PubMed Health⌕ Search
Home/Archive/PubMed

PubMed · 7362203

Estimating genetic correlations.

C A Smith
View original source ↗Export metadata ↓

Abstract

A method is proposed for simultaneous estimation of genetical variance and covariance components for quantitative characters and hence correlations and cross-correlations between relatives. It proceeds by successive approximations, which are not difficult to compute. Judging by examples, they appear to converge rapidly in practice. When distributions are normal and homoscedastic, the method gives the maximum-likelihood estimates and their error variances and covariances. It can be readily modified to take into account assumptions such as that means and variances are equal in fathers and sons. But the amount of calculations required goes up very rapidly with the number of characters and relatives considered stimultaneously.

Explore related subjects

FemaleGenetic VariationHumansMaleModels, GeneticJournal Article

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

C A Smith. 1980. Estimating genetic correlations.. https://doi.org/10.1111/j.1469-1809.1980.tb01560.x

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related citations

PubMed2026

Cross-Ancestry and Phenome-Wide Associations of Cancer-Specific Polygenic Risk Scores.

PURPOSE: Genome-wide association studies have identified many common variants associated at low effect sizes with various cancers. Summing the effects of these variants into polygenic risk scores (PRS) can improve cancer risk prediction. However, cross-cancer and cross-phenotype pleiotropic associations of cancer-specific PRS are limited. METHODS: Using logistic regression models, we tested the association of 13 cancer-specific PRS with curated phenotypes representing the same 13 cancers and 340 cancer and cardiometabolic phecodes in 560,287 individuals (114,255 African ancestry [AFR] and 446,032 European ancestry [EUR]) from the Million Veteran Program. Models were stratified by ancestry and used age, principal components, and cancer-specific PRS per standard deviation as independent variables, and correction was applied for multiple comparisons. RESULTS: All 13 cancer-specific PRS were significantly associated with their respective cancers among EUR individuals with odds ratios per standard deviation of PRS (odds ratio [OR]) 1.05-1.70. Among AFR individuals, the effect sizes of the cancer PRS were lower, with OR 1.01-1.48, and cancer-specific PRS were significantly associated with their respective cancers for five of 13 cancers (bladder, breast in female patients, colorectal, prostate, and thyroid). In cancer-cancer pleiotropy studies, only the renal cancer-specific PRS was significantly associated with skin cancer (OR = 1.04, P = 4.5 × 10-06) among EUR individuals. PheWAS demonstrated five positive pleotropic associations with cardiometabolic conditions (thyroid cancer PRS with thyroid goiter, oral cancer PRS with diabetes phenotypes, and hypothyroidism) and two negative associations (oral and lung cancer PRS separately with coronary artery disease). CONCLUSION: Cancer PRS have stronger associations per cancer among EUR versus AFR individuals. In contrast to PRS of other chronic diseases, the majority of cancer-related PRS are highly specific and pleiotropic associations with other cancers and cardiometabolic traits are uncommon.

Female↗
PubMed2026

Integrative analysis and experiment validation of SLC12A8 as a biomarker for the malignant transition from endometriosis to endometriosis associated ovarian cancer.

Endometriosis (EM) is a chronic inflammatory, estrogen‑dependent benign gynecological disorder. A subset of patients with EM may subsequently develop endometriosis‑associated ovarian cancer (EAOC), implying a biological continuum between these two conditions. Nevertheless, the molecular events underlying the progression from benign endometriotic lesions toward EAOC remain incompletely characterized. In this study, transcriptomic datasets retrieved from the GEO database were interrogated through differentially expressed gene screening, functional enrichment analysis, and weighted gene co‑expression network analysis (WGCNA) to identify key genes and pathways relevant to EM and EAOC. Candidate genes were further prioritized by integrating survival analysis via the Kaplan‑Meier Plotter, LASSO regression, random‑forest modeling, and CIBERSORT immune‑infiltration profiling. Loss and gain‑of‑function cellular models were established using siRNA and overexpression plasmids, and in‑vitro functional assays were performed to characterize the phenotypic effects of target genes.We identified several candidate genes associated with EM and EAOC and evaluated their discriminatory performance. Among them, SLC12A8 elevated expression across EM and EAOC tissues and exhibited moderate diagnostic capacity. Higher SLC12A8 expression was also associated with poorer prognosis in EAOC patients. In‑vitro experiments further demonstrated that SLC12A8 modulates proliferation, invasion, and migration in both EM and EAOC cell lines. Collectively, our exploratory research findings support SLC12A8 as a candidate functional mediator and potential biomarker linked to EM‑EAOC pathological progression, thereby extending the mechanistic understanding of these disorders.

Female↗
PubMed2026

Recurrence of peripartum cardiomyopathy in subsequent pregnancy stratified by left ventricular function: a systematic review and meta-analysis.

AIMS: Subsequent pregnancy in women with prior peripartum cardiomyopathy (PPCM) carries a risk of relapse and adverse maternal outcomes. This meta-analysis aimed to determine the recurrence of PPCM relapse and associated maternal and foetal outcomes during subsequent pregnancy, stratified by baseline (pre-subsequent pregnancy) left ventricular ejection fraction (LVEF). METHODS: A systematic review and meta-analysis was conducted in accordance with PRISMA guidelines. Nine databases were searched through June 2025 for cohort studies reporting subsequent pregnancy outcomes in women with prior PPCM, stratified as recovered (LVEF &#x2265;50%) or non-recovered (LVEF <50%) groups. Outcomes included PPCM relapse, maternal mortality, LVEF during and after pregnancy, LV recovery, symptom worsening, and obstetric/neonatal events. Risk of bias was assessed with ROBINS-E, and random-effects models were used. RESULTS: Six cohort studies comprising 266 women were included (174 in recovered group and 92 in non-recovered group). Relapse occurred in both groups with no significant difference [rate ratio (RR) 0.77, 95% CI 0.50-1.19; I2 = 3%]. Maternal mortality was significantly lower in the recovered group (1.7% vs 10.9%; RR 0.27, 95% CI 0.09-0.87; I2 = 0%). Recovered group had higher mean LVEF during subsequent pregnancy (mean difference [MD] 17.0; P < .001), higher postpartum LVEF (MD 11.69; P = .005; I2 = 84%), and greater likelihood of LV recovery (RR 2.07; P = .005; I2 = 0%). No significant differences were observed in symptom worsening or obstetric/neonatal outcomes. CONCLUSION: Recovered LVEF prior to subsequent pregnancy is associated with improved maternal outcomes, yet relapse remains common. Left ventricular ejection fraction alone is insufficient for risk stratification, and individualized multidisciplinary care is essential for all women with prior PPCM.

Female↗