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Results for “Phenotype modeling”

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PubMed1979

The use of twins in the analysis of assortative mating.

The simulations illustrated show that a plausible model for mate selection can generate data on the similarity of twins and their spouses which are remarkably consistent with a transitive model for the effects of mate selection. This is, biological considerations impose constraints upon the relative values of correlations which are not foreseen, for example, by the some advocates of conventional path models although they might be predicted by common sense. In particular, the correlation between the spouses of twins is expected to be non-zero under a model of phenotypic assortment and turns out to be approximately equal to the product of the twin correlation and the square of the marital correlation. The relative magnitudes of the correlations derived from an empirical study of such relationships should enable models of phenotypic assortment to be tested more rigorously. Including both identical and non-identical twins in the sample studied should permit the inherited and cultural components of the mating system to be identified with more conviction. In the event of one sex playing a more significant role in mate selection for particular traits, such studies should reveal diagnostic patterns of familial correlations as long as male and female twins and their spouses are analysed separately. If the analysis is restricted to phenotypic correlations of the parents, the qualitative findings do not appear to be greatly affected by selection due to assortative mating although a reduction in variance is to be expected if a large proportion of individuals is unable to mate. In such cases twins will also be significantly concordant for mating. The consequences of such varied regimes of assortation for the population structure and the relationship between traits in subsequent generations remain the object of future inquiry.

Female↗

PubMed1977

Polymorphism at two loci through selection for linear metric deviation.

A model of phenotypic stabilising selection in which the fitness of an individual depends solely on its phenotype, and not directly on its genetic constitution, is explored algebraically for a system of two linked loci of unequal effect. It is found that selection for metric deviation gives rise to polymorphic gametefrequency equilibria for a variety of fitness regimes. Stability of non-trivial equilibria occurs for a wide range of parameter sets. Stability is facilitated by close linkage and inequality between gene effects. It is suggested that, in general genetic variation may be maintained under stabilising selection when the fitness of double heterozygotes exceeds that of the phenotypically intermediate homozygotes.

Animals↗

PubMed2025

Tulp3 quantitative alleles titrate requirements for viability, brain development, and kidney homeostasis but do not suppress Zfp423 mutations in mice.

Tubby-like protein 3 (TULP3) regulates receptor trafficking in primary cilia and antagonizes SHH signaling. Tulp3 knockout mice are embryonic lethal with developmental abnormalities in multiple organs, while tissue-specific knockouts and viable missense alleles cause polycystic kidney disease. Human patients with TULP3 mutations present with variable, but often multi-organ fibrotic disease. We previously showed that mouse and human Tulp3 expression is negatively regulated by ZNF423, which is required for SHH sensitivity in some progenitor cell models. The level of TULP3 function required to prevent mutant phenotypes has not been known. Here we report a Tulp3 quantitative allelic series, designed by targeting the polypyrimidine tract 5' to the splice acceptor of a critical exon, that shows distinct dose-response effects on viability, brain overgrowth, weight gain, and cystic kidney disease. We find limited evidence for genetic interaction with Zfp423 null or hypomorphic mutations. Together, these results establish an approach to developing quantitative allelic series by exon exclusion, rank-order dose-sensitivity of Tulp3 phenotypes, and model thresholds for TULP3 function to prevent severe outcomes.

Journal Article↗

PubMed2026

A sequence-based classifier distinguishes phenotype-associated genes from other gene models in plants.

Only a small fraction of annotated plant genes possess experimentally validated associations with specific phenotypes. Phenotype-associated genes have distinct structural, molecular, and evolutionary characteristics compared with nonvalidated gene models. Here, we develop a simple classifier that uses sequence and evolutionary features, which can be generated for any species with an annotated reference genome assembly, to accurately distinguish phenotype-associated genes from both the overall population of annotated gene models and a specific set of genes identified as being tolerant of premature stop mutations. A model trained solely on genes from maize (Zea mays) identifies and prioritizes rice (Oryza sativa) and Arabidopsis (Arabidopsis thaliana) genes that are highly enriched in genes with experimentally validated links to phenotypes in both of these evolutionarily distant species. Gene models predicted to have a higher probability of being linked to phenotypes display patterns consistent with known biological properties of phenotype-associated genes. Notably, the sets of genes predicted to have a high probability of being linked to phenotype variation do not consist exclusively of well-characterized gene families but included many uncharacterized gene families carrying domains of unknown function. The quantitative scores generated by this model offer a valuable resource for prioritizing and exploring the vast number of uncharacterized gene models in plants, reducing the risk of failure in future reverse genetic efforts and potentially accelerating gene discovery and functional annotation in crops.

Phenotype↗

PubMed2026

Disruption of GAD1 protein architecture by a novel missense variant in a consanguineous family with autosomal recessive intellectual disability.

BACKGROUND: Intellectual disability represents a heterogeneous group of neurodevelopmental disorders marked by significant impairments in intellectual functioning and adaptive behavior. Among the various causes, genetic factors play a major role, with autosomal recessive intellectual disability (ARID) constituting a genetically diverse subgroup. ARID is prevalent in consanguineous families and arises from homozygous mutations that disrupt critical genes involved in brain development and function. OBJECTIVE: This study aimed to identify disease-causing genetic variants responsible for ARID in a consanguineous Pakistani family and to evaluate the structural and functional impact of a novel variant identified in GAD1 through protein modeling. METHODS: A consanguineous family affected with intellectual disability was enrolled. Whole-exome sequencing was performed on an affected individual, followed by bioinformatics analysis including alignment to the GRCh38 reference genome, variant calling, and annotation. Variants were filtered based on rarity, predicted functional impact, and autosomal recessive inheritance pattern. Candidate variants were validated and assessed by Sanger sequencing and segregation analysis. Protein modeling was performed to evaluate the structural impact of the identified variant. RESULTS: A novel homozygous missense variant NM_000817:c.1700G>A;p.Arg567Gln in GAD1 was identified. Segregation analysis confirmed co-segregation of the variant with the affected phenotype. Protein modeling suggested that the variant may disrupt GAD1 enzymatic function involved in gamma-aminobutyric acid synthesis. CONCLUSION: This study emphasizes the significance of genetic investigation in familial cases and the crucial role that GAD1 mutations play in neurodevelopmental disorders with intellectual disability. The results advance the knowledge of molecular causes of ARID and broaden the mutational range.

Pakistani↗

PubMed1992

Sympathetic modulation of the cardiac myocyte phenotype: studies with a cell-culture model of myocardial hypertrophy.

Myocardial hypertrophy is the common endpoint of many cardiovascular stimuli such as hypertension, myocardial infarction, valvular disease, and congestive failure. Catecholamines have long been implicated in the pathogenesis of myocardial hypertrophy, however, it is very difficult to sort out catecholamine mechanisms in vivo. We have developed a cell-culture model which excludes hemodynamic effects and allows the assignment of receptor specificity to catecholamine effects. Utilizing this system, we have shown that stimulation of the alpha 1 adrenergic receptor leads to the development of myocardial hypertrophy and results in the selective up-regulation of the fetal/neonatal mRNAs encoding skeletal alpha-actin and beta-MHC, a pattern similar to that seen with hypertrophy in-vivo. Utilizing a co-transfection assay, we have also obtained data that suggest that the beta-PKC isozyme is in a pathway regulating transcription of the beta-MHC isogene. Beta adrenergic stimulation of the cultured cardiac myocytes also results in a modest degree of hypertrophy, however, this effect may be dependent upon myocyte contractile activity and may involve, at least in part, the non-muscle cells present in the culture system.

Animals↗

PubMed1976

Phenotypic structure and bifurcation behavior of population models.

Explore the source record for details and available documents.

Age Factors↗

PubMed2017

Drug target ontology to classify and integrate drug discovery data.

BACKGROUND: One of the most successful approaches to develop new small molecule therapeutics has been to start from a validated druggable protein target. However, only a small subset of potentially druggable targets has attracted significant research and development resources. The Illuminating the Druggable Genome (IDG) project develops resources to catalyze the development of likely targetable, yet currently understudied prospective drug targets. A central component of the IDG program is a comprehensive knowledge resource of the druggable genome. RESULTS: As part of that effort, we have developed a framework to integrate, navigate, and analyze drug discovery data based on formalized and standardized classifications and annotations of druggable protein targets, the Drug Target Ontology (DTO). DTO was constructed by extensive curation and consolidation of various resources. DTO classifies the four major drug target protein families, GPCRs, kinases, ion channels and nuclear receptors, based on phylogenecity, function, target development level, disease association, tissue expression, chemical ligand and substrate characteristics, and target-family specific characteristics. The formal ontology was built using a new software tool to auto-generate most axioms from a database while supporting manual knowledge acquisition. A modular, hierarchical implementation facilitate ontology development and maintenance and makes use of various external ontologies, thus integrating the DTO into the ecosystem of biomedical ontologies. As a formal OWL-DL ontology, DTO contains asserted and inferred axioms. Modeling data from the Library of Integrated Network-based Cellular Signatures (LINCS) program illustrates the potential of DTO for contextual data integration and nuanced definition of important drug target characteristics. DTO has been implemented in the IDG user interface Portal, Pharos and the TIN-X explorer of protein target disease relationships. CONCLUSIONS: DTO was built based on the need for a formal semantic model for druggable targets including various related information such as protein, gene, protein domain, protein structure, binding site, small molecule drug, mechanism of action, protein tissue localization, disease association, and many other types of information. DTO will further facilitate the otherwise challenging integration and formal linking to biological assays, phenotypes, disease models, drug poly-pharmacology, binding kinetics and many other processes, functions and qualities that are at the core of drug discovery. The first version of DTO is publically available via the website http://drugtargetontology.org/ , Github ( http://github.com/DrugTargetOntology/DTO ), and the NCBO Bioportal ( http://bioportal.bioontology.org/ontologies/DTO ). The long-term goal of DTO is to provide such an integrative framework and to populate the ontology with this information as a community resource.

Biological Ontologies↗

PubMed2026

MicroRNA-mRNA Networks in Skeletal Muscle of Tailored Pig Models for Dystrophinopathies.

BACKGROUND: Duchenne muscular dystrophy (DMD) and Becker muscular dystrophy (BMD) are X-linked dystrophinopathies caused by mutations in the dystrophin (DMD) gene. A common DMD-causing mutation in humans is exon 52 deletion (DMDΔ52), which disrupts the reading frame and abolishes dystrophin expression. Therapeutic skipping of exon 51 or 53 can restore the reading frame, producing a truncated but functional protein and generating a BMD-like phenotype. Porcine models recapitulating DMDΔ52 (DMD) and DMDΔ51-52 (BMD-like) were used to identify molecular differences and condition-specific miRNA-mRNA networks. METHODS: Skeletal muscle (triceps brachii) from four DMD, four BMD, and five wild-type (WT) pigs at 3.5 months of age underwent stranded total RNA-seq and small RNA-seq. Differentially expressed mRNAs (|log2FC| ≥ 1, adj. p ≤ 0.05) and miRNAs (adj. p ≤ 0.05) were identified with DESeq2. miRNA-mRNA networks were constructed using RNAhybrid predictions (MFE < -25 kcal/mol, seed pairing) filtered by inverse Pearson correlation. RESULTS: Compared with WT, DMD muscle exhibited 1440 upregulated and 487 downregulated genes, characterized by strong repression of structural, contractile, calcium-handling and metabolic genes (e.g., MYBPC2, MYL3, MYLK2, CACNA2D3, CACNA2D4) and marked upregulation of inflammatory mediators and innate immune receptors (e.g., IL6, IL18, IL1R1, CCR1/2/5, TLR1/2/4/7/9). In contrast, BMD muscle showed partial restoration of these pathways and clustered closer to WT in global expression profiles. Distinct miRNA signatures were observed between DMD and BMD. Differential expression analysis identified 22 upregulated and 12 downregulated miRNAs in DMD versus WT and 36 upregulated and 21 downregulated miRNAs in BMD versus WT. Integration of miRNA and mRNA data yielded extensive regulatory networks (1013 unique pairs for upregulated miRNAs in DMD; 2679 pairs for downregulated miRNAs in BMD). Two condition-specific miRNAs emerged as strong biomarker candidates: ssc-miR-296-3p (upregulated exclusively in DMD, targeting 228 genes enriched in muscle structure and fatty acid metabolism) and ssc-miR-423-5p (elevated specifically in BMD, targeting 67 genes involved in calcium signalling and tissue development). Several dysregulated miRNAs, including miR-199a-5p and miR-199b, overlapped with those reported in human DMD and other muscular dystrophies. CONCLUSIONS: Exon 51 skipping in the DMDΔ52 background partially restores key transcriptional programmes in skeletal muscle but does not fully normalize them to WT patterns. The identification of condition-specific miRNAs highlights post-transcriptional regulatory differences between DMD and BMD, positioning them as promising biomarkers and therapeutic targets. These findings underscore the translational value of porcine dystrophinopathy models for mechanistic studies and preclinical evaluation of RNA-targeted interventions.

Animals↗

PubMed1992

Gaucher disease in the neonate: a distinct Gaucher phenotype is analogous to a mouse model created by targeted disruption of the glucocerebrosidase gene.

A group of neonates with Gaucher disease with a particularly devastating clinical course is described. The phenotype of these infants is analogous to that of a Gaucher mouse, which was created by targeted disruption of the mouse glucocerebroside gene. Similar to the homozygous mutant mice with glucocerebrosidase deficiency, these infants present at or shortly after birth, have rapidly progressing fulminant disease, and many have associated ichthyotic skin and/or hydrops fetalis. This transgenetic mouse model of Gaucher disease has helped us to appreciate a distinct Gaucher phenotype. Potentially, as this technology is applied to create other animal models of metabolic diseases, it may enable the recognition of other, as yet unappreciated presentations of inherited disorders.

Animals↗

PubMed2026

Detection of antibiotic heteroresistance in clinical microbiology: current and emerging methodologies.

BACKGROUND: Antibiotic heteroresistance (HR) is characterised by the coexistence of susceptible and resistant subpopulations within an apparently isogenic bacterial isolate. Because routine antimicrobial susceptibility testing (AST) primarily assesses the dominant population, HR may escape detection, potentially leading to discrepancies between laboratory susceptibility categorisation and the underlying bacterial population structure. OBJECTIVES: To provide a critical and practice-oriented evaluation of current and emerging methodologies for HR detection and to discuss their strengths, limitations, and potential for clinical implementation. SOURCES: Narrative review based on PubMed searches, complemented by screening of key reference lists and relevant EUCAST and CLSI documents. Peer-reviewed literature was prioritised. CONTENT: Phenotypic approaches, particularly population analysis profiling, remain the reference method for HR definition, but their labour-intensive workflows, long turnaround times, and limited standardisation restrict routine implementation. Alternative strategies, including modified AST assays, metabolic assays, and single-cell platforms, offer gains in speed or throughput but require broader validation. Molecular approaches such as quantitative PCR, droplet digital PCR, targeted deep sequencing, and whole-genome sequencing improve detection of minority resistance determinants. Emerging computational frameworks, including machine learning models integrating phenotypic and genomic data, represent a promising frontier for scalable HR prediction. IMPLICATIONS: Available evidence supports the clinical relevance of HR, although its association with adverse outcomes varies across bacterial species and antibiotic classes. Harmonised methodologies and clinically validated interpretive criteria are needed to support integration of HR assessment into routine diagnostics. Prospective multicentre studies and further standardisation, including engagement with EUCAST and CLSI, will be important to advance clinical implementation.

Antimicrobial resistance↗

PubMed2026

Hologenomic interactions promote the higher-order evolvability of phenotypic complexity.

Current models for evolvability and complexity generally focus on mutational and regulatory processes in the host genome alone, limiting their ability to explain the origin, inheritance, and dynamics of many phenotypes. We describe a framework treating multigenome interactions in the holobiont as a central process that impacts the genotype-phenotype map, expanding the dimensionality of mechanisms producing heritable variation, generating novel traits, and exploring adaptive trajectories. These mechanisms can promote both complex phenotypic innovation and evolutionary systems drift. Many evolutionary pathways and novelties cannot be fully understood from host data alone but require consideration of hologenomic targets of selection. We outline hypotheses and methods to quantify and evaluate their impacts as a fundamental macroevolutionary process.

cellular innovation↗

PubMed2025

Multiomic clocks to predict phenotypic age in mice.

Biological age refers to a person's overall health in aging, as distinct from their chronological age. Diverse measures of biological age, referred to as "clocks," have been developed in recent years and enable risk assessments and an estimation of the efficacy of longevity interventions in animals and humans. Although most clocks are trained to predict chronological age, clocks have been developed to predict more complex composite biological age outcomes, at least in humans. These composite outcomes can be made up of a combination of phenotypic data, chronological age, and disease or mortality risk. Here, we develop the first such composite biological age measure for mice: the mouse phenotypic age model (Mouse PhenoAge). This outcome is based on frailty measures, complete blood counts, and mortality risk in a longitudinally assessed cohort of male and female C57BL/6 mice. We then develop clocks to predict Mouse PhenoAge, based on multiomic models using metabolomic and DNA methylation data. Our models accurately predict Mouse PhenoAge, and residuals of the models are associated with remaining lifespan, even for mice of the same chronological age. These methods offer novel ways to accurately predict mortality in laboratory mice, thus reducing the need for lengthy and costly survival studies.

Animals↗

PubMed1992

Alternative models for early onset of childhood leukaemia.

This paper considers theoretical models for early-onset childhood leukaemia. The major focus of attention is the two-hit mutational model. A simple mathematical representation is used to explore mechanisms which might lead to onset of leukaemia at an unusually early age. Two such mechanisms are considered. The first of these, a germinal or very early embryonic first mutation is shown to imply that multiple independent leukaemic clones are likely to arise sequentially in very young patients. Clonal multiplicity could underlie the poor prognosis which has been associated with early onset childhood acute lymphoblastic leukaemia. It implies that curative therapy might require intensive treatment followed by bone marrow rescue to ensure eradication of all single-hit predisposed target cells. The prediction of multiple leukaemic clones might be tested in female patients by means of X-linked restriction fragment length polymorphisms and in patients with B-lineage neoplasms by determination of immunoglobin gene rearrangements. A second mechanism for early onset leukaemogenesis is the occurrence of a high cellular mutation rate in some patients. This is shown to result in leukaemia at significantly earlier age if the mutation rate is sufficiently high to influence target cell loss rate. This mechanism would enable more rapid clonal evolution of leukaemic cells and the early emergence of drug resistant variants. The prediction might be tested experimentally by sequential observation of genetic markers (e.g. Karyotypes, DNA fingerprint patterns) and the rate of emergence of drug resistant phenotypes. Other models, considered more briefly, include one-hit mutational 'dominants' in the developing embryo and faster growth kinetics in neoplasms of younger patients.(ABSTRACT TRUNCATED AT 250 WORDS)

Cell Division↗

PubMed2025

Cost-effectiveness of alternative cascade screening strategies for familial hypercholesterolemia with realistic cascade screening acceptance rates and use of novel treatment.

BACKGROUND AND AIMS: Cascade screening (CS) for familial hypercholesterolemia (FH) has been found to be cost-effective in many published studies. However, most existing studies (i) ignored or overstated first-degree relative (FDR) participation rate (as 60-100 %), (ii) did not consider novel and expensive therapies, e.g. PCSK9 inhibitors (PCSK9i), and (iii) were conducted outside of Asia. This study, conducted in Singapore, where FDR participation rate is about 25 % among probands who have known pathogenic variants, aims to identify drivers of cost-effectiveness of CS protocols for FH. METHODS: Four CS protocols, which vary in the application of genetic tests, were examined using a hybrid decision tree-Markov model. Sensitivity analyses were conducted to identify drivers of cost-effectiveness. RESULTS: Cascade acceptance rates are key drivers of cost-effectiveness. Other drivers include age of proband, prevalence of FH among probands, health-related quality of life loss with cardiovascular disease, timeliness of starting treatment post-screening, treatment effectiveness, cost of PCSK9i and discount rate for cost and QALY. With cascade acceptance rates observed in Singapore, among various screening protocols examined, probabilities of being cost-effective ranged from 86 % to 95 % when no access to PCSK9i and ranged from 75 % to 98 % when PCSK9i are provided. The most cost-effective protocol differs depending on cascade acceptance rates and whether PCSK9i is provided. CONCLUSION: For better cost-effectiveness of CS for FH, health systems need to look for ways to improve proband's willingness to share contact of their relatives and relatives' willingness to be screened and to lower the cost of novel treatment. Other ways to improve cost-effectiveness include to select age groups for proband screening, improve screening detection rate among probands, and start timely treatment post-screening.

Humans↗

PubMed1992

Genetic alterations in the adenoma--carcinoma sequence.

Tumorigenesis is thought to be a multistep process in which genetic alterations accumulate, ultimately producing the neoplastic phenotype. A model was proposed to explain the genetic basis of colorectal neoplasia that included several salient features. First, colorectal tumors appear to occur as a result of the mutational activation of oncogenes coupled with the inactivation of tumor-suppressor genes. Second, mutations in at least four or five genes are required to produce a malignant tumor. Third, although the genetic alterations often occur in a preferred sequence, the total accumulation of changes, rather than their chronologic order of appearance, is responsible for determining the tumor's biologic properties. Several different genetic alterations were identified that occur during colorectal tumorigenesis. Activational mutation of the ras oncogene was found in approximately 50% of colonic carcinomas and in a similar percentage of intermediate-stage and late-stage adenomas. Allelic deletions were discovered of specific portions of chromosomes 5, 17, and 18, which presumably harbor tumor-suppressor genes. The target of allelic loss events on chromosome 17 has been shown to be the p53 gene, which is mutated, not only in colonic cancer, but also in a large percentage of other human solid tumors. The gene dcc recently was identified; this candidate tumor-suppressor gene on chromosome 18 appears to be altered in colorectal carcinomas. The protein encoded by the dcc gene has significant sequence similarity to neural cell adhesion molecules and other related cell-surface glycoproteins. By mediating cell-cell and cell-substrate interactions, this class of molecules may have important functions in mediating cell growth and differentiation. Alterations of the dcc gene may interfere with maintenance of these controls and thus may play a role in the pathogenesis of colorectal neoplasia. Another candidate tumor-suppressor gene also was identified on chromosome 5, mcc (for mutated in colorectal cancers). The mcc genetic alterations include one tumor with somatic rearrangement of one mcc allele and several tumors with somatically acquired point mutations in the coding region. Studies currently are ongoing to (1) identify additional tumor-suppressor gene candidates, (2) increase our understanding of normal tumor-suppressor gene function, and (3) demonstrate the functional tumor-suppressor ability of these genes both in vivo and in vitro.

Adenoma↗

PubMed2025

Study research protocol for Phenome India-CSIR Health Cohort Knowledgebase: A prospective multi-modal follow-up study on a nationwide employee cohort.

Predicting individual health trajectories based on risk scores can help formulate effective preventive strategies for diseases and their complications. Currently, most risk prediction algorithms rely on epidemiological data from the Caucasian population, which often do not translate well to the Indian population due to ethnic diversity, differing dietary and lifestyle habits, and unique risk profiles. In this multi-center prospective longitudinal study conducted across India, we aim to address these challenges by developing clinically relevant risk prediction scores for cardio-metabolic diseases specifically tailored to the Indian population. India, which accounts for nearly 18% of the global population, also has a significant diaspora worldwide. This program targets longitudinal collection and bio-banking of samples from over 10 000 employees both working and retirees of the Council of Scientific and Industrial Research and their spouses, with baseline sample collection already completed. During the baseline collection, we gathered multi-parametric data including clinical questionnaires, lifestyle and dietary habits, anthropometric parameters, lung function assessments, liver elastography by Fibroscan, electrocardiogram readings, biochemical data, and molecular assays, including but not limited to genomics, plasma proteomics, metabolomics, and fecal microbiome analysis. In addition to exploring associations between these parameters and their cardio-metabolic outcomes, we plan to employ artificial intelligence algorithms to develop predictive models for phenotypic conditions. This study could pave the way for precision medicine tailored to the Indian population, particularly for the middle-income strata, and help refine the normative values for health and disease indicators in India.

cardio-metabolic↗

PubMed2025

Uncovering the genetic architecture of ME/CFS: a precision approach reveals impact of rare monogenic variation.

BACKGROUND: Myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS) is a disabling and heterogeneous disorder lacking validated biomarkers or targeted therapies. Clinical variability and elusive pathophysiology hinder progress toward effective diagnostics and treatment. Core symptoms include persistent fatigue, post-exertional malaise, unrefreshing sleep, cognitive dysfunction, and pain. We tested whether an individualized, “n-of-1” genomic and transcriptomic framework combined with comprehensive, participant-informed phenotyping could reveal molecular signatures unique to each patient. METHODS: Clinical-grade whole-genome sequencing was conducted in 31 affected individuals from 25 families, with RNA-seq performed on a subset (16 affected, 7 unaffected) using blood samples. Machine-learning assisted variant triage, transcript-aware damage prediction, and expert review identified pathogenic or likely pathogenic variants in 8 of 25 probands (32%) and 12 of 31 affected individuals (39%). RESULTS: Findings revealed marked genetic heterogeneity, including large-effect rare and more common variants. Implicated pathways included ATP generation, oxidative phosphorylation, fatty acid oxidation; regulation of glycolysis, amino acid and lipid turnover; ion and solute homeostasis; synaptic signaling, excitability, oxygen transport, and muscle integrity, resilience, and post-exertional recovery; previously implicated processes. Plausible modifiers influencing disease onset, severity, and relapsing–remitting patterns and possibly explaining intrafamilial variability and inconsistent findings across studies, were also identified. Despite gene-level diversity, downstream effects converged on impaired energy production, reduced stress resilience, and vulnerability to post-exertional metabolic failure; disruptions consistent with core ME/CFS symptoms of exertional intolerance, cognitive fog, and fatigue. CONCLUSIONS: Our findings support the hypothesis that at least a subset of ME/CFS cases represent distinct molecular disorders that converge on shared physiological pathways. Validation in larger, more diverse cohorts will be essential to test this hypothesis and establish generalizability, but increase size alone is unlikely to resolve causation in a disorder defined by rarity, heterogeneity, and molecular complexity. We suggest that progress will require experimental designs that integrate individual-level genomic data with deep, participant-informed deep phenotyping, capturing the combined effects of rare and common variants and environmental modifiers on disease expression and progression. We believe that an individualized precision medicine framework will uncover molecular drivers and modifiers of ME/CFS previously obscured by heterogeneity, enabling biologically informed stratification, improved trial design, biomarker discovery, and targeted interventions in this historically neglected condition.

Humans↗