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PubMed2026

Distinct mutational landscapes for germline and somatic cancer variants in forty tumor suppressor genes.

Germline and somatic cancer variants in tumor suppressor genes (TSGs) share loss-of-function mechanisms, but studies of a few genes (DICER1 and CEBPA) have demonstrated differences in variant consequence and location. To systematically assess whether TSGs display distinct mutational patterns, we leveraged large public genetic databases and compared 32,941 high-quality pathogenic/likely pathogenic (P/LP) germline variants in ClinVar, with 12,907 oncogenic/likely oncogenic (O/LO) somatic tumor variants from cBioPortal across 40 TSGs. Only 3,863 (9.2%) variants were shared. Eighteen TSGs showed significantly different distributions of variant occurrences by molecular consequence, replicated with non-overlapping somatic data from the COSMIC database (chi-squared tests, false discovery rate = 5%). DICER1, TP53, and SMAD4 displayed excess somatic missense events, while nine TSGs (e.g., RB1 and APC) contained excess somatic stop-gain events throughout the coding sequence. Analysis by tumor type revealed excess stop-gain events in tissues exposed to environmental mutagens with corresponding mutation signatures. For several TSGs (WT1), germline variants predispose to tumors (Wilms' tumor) distinct from the majority source of somatic data (myeloid leukemia). Germline and somatic events are also distributed unevenly across cDNA locations, with 103 regions of preferential clustering in 39 TSGs (78 somatic and 25 germline). Twenty somatic clusters contained recurring frameshifts in homopolymer runs, many in tumors with microsatellite instability. Germline clusters contain more germline-exclusive variants, some driving non-cancer phenotypes reflecting genetic pleiotropy. Altogether, germline and somatic variants of TSGs represent unique sets with substantially different patterns shaped by selection pressures from gene-specific and somatic mutational mechanisms. Characterizing these distinctions enables more accurate clinical interpretation of TSG variants.

Humans↗
PubMed1995

Statistical genetics of normal variation in family data for oligogenic diseases.

A quadrivariate quantitative genetic analysis detected significant heritabilities for four simulated quantitative traits (Q1-Q4) with additive genetic pleiotropy between traits Q1, Q2, and Q3. Using univariate segregation analysis, we tentatively detected five major loci: one each for Q2, Q3, and Q4 and two, at different maxima, for Q1. Bivariate one-locus segregation analysis identified significant major locus pleiotropy for Q1, Q2, and Q3 only; and suggested identity between one of Q1's major genes and that for Q2, and between the second Q1 major gene and that for Q3. Patterns of linkage, supportive of inferences from the bivariate segregation analyses, were detected between three candidate genes and the major genes for Q1, Q2 and Q4.

Alleles↗
PubMed2025

A genome-wide analysis of the shared genetic risk architecture of complex neurological and psychiatric disorders.

Although neurological and psychiatric disorders have historically been considered to reflect distinct pathogenic entities, recent findings suggest shared pathophysiological mechanisms. However, the extent to which these heritable disorders share genetic influences remains unclear. Here we performed a comprehensive analysis of genome-wide association study data, involving nearly 1 million cases across ten neurological diseases and ten psychiatric disorders, to compare their common genetic signal and biological associations. Using complementary statistical tools, we demonstrate that a large set of common genetic variants impacts the risk of multiple neurological and psychiatric disorders, even in the absence of genetic correlations. Furthermore, genome-wide association studies on psychiatric disorders consistently implicate neuronal biology, whereas neurological diseases are associated with diverse neurobiological processes. Together, this study elucidates the genetic relationship between complex neurological and psychiatric disorders, indicating a larger degree of genetic pleiotropy than previously recognized. The findings have implications for disease classification, precision medicine and clinical practice.

Humans↗
PubMed2004

Cell-to-cell signalling in Escherichia coli and Salmonella enterica.

Cell-to-cell signalling in prokaryotes that leads to co-ordinated behaviour has been termed quorum sensing. This type of signalling can have profound impacts on microbial community structure and host-microbe interactions. The Gram-negative quorum-sensing systems were first discovered and extensively characterized in the marine Vibrios. Some components of the Vibrio systems are present in the classical genetic model organisms Escherichia coli and Salmonella enterica. Both organisms encode a signal receptor of the LuxR family, SdiA, but not a corresponding signal-generating enzyme. Instead, SdiA of Salmonella detects and responds to signals generated only by other microbial species. Conversely, E. coli and Salmonella encode the signal-generating component of a second system (a LuxS homologue that generates AI-2), but the sensory apparatus for AI-2 differs substantially from the Vibrio system. The only genes currently known to be regulated by AI-2 in Salmonella encode an active uptake and modification system for AI-2. Therefore, it is not yet clear whether Salmonella uses AI-2 as a signal molecule or whether AI-2 has some other function. In E. coli, the functions of both SdiA and AI-2 are unclear due to pleiotropy. Genetic strategies to identify novel signalling systems have been performed with E. coli and Providencia stuartii. Several putative signalling systems have been identified, one that uses indole as a signal and another that releases what appears to be a peptide. The latter system has homologues in E. coli and Salmonella, as well as other bacteria, plants and animals. In fact, the protease components from Providencia and Drosophila are functionally interchangeable.

Bacterial Proteins↗
PubMed2000

Pleiotropy of the serotonin transporter gene for seasonality and neuroticism.

Pleiotropy refers to the ability of a single gene to influence multiple traits. A polymorphism in the regulatory region of the serotonin transporter gene (5-HTTLPR) has previously been found to be associated both with the personality trait of neuroticism and with seasonal changes in mood and behavior, or seasonality. Hypothesizing that the contribution of the serotonin transporter gene to seasonality is specific, i.e. independent of neuroticism, we measured 5-HTTLPR genotypes and both psychological traits in 236 healthy volunteers. The results indicated that the 5-HTTLPR contributions to variation in the two traits are largely independent; approximately three-quarters of the effect of the gene on seasonality are not related to its effects on neuroticism. Moreover, the gene has a larger effect on the covariation between neuroticism and seasonality than it does on either trait alone. Sibling-pair analysis confirmed that the effects of the 5-HTTLPR are due to genetic pleiotropy rather than population stratification.

Adult↗
PubMed1997

Sex chromosomes and human growth. A dental approach.

Studies on tooth crown size and structure of individuals with various sex chromosome anomalies and their normal male and female relatives have demonstrated differential direct effects on growth of genes on the human X and Y chromosomes. The Y chromosome promotes growth of both tooth enamel and dentin, whereas the effect of the X chromosome on tooth growth seems to be restricted to enamel formation. Enamel growth is decisively influenced by cell secretory function and dentin growth by cell proliferation. It is suggested that these differential effects of the X and Y chromosomes on growth explain the expression of sexual dimorphism in various somatic features, such as the size, shape and number of teeth, and, under the assumption of genetic pleiotropy, torus mandibularis, statural growth, and sex ratio. Future questions concern, among other topics, the Y chromosome and the mineralization process, concentric control of enamel and dentin growth, and gene expression.

Dental Enamel↗
PubMed2026

Characterising the motif composition and allele length distribution of ZFHX3 GGC repeat expansions in amyotrophic lateral sclerosis.

A pathogenic GGC repeat expansion in zinc finger homeobox 3 (ZFHX3), encoding a pure polyglycine (polyG) tract, causes spinocerebellar ataxia type 4 (SCA4). Intermediate expansions of other SCA loci have been implicated in amyotrophic lateral sclerosis (ALS), while repeat motif composition is recognised to influence pathogenicity in neurodegenerative diseases. Given the genetic pleiotropy between ALS and SCA, we evaluated whether ZFHX3 GGC expansions are associated with ALS and characterised repeat motif composition. ZFHX3 GGC repeat sizes were genotyped using ExpansionHunter in short-read whole-genome sequencing data from ALS cases and healthy controls of European ancestry. Repeat sizes were visually inspected using REViewer, and motif configurations were manually derived from a subset. Receiver operating characteristic analysis and Youden's J statistic identified a candidate repeat size threshold. Logistic regression tested associations of repeat length and motif composition with ALS, while regression models assessed clinical phenotypes. Across 5785 ALS cases and 7982 controls, no association was observed between ZFHX3 expansions and ALS risk. Longer alleles showed a nominal association with later disease onset, however this did not remain significant after Bonferroni correction. Among 802 ALS cases and 800 controls, 50 distinct motif compositions were identified, including 11 encoding pure polyG tracts characteristic of pathogenic SCA4 expansions; none were associated with ALS. Although no association with ALS was observed, this study established the dynamic nature of ZFHX3 repeat motif composition and configuration. Variation within and between repeat sizes, including pure polyG repeats, supports consideration of motif composition alongside allele length when evaluating neurodegenerative disease risk.

Journal Article↗
PubMed2025

Exploring the causal relationship between plasma proteins and postherpetic neuralgia: a Mendelian randomization study.

BACKGROUND: The proteome represents a valuable resource for identifying therapeutic targets and clarifying disease mechanisms in neurological disorders. This study investigated potential causal relationships between plasma proteins and postherpetic neuralgia (PHN). METHODS: We conducted a two-sample Mendelian randomization (MR) analysis using genome-wide association study (GWAS) summary statistics from the Decode Genetics dataset (4,907 plasma proteins) and the FinnGen database (490 PHN cases and 435,371 controls). Instrumental variables (IVs) were selected based on relevance, independence, and exclusivity. Causal associations were assessed using inverse-variance weighted (IVW), MR-Egger regression, simple mode, weighted mode, and weighted median methods. Sensitivity analyses, including leave-one-out tests, evaluated result robustness, while colocalization analysis examined shared causal variants between traits. RESULTS: Eight plasma proteins showed significant associations with PHN (PFDR < 0.05). Higher levels of ATRN, PIANP, and CD48 correlated with increased PHN risk, whereas elevated KIR2DL5A, GPI, SEMG2, EIF4B, and HFE2 levels were associated with reduced risk. Sensitivity analyses supported these findings and excluded genetic pleiotropy as a major confounding factor. Colocalization analysis did not detect shared causal variants (PPH4 < 0.8). CONCLUSION: These results suggest a potential causal role for eight plasma proteins in PHN pathogenesis. While these proteins may serve as biomarkers or therapeutic candidates, further validation is required. This study advances understanding of PHN pathophysiology and supports future investigations into diagnostic and therapeutic strategies.

Mendelian randomization↗
PubMedDate not supplied

The contribution of epistatic pleiotropy to the genetic architecture of covariation among polygenic traits in mice.

The contribution that pleiotropic effects of individual loci make to covariation among traits is well understood theoretically and is becoming well documented empirically. However, little is known about the role of epistasis in determining patterns of covariation among traits. To address this problem we combine a quantitative trait locus (QTL) analysis with a two-locus model to assess the contribution of epistasis to the genetic architecture of variation and covariation of organ weights and limb bone lengths in a backcross population of mice created from the M16i and CAST/Ei strains. Significant epistasis was exhibited by 14 pairwise combinations of QTL for organ weights and 10 combinations of QTL for limb bone lengths, which contributed, on average, about 5% of the variation in organ weights and 8% in limb bone lengths beyond that of single-locus QTL effects. Epistatic pleiotropy was much more common in the limb bones (seven of 10 epistatic combinations affecting limb bone lengths were pleiotropic) than the organs (three of the 14 epistatic combinations affecting organ weights were pleiotropic). In both cases, epistatic pleiotropy was less common than single-locus pleiotropy. Epistatic pleiotropy accounted for an average of 6% of covariation among organ weights and 21% of covariation among limb bone lengths, which represented an average of one-fifth (for organ weights) and one-third (for limb bone lengths) of the total genetic covariance between traits. Thus, although epistatic pleiotropy made a smaller contribution than single-locus pleiotropy, it clearly made a significant contribution to the genetic architecture of variation/covariation.

Animals↗
PubMed2005

Epistatic pleiotropy and the genetic architecture of covariation within early and late-developing skull trait complexes in mice.

The role of epistasis as a source of trait variation is well established, but its role as a source of covariation among traits (i.e., as a source of "epistatic pleiotropy") is rarely considered. In this study we examine the relative importance of epistatic pleiotropy in producing covariation within early and late-developing skull trait complexes in a population of mice derived from an intercross of the Large and Small inbred strains. Significant epistasis was found for several pairwise combinations of the 21 quantitative trait loci (QTL) affecting early developing traits and among the 20 QTL affecting late-developing traits. The majority of the epistatic effects were restricted to single traits but epistatic pleiotropy still contributed significantly to covariances. Because of their proportionally larger effects on variances than on covariances, epistatic effects tended to reduce within-group correlations of traits and reduce their overall degree of integration. The expected contributions of single-locus and two-locus epistatic pleiotropic QTL effects to the genetic covariance between traits were analyzed using a two-locus population genetic model. The model demonstrates that, for single-locus or epistatic pleiotropy to contribute to trait covariances in the study population, both traits must show the same pattern of single-locus or epistatic effects. As a result, a large number of the cases where loci show pleiotropic effects do not contribute to the covariance between traits in this population because the loci show a different pattern of effect on the different traits. In general, covariance patterns produced by single-locus and epistatic pleiotropy predicted by the model agreed well with actual values calculated from the QTL analysis. Nearly all single-locus and epistatic pleiotropic effects contributed positive components to covariances between traits, suggesting that genetic integration in the skull is achieved by a complex combination of pleiotropic effects.

Age Factors↗
PubMed1993

Antagonistic pleiotropy, mutation accumulation, and human genetic disease.

The antagonistic pleiotropy theory of senescence is the most convincing theoretical explanation of the existence of aging. As yet, no locus or allele has been identified in a wild population with the features predicted by the pleiotropic theory. Human genetic diseases offer the opportunity to identify potentially pleiotropic alleles/loci. Four human genetic diseases--Huntington's disease, idiopathic hemochromatosis, myotonic dystrophy, and Alzheimer's disease--may exhibit pleiotropic effects and further study of these diseases might result in the identification of pleiotropic genes causing aging. Inability to find an early life selective benefit associated with these disease-causing alleles would favor the major alternative genetic explanation for aging, the mutation accumulation theory.

Aging↗
PubMed1990

The quantitative genetic consequences of pleiotropy under stabilizing and directional selection.

The independence of two phenotypic characters affected by both pleiotropic and nonpleiotropic mutations is investigated using a generalization of M. Slatkin's stepwise mutation model of 1987. The model is used to determine whether predictions of either the multivariate normal model introduced in 1980 by R. Lande or the house-of-cards model introduced in 1985 by M. Turelli can be regarded as typical of models that are intermediate between them. We found that, under stabilizing selection, the variance of one character at equilibrium may depend on the strength of stabilizing selection on the other character (as in the house-of-cards model) or not (as in the multivariate normal model) depending on the types of mutations that can occur. Similarly, under directional selection, the genetic covariance between two characters may increase substantially (as in the house-of-cards model) or not (as in the multivariate normal model) depending on the kinds of mutations that are assumed to occur. Hence, even for the simple model we consider, neither the house-of-cards nor the multivariate normal model can be used to make predictions, making it unlikely that either could be used to draw general conclusions about more complex and realistic models.

Genes↗
PubMed1994

Cowden syndrome and Lhermitte-Duclos disease in a family: a single genetic syndrome with pleiotropy?

Cowden syndrome is an autosomal dominant condition of multiple hamartomas. Patients with this phakomatosis have an increased risk of breast cancer and thyroid tumours. Lhermitte-Duclos disease is usually a sporadic condition of cerebellar ganglion cell hypertrophy, ataxia, mental retardation, and self-limited seizure disorder. We describe a three generation family with Cowden syndrome and Lhermitte-Duclos disease. Karyotyping performed on the peripheral lymphocytes of the proband and her affected mother showed a 46,XX complement. Single strand conformational polymorphism analysis failed to show any germline p53 mutations as a cause of the syndrome in this family.

Adult↗
PubMed2006

Structural model analysis of multiple quantitative traits.

We introduce a method for the analysis of multilocus, multitrait genetic data that provides an intuitive and precise characterization of genetic architecture. We show that it is possible to infer the magnitude and direction of causal relationships among multiple correlated phenotypes and illustrate the technique using body composition and bone density data from mouse intercross populations. Using these techniques we are able to distinguish genetic loci that affect adiposity from those that affect overall body size and thus reveal a shortcoming of standardized measures such as body mass index that are widely used in obesity research. The identification of causal networks sheds light on the nature of genetic heterogeneity and pleiotropy in complex genetic systems.

Adipose Tissue↗
PubMed2026

Genetic insights into the relationship between age at menarche and mental health-related phenotypes.

BACKGROUND: Multiple observational studies have reported associations between age at menarche (AAM) and mental health problems, yet their shared genetic architecture remains poorly characterized. METHODS: We leveraged genome-wide association study summary statistics for AAM and 15 mental health-related phenotypes. We conducted a multi-method integrative analysis encompassing linkage disequilibrium score regression, pleiotropic analysis under the composite null hypothesis, functional mapping and annotation, multi-marker analysis of genomic annotation, pathway enrichment, and bidirectional two-sample Mendelian randomization (MR) to explore shared genetic architecture and potential causal relationships. RESULTS: Our study identified significant genetic correlations between AAM and eight mental health-related phenotypes (miserableness, fed-up feelings, nervous feelings, ever thought that life is not worth living, ever self-harmed, depression, ever smoker, and age started smoking in former smokers). A total of 155 pleiotropic loci, 18 colocalized loci (e.g., 6q16.3), and 203 pleiotropic genes (e.g., LIN28B) were identified. These genes are expressed in multiple regions, including the cerebral cortex and hypothalamus, and are involved in various biological processes and signaling pathways. Additionally, MR analysis revealed causal associations between AAM and 5 mental health-related phenotypes (mood swings, miserableness, fed-up feelings, and age at which smokers started smoking in former/current smokers). CONCLUSIONS: Our study revealed extensive genetic associations between AAM and mental health-related phenotypes, and further explored the potential causal relationships between them. These findings enhance our understanding of the relationship from a genetic perspective and establish a foundation for future research to explore the biological pathways and environmental interactions contributing to these associations.

Genome-Wide Association Study↗
PubMed2007

C-reactive protein, an 'intermediate phenotype' for inflammation: human twin studies reveal heritability, association with blood pressure and the metabolic syndrome, and the influence of common polymorphism at catecholaminergic/beta-adrenergic pathway loci.

BACKGROUND: C-reactive protein (CRP) both reflects and participates in inflammation, and its circulating concentration marks cardiovascular risk. Here we sought to understand the role of heredity in determining CRP secretion. METHODS: CRP, as well as multiple facets of the metabolic syndrome, were measured in a series of 229 twins, both monozygotic (MZ) and dizygotic (DZ), to estimate trait heritability (h2). Single nucleotide polymorphism (SNP) genotyping was done at adrenergic pathway loci. Haplotypes were inferred from genotypes by likelihood methods. Association of CRP with hypertension and the metabolic syndrome was studied in a larger series of 732 individuals, including 79 with hypertension. RESULTS: MZ and DZ twin variance components indicated substantial h2 for CRP, at approximately 56 +/- 7% (P < 0.001). CRP was significantly associated (P < 0.05) with multiple features of the metabolic syndrome in twins, including body mass index (BMI), blood pressure (BP), leptin and lipids. In established hypertension, elevated CRP was associated with increased BP, BMI, insulin, HOMA (index of insulin resistance), leptin, triglycerides and norepinephrine. Twin correlations indicated pleiotropy (shared genetic determination) for CRP with BMI (P = 0.0002), leptin (P < 0.001), triglycerides (P = 0.002) and systolic blood pressure (SBP) (P = 0.042). Approximately 9800 genotypes (43 genetic variants at 17 loci) were scored within catecholaminergic pathways: biosynthetic, receptor and signal transduction. Plasma CRP concentration in twins was predicted by polymorphisms at three loci in physiological series within the catecholamine biosynthetic/beta-adrenergic pathway: TH (tyrosine hydroxylase), ADRB1 (beta1-adrenergic receptor) and ADRB2 (beta2-adrenergic receptor). In the TH promoter, common allelic variation accounted for up to approximately 6.6% of CRP inter-individual variance. At ADRB1, variation at Gly389Arg predicted approximately 2.8% of CRP, while ADRB2 promoter variants T-47C and T-20C also contributed. Particular haplotypes and diplotypes at TH and ADRB1 also predicted CRP, though typically no better than single SNPs alone. Epistasis (gene-by-gene interaction) was demonstrated for particular combinations of TH and ADRB2 alleles, consistent with their actions in a pathway in series. In an illustration of pleiotropy, not only CRP but also plasma triglycerides were predicted by polymorphisms at TH (P = 0.0053) and ADRB2 (P = 0.027). CONCLUSIONS: CRP secretion is substantially heritable in humans, demonstrating pleiotropy (shared genetic determination) with other features of the metabolic syndrome, such as BMI, triglycerides or BP. Multiple, common genetic variants in the catecholaminergic/beta-adrenergic pathway contribute to CRP, and these variants (especially at TH and ADRB2) seem to interact (epistasis) to influence the trait. The results uncover novel pathophysiological links between the adrenergic system and inflammation, and suggest new strategies to probe the role and actions of inflammation within this setting.

Adult↗
PubMed2026

Dissecting pleiotropy between major depressive disorder and physical disease comorbidities.

Major depressive disorder (MDD) is characterized by substantial comorbidity with medical conditions. To achieve better outcomes for patients with MDD, an improved understanding of the mechanisms underlying pervasive comorbidities is required. Here, to this end, we mapped patterns of pleiotropy by defining four clusters of physical diseases (cardiovascular, metabolic, gastrointestinal and immune) and analyzed their genetic relationships with MDD using genomic structural equation modeling. Three disease clusters exhibited independent associations with MDD and accounted for 47% of MDD h2SNP, with the gastrointestinal disease cluster having the strongest association (&#x3b2;&#x2009;=&#x2009;0.63, s.e.&#x2009;=&#x2009;0.05, P&#x2009;=&#x2009;3.04&#x2009;&#xd7;&#x2009;10-30). In addition, we identified independent loci associated with the shared genetic liability between each disease cluster and MDD, revealing different pleiotropic components. Characterization of these loci revealed previously unidentified associations with MDD and physical disease traits, along with unique biological pathways, drug groups, cell types and genes associated with each disease-MDD cluster. Our findings reveal genetic connections implicating the gut-brain axis as a key mechanism underlying the comorbidity of physical diseases in MDD. This work advances our understanding of MDD by highlighting unique and shared genetic components across different disease systems.

Major Depressive Disorder↗