent gene flow across the Americas. Additionally, we developed GLAD-match, a simulated annealing-based algorithm, to match the genetic background of external samples to our database, sharing summary statistics (i.e., allele and haplotype frequencies) without transferring individual-level genotypes. Finally, we demonstrate the potential of GLAD as a critical resource for evaluating statistical genetic software in the presence of admixture. By providing this resource, we promote genomic research in Latin Americans and contribute to the promises of personalized medicine to more people.
PURPOSE: The increasing demand for genetic testing and a global shortage of geneticists has significantly strained health care systems worldwide. This highlighted the need for new strategies aiming to increase testing accessibility, reduce wait times, and enhance patient care quality. METHODS: We implemented a 4-step program, "Genetics First," to empower nongeneticist physicians (NGPs) to play an active role in the process of genetic consultation and testing. The steps included (1) establishing criteria to identify suitable clinical domains, (2) selecting clinical indications within the domain through expert panel review, (3) designing tailored education and workflows for NGPs across indications, and (4) monitoring test outcomes and providing further support for complex cases. Test outcomes were compared between NGPs and clinical geneticists. RESULTS: Endocrinology was selected as the first domain, with 114 endocrinologists who completed the program. During the study, 260 gene panels were performed for monogenic diabetes, with NGPs initiating 68% of tests, leading to a 107% increase in referrals. The diagnostic yield was 30%, with no significant difference between NGP- and clinical geneticist-initiated tests. CONCLUSION: This study demonstrates the feasibility and impact of involving NGPs in genetic testing, offering a paradigm shift that could expand access to genetic testing and improve patients' care and clinical outcomes.
BACKGROUND: This research attempts to clarify whether there are any genetic similarities between sleep traits and hypothyroidism based on publicly accessible large-scale genomewide association studies. METHODS: The methodology included colocalization analysis, cross-phenotype association analysis, and linkage disequilibrium score regression analysis to find common genetic overlap. Through tissue function specificity and functional mapping, we were able to identify the shared genetic level. Genetic instrumental factors were used for causal inference in two-sample univariate and multivariable Mendelian randomization analyses. RESULTS: A hereditary correlation between hypothyroidism and napping during the day and getting up in the morning (rg= -0.0982, P= 0.0007; rg= -0.101, P= 0.0001). MAGI3, and HLA-DRB1 BX296568.1 may be potential targets for shared treatments. Colocalization and tissue-specific analysis demonstrated that the common genes and SNPs were identified in the thyroid, lung, brain, and lymphatic tissues. Functional analysis emphasized the importance of these common genes in processes like as protein transport, inflammatory response, and MHC class II protein synthesis. Furthermore, an association has been established between hypothyroidism and sleep duration (IVW, OR 1.5208; 95% CI 1.1142-2.0758, P=0.0082) and getting up in the morning (IVW, OR 1.8375; 95%CI: 1.4502-2.3284, P=4.73E-07). Furthermore, the reverse MR analysis revealed no causal connection between aberrant sleep traits and hypothyroidism. The enduring impact of insomnia on hypothyroidism persists despite controlling for alcohol consumption and smoking habits. CONCLUSION: Certain genetic correlations between sleep traits and hypothyroidism have been emphasized. These findings may elucidate the origin of comorbidity and have implications for future clinical trials.
PURPOSE: The increasing complexity of genetic technologies paired with more genetic tests being ordered by nongenetic health care providers, has resulted in an increase in the number of inappropriately ordered tests. Genetic counselors (GCs) are ideally suited to assess the appropriateness of a genetic test. METHODS: We performed a scoping review of GC involvement in utilization management initiatives in order to describe the impact of having GCs involved in this process. Five databases (MEDLINE, EMBASE, CINHAL, EBM reviews, and Web of Science Core Collection) and gray literature were searched. We considered literature published in English since 2010. RESULTS: A total of 51 studies were included. The most commonly evaluated outcomes included cancellation rate, economic efficiencies, impact on medical management, diagnostic rate, and time or triage efficiencies. Several studies also described GC impact on nongenetic health care providers. CONCLUSION: Employment of GCs in the laboratory has been implemented widely as a solution to test misordering. These studies describe ways in which GCs can be integrated into testing workflows to reduce the number of inappropriate tests and have wider impacts on nongenetic health care providers' ordering practices and the patient experience.
Actinobacillus pleuropneumoniae is the causative agent of pleuropneumonia in swine, a highly contagious and economically significant disease. The genetic variability of A. pleuropneumoniae complicates disease control efforts, as it enables rapid adaptation to various stressors, including antimicrobial treatments. To better understand the molecular mechanisms underlying this adaptability, we investigated the role of the bacterial defensome and its relationship with mobile genetic elements (MGEs), such as prophages, plasmids, and integrative conjugative elements (ICEs). Using bioinformatic tools, we identified a diverse and rich defensome in A. pleuropneumoniae, with an average of 16 different defense systems per strain. We found that CRISPR-Cas systems, along with other defense mechanisms, are actively involved in restricting the entry of foreign genetic material, playing a crucial role in bacterial adaptation. Additionally, we characterized several novel prophages and examined their distribution across different strains, revealing their potential contribution to the bacterium's evolutionary success. Our findings underscore the complex interplay between the bacterium's defense systems and MGEs, shedding light on how A. pleuropneumoniae maintains genetic diversity while also safeguarding itself against external threats. These insights provide a better understanding of the genetic factors that influence the pathogen's adaptability and highlight potential avenues for more effective disease control strategies.
Despite significant progress, malaria remains a public health problem in many regions, particularly in sub-Saharan Africa. This situation is partly explained by the mosquito's resistance to insecticides and the emergence of parasite resistance to antimalarial drugs. Indeed, in spite of the various vectors' controls, insecticide resistance emerges from multi-generational selection and poses worldwide concern. In parallel, artemisinin resistance unfortunately emerged independently in multiple countries in eastern Africa. Since 2014, artemisinin resistance has been observed in 6 countries in Africa and, more concerningly, the evidence from longitudinal molecular surveys in these countries suggests that it is spreading. While phenotypic evidence of treatment failure is still limited, the increasing reports of validated artemisinin resistance mutations are alarming. Unlike the emergence of artemisinin resistance in South-East Asia, our understanding of the genetic determinants of artemisinin resistance and our ability to sequence and map the spread of resistance are significantly greater. In addition to mosquito and parasite genetics affecting malaria evolution, many human individual variants have been identified that are associated with malaria protection, but the most important of all relates to the structure or function of red blood cells, the classical polymorphisms that causes sickle cell trait, α-thalassaemia, G6PD deficiency, and the major red cell blood group variants. In that biological complex context, there is a need to characterize the various genetic factors in Plasmodium falciparum, humans and mosquitoes that are potentially associated with resistance to antimalarial drugs and insecticides, and their involvement in the evolution, severity and transmission of malaria. In this direction, A comprehensive literature review was conducted to capture the objectives highlighted above. The advances in genomic surveillance and emerging genetic control strategies, such as gene drive technology were also considered in this review. We used search engines such as PubMed and Google scholar to retrieve articles useful to the objective of this paper and information on the knowledge of genetic factors and methods that contributed to malaria control were synthesized.
Ongoing efforts to identify genes involved in substance use disorders (SUDs) often focus on individual disorders despite high rates of co-occurrence with each other and other externalizing traits. Here, we investigate whether incorporating data on other externalizing traits can boost power to detect without sacrificing specificity of SUD genetic signal. We used multivariate genomic analyses and downstream biological annotation and genetic association analyses to explore this question. We found that joint analysis of SUDs and other externalizing traits resulted in increased insights into the neurobiology of broad and substance-specific SUD risk. We found no evidence of loss of specificity for SUD genetic signal but note improvements in our ability to characterize the neurobiology of broad and substance-specific SUD genetic effects. Our findings suggest that genetic risk for SUDs operates largely via pathways shared with other behaviors characterized by behavioral disinhibition, with additional substance-specific risk, and that modeling this shared disposition improves gene discovery.
Striking disparities in lung cancer exist, with Black/African American individuals disproportionately affected by lung cancer, yet the genetic architecture in African ancestry individuals is poorly understood. We aimed to address this by performing a comprehensive genetic association study of lung cancer, incorporating local ancestry, across 6,490 African ancestry individuals (2,390 individuals with lung cancer and 4,100 control subjects). We identified a single genome-wide significant (p < 5 × 10-8) locus, 15q25.1 (lead SNP rs17486278, OR [95% CI] = 1.34 [1.23-1.45], p = 4.52 × 10-12), that has consistently shown a strong association with lung cancer across populations. Additionally, we identified nine suggestive (p < 1 × 10-6) loci. Four of these loci (3p12.1, 8q22.2, 14q11.2, and 18q22.3) have no prior reported associations with lung cancer. We performed a multi-ancestry lung cancer meta-analysis using prior large-scale summary statistics from European and Asian ancestry populations, incorporating our African ancestry results. The meta-analysis identified 17 genome-wide significant loci, including an association with locus 4q35.2 (p = 1.22 × 10-8), a genomic region that has been previously linked to forced expiratory volume. Genome-wide SNP-based heritability for lung cancer was 16% among African ancestry individuals. Follow-up in silico functional analyses identified genetically regulated gene expression (GReX) of nine genes (AC012184.3, ADK, CCDC12, CHRNA3, EML4, PSMA4, SNRNP200, TMEM50A, and ZYG11A) associated with lung cancer risk and biological pathways relevant to cancer and lung function. Cumulatively, these findings further elucidate the genetic architecture of lung cancer in African ancestry individuals, confirming prior loci and revealing new loci.
BACKGROUND: Multiple sclerosis (MS) is a severe neuroinflammatory disease causing substantial long-term disability. Strong epidemiologic evidence links Epstein-Barr virus (EBV) exposure with MS risk, but genetic evidence for immune target prioritization in EBV-related phenotypes remains limited. METHODS: We integrated single-cell cis-eQTL data from 14 immune cell types with GWASs of an EBV-related clinical phenotype and MS using a single-cell Mendelian randomization framework with colocalization analyses. Candidate eGenes were evaluated in independent cohorts. For multi-SNP instruments, we performed heterogeneity, pleiotropy, MR-Egger, weighted median, mode-based, and MR-PRESSO sensitivity analyses. We also conducted phenome-wide association analyses and queried DrugBank to annotate candidate compounds targeting prioritized genes. RESULTS: We prioritized 43 immune-cell-specific candidate eGenes with convergent genetic support, including 6 for the EBV-related phenotype and 37 for MS. SERPINB1 in NK cells was associated with increased risk of the EBV-related phenotype, whereas HLA-G was associated with decreased risk. For MS, APOM and MSH5 showed protective associations, while AHI1 showed cell-type-dependent, bidirectional associations across immune lineages. Colocalization and independent cohort evaluation supported these findings. Among FDR-significant multi-SNP associations, MR-Egger intercept tests did not indicate directional pleiotropy, although a small subset showed heterogeneity or MR-PRESSO signals. Phenome-wide analyses identified no significant adverse phenotypic associations among evaluable genes at the prespecified threshold. DrugBank annotation nominated sodium nitroprusside, fasudil, artenimol, and choline as hypothesis-generating compounds for experimental follow-up. CONCLUSIONS: This study provides a single-cell genetic framework for prioritizing immune-cell-specific candidate targets for EBV-related phenotypes and MS, and nominates genetically supported targets and pharmacologic hypotheses for experimental investigation.
Cardiac iron homeostasis is essential for myocardial energy metabolism and contractile function, yet the genetic and molecular mechanisms governing iron levels within the heart remain poorly understood. We used a systems genetics approach to dissect the transcriptional regulation of cardiac iron homeostasis. Myocardial iron level varies substantially across BXD strains (40-112 μg/g) and is under heritable genetic control (H2 = 0.38). Elevated cardiac iron is associated with reduced ventricular mass, increased ventricular ectopy, and prolonged atrioventricular conduction in the BXD population. Weighted gene co-expression network analysis of the BXD heart transcriptome identified a co-expression module that was significantly and negatively correlated with cardiac iron levels in both young and old BXD mice and enriched for pathways related to metabolic regulation, cyclic AMP (cAMP) signaling, circadian entrainment, and cardiovascular physiology. The module showed substantial overlap with a curated cardiac iron gene set, and cross-species enrichment analysis confirmed its conservation in human cardiomyopathy differentially expressed genes (enrichment ratio = 1.49; false discovery rate [FDR] = 0.0342). Quantitative trait locus (QTL) mapping of the first principal component of the overlapping module iron genes (n = 38), corroborated by individual gene mapping, identified trans-eQTL hotspots on multiple chromosomes, implicating Fcho2, Gcc2, and Rmdn1 as candidate upstream regulators operating through sequential steps of intracellular iron trafficking. Together, these findings establish a systems-level map of cardiac iron gene regulation, identify candidate genetic regulators, and provide a molecular framework linking disruption of iron-related transcriptional networks to structural and electrical cardiac dysfunction with implications for iron-related heart diseases.
BACKGROUND: Despite increases in genetic testing, longitudinal data regarding changes in diagnostic yield and variant reclassification for inherited arrhythmia syndromes are limited. OBJECTIVE: Determine longitudinal changes in diagnostic yield and variant classification. METHODS: Single-center retrospective study of probands <18 years undergoing genetic testing for suspected inherited cardiac conditions associated with arrhythmias, 2007 to 2018. Variants were classified as diagnostic (pathogenic/likely pathogenic), non-diagnostic (benign/likely benign [B/LB]), or variants of uncertain significance (VUS). Variant reclassification was performed in October 2023 using VarSome and American College of Medical Genetics criteria. We evaluated results by era (early 2007-2013 vs. later 2014-2018, coinciding with Sanger and next-generation sequencing, respectively) and by likelihood of disease based on clinical evaluation. RESULTS: Of 306 probands, initial testing was 23.2% diagnostic, 55.6% non-diagnostic (33.7% no variant, 21.9% B/LB), and 21.2% VUS. When comparing eras, diagnostic yield decreased (34.1%-15.3%), VUS increased (9.3%-29.9%), and non-diagnostic remained similar (55% to 57%). Variants for 22.7% (46/203) of probands with ≥1 variant changed: 9.9% of diagnostic variants (7/71) downgraded to VUS or non-diagnostic, and 60.0% of VUS changed (23.1% upgraded, 36.9% downgraded). B/LB variants did not change. Probands with higher disease likelihood had 6-times the odds of diagnostic results compared to lower disease likelihood, regardless of era (odds ratio 6.3, 95% confidence interval 3.2-12.4, P < .0001). CONCLUSION: Variant reclassification led to changes in 23% of probands, both downgrading and upgrading status, even among probands initially thought to be pathogenic. When comparing later to earlier eras, VUS variants increased while diagnostic yield decreased. Findings support the need for variant re-interpretation and periodic reclassification over time.
Postpartum psychosis is a severe psychiatric condition marked by the abrupt onset of psychosis, mania, or psychotic depression following childbirth. Despite evidence for a strong genetic basis, the roles of common and rare genetic variation remain poorly understood. Leveraging data from Swedish national registers and genomic data from the All of Us Research Program, we estimated family-based heritability at 55% and whole-genome sequencing-based heritability at 46%. Rare coding variant analysis identified HMGCR as a gene in which rare damaging variants confer risk for postpartum psychosis (FDR < 0.05). Analyses of 240,009 participants from the All of Us Research Program and 58,990 participants from the Mount Sinai BioMe Biobank identified significant associations linking deleterious rare variants in HMGCR to vascular dementia and mental disorder, not otherwise specified, supporting the gene's broader psychiatric relevance. Additionally, among the top 200 genes ranked by association statistics, 17% of bipolar disorder, 21% of schizophrenia, and 16-25% of multiple autoimmune disorders exhibit a possible association with postpartum psychosis. These findings reveal unique genetic contributions and shared pathways, providing a foundation for understanding pathophysiology and advancing therapeutic strategies.