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Results for “mendelian randomization study”

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PubMed1997

WPC test based on randomization for analyzing quantitative traits on simulated pedigrees.

The weighted pairwise correlation (WPC) approach provides simple and flexible tests for genetic linkage which may be adapted to qualitative, quantitative or age-dependent traits. These tests also seem to have good power. However, when working with large pedigrees, a disease susceptibility gene not linked to the marker studied induces correlations of the trait values, leading to inflated type I errors for these tests. We propose here a new approach for inference based on the randomization of the alleles following the Mendelian laws and conditioning on the alleles of the founders. This approach is applied to the analysis of the quantitative traits in a set of simulated pedigrees. The alpha posteriori comparison of the findings to the true model indicates directions for future work.

Aging↗
PubMed2025

New insights into genetic comorbidity mechanisms: type 2 diabetes and primary open-angle glaucoma.

AIMS: To investigate the shared genetic mechanisms between type 2 diabetes (T2D) and primary open-angle glaucoma (POAG). Using large-scale genome-wide association study (GWAS) data, we performed single nucleotide polymorphism (SNP) level analysis to detect pleiotropic variants and loci, paired eQTL mapping analysis and gene-level analysis to identify candidate pleiotropic genes. In addition, Mendelian randomisation (MR) analysis was performed to assess causal associations. MATERIALS AND METHODS: We used POAG GWAS data from Finngen (9565 cases and 430 250 controls) and T2D GWAS data from 55 555 European ancestry samples. We used Linkage Disequilibrium SCore (LDSC) regression to assess the genetic association between T2D and POAG and further used PLeiotropic Analysis under the COmposite null hypothesis (PLACO) to identify shared genetic variants between paired traits. Finally, we further used MR analysis to explore the causal association between T2D and POAG at the genetic level. RESULTS: The LDSC results and MR analysis revealed that the T2D effect was significantly higher than that of the POAG (OR=1.09, 95% CI 1.03 to 1.14, p=1.50×10-3). The PLACO property analysis determined that the T2D sum POAG shared 178 individual SNPs, separate localisation of 79 individual causes. The five most popular choices are based on the effectiveness of CCND2, SVEP1, ST6GAL1, TCF7L2 and HMGA2. expression quantitative trait loci mapping further revealed 36 genes with regulatory roles in optic nerve-related brain tissues. Functional enrichment analyses indicated that these pleiotropic genes are involved in neurodevelopmental, neuroprotective and metabolic pathways, with tissue-specific enrichment observed in neural, pancreatic, adipose and retinal tissues. It is possible to present the main comorbid mechanisms of T2D and POAG. CONCLUSIONS: Our study provides new insights into the aetiology and pathogenesis of T2D and POAG at the genetic level.

Humans↗
PubMed2026

Artificial Intelligence-Driven Multi-Omics Analysis Reveals Hydroxytyrosol Targeting of the TXNIP-NLRP3 Inflammasome Axis in Traumatic Brain Injury.

Traumatic brain injury (TBI) induces secondary neuroinflammation driven by oxidative stress, inflammasome activation, and immune remodeling, yet specific mechanism-guided pharmacological interventions remain limited. This study established an artificial intelligence (AI)-integrated network pharmacology and multi-omics framework to evaluate whether hydroxytyrosol (HT), an olive-derived natural polyphenol, may regulate TBI-related neuroinflammatory targets centered on the TXNIP/NLRP3 inflammasome axis. Starting from the SMILES structure of HT, potential targets were predicted using PharmMapper, SwissTargetPrediction, and the Similarity Ensemble Approach and were standardized to UniProt identifiers. TBI-associated genes were integrated from GeneCards, DisGeNET, OMIM, and the Therapeutic Target Database. The overlapping target set was analyzed using STRING-based protein-protein interaction (PPI) networks, MCODE, CytoHubba, Gene Ontology (GO), and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment. Public GEO transcriptomic datasets (GSE123831 and GSE104687) were used for cross-platform expression validation, differential expression analysis, and exploratory CIBERSORT-based immune infiltration estimation. Random forest (RF), multilayer perceptron (MLP), graph convolutional network (GCN), graph attention network (GAT), SHAP/LIME explainability analysis, LASSO inflammatory-risk scoring, and two-sample Mendelian randomization (MR) were further applied for target prioritization, immune phenotype mapping, and genetic association analysis. Seventy-three overlapping HT-TBI targets were identified. PPI and topology analyses prioritized TXNIP, NLRP3, CASP1, MAPK1, and TP53 as key hubs enriched in inflammasome activation, oxidative stress, apoptosis, and NOD-like receptor signaling. TXNIP, NLRP3, and CASP1 were consistently upregulated in both TBI transcriptomic datasets. LM22-based immune deconvolution suggested increased pro-inflammatory immune signatures and a positive TXNIP-M1 macrophage association (r&#x202f;=&#x202f;0.63, p < 0.001), which should be interpreted as a transcriptome-derived hypothesis rather than validated murine immune-cell proportions. AI-based models consistently ranked TXNIP/NLRP3 as high-contribution features under internal validation, and removal of these targets reduced model performance. A five-gene inflammatory score achieved an internally evaluated AUC of 0.87, while two-sample MR supported positive genetic associations involving TXNIP expression, TBI risk, NLRP3 and IL-1&#x3b2; expression. Collectively, these findings prioritize the TXNIP/NLRP3/CASP1 module as a computationally supported candidate mechanism through which HT may influence oxidative stress-inflammasome-immune coupling in TBI. This study provides an interpretable drug-target-pathway-phenotype framework and identifies TXNIP, NLRP3, and CASP1 as priority nodes for future experimental validation.

Artificial Intelligence↗
PubMed2006

Immunoglobulin constant heavy G chain genes as risk factors in childhood allergies.

BACKGROUND: Several candidate genes have been found to be associated with the inflammatory response of IgE-mediated allergy, so also the immunoglobulin constant heavy G chain (IGHG) genes. The IGHG genes are situated close to the IGHE gene on chromosome 14q32, 5'mu, delta, gamma3, gamma1, alpha1, gamma2, gamma4, epsilon, alpha2, 3'. They are inherited in a Mendelian fashion and expressed randomly in allelic exclusion. The alternative and functionally different gamma3, gamma1 and gamma2 gene variants are found in four IGHG haplotypes, coding four B cell variants. OBJECTIVE: The aim of this study was to assess the frequency of different IGHG genes in relation to phenotypes associated with allergy, in a case-control study. METHODS: We identified the constant heavy-chain genes of IgG in 198 allergic and non-allergic children participating in the Phase II of the International Study of Asthma and Allergy in Children. The IGHG genes were assessed by the alternative serum IgG subclass allotypes expressing the alternative alleles of gamma3, gamma1 and gamma2 genes, using ELISA and double immunodiffusion. RESULTS: The IGHG*bfn haplotype (=B1 cells) and IGHG2*n allele dominated (51% vs. 24%, P=0.002) and the IGHG*bf-n haplotype (=B2 cells) was infrequent (16% vs. 52%, P < 0.001) in allergic children with a family history of allergy, clinical manifest allergy and positive skin prick test (SPT). The frequency of IGHG genes was similar in children with maternal and paternal heredity and in children with wheezing, eczema or rhinitis, as well as in children with different positive SPT. The IGHG*bfn haplotype with the IGHG2*n allele was strongly associated with heredity for allergy. The IGHG*bf-n haplotype was inversely related to allergy. Conclusions IgG allotypes, immunochemical and functional variants of IgG molecules from IGHG genes are associated with atopy. The IGHG*bfn haplotype (=B1 cells) with the IGHG2*n allele dominates, associated with an increased risk for atopy. In contrast, the IGHG*bf-n haplotype (=B2 cells) with the IGHG2*-n allele is associated with low risk.

Alleles↗
PubMed1996

Evidence for major gene inheritance of Alzheimer disease in families of patients with and without apolipoprotein E epsilon 4.

Apolipoprotein E (APOE) genotype is the single most important determinant to the common form of Alzheimer disease (AD) yet identified. Several studies show that family history of AD is not entirely accounted for by APOE genotype. Also, there is evidence for an interaction between APOE genotype and gender. We carried out a complex segregation analysis in 636 nuclear families of consecutively ascertained and rigorously diagnosed probands in the Multi-Institutional Research in Alzheimer Genetic Epidemiology study in order to derive models of disease transmission which account for the influences of APOE genotype of the proband and gender. In the total group of families, models postulating sporadic occurrence, no major gene effect, random environmental transmission, and Mendelian inheritance were rejected. Transmission of AD in families of probands with at least one epsilon 4 allele best fit a dominant model. Moreover, single gene inheritance best explained clustering of the disorder in families of probands lacking epsilon 4, but a more complex genetic model or multiple genetic models may ultimately account for risk in this group of families. Our results also suggest that susceptibility to AD differs between men and women regardless of the proband's APOE status. Assuming a dominant model, AD appears to be completely penetrant in women, whereas only 62%-65% of men with predisposing genotypes develop AD. However, parameter estimates from the arbitrary major gene model suggests that AD is expressed dominantly in women and additively in men. These observations, taken together with epidemiologic data, are consistent with the hypothesis of an interaction between genes and other biological factors affecting disease susceptibility.

Adult↗
PubMed1984

Lipoprotein genes and hyperlipidemia.

The hyperlipidemias, with hypertension, diabetes mellitus and cigarette smoking, are amongst the major risk factors for the development of atheroma. The inter-relationships of hyperlipidemia and atheroma are complex but both appear to have a strong inherited component. Amongst the multiple genetic factors determining the common forms of hyperlipidemia, the apolipoprotein genes coding for the major peptides of the plasma lipoproteins (chylomicrons, VLDL, LDL and HDL) may be of particular relevance since the latter form a system of inter-converting particles for the delivery of lipid (triglyceride and cholesterol) to peripheral tissues (including the arterial wall). Recently several apolipoprotein genes have been isolated. Particularly interesting results have been obtained with the apolipoprotein AI and CIII genes. The DNA sequence of both genes and their immediate flanking region was determined. The two genes are physically linked and convergently transcribed. The cloning of the apolipoprotein genes made possible a detailed genetic study of patients with defects in lipid metabolism. An altered apo AI gene was shown to be inherited as a Mendelian trait linked to premature atherosclerosis in an affected family. Furthermore, the alteration of the apo AI gene seems to affect the expression of the apo CIII gene. Another DNA polymorphism that generates a new SstI site was shown to be present at low frequency (8%) in a random sample of the population. However, its frequency increased dramatically (42%) in a group of hypertriglyceridemic patients. It is thus not inconceivable that further studies of the genes involved in lipid metabolism will eventually help to replace the present phenotype based classification of lipid metabolism disorders by a genotype based system.(ABSTRACT TRUNCATED AT 250 WORDS)

Apolipoproteins↗
PubMed2003

Robustness of inference on measured covariates to misspecification of genetic random effects in family studies.

Family studies to identify disease-related genes frequently collect only families with multiple cases. It is often desirable to determine if risk factors that are known to influence disease risk in the general population also play a role in the study families. If so, these factors should be incorporated into the genetic analysis to control for confounding. Pfeiffer et al. [2001 Biometrika 88: 933-948] proposed a variance components or random effects model to account for common familial effects and for different genetic correlations among family members. After adjusting for ascertainment, they found maximum likelihood estimates of the measured exposure effects. Although it is appealing that this model accounts for genetic correlations as well as for the ascertainment of families, in order to perform an analysis one needs to specify the distribution of random genetic effects. The current work investigates the robustness of the proposed model with respect to various misspecifications of genetic random effects in simulations. When the true underlying genetic mechanism is polygenic with a small dominant component, or Mendelian with low allele frequency and penetrance, the effects of misspecification on the estimation of fixed effects in the model are negligible. The model is applied to data from a family study on nasopharyngeal carcinoma in Taiwan.

Analysis of Variance↗
PubMed2025

Epigenetic mechanisms underlying variation of IL-6, a well-established inflammation biomarker and risk factor for cardiovascular disease.

BACKGROUND AND AIMS: Cardiovascular disease (CVD) is one of the leading causes of morbidity and mortality worldwide, yet the underlying molecular mechanisms remain less understood. Chronic low-grade inflammation is a complex immune response contributing to the pathophysiology of cardiovascular disease. This response is signaled in part by interleukin-6 (IL-6), a pleiotropic, pro-inflammatory cytokine. Phenotypic variance in circulating IL-6 level may be explained in part by DNA methylation which is increasingly being associated with cardiovascular effects. METHODS: In this study we evaluated methylated DNA (CpG sites) associated with blood IL-6 levels across &#x223c;4,400 ancestrally diverse individuals (81&#xa0;% self-reported White; 9&#xa0;% Black or African American, 8&#xa0;% Hispanic or Latino/a, and 2&#xa0;% Chinese American). RESULTS: We identified 178 CpG sites associated with IL-6 (p<0.05/&#x223c;395,000). Among the sites, cg04437762 is located within the transcription unit of IL6R, a current therapeutic target for inflammatory disease, and cg26692003 and cg00464927 were significant for IL6 and IL6ST trans-CpG-gene transcripts. Functional gene expression downstream of methylation identified cellular response to IL-6 and B-cell regulation and activation pathways. Four genes were linked with both a genetic component of cardiovascular disease and an IL-6 associated CpG site. Three CpG sites identified through Mendelian randomization analyses supported inference of a causal effect on IL-6 levels, including the LYN gene that regulates immune cell signaling and has been previously associated with atherosclerosis. CONCLUSIONS: Overall, we identified several novel IL-6-CpG sites and downstream pathways affected by methylation. Follow-up functional studies including the regulation of IL-6 would complement current knowledge of CVD pathophysiology and potential therapeutic targets.

Humans↗
PubMed1998

Sib-pair collection strategies for complex diseases.

When planning an affected sib pair collection for use in a genomewide search for complex trait loci, researchers must ask: (a) Which family structures will yield the most informative pairs? and (b) Should recruitment extend beyond the index sib pair? The optimal collection strategy will depend on the trait's genetic architecture, but this is rarely known for non-Mendelian diseases. In the present report, we study the consequences of collecting only those sib pairs arising from pedigrees with a precisely specified structure as opposed to a strategy that collects all affected sib pairs at random (i.e., blind to the affection status of first-degree relatives). The former approach turns out to be risky because the power of specific pedigree structures can vary dramatically even among models producing identical observable parameters (such as population prevalence and sibling recurrence rate). In contrast, the latter approach typically involves only a modest loss of power as compared with the optimal (but unknowable) design. Further, we compare the strategy of collecting all affected sib pairs at random with the alternative of imposing some modest limitations on family structure (e.g., presence of at least one unaffected sib or parent). The latter approach generally provides some increase in power but entails additional effort to contact and phenotype relatives: the overall merit of imposing such requirements needs to be evaluated in the context of the specific disease to be studied and of the clinical and analytical resources available. In addition, these findings suggest that a further explanation for failure to replicate positive complex trait linkages lies in differences in ascertainment strategy between data sets.

Data Collection↗
PubMed2024

Whole -genome survival analysis of 144&#x200a;286 people from the UK Biobank identifies novel loci associated with blood pressure.

This study utilized UK Biobank data from 144&#x200a;286 participants and employed whole-genome sequencing (WGS) data and time-to-event data over a 12-year follow-up period to identify susceptibility in genetic variants associated with hypertension. Following genotype quality control, 6&#x200a;319&#x200a;822 single nucleotide polymorphisms underwent analysis, revealing 31 significant variant-level associations. Among these, 29 were novel - 15 in Fibrillin-2 ( FBN2 ) and 4 in Junctophilin-2 ( JPH2 ). Mendelian randomization utilizing two identified variants (rs17677724 and rs1014754) suggested that a genetically induced decrease in heart FBN2 expression and an increase in adrenal gland JPH2 expression were causally linked to hypertension. Phenome-wide association (PheWAS) analysis using the FinnGen dataset confirmed positive associations of rs17677724 and rs1014754 with hypertension, assessed across 2727 traits in 377&#x200a;277 individuals. Lastly, rs1014754 positively associated with kallistatin, whereas rs17677724 negatively associated with renin in the Fenland study, suggesting a counterregulatory response to high blood pressure. This study, employing WGS data, identified novel genetic loci and potential therapeutic targets for hypertension.

Humans↗
PubMed2006

Estimation of bias in nongenetic observational studies using "mendelian triangulation".

PURPOSE: Phenotype-disease odds ratios calculated from the effect of a genotype on its phenotype and on disease risk ("Mendelian triangulation") can be used as a standard to assess bias on the corresponding odds ratio from nongenetic studies. Statistical tests are commonly used to compare these odds ratios. We propose a method to estimate the magnitude of the bias and judge the validity of the phenotype-disease association. METHODS: For four published examples, we obtained 10,000 random values from distributions of the odds ratios from both genetic and nongenetic studies. A range of values compatible with an unbiased odds ratio was then calculated from the empirical distribution of the differences between both odds ratios. RESULTS: We show that estimating a range of likely values for an unbiased odds ratio is useful to judge the effect of the phenotype and identify cases for which information from genetic studies adds little to the evaluation of the phenotype-disease association. Conversely, statistical tests could be misleading. CONCLUSIONS: Estimating a range of values for an unbiased odds ratio is more informative and appropriate than statistical tests when using the Mendelian triangulation approach for assessment of bias in phenotype-disease association studies.

Bias↗
PubMed2001

Two hits revisited again.

INTRODUCTION AND METHODS: Since the concept of the "two hit hypothesis" was introduced over 20 years ago, a wealth of genetic data has accumulated on the mutations found at tumour suppressor loci. Perhaps surprisingly, these data conceal large gaps in our knowledge which genetic and functional studies are beginning to uncover. The "two hit hypothesis" must be updated to take account of this new information. RESULTS AND DISCUSSION: Here, we discuss both the results of recent studies and some of the questions that they highlight. In particular, how valid are conclusions from inherited Mendelian syndromes when applied to sporadic cancers? Why is allelic loss so common and how does it occur? Are the "two hits" random or interdependent? Is abolition of protein function always optimal for tumorigenesis? Can "third hits" occur and, if so, why? How can mismatch repair deficiency and the methylator phenotype be incorporated into the "two hit" hypothesis? We suggest that the "two hit hypothesis" is not fixed but is evolving as our knowledge expands.

Humans↗
PubMed2026

Reassessing Instrument Strength in Two-Sample Mendelian Randomization Analysis.

Mendelian randomization (MR) analysis is widely used to estimate causal relationships between risk factors and outcomes of interest. Two-sample MR approaches have gained increasing attention in genetic epidemiology due to the growing availability of Genome-Wide Association Study (GWAS) summary statistics from public databases. A critical step in two-sample MR is the selection of genetic variants as instrumental variables (IVs). Although genome-wide significant variants are typically preferred, the inclusion of variants with weaker association p-values is considered, as they may potentially improve power through an increased instrument number of instruments, while they may introduce weak instrument bias and attenuate effect estimates towards the null. Our simulation results show that even modest levels of pleiotropy substantially increase the variability of causal effect estimates, while the inclusion of weak IVs does not substantially affect the direction and variability of causal effect estimates in most cases. In real data analyses, we used two released versions of FinnGen GWAS summary statistics with different sample sizes as exposure GWASs to assess the influence of weak IVs. Here, the inclusion of IVs with higher exposure-association p-values resulted in weakened estimated effect sizes, particularly when the exposure GWAS sample size was small. These findings suggest that incorporating weak IVs is reasonable when the exposure GWAS sample size is large, but it poses a risk of falsely concluding null associations when the exposure GWAS sample size is small.

Journal Article↗
PubMedDate not supplied

Mapping genes for polygenic disorders: considerations for study design in the complex trait of inflammatory bowel disease.

While the methodology for the mapping of Mendelian disorders is well established, the practical and theoretical steps required for successful gene identification in a complex trait are still difficult to predict. A number of analytical models and simulations based on repetitive drawings from predefined statistical distributions are available. To supplement these analytical models, we developed an integrated simulation approach by directly simulating entire populations under a disease model based on epidemiological data. Random mating, nonoverlapping populations and the absence of differential fitness were assumed. Samples were drawn from these homogeneous and heterogeneous populations and analyzed with established analysis tools. We investigated the properties of linkage and association studies in inflammatory bowel disease - modeled as a six-locus polygenic disorder - as an example of this approach. In nonparametric linkage studies, lod scores varied widely, with the median required sample size depending on the locus-specific relative sibling risk. A fine mapping resolution <4 cM was found to require nonparametric lod scores >10. Family-based association studies (TDT test) and case-control studies showed a similar sensitivity and can identify risk loci in populations with moderate levels of linkage disequilibrium in sample sizes of 500-800 triplets. Case-control association studies were prone to false-positive results if applied in heterogeneous populations, with the false-positive rate increasing with sample size because population heterogeneity is detected with increasing power.

Alleles↗
PubMed2025

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

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

Humans↗
PubMed2026

Impacts of host genetics on gut microbiome composition in Alzheimer's disease.

BACKGROUND: Host-microbiome interactions play essential roles in the development of Alzheimer's disease (AD), yet&#xa0;the host genetic impacts on gut microbial alterations in AD remain poorly understood. RESULTS: Here, we simultaneously profiled host genotype and gut microbiome in 252 Chinese individuals with varying degrees of cognitive disability. Using the latent Dirichlet allocation topic model, we identified the Anaerostipes-enriched enterosignature (ES-Ana) at the microbial subgroup level as significantly negatively associated with cognitive disability, which could be recapitulated in external cohorts. With the whole-genome sequencing data, we performed microbiome genome-wide association studies for the ES-Ana relative abundance. We prioritized 41 lead genetic variants and confirmed that the high ES-Ana relative abundance showed a negative correlation with the polygenic risk score of AD, indicating&#xa0;its protective effect against AD. Furthermore, we identified 174 ES-Ana-associated genes, which&#xa0;are&#xa0;enriched in AD-related biological functions and phenotypes, and exhibite pervasive underexpression in glial cells during brain aging. CONCLUSIONS: In summary, our study reveals the complex genetic effects on the gut microbiota in AD, and provides novel evidence for the roles of the gut-brain axis in AD. Video Abstract.

Alzheimer Disease↗
PubMed1992

Risk factors for cancer.

It is no longer reasonable to divide cancers into those that are genetic in origin and those that are environmental in origin. With rare exception, carcinogenesis involves environmental factors that directly or indirectly exert a change in the cell's genome. Virtually all causes of cancer are multifactorial, sometimes involving an inherited predisposition to the carcinogenic effects of environmental factors, which include chemicals, ionizing radiation, and oncogenic virus. Carcinogenesis is a multistep process including induction, promotion, and progression. Initiation requires an irreversible change in the cellular genome, whereas promotion is commonly associated with prolonged and reversible exposure. Tumor progression results in genotypic and phenotypic changes associated with tumor growth, invasion, and metastasis. Most information on human cancer risk is based on epidemiologic studies involving both exposed and unexposed individuals. The quality of such studies depends on their ability to assess the strength of any association of exposure and disease and careful attention to any potential bias. Few cancers are inherited in a Mendelian fashion. Several preneoplastic conditions, however, are clearly inherited and several malignancies demonstrate weak familial patterns. Environmental factors may exert their effect on DNA in a random fashion, but certain consistent changes, including specific translocations of genetic information, are often found. Currently, there is great interest in the close proximity of certain oncogenes governing growth control to the consistent chromosomal changes observed. Such changes may represent a final common pathway of action for environmental carcinogens. Sufficient laboratory and epidemiologic evidence exists to establish a causal association of several chemical agents with cancer. The most important carcinogenic chemicals are associated with life-style factors, whereas agents related to other environmental, occupational, or medical exposure are numerically less important. Most chemical agents exert their carcinogenic effects as electrophilic reactants covalently binding to DNA. Certain agents such as asbestos are carcinogenic by virtue of their physical properties. Several short-term tests have been used to screen for chemical carcinogens. Whole-animal studies remain the standard for predicting carcinogen risk in humans, although major limitations in such studies exist. Ionizing radiation also exerts its carcinogenic effect through damage to cellular macromolecules including DNA. Excess cancer risk appears after a latent period of several years following exposure. Risk increases in approximately a linear fashion in proportion to the radiation energy, cumulative dose, and a variety of host biologic factors. The greatest source of average radiation exposure to the US population is from the uranium decay product radon.(ABSTRACT TRUNCATED AT 400 WORDS)

Animals↗