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PubMed2025

Underrepresented populations in genomic research: a qualitative study of researchers' perspectives.

BACKGROUND: The lack of diversity in genomic data limits researchers' ability to investigate the relationships between genetic profiles, disease manifestations, and responses to new therapies. As a result, innovations in treatment could have potentially harmful effects on a significant portion of the population due to incomplete or inaccurate genomic data. In addition, the lack of harmonization in the use of population descriptors in genomic studies raises both ethical and scientific concerns regarding which descriptors should be used to study and recruit underrepresented populations. Therefore, understanding the factors contributing to the lack of diversity in genomic research is an urgent scientific, clinical, and public health priority. This study aims to explore the social and contextual factors influencing the participation of underrepresented populations in genomic research, from the perspective of researchers in the field. METHODS: A total of 13 semi-structured interviews were conducted with researchers experienced in genomic research in Canada and fluent in either French or English. The interview transcripts were analyzed using thematic analysis. RESULTS: Researchers identified several factors contributing to the low participation of underrepresented populations in genomic research, with one key factor being the geographic distribution of research institutions and the disconnect between research efforts and the communities being studied. To address this issue, participants stressed the importance of moving away from colonial practices, such as conducting research on a community without consulting its members in the design phase. Furthermore, it was suggested that existing diversity, equity, and inclusion policies alone were insufficient to effectively address the challenge. Lastly, the study also highlighted a potential link between how study populations are categorized and the willingness of underrepresented groups to participate in genomic research. CONCLUSION: Although researchers are generally aware of the literature on the causes, consequences, and potential solutions for increasing participation, confusion remains regarding the use of population descriptors. Our findings highlight the need for improved education, greater consensus, and expanded dialogue within the genomic research community to promote the harmonization of population descriptors.

Humans↗

PubMed2026

Current knowledge in pharmacogenomics and precision medicine: perspectives of the PGRN global PGx committee on improving drug therapies in underrepresented ethnic populations.

A precision medicine strategy is likely to be more impactful, when pharmacogenomics (PGx) guided selection of drugs and dosage wherever applicable is implemented across the globe. In regions where resources are disproportionately distributed, PGx implementation in routine clinical care can play a critical role in ensuring the optimal use of limited healthcare infrastructure. At present, PGx data from the majority of the distinct ethnic populations across Asia, Africa, and South America is limited. While international consortia, working groups, and scientific bodies have made significant contributions toward evaluating the evidence for PGx implementation, the majority of existing guidelines and recommendations are derived primarily from studies conducted in a limited number of ethnic groups. Precision Medicine Initiatives in countries like Korea, Taiwan, and Malaysia and PGx organizations like the African Institute of Biomedical Science and Technology (AiBST), Consortium for Genomics & Therapeutics in Africa (CGTA), implementation of pharmacogenetic testing for the effective care and treatment in Africa, Greater Middle East (GME) whole exome sequencing program, Ibero-American Network of Pharmacogenetics and Pharmacogenomics (RIBEF), Latin American Society of Pharmacogenomics and Personalized Medicine (SOLFAGEM), Latin American Network for Validation and Implementation of Pharmacogenomic Clinical Guidelines (RELIVAF), IndiGen initiative, Southeast Asian Pharmacogenomics Research Network (SEAPharm), are working toward consolidating the PGx presence in these regions.

Precision Medicine↗

PubMed2025

Comparative genomic analysis of key oncogenic pathways in hepatocellular carcinoma among diverse populations.

BACKGROUND/OBJECTIVES: Hepatocellular carcinoma (HCC) is a leading cause of cancer-related mortality, with significant racial and ethnic disparities in incidence, tumor biology, and clinical outcomes. Hispanic/Latino (H/L) patients tend to be diagnosed at younger ages and more advanced stages than Non-Hispanic White (NHW) patients, yet the molecular mechanisms underlying these disparities remain poorly understood. Key oncogenic pathways, including RTK/RAS, TGF-Beta, WNT, PI3K, and TP53, play pivotal roles in tumor progression, treatment resistance, and response to targeted therapies. However, ethnicity-specific alterations within these pathways remain largely unexplored. This study aims to compare pathway-specific mutations in HCC between H/L and NHW patients, assess tumor mutation burden, and identify ethnicity-associated oncogenic drivers using publicly available datasets. Findings from this analysis may inform precision medicine strategies for improving early detection and targeted therapies in underrepresented populations. METHODS: We conducted a bioinformatics analysis using publicly available HCC datasets to assess mutation frequencies in RTK/RAS, TGF-Beta, WNT, PI3K, and TP53 pathway genes. The study included 547 patients, consisting of 69 H/L patients and 478 NHW patients. Patients were stratified by ethnicity (H/L vs. NHW) to evaluate differences in mutation prevalence. Chi-squared tests were used to compare mutation frequencies, while Kaplan-Meier survival analysis assessed overall survival differences associated with pathway-specific alterations in both populations. RESULTS: Significant differences were observed in the RTK/RAS pathway related genes, particularly in FGFR4 mutations, which were more prevalent in H/L patients compared to NHW patients (4.3% vs. 0.6%, p = 0.02). Additionally, IGF1R mutations exhibited borderline significance (7.2% vs. 2.9%, p = 0.07). In the PI3K pathway, INPP4B alterations were more frequent in H/L patients than in NHW patients (4.3% vs. 1%, p = 0.06), while in the TGF-Beta pathway, TGFBR2 mutations were more common in H/L patients (2.9% vs. 0.4%, p = 0.07), suggesting potential ethnicity-specific variations. Survival analysis revealed no significant differences in overall survival between H/L and NHW patients, indicating that molecular alterations alone may not fully explain survival disparities and suggesting a role for additional factors such as immune response, environmental exposures, or access to targeted therapies. CONCLUSIONS: This study provides one of the first ethnicity-focused analyses of key oncogenic pathway alterations in HCC, revealing distinct molecular differences between H/L and NHW patients. The findings suggest that RTK/RAS (FGFR4, IGF1R), PI3K (INPP4B), and TGF-Beta (TGFBR2) pathway alterations may play a distinct role in HCC among H/L patients, while their prognostic significance in NHW patients remains unclear. These insights emphasize the importance of incorporating ethnicity-specific molecular profiling into precision medicine approaches to improve early detection, targeted therapies, and clinical outcomes in HCC, particularly for underrepresented populations.

PI3K pathway↗

PubMed2026

Pharmacogenomic diversity in Amazonian Indigenous populations: implications for Berlin-Frankfurt-Münster acute lymphoblastic leukemia therapy.

PURPOSE: This study aimed to characterize pharmacogenomic variation in genes involved in the metabolism and transport of drugs used in Berlin-Frankfurt-Münster-based therapy in Amazonian Indigenous individuals and to compare allele frequencies with major continental populations. METHODS/PATIENTS: Whole-exome sequencing data previously generated from 64 healthy Indigenous individuals from 12 Amazonian ethnic groups were analyzed. A total of 120 genes associated with drugs used in Berlin-Frankfurt-Münster protocols were selected. Variants were annotated and filtered using bioinformatic quality-control criteria, and allele frequencies were compared with African, Admixed American, East Asian, European, and South Asian populations from the 1000 Genomes Project. Multidimensional scaling was used to assess population-level genetic similarity. RESULTS: After quality control, 648 variants were identified. Twenty-eight variants were observed exclusively in the Indigenous study population, including four nonsynonymous coding variants with moderate predicted impact. Significant allele-frequency differences were observed for ADA rs11555566, CBR3 rs881711, and CYP2B6 rs3745274; rs881711 and rs3745274 differed from all five reference populations. Multidimensional scaling showed a distinct Indigenous pharmacogenomic profile, with greater similarity to the Admixed American population. CONCLUSIONS: Amazonian Indigenous populations exhibit substantial pharmacogenomic diversity in genes relevant to Berlin-Frankfurt-Münster-based therapy. These findings identify candidate variants for functional and clinical validation and reinforce the importance of including underrepresented populations in pharmacogenomic research.

Acute lymphoblastic leukemia↗

PubMed2026

Survey to inform personalised prescribing in a British South Asian community: pharmacogenomics and traditional medicine use.

BACKGROUND: Pharmacogenomics (PGx) uses genetic information to personalize medication, reducing adverse reactions and improving efficacy. Despite its promise, low public awareness and disparities in PGx acceptability among under-represented groups may exacerbate health inequalities. The objective of this study was to elucidate a British South Asian community's attitudes toward personalised prescribing. METHODS: Adults of Bangladeshi or Pakistani ancestry from the Genes & Health (G&H) study completed a survey. Community feedback guided theme prioritization. Multivariable logistic regression analyses (controlling for age and gender) explored relationships among survey variables, and case-control Genome Wide Association Studies (GWAS) and candidate variant enrichment analysis examined the genetic architecture underlying herbal remedy use. RESULTS: Out of 553 respondents (57% female, mostly aged 25-54), 72% reported medication inefficacy, and 54% experienced side effects. Herbal remedies were widely used (66%), notably Black seed (39%), Turmeric (37%), and Ginger (36%). Participants who reported not using traditional or herbal medicines had higher medication adherence MARS-5 scores (Odds Ratio (OR) 1.10, 95% Confidence Interval (CI) 1.05-1.16, p < 0.0002). All three commonly used herbal remedies inhibit the pharmacogenomically variable CYP2C9 enzyme responsible for metabolising commonly used medications. 58% of respondents were willing to provide DNA samples for PGx testing, yet 70% agreed that they would be more likely to take medication as instructed if PGx results suggested the medicine would suit them. Concerns about PGx testing were common (27%), especially among non-English speakers. Most (69%) were concerned about misuse of PGx data, particularly by pharmaceutical companies (82%). Importantly, 87% demanded stronger PGx data protections compared to other health data. CONCLUSIONS: Compared to a national UK population, the surveyed subpopulation reported higher rates of adverse drug reactions (ADRs) and perceived medication inefficacy, yet fewer respondents indicated willingness to undergo PGx testing. This highlights the need for tailored implementation strategies and underscores the importance of engaging underrepresented populations in policy development. The inverse relationship between medication adherence and herbal remedy use indicates an association between cultural health practices and medication behaviours that merits further investigation. Increased awareness of the common use of these CYP2C9 inhibitors and further research into the genetic architecture underlying herbal remedy use are warranted.

Humans↗

PubMed2026

Resistome and microbiome-immune interactions in an Eastern European population with high antibiotic use.

The gut microbiome influences host health, affecting gastrointestinal, metabolic, immune, cardiovascular, and neurological functions. A balanced microbiome is associated with favorable health outcomes. However, excessive antibiotic use and dietary habits can disrupt this ecosystem, leading to dysbiosis and affecting body homeostasis. This first comprehensive metagenomic analysis of the gut microbiome in a healthy Romanian cohort, a population underrepresented in microbiome studies and characterized by high antibiotic consumption, addresses a gap in current microbiome research. We report an enrichment of Enterobacteriaceae although overall composition is more comparable to other European than non-European cohorts. Community configurations align with established enterotype patterns, and our analysis provides insight into their relationship with within-phylum diversity. The analysis of antimicrobial resistance provides insight into the prevalence of resistance genes within this reservoir. We specifically report the presence of cfr(E), a Clostridioides difficile gene, and tet(X5), a variant from the ubiquitous tet family, genes not previously reported in healthy European populations. Integration with data from the European Centre for Disease Prevention and Control links the overall prevalence of resistance genes in this reservoir to antibiotic classes with higher community consumption in this population, notably beta-lactams and quinolones, highlighting potential targets for antibiotic stewardship programs. Finally, we investigate the relationship between the microbial profile and the systemic immune responses, inferred from correlations with in vitro cytokine production. Notably, we identify potential immune-priming roles for Collinsella, Flavonifractor, and Bifidobacterium species.IMPORTANCEThis first comprehensive study of the healthy gut microbiome in a Romanian cohort addresses a gap in current microbiome research, dominated by data sets from a limited number of regions. It sets a baseline for the microbiome and resistome composition of this population, and, while definitions of "healthy" microbiomes, or baseline resistomes, remain lacking, such study helps contextualize future studies and support the monitoring of dynamics. The Enterobacteriaceae abundance suggests a microbiome composition potentially influenced by antimicrobial consumption, a relevant pattern in a region with a high burden of nosocomial infections. In addition, the prevalence of antimicrobial resistance genes and the concordance with commonly used antibiotics in the community reinforce the need to address antibiotic use in public health strategies. Although gut microbiome-immunity relationships remain incompletely understood, our findings support a role for microbiome composition in immune-related traits and provide a valuable resource for future studies.

Humans↗

PubMed2026

Revisiting the Association of Pesticide Exposure and Parkinson's Disease: Systematic Review and Meta-Analysis.

The association between pesticide exposure and Parkinson's disease (PD) is substantial, but heterogeneity in methodology and lack of categorization according to the type of exposure and pesticide classes in previous meta-analyses impair the interpretation of data. This study aims to update evidence of the association between pesticide exposure and PD. We conducted a systematic review and meta-analysis of studies investigating associations between pesticide exposure and PD according to the type of pesticide exposure and pesticide class. We searched PubMed, EMBASE, and Web of Science until July 2024. Reviewers screened titles and abstracts. Afterward, reviewers reanalyzed the selection criteria and extracted the data based on the full paper. Meta-analyses were conducted to assess the association between pesticide exposure and PD. A total of 124 studies were eligible. There is a lack of diversity in the populations represented and a high variability in methodology among the included studies. Considering only studies with any type of exposure, we found a positive association of PD with any pesticide class and herbicides. Occupational exposure was associated with PD for all pesticide classes except for fungicides. Exclusive household pesticide exposure was also associated with PD. Pesticide exposure remains a significant environmental risk factor for the development of PD, regardless of the type of exposure. Herbicides are the pesticide class with the most substantial evidence of association with the disease. Further studies with new methods of pesticide exposure measurement, innovative design studies, and the inclusion of underrepresented populations are still needed.

Pesticides↗

PubMed2026

Variant harmonization critically determines polygenic score transferability for lipid traits in Samoan populations.

Dyslipidemia is a significant risk factor for cardiovascular disease (CVD), the leading cause of death in Samoa. Polygenic scores (PGSs) for lipid traits offer promise for improved CVD risk prediction; however, their performance in Pacific Islander populations-comprising only 0.002% of genome-wide association study (GWAS) participants as of 2024-remains unknown. We evaluated the transferability of multi-ancestry PGS for LDL cholesterol (LDL-C), HDL cholesterol (HDL-C), triglycerides (TGs), and total cholesterol (TC) in 4,342 Samoan adults across five cohorts spanning 1990-2010. PGSs from Graham et al. and Kanoni et al. multi-ancestry meta-analyses were harmonized with genome-wide imputed genotypes using a Samoan-specific reference panel, and performance was assessed via incremental R2 from linear mixed models with bootstrapped confidence intervals. HDL-C showed the highest performance (incremental R2 5.0%-15.0%), followed by TC (5.0%-10.7%), LDL-C (5.7%-8.6%), and TG (3.5%-7.0%). Critically, meaningful LDL-C performance was achieved only with the genome-wide PRS-CS score (99.6%-99.7% variant matching), while a curated pruning-and-thresholding score achieved ∼9% matching and near-zero performance. These findings establish systematic lipid PGS benchmarks in Samoans, demonstrating meaningful transferability when genome-wide variant coverage is ensured, and highlight variant harmonization as a critical precondition for PGS deployment in underrepresented populations.

Pacific Islanders↗

PubMed2026

A recurrent CCDC82 frameshift variant associated with syndromic neurodevelopmental disorder in a consanguineous Pakistani family.

BACKGROUND: Intellectual disabilities (IDs) are part of neurodevelopmental disorders (NDDs) and are genetically heterogeneous conditions characterized by impairments in cognition, learning, and adaptive functioning. Despite advances in gene discovery, many individuals, particularly those from understudied populations, remain without a molecular diagnosis. Recent reports implicate CCDC82 (HGNC: 26282) as an autosomal recessive ID gene, although the phenotypic spectrum and biological context remain incompletely defined. METHODS: Exome sequencing (ES) was performed in a consanguineous Pakistani family (PKMR06A) with four affected individuals presenting with moderate to severe ID. Variant segregation was confirmed by Sanger sequencing. In silico analyses, including pathogenicity prediction, protein structural modeling, and domain intolerance assessment, were used to evaluate the functional consequences of the identified variant. Spatiotemporal gene expression patterns were examined using bulk and single-cell human brain transcriptomic datasets. RESULTS: Clinically, affected individuals of family PKMR06A presented with early childhood global developmental delay, speech delay, hypotonia, gait abnormalities, spasticity, and mild facial dysmorphism. Genetic screening revealed a recurrent rare homozygous frameshift variant in CCDC82 (NM_024725.4): c.373del; p.(Asp125Ilefs*6), segregating with disease in all available affected individuals of the family. The identified c.373del variant was absent from the gnomAD database and was classified as pathogenic (PVS1, PM2, and PP1) based on ACMG/AMP criteria. The c.373del variant is predicted to introduce a premature termination codon, p.(Asp125Ilefs*6), leading to deletion of essential coiled-coil domains from the encoded protein, supporting a loss-of-function mechanism. In silico, transcriptomic analyses demonstrated preferential CCDC82 expression during prenatal human brain development, providing developmental context for the neurodevelopmental phenotype associated with the identified truncating variant. CONCLUSIONS: This study expands the mutational landscape of CCDC82 and provides additional clinical and molecular evidence supporting its role in autosomal recessive NDD. The findings reinforce the importance of CCDC82 in human neurodevelopment and highlight the value of genomic investigation in underrepresented populations.

Autosomal recessive↗

PubMed2025

Building a Digital Health Research Platform to Enable Recruitment, Enrollment, Data Collection, and Follow-Up for a Highly Diverse Longitudinal US Cohort of 1 Million People in the All of Us Research Program: Design and Implementation Study.

BACKGROUND: Longitudinal cohort studies have traditionally relied on clinic-based recruitment models, which limit cohort diversity and the generalizability of research outcomes. Digital research platforms can be used to increase participant access, improve study engagement, streamline data collection, and increase data quality; however, the efficacy and sustainability of digitally enabled studies rely heavily on the design, implementation, and management of the digital platform being used. OBJECTIVE: We sought to design and build a secure, privacy-preserving, validated, participant-centric digital health research platform (DHRP) to recruit and enroll participants, collect multimodal data, and engage participants from diverse backgrounds in the National Institutes of Health's (NIH) All of Us Research Program (AOU). AOU is an ongoing national, multiyear study aimed to build a research cohort of 1 million participants that reflects the diversity of the United States, including minority, health-disparate, and other populations underrepresented in biomedical research (UBR). METHODS: We collaborated with community members, health care provider organizations (HPOs), and NIH leadership to design, build, and validate a secure, feature-rich digital platform to facilitate multisite, hybrid, and remote study participation and multimodal data collection in AOU. Participants were recruited by in-person, print, and online digital campaigns. Participants securely accessed the DHRP via web and mobile apps, either independently or with research staff support. The participant-facing tool facilitated electronic informed consent (eConsent), multisource data collection (eg, surveys, genomic results, wearables, and electronic health records [EHRs]), and ongoing participant engagement. We also built tools for research staff to conduct remote participant support, study workflow management, participant tracking, data analytics, data harmonization, and data management. RESULTS: We built a secure, participant-centric DHRP with engaging functionality used to recruit, engage, and collect data from 705,719 diverse participants throughout the United States. As of April 2024, 87% (n=613,976) of the participants enrolled via the platform were from UBR groups, including racial and ethnic minorities (n=282,429, 46%), rural dwelling individuals (n=49,118, 8%), those over the age of 65 years (n=190,333, 31%), and individuals with low socioeconomic status (n=122,795, 20%). CONCLUSIONS: We built a participant-centric digital platform with tools to enable engagement with individuals from different racial, ethnic, and socioeconomic backgrounds and other UBR groups. This DHRP demonstrated successful use among diverse participants. These findings could be used as best practices for the effective use of digital platforms to build and sustain cohorts of various study designs and increase engagement with diverse populations in health research.

Humans↗

PubMed2025

Molecular alterations in TP53, WNT, PI3K, TGF-Beta and RTK/RAS pathways in gastric cancer among ethnically heterogeneous cohorts.

BACKGROUND/OBJECTIVES: Gastric cancer (GC) remains a leading cause of cancer-related mortality worldwide, with significant racial and ethnic disparities in incidence, molecular characteristics, and patient outcomes. However, genomic studies focusing on Hispanic/Latino (H/L) populations remain scarce, limiting our understanding of ethnicity-specific molecular alterations. This study aims to characterize pathway-specific mutations in TP53, WNT, PI3K, TGF-Beta and RTK/RAS signaling pathways in GC and compare mutation frequencies between H/L and Non-Hispanic White (NHW) patients. Additionally, we evaluate the impact of these alterations on overall survival using publicly available datasets. METHODS: We conducted a bioinformatics analysis using publicly available GC datasets to assess mutation frequencies in TP53, WNT, PI3K, TGF-Beta and RTK/RAS pathway genes. A total of 800 patients were included in the analysis, comprising 83 H/L patients and 717 NHW patients. Patients were stratified by ethnicity (H/L vs. NHW) to evaluate differences in mutation prevalence. Chi-squared tests were performed to compare mutation rates between groups, and Kaplan-Meier survival analysis was used to assess overall survival differences based on pathway alterations among both H/L and NHW patients. RESULTS: Significant differences were observed in the TP53 pathway and related genes when comparing GC in H/L patients to NHW patients. TP53 mutations were less prevalent in H/L patients (9.6% vs. 19%, p = 0.03). Borderline significant differences were noted in the WNT pathway when comparing GC in H/L patients to NHW GC patients, with WNT alterations more frequent in H/L GC (8.4% vs. 4%, p = 0.08), and APC mutations significantly higher (3.6% vs. 0.8%, p = 0.05). Although alterations in PI3K, TGF-Beta and RTK/RAS pathways were not statistically significant, borderline significance was observed in genes related to these pathways, including EGFR (p = 0.07), FGFR1 (p = 0.05), FGFR2 (p = 0.05), and PTPN11 (p = 0.05) in the PI3K pathway, and SMAD4 (p = 0.08) in the TGF-Beta pathway. Survival analysis revealed no significant differences among H/L patients. However, NHW patients with TP53 and PI3K pathway alterations exhibited significant differences in overall survival, while those without TGF-Beta pathway alterations also showed a significant survival impact. In contrast, WNT pathway alterations were not associated with significant survival differences. These findings suggest that TP53, PI3K, and TGF-Beta pathway disruptions may have distinct prognostic implications in NHW GC patients. CONCLUSIONS: This study provides one of the first ethnicity-focused analyses of TP53, WNT, PI3K, TGF-Beta and RTK/RAS pathway alterations in GC, revealing significant racial/ethnic differences in pathway dysregulation. The findings suggest that TP53 and WNT alterations may play a critical role in GC among H/L patients, while PI3K and TGF-Beta alterations may have greater prognostic significance in NHW patients. These insights emphasize the need for precision medicine approaches that account for genetic heterogeneity and ethnicity-specific pathway alterations to improve cancer care and outcomes for underrepresented populations.

PI3K pathway↗

PubMed2026

A Novel BRCA1 Pathogenic Variant in Tunisian Patient With High Grade Ovarian Cancer: Favorable Therapeutic Response to Olaparib.

BACKGROUND: Ovarian cancer is one of the leading causes of death from gynecological cancer worldwide. Genetic mutations in genes involved in key cellular functions such as BRCA1/2 play a central role in tumorigenesis and have major implications for targeted therapeutic strategies, especially the use of poly (ADP-ribose) polymerase (PARP) inhibitors. CASE: Herein, we described a case of a 50-year-old woman diagnosed with severe anemia secondary to heavy menometrorrhagia. Initial gynecological evaluation, including transvaginal ultrasound, was unremarkable, and endometrial biopsy was not indicated. Imaging revealed no ovarian abnormalities; however, exploratory laparotomy identified a peritoneal nodule, leading to further investigation. Targeted NGS was performed on somatic and germline DNA samples and showed a frame shift deletion of 10 bp (c.1256_1265del: p.R419Ter) in the BRCA1 gene. This variant, identified only in tumor tissues, is novel and classified as pathogenic in ClinVar and ACMG databases. Additional somatic alterations were detected in TP53 and MSH6, while germline testing revealed only a variant of uncertain significance in BARD1. After first-line chemotherapy, the patient benefited from olaparib and achieved a progression-free survival of 23 months with good tolerance and no evidence of disease recurrence. CONCLUSION: This finding highlights the importance of integrating tumor-based genomic profiling with germline testing to identify actionable mutations and guide precision oncology. The identification of a novel somatic BRCA1 mutation expands the mutational spectrum of HGSOC and underscores the need to include underrepresented populations, such as those from North Africa, in genomic studies.

Humans↗

PubMed2026

Artificial Intelligence and Machine Learning Applications in Fibromuscular Dysplasia: Transforming Diagnosis, Risk Stratification, and Clinical Decision-Making.

Fibromuscular dysplasia (FMD) is a non-atherosclerotic vascular disorder with heterogeneous presentations, making diagnosis and management highly dependent on imaging and clinical expertise. This narrative review examines how artificial intelligence (AI) and machine learning (ML) are transforming FMD care. AI-enhanced imaging, particularly convolutional neural network-based analysis, improves detection of the characteristic "string-of-beads" pattern on CT angiography, magnetic resonance angiography, and ultrasound, although FMD-specific validation remains limited. ML models facilitate risk stratification, prediction of disease progression, and early identification of complications such as aneurysms and stroke by integrating clinical, imaging, and genomic data. AI-driven clinical decision support systems further enable personalized treatment selection through pharmacogenomic insights and robot-assisted interventions. Despite promising real-world applications, challenges persist, including limited large-scale datasets, workflow integration, regulatory barriers, and algorithmic bias affecting underrepresented populations. Future advances in explainable AI, federated learning, and digital health integration may enable a shift toward predictive, patient-centered FMD management.

Humans↗

PubMed2026

Underrepresented voices in a Colorado Biobank: Perspectives from focus groups on motivations, return of results, and data sharing.

Most participants in large cohorts, such as biobanks, are of European descent. This lack of representation has been an ongoing challenge in genomic research. Understanding the perspectives on genomics research and participation in biobanks of historically underrepresented populations could provide insight into ways to better engage with these groups. We conducted a series of virtual and in-person focus groups with individuals who self-identified as American Indian or Alaska Native (AI/AN), African American/Black (AA/B), or Hispanic/Latino (H/L) and who were enrolled in the Colorado Center for Personalized Medicine (CCPM) biobank. The focus group discussions were centered on participant experiences, including but not limited to their motivations, return of results, and data sharing. There was a total of 23 participants across the six focus groups. The majority of participants identified as AI/AN (60.9%), followed by H/L (39.1%), and AA/B (21.7%); many participants identified with multiple race/ethnicities. The motivations for participating in the biobank included the potential to advance science and health, the potential for return of results, to learn more about one's ancestry, and a few indicated that they were interested in helping the biobank be more representative of all populations. Notably, many expressed positive feedback of the focus groups and felt that their views were valued, illustrating the importance of community-centered work. Our findings can be used to guide recruitment and engagement of biobank participants, especially from diverse backgrounds, contributing to enhanced partnerships advancing knowledge and healthcare.

biobank↗

PubMed2026

Whole-Exome Sequencing in a Consanguinity-Enriched South Indian Retinitis Pigmentosa Cohort: Diagnostic Yield and Molecular Spectrum.

PURPOSE: To determine the molecular diagnostic yield, variant spectrum, inheritance architecture, and influence of consanguinity on whole-exome sequencing outcomes in a South Indian retinitis pigmentosa (RP) cohort. DESIGN: Prospective, registry-based cohort study. SUBJECTS: A total of 113 affected participants were enrolled through the Aravind Registry for Inherited Diseases of the Eye, including 109 unrelated probands and 4 affected relatives from already represented families. Primary analyses were restricted to the 109 unrelated probands. METHODS: Whole-exome sequencing was performed using a clinical exome workflow. Variants were interpreted using American College of Medical Genetics and Genomics/Association for Molecular Pathology criteria and cases were categorized as solved, possibly solved, inconclusive, or unsolved using prespecified inheritance-aware rules. MAIN OUTCOME MEASURES: Molecular diagnostic yield, distribution of implicated genes and variant classes, inheritance architecture, and diagnostic yield stratified by consanguinity status. RESULTS: Among the 109 unrelated probands, mean age at testing was 39.3 ± 14.1 years and 58.7% were male. Whole-exome sequencing identified 186 distinct rare variants across 92 inherited retinal disease genes, including 26 pathogenic and 33 likely pathogenic variants. A molecular diagnosis was established in 50 of 109 probands (45.9%), including 42 solved and 8 possibly solved cases; 45 (41.3%) were inconclusive and 14 (12.8%) remained unsolved, including 4 (3.7%) in whom no candidate variant was identified. EYS, USH2A, and ADGRV1 were the most frequently implicated genes. Autosomal recessive (AR) disease predominated (44/50, 88.0%). Consanguineous AR cases were exclusively homozygous (17/17); notably, 68.0% of nonconsanguineous AR cases were also homozygous (P = 0.013). Diagnostic yield was higher in consanguineous probands (51.4% vs. 41.7%), without reaching significance. Recurrent alleles included an established South Asian founder variant (MFSD8 c.1361T>C) and candidate founder alleles in EYS (c.4321C>T) and ADGRV1 (c.14329C>T). CONCLUSIONS: Whole-exome sequencing established a molecular diagnosis in nearly half of this South Indian RP cohort and revealed a predominantly recessive, homozygosity-enriched architecture shaped by consanguinity. These findings define a region-specific variant landscape to support clinical interpretation, genetic counseling, and future trial enrollment in this underrepresented population. FINANCIAL DISCLOSURES: The authors have no proprietary or commercial interest in any materials discussed in this article.

Consanguinity↗

PubMed2025

Privacy-hardened and hallucination-resistant synthetic data generation with logic-solvers.

MOTIVATION: Machine-generated or synthetic data is a valuable resource for training artificial intelligence algorithms, evaluating rare workflows, and sharing data under stricter data legislations. However, current statistical and deep learning methods struggle with large data volumes, are prone to hallucinating scenarios incompatible with reality, and seldom quantify privacy meaningfully. RESULTS: Here, we introduce Genomator, a logic solving approach (SAT solving), which efficiently produces private and realistic representations of the original data. We demonstrate the method on genomic data, which arguably is the most complex and private information. We benchmark Genomator against state-of-the-art methodologies (Markov generation, Wasserstein Generative Adversarial Network and Conditional Restricted Boltzmann Machines), demonstrating a 40%-530% accuracy improvement and 57%-172% higher privacy. Genomator is also 3-100 times more efficient, making it the only tested method that scales to whole genomes. We show the universal trade-off between privacy and accuracy, and use Genomator's tuning capability to cater to all applications along the spectrum, from provable private representations of sensitive cohorts, to datasets with indistinguishable pharmacogenomic profiles. Demonstrating the production-scale generation of tuneable synthetic genomes hold great potential for balancing underrepresented populations in medical research and advancing global data exchange. AVAILABILITY AND IMPLEMENTATION: Genomator is available at https://github.com/csiro/genomator.

Algorithms↗

PubMed2025

Pathway-specific genomic alterations in pancreatic cancer across diverse cohorts.

BACKGROUND/OBJECTIVES: Pancreatic cancer (PC) is an aggressive malignancy with rising incidence and poor survival rates. While Hispanic/Latino (H/L) patients have a lower overall incidence compared to Non-Hispanic White (NHW) patients, they are diagnosed at younger ages, often present with more advanced disease, and experience worse survival outcomes. The molecular drivers underlying these disparities remain poorly understood. Key oncogenic pathways, including TP53, WNT, PI3K, TGF-Beta, and RTK/RAS, play crucial roles in tumor progression, therapy resistance, and response to targeted treatments. However, their ethnicity-specific alterations and prognostic implications in PC remain largely unexplored. This study aims to characterize pathway-specific mutations in PC among H/L and NHW patients, assess tumor mutation burden, and identify ethnicity-specific oncogenic drivers using publicly available datasets. The findings may provide critical insights to optimize precision medicine strategies and enhance targeted therapies for underrepresented populations. METHODS: A bioinformatics analysis was performed using publicly available PC datasets to evaluate mutation frequencies in genes associated with the TGF-Beta, RTK/RAS, WNT, PI3K, and TP53 pathways. The study included 4,248 patients, with 407 identified as H/L and 3,841 as NHW. Patients were stratified by ethnicity to assess differences in mutation prevalence. Chi-squared tests were conducted to compare mutation rates between groups, while Kaplan-Meier survival analysis was performed to evaluate overall survival differences based on pathway-specific alterations. RESULTS: Significant differences were observed in the TGF-Beta pathway between H/L and NHW patients. TGF-Beta mutations were less prevalent in H/L patients (18.4% vs. 24.4%, p = 8.6e-3). Additionally, genes related to the TGF-Beta pathway showed significant alterations, with SMAD2 (1.5% vs. 0.4%, p = 6.3e-3) and SMAD4 (15% vs. 19.9%, p = 0.02) exhibiting notable differences. Although RTK/RAS, WNT, PI3K, and TP53 pathway mutations were not statistically significant overall, borderline significance was observed in genes associated with these pathways, including ERBB4 (3.4% vs. 1.8%, p = 0.03), ALK (2.7% vs. 1.1%, p = 0.01), HRAS (1.2% vs. 0.1%, p = 1.3e-4), and RIT1 (0.7% vs. 0.1%, p = 0.03) in the RTK/RAS pathway, as well as CTNNB1 (2.9% vs. 1.3%, p = 0.01) in the WNT pathway. Survival analysis revealed no significant differences in overall survival among H/L patients. However, NHW patients with TP53 pathway alterations exhibited borderline significant differences in survival outcomes.

PI3K pathway↗

PubMed2026

First report of MUTYH-associated polyposis with c.1353_1355del and c.452A>G mutations in Tolima Grande region from Colombia: a case report.

INTRODUCTION: The MUTYH gene encodes a protein involved in DNA repair and is known for MUTYH-associated polyposis (MAP), a rare autosomal recessive condition that predisposes individuals to colorectal cancer (CRC), colorectal polyps and familial colorectal cancer syndrome. CASE REPORT: We describe the first Tolima Grande region from a Colombian report of individuals carrying pathogenic MUTYH variants c.452A>G and c.1353_1355del associated with polyposis phenotypes. Three main cases with detailed histopathological findings and family history are presented. Additionally, independent findings from Clinaltec identified three further individuals carrying c.452A>G and one heterozygous carrier of c.1353_1355del detected during predictive multigene panel testing. DISCUSSION: These cases highlight the diagnostic and clinical challenges of distinguishing biallelic pathogenic MUTYH variants, which define MAP and confer high CRC risk, from monoallelic carriers, whose cancer risk is substantially lower. Misclassification may result in inappropriate surveillance strategies and missed opportunities for early detection. From a public health perspective, these findings emphasize persistent gaps in hereditary CRC prevention in underrepresented populations, including fragmented cancer registries and limited incorporation of genetic and family history data into clinical decision-making. CONCLUSION: This report provides evidence in Colombia of polyposis-associated pathogenic MUTYH variants c.452A>G and c.1353_1355del, underscoring the importance of expanding genetic evaluation for hereditary CRC in Latin American populations.

Colombian population↗