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Segregation analysis of body mass index in an unselected French-Canadian sample: the Québec Family Study.

Interest in a single gene etiology for obesity, as assessed by the body mass index (BMI), has been spurred recently by reports of a putative recessive major gene for extreme values, which accounts for as much as 40% of the variance. The major gene hypothesis was evaluated here in the Québec Family Study, a random sample of 375 French-Canadian volunteer families. This report represents one component in a more complete investigation of obesity in these families. In contrast to the recent studies, a major gene hypothesis for BMI was not verified here. Although there was a major effect, it did not conform to a Mendelian pattern of transmission. A multifactorial component (i.e., polygenic and/or common environmental factors) accounted for 42% of the phenotypic variance. In addition, evidence of heterogeneity between the generations was found. The heterogeneity was traced to the major non-Mendelian component (which accounted for 0.01% of the variance in parents and over 40% in offspring) rather than to the multifactorial one. These results would suggest that a simple recessive gene mixed model may not be sufficient to explain the familial distribution of the BMI. Several factors which may have contributed to these results include temporal trends and surrogate effects such as those related to variation in body composition and energy balance components.

Adipose Tissue↗

Identification of RAPD markers and their use for molecular mapping in pea (Pisum sativum L.).

The RAPD method (Random Amplified Polymorphic DNA) was used for identifying and mapping new molecular markers in pea. RAPD analysis of various cultivars and lines of pea was carried out using 10-mer random primers. The presence of multiple polymorphism between cultivars and lines was revealed; at least one fragment for any given primer was present in the DNA of one form of pea and absent in the DNA of another line or cultivar. To detect molecular markers linked to the genes of chi-15, xa-18 and also to the 12 morphological markers of the L-1238 line, the F2 populations (Chi-15 ? L-1238), (Vio ? L-1238), (Xa-18 ? L-1238), (L-111 ? Chi-15) and (L-84 ? Xa-18) were studied via bulked segregant analysis. DNA molecular analysis of F1 hybrids revealed the presence of parental polymorphic fragments in all of the populations. The study of the F2 plants showed that the obtained fragments are inherited as Mendelian factors. 13 RAPD-markers linked to genes of A/a (flower color), I/i (seed color), Gp/gp (pod color), R/r (seed form), S/s (seeds linkage), and also to genes of Chi-15/chi-15 (leaf color) and Xa-18/xa-18 (leaf color) were discovered. The study of individual plant DNA from the F2 populations allowed us to determine the genetic distances between genes and the RAPD markers linked to them.

Base Sequence↗

Distinct Genetic Risk Profile in Aortic Stenosis Compared With Coronary Artery Disease.

IMPORTANCE: Aortic stenosis (AS) and coronary artery disease (CAD) frequently coexist. However, it is unknown which genetic and cardiovascular risk factors might be AS-specific and which could be shared between AS and CAD. OBJECTIVE: To identify genetic risk loci and cardiovascular risk factors with AS-specific associations. DESIGN, SETTING, AND PARTICIPANTS: This was a genomewide association study (GWAS) of AS adjusted for CAD with participants from the European Consortium for the Genetics of Aortic Stenosis (EGAS) (recruited 2000-2020), UK Biobank (recruited 2006-2010), Estonian Biobank (recruited 1997-2019), and FinnGen (recruited 1964-2019). EGAS participants were collected from 7 sites across Europe. All participants were of European ancestry, and information on comorbid CAD was available for all participants. Follow-up analyses with GWAS data on cardiovascular traits and tissue transcriptome data were also performed. Data were analyzed from October 2022 to July 2023. EXPOSURES: Genetic variants. MAIN OUTCOMES AND MEASURES: Cardiovascular traits associated with AS adjusted for CAD. Replication was performed in 2 independent AS GWAS cohorts. RESULTS: A total of 18 792 participants with AS and 434 249 control participants were included in this GWAS adjusted for CAD. The analysis found 17 AS risk loci, including 5 loci with novel and independently replicated associations (RNF114A, AFAP1, PDGFRA, ADAMTS7, HAO1). Of all 17 associated loci, 11 were associated with risk specifically for AS and were not associated with CAD (ALPL, PALMD, PRRX1, RNF144A, MECOM, AFAP1, PDGFRA, IL6, TPCN2, NLRP6, HAO1). Concordantly, this study revealed only a moderate genetic correlation of 0.15 (SE, 0.05) between AS and CAD (P = 1.60 × 10-3). Mendelian randomization revealed that serum phosphate was an AS-specific risk factor that was absent in CAD (AS: odds ratio [OR], 1.20; 95% CI, 1.11-1.31; P = 1.27 × 10-5; CAD: OR, 0.97; 95% CI 0.94-1.00; P = .04). Mendelian randomization also found that blood pressure, body mass index, and cholesterol metabolism had substantially lesser associations with AS compared with CAD. Pathway and transcriptome enrichment analyses revealed biological processes and tissues relevant for AS development. CONCLUSIONS AND RELEVANCE: This GWAS adjusted for CAD found a distinct genetic risk profile for AS at the single-marker and polygenic level. These findings provide new targets for future AS research.

Humans↗

A genetic signal at 8q12.3 modulates GGT levels via the Runx1-CYP7B1 axis in female ethnic minorities from Guizhou.

Gamma-glutamyl transferase (GGT) regarded as a biomarker of liver dysfunction or excessive alcohol consumption; however, existing genome-wide association studies (GWAS) have been conducted predominantly in European populations and East Asian populations from Japan and the Taiwan region, with limited investigation in ethnic minorities from Guizhou Province. Previous genetic studies have demonstrated that Guizhou ethnic minorities share an East Asian genetic background while exhibiting specific genetic structures, a pattern that is also confirmed by our principal component analysis (PCA) results. We therefore performed a GWAS in this population and identified a genome-wide significant signal at 8q12.3 in female ethnic minorities from Guizhou. Fine-mapping and functional annotation analyses suggest that a regulatory pathway involving Runt-related transcription factor 1 (Runx1)-Cytochrome P450 family 7 subfamily B member 1 (CYP7B1)-cholesterol-reactive oxygen species (ROS)-glutathione (GSH) may contribute to the regulation of GGT levels. Mendelian randomization (MR) analyses further supported a causal relationship between GGT levels and autoimmune hepatitis (AIH). These findings uncover a genetic mechanism underlying GGT variation at 8q12.3 in female ethnic minorities from Guizhou, implicating a pathway linked to cholesterol metabolism and oxidative stress, and providing potential targets and insights for precision prevention and treatment of related diseases.

Female↗

Causal Associations and Potential Mediating Factors between Sarcopenia-Related Traits and Heart Failure Risk: A Mendelian Randomization Study.

INTRODUCTION: In this two-sample, two-step Mendelian randomization (MR) study, we aimed to elucidate the causal associations between sarcopenia-related characteristics and heart failure (HF) risk, and to identify the factors mediating these associations, with a particular focus on the mediating roles of obesity and sedentary habits. METHODS: Genetic instruments for appendicular lean mass (ALM), hand grip strength (HGS), walking pace (WP), and potential mediators were extracted from genome-wide association studies. Inverse-variance weighting (IVW) was used as the primary analytical method, supplemented by MR-Egger regression, weighted median, and weighted mode analyses. Sensitivity analyses including Cochran's Q test and MR-Egger intercept method were performed to assess heterogeneity and pleiotropy. Bidirectional MR was conducted to exclude reverse causation. RESULTS: IVW revealed that a faster genetically predicted WP was associated with lower HF risk (odds ratio [OR] 0.44, 95% confidence interval [CI] 0.33-0.60, p = 5.806 × 10-7). The mediation analysis indicated that body mass index (BMI) accounted for 32% of this effect, while time spent watching television accounted for 14%. Elevated ALM showed a slight but significant positive association with HF risk (OR 1.06, 95% CI 1.03-1.09, p = 5.437 × 10-4). However, multivariable MR adjusting for BMI completely attenuated this association (p = 0.693), suggesting ALM reflects overall body composition rather than isolated muscle mass. No significant associations were found between HGS and HF. Bidirectional MR showed no robust reverse effects. CONCLUSIONS: These findings suggest that genetically predicted increased WP exerts beneficial effects against HF, partially mediated by obesity and sedentary habits. Targeting weight management and anti-sedentary interventions may mitigate HF risk in individuals with sarcopenia-related characteristics.

Heart failure↗

Familial correlation and segregation analysis of forced expiratory volume in one second (FEV1), with and without smoking adjustments, in a Tucson population.

BACKGROUND: Previous researchers have found significant familial aggregation but no evidence of Mendelian inheritance of forced expiratory volume in one second (FEV1) in general population studies. However, the influence of cigarette smoking on familial aggregation of FEV1 has been difficult to assess in these studies. OBJECTIVES: The main objective of our study was to attempt to discern the effects of smoking on familial correlation and segregation models of FEV1. SUBJECTS AND METHODS: In a randomly selected sample of white, non-Mexican American families in Tucson, Arizona, we performed two separate familial correlation and segregation analyses of FEV1, one adjusted for cigarette smoking and one unadjusted for smoking. In both, initial survey measures of FEV1 for 1329 females and 1291 males in 746 families were standardized for gender, age, height and height-squared using piecewise linear regression models. In the smoking-adjusted model, total number of pack-years smoked, current and ex-smoking status, and the interaction between total pack-years and current smoking status were also included. RESULTS: FEV1 was significantly correlated among sibling pairs and parent-offspring pairs (both p < 0.001), regardless of smoking adjustment, but sibling correlation was significantly higher than parent-offspring correlation (p < 0.05), suggesting additional effects beyond common parentage. Spousal correlations were not significant even when both spouses smoked. We found no evidence of major gene segregation of FEV1, with or without smoking adjustment, and all of the segregation models were significantly different from the unrestricted model. CONCLUSIONS: The best-fitting model was an environmental model with three distinct distributions of FEV1 and significant residual familial effects. A significant familial component suggests the presence of polygenic factors and/or effects due to a shared environment (multifactorial). That familial correlations of smoking-adjusted and smoking-unadjusted residuals were not appreciably different suggests that current smoking status and number of pack-years smoked do not account for the observed familial aggregation of FEV1.

Adolescent↗

Population based linkage disequilibrium mapping of QTL: an application to simulated data in an isolated population.

Despite successes in mapping and cloning genes involved in rare Mendelian diseases, genetic dissection of quantitative traits into single Mendelian factors still remains a challenging task. As the dense map of single nucleotide polymorphism (SNP) markers becomes available in the near future, linkage disequilibrium (LD) mapping will become one of major tools for mapping and identifying quantitative trait loci (QTL). In this report, we present a population-based linkage disequilibrium mapping of QTL. This method unifies the analysis of mapping QTL in humans and in model organisms and can be used for randomly sampled individuals. The proposed method is applied to search for polymorphism sites within the candidate genes 2 and 6, which influence quantitative traits Q1 and Q2 or Q5, in a simulated data set in an isolated population.

Chromosome Mapping↗

The reporting and handling of missing data in genetic epidemiological studies of mental health in childhood and adolescence: A systematic review.

BACKGROUND: Genetic epidemiological analyses of child and adolescent mental health often use data from prospective longitudinal cohorts. Missingness due to selective attrition is therefore an important potential source of bias in such analyses. Informatively reporting on missingness and taking appropriate steps to handle it in analyses can mitigate this potential bias. Here, we aim to systematically assess how researchers report and address missingness in genetic epidemiological studies of child and adolescent mental health-related outcomes using cohort data. METHODS: We systematically searched the Ovid Medline database for studies published between August 2012 and August 2025, reporting polygenic score, genome-wide association, or Mendelian randomization analyses, of data on children or adolescents participating in cohort studies. We extracted information from eligible studies based on criteria adapted from the strengthening and reporting of observational studies in epidemiology (STROBE) guidelines. RESULTS: A total of 133 eligible studies were included, of which 125 (93.98%) reported the number of complete cases in all waves, while 84 (63.16%) detailed the amount of missingness on all key variables. Most studies used complete case analysis, while 39 studies explicitly reported applying other methods to handle missingness, with multiple imputation (n&#xa0;=&#xa0;20, 15.04%) being the most common, followed by full information maximum likelihood 10 (8.1%). Only 18 studies (13.53%) reported an assumed missing mechanism along with the method used to address missingness. Full reporting of both the extent and handling of missingness at the item level was rare, occurring in only 5 (3.76%) and 15 (11.28%) studies, respectively, among the 123 studies that used multi-item instruments. CONCLUSION: Best practice recommendations for reporting on missing data handling emphasize the importance of detailing the proportion of missingness, types of mechanisms underpinning missingness, and details of approaches used. Based on this review, these recommendations for proper reporting of missing data are rarely followed in full.

children and adolescents↗

A novel missense mutation in the mouse growth hormone gene causes semidominant dwarfism, hyperghrelinemia, and obesity.

The SMA1-mouse is a novel ethyl-nitroso-urea (ENU)-induced mouse mutant that carries an a-->g missense mutation in exon 5 of the GH gene, which translates to a D167G amino acid exchange in the mature protein. Mice carrying the mutation are characterized by dwarfism, predominantly due to the reduction (sma1/+) or absence (sma1/sma1) of the GH-mediated peripubertal growth spurt, with sma1/+ mice displaying a less pronounced phenotype. All genotypes are viable and fertile, and the mode of inheritance is in accordance with a semidominant Mendelian trait. Adult SMA1 mice accumulate excessive amounts of sc and visceral fat in the presence of elevated plasma ghrelin levels, possibly reflecting altered energy partitioning. Our results suggest impaired storage and/or secretion of pituitary GH in mutants, resulting in reduced pituitary GH and reduced GH-stimulated IGF-1 expression. Generation and identification of the SMA1 mouse exemplifies the power of the combination of random mouse mutagenesis with a highly detailed phenotype-analysis as a successful strategy for the detection and analysis of novel gene-function relationships.

Adipose Tissue↗

Familial correlation of dietary intakes among postmenopausal women.

A positive family history is a risk factor for many chronic diseases, including most cancers, coronary heart disease, and diabetes. Since diet is also associated with most chronic diseases, one possible explanation for non-Mendelian familial clustering is shared eating habits. Food frequency data were obtained on 3,515 sisters in the Iowa Women's Health Study, a prospective cohort of postmenopausal women. Intraclass correlations between sisters were computed on a range of energy-adjusted nutrients to determine whether dietary intakes were more similar among siblings than among unrelated individuals. Two methods were used to calculate correlations: analysis of variance modeling and weighted sibling correlations. F-tests and randomization tests were used to determine statistical significance. The intraclass correlations for all of the nutrients examined were statistically significantly greater than the hypothesized value of zero (P < 0.05). Representative correlations include dietary fiber (0.15), animal fat (0.12), vegetable fat (0.13), calcium (0.14), iron (0.04), cholesterol (0.08), sodium (0.10), vitamin D (0.16), and total energy intake (0.11). When corrected for measurement error, the magnitude of these correlations increased, on average 62%. Although modest in magnitude, these correlations may be high enough to influence familial clustering of complex diseases that are attributed, in part, to diet.

Aged↗

Multistage Genetic, Transcriptomic, and Single-Cell Evidence Prioritizes MAP1LC3A among Ferroptosis-Related Genes in Glioblastoma.

Glioblastoma (GBM) remains a highly aggressive malignancy, and the contribution of ferroptosis-related genes to disease susceptibility remains incompletely understood. A genetically anchored, multistage framework was applied to prioritize ferroptosis-related genes associated with GBM. Among 483 genes curated from FerrDb V2, 315 had candidate cis-expression quantitative trait loci (cis-eQTLs) in eQTLGen, 250 retained at least three independent instruments after linkage disequilibrium clumping, and 226 yielded valid inverse-variance weighted (IVW) Mendelian randomization estimates using a GBM genome-wide association study comprising 6,183 cases and 18,169 controls. Thirty-four genes met the exploratory discovery criteria of P < 0.05 and a Benjamini-Hochberg false discovery rate (BH-FDR) < 0.20, with directionally concordant Bayesian weighted Mendelian randomization (BWMR) estimates. Replication-stage Mendelian randomization using GTEx V10 whole-blood cis-eQTLs supported four genes: ATG7, RPTOR, MAP1LC3A, and CHMP6. Evaluation across three independent tumor-control transcriptomic cohorts demonstrated that MAP1LC3A was consistently downregulated in tumor tissue and showed a significant random-effects pooled estimate (log&#x2082; fold change, -1.273; 95% confidence interval, -1.625 to -0.920; false discovery rate = 0.016), whereas the other three genes lacked comparable cross-cohort statistical support. Single-cell virtual knockout analysis was subsequently performed in a patient-balanced subset of 2,400 malignant cells selected from 4,916 eligible cells across 20 adult IDH-wild-type GBM tumors. Across five independently seeded runs, 3, 15, 4, and 7 robust downstream genes were identified for ATG7, RPTOR, MAP1LC3A, and CHMP6, respectively. The resulting consensus sets comprised 17 unique genes, with RND3 shared across all four targets. Gene Ontology analysis indicated enrichment of cell-adhesion and cell-surface processes, whereas no KEGG or Reactome pathways remained significant after multiple-testing correction. Collectively, these findings prioritize MAP1LC3A for future experimental investigation while distinguishing genetic association, tumor-expression concordance, and computational perturbation from definitive evidence of causality or mechanism.

Humans↗

The random phenotype concept, with applications.

A random phenotype is defined as a probability distribution over any given set of phenotypes. This includes as special cases the kinds of phenotypes usually considered (qualitative, quantitative, and threshold characters) and all others. Correspondingly general methods are indicated for analyzing data of all forms in terms of the classical Mendelian factor concept (as distinct from the biometrical methods usually applied to measurement and graded data, associated with the effective factor concept). These are applied in a new analysis of the data of E. L. Green (1951, 1954, 1962) on skeletal variation in the mouse. The adequacies of various classical one-factor and several-factor models are considered. Indications of an underlying scale are found from this new standpoint. The results are compared with those obtained by Green using the scaling approach. An illustrative application is also made to some of Bruell's (1962) continuous behavioural data on mice. This work was substantially completed in 1959 but not previously prepared for publication. The same approach was originated and developed independently by R. L. Collins who has treated a wider range of theoretical problems (cf. Collins 1967, 1968a, 1969b, 1970c) and a wider range of applications (cf. Collins and Fuller 1968; Collins 1968b, 1969a, 1970a). A less general independent development is that of Mode and Gasser 1972.

Animals↗

Statistical tools for linkage analysis and genetic association studies.

Genetic mapping by linkage analysis has been an invaluable tool in the positional strategy to identify the molecular basis of many rare Mendelian disorders. With the attention of the scientific and medical community shifting towards the analysis of more common, complex traits, it has become necessary to develop new approaches that take into account the complexity of the genetic basis of these disorders and their possible interaction with other, nongenetic factors. Linkage disequilibrium studies are now becoming increasingly popular thanks to the advent of genotyping platforms that allow genome-wide searching for association between hundreds of thousands of random polymorphisms and disease phenotypes in large samples of unrelated individuals. Moreover, the definition of the disease phenotype itself is being reconsidered to include quantitative traits that may better define the underlying biologic mechanisms for many pathologic conditions. This article will review classic and new approaches to genetic mapping by linkage and association analysis and discuss the directions this field is likely to take in the near future.

Alleles↗

Are variants in the CAPN10 gene related to risk of type 2 diabetes? A quantitative assessment of population and family-based association studies.

The calpain-10 gene (CAPN10) on chromosome 2q37.3 was the first candidate gene for type 2 diabetes (T2D) identified through a genomewide screen and positional cloning. One polymorphism (UCSNP-43: G-->A) and a specific haplotype combination defined by three polymorphisms (UCSNP-43, -19, and -63) were linked to an increased risk of T2D in several populations. To quantitatively assess the collective evidence for the effects of CAPN10 on risk of T2D, we conducted a meta-analysis of both population-based and family-based association studies. We retrieved data from the MEDLINE, PubMed, and Online Mendelian Inheritance in Man databases, as well as from other relevant reports and abstracts published up to July 2003. From a total of 26 studies with primary data (21 population-based studies: 5,013 cases and 5,876 controls; 5 family-based studies: 487 parent-offspring trios), we developed a summary database that contains variables of study design, study population/ethnicity, specific polymorphisms and haplotype combinations in CAPN10, and diabetes-related metabolic phenotypes. For population-based studies, we used both fixed-effects and random-effects models to calculate the pooled odds ratio (OR) and 95% confidence interval (CI) for the associations of CAPN10 genotypes with the risk of T2D. We also calculated weighted mean differences for the associations between CAPN10 and diabetes-related quantitative traits. Under either an additive or a dominant effect model, we found no statistically significant relation between CAPN10 genotypes in the UCSNP-43 locus and T2D risk. However, under a recessive model, individuals homozygous for the common G allele had a statistically significant 19% higher risk of T2D than carriers of the A allele (OR 1.19; 95% CI 1.07-1.33). The association between the 112/121 haplotype combination and T2D risk appeared to be overestimated by several initial small studies with positive findings (OR 1.38; 95% CI 1.04-1.84). After we removed these initial studies, this association became nonsignificant (OR 1.11; 95% CI 0.91-1.35). Moreover, we found no evidence for the associations between the UCSNP-43 G/G genotype and the 112/121 haplotype combination and metabolic phenotypes. Our meta-analysis of family-based studies showed only an overtransmission of the rare allele C in UCSNP-44 from heterozygous parents to their affected offspring with T2D. Our analysis indicates that inadequate statistical power, racial/ethnic differences in frequencies of alleles, haplotypes and haplotype combinations, potential gene-gene or gene-environment interactions, publication bias, and multiple hypothesis testing may contribute to the significant heterogeneity in previous studies of CAPN10 and T2D. Our findings also suggest that both large-scale, well-designed association studies and functional studies are warranted to either reliably confirm or conclusively refute the initial hypothesis regarding the role of CAPN10 in T2D risk.

Alleles↗

Unveiling the power of TIIC: A prognostic tool for esophageal adenocarcinoma.

BACKGROUND: Esophageal adenocarcinoma (EAC) remains a lethal malignancy with limited prognostic tools for guiding immunotherapy. Tumor-infiltrating immune cells (TIICs) play a critical role in EAC prognosis and treatment response. METHODS: We integrated single-cell RNA sequencing and bulk transcriptome data from TCGA and GEO databases. TIIC-specific RNAs were identified via tissue specificity index calculation combined with machine learning feature selection. Twenty machine learning algorithms were benchmarked to construct an optimal TIIC signature score (TIIC-Score) based on the comprehensive C-index. Immunotherapy response, genomic mutation, and copy number variation were analyzed. Summary-data-based Mendelian randomization (SMR) and two-sample Mendelian randomization (MR) were performed to explore genetic associations. Core prognostic TIIC-related genes were functionally validated in esophageal cancer cell lines through loss-of-function assays. RESULTS: The TIIC-Score demonstrated robust prognostic value for 1-, 2-, and 3-year overall survival across multiple cohorts, outperforming 22 published models. High TIIC-Score was associated with poor survival and increased chromosomal instability. Mutation profiling revealed high frequencies of TP53 (78.2%), TTN (48.7%), and SYNE1 (30.8%). MR analysis identified a significant association between gastro-oesophageal reflux and EAC risk at SNP rs8130507. Functionally, CCNI was upregulated in esophageal cancer cells, and its knockdown suppressed malignant phenotypes while promoting apoptosis, supporting its pro-tumorigenic role. CONCLUSION: The TIIC-Score provides a novel prognostic framework for EAC that effectively stratifies patient risk and may help identify individuals most likely to benefit from immunotherapy.

Esophageal adenocarcinoma↗

Segregation analysis of fat mass and other body composition measures derived from underwater weighing.

Segregation patterns of three body composition measures which were derived from underwater weighing were evaluated in a random sample of 176 French-Canadian families. Two of the variables can be considered as primary partitions of weight (fat mass [FM] and fat-free mass [FFM]), while the remaining variable (percent body fat [%BF]) is a derived index combining the measures of both fat and fat-free weight. This study represents the first report investigating major gene effects for these measures. Segregation analyses revealed that a major locus hypothesis could not be rejected for two of the three phenotypes. The single exception was FFM, for which nearly 60% of the variance was accounted for by a non-Mendelian major effect, which may reflect environmentally based commingling or may be in part a function of gene-environment interactions or correlations. In contrast to the results for FFM, the results for each of FM and %BF were similar and suggested a major locus which accounted for 45% of the variance, with an additional 22%-26% due to a multifactorial component. Given the similarity of the major gene characteristics for these two phenotypes, the possibility that the same gene underlies both measures warrants investigation. A reasonable hypothesis is to consider genes that may influence nutrient partitioning, as the family of candidate genes to receive the major attention.

Adipose Tissue↗

Probability of detection of genotyping errors and mutations as inheritance inconsistencies in nuclear-family data.

Gene-mapping studies routinely rely on checking for Mendelian transmission of marker alleles in a pedigree, as a means of screening for genotyping errors and mutations, with the implicit assumption that, if a pedigree is consistent with Mendel's laws of inheritance, then there are no genotyping errors. However, the occurrence of inheritance inconsistencies alone is an inadequate measure of the number of genotyping errors, since the rate of occurrence depends on the number and relationships of genotyped pedigree members, the type of errors, and the distribution of marker-allele frequencies. In this article, we calculate the expected probability of detection of a genotyping error or mutation as an inheritance inconsistency in nuclear-family data, as a function of both the number of genotyped parents and offspring and the marker-allele frequency distribution. Through computer simulation, we explore the sensitivity of our analytic calculations to the underlying error model. Under a random-allele-error model, we find that detection rates are 51%-77% for multiallelic markers and 13%-75% for biallelic markers; detection rates are generally lower when the error occurs in a parent than in an offspring, unless a large number of offspring are genotyped. Errors are especially difficult to detect for biallelic markers with equally frequent alleles, even when both parents are genotyped; in this case, the maximum detection rate is 34% for four-person nuclear families. Error detection in families in which parents are not genotyped is limited, even with multiallelic markers. Given these results, we recommend that additional error checking (e.g., on the basis of multipoint analysis) be performed, beyond routine checking for Mendelian consistency. Furthermore, our results permit assessment of the plausibility of an observed number of inheritance inconsistencies for a family, allowing the detection of likely pedigree-rather than genotyping-errors in the early stages of a genome scan. Such early assessments are valuable in either the targeting of families for resampling or discontinued genotyping.

Alleles↗

Genetic etiology of nuclear cataract: evidence for a major gene.

Sibling correlations and segregation analysis were used to examine the familial distribution of age-sex-adjusted measures of nuclear sclerosis in 1,247 individuals from 564 sibships in the Beaver Dam Eye Study. There are highly significant sibling correlations for all sibs, and separately for sister-sister, sister-brother, and brother-brother pairs. Two transformed normal distributions give the best fit to the data. The hypothesis of mendelian transmission of a major effect cannot be rejected, but the hypothesis of a random environmental major effect is rejected. The parameters of the tau AB free model showed close similarity to the values expected under a mendelian hypothesis. Our results suggest that a single major gene can account for 35% of the total variability of age-sex-adjusted measures of nuclear sclerosis.

Adult↗