Twin Research and Human Genetics最新文献

Is general intelligence (g) a reflective construct, representing a latent causal entity underlying subtest performance, or a formative construct, better understood as an aggregate variable shaped by and summarizing variation across subtests? Genetically informative data provide a framework for testing whether a construct is reflective or formative by comparing common pathway and independent pathways structural equation models (SEMs). Previous studies using biometric SEMs have predominantly supported the reflective model, with phenotypic g mediating the effects of additive genetic and environmental influences on lower level abilities. In the current study, four large genetically informed datasets (three from the US and one from the UK) were analyzed to test three competing SEM models - common pathway, independent pathways, and merged - using Confirmatory Factor Analysis (CFA). Genetic g was estimated in each sample as a latent variable derived from polygenic scores indexing educational attainment and cognitive abilities. The models were compared as follows: the common pathway model, consistent with a reflective g, included a direct path from genetic g to phenotypic g; the independent pathways model, consistent with a formative g, featured indirect paths from genetic g to phenotypic g via subtests; and the merged model incorporated both direct and indirect paths. Across all four datasets, the merged model consistently provided the best fit (based on goodness-of-fit and parsimony criteria). Phenotypic g mediated between 31% and 81% of the effects of genetic g on subtests. These findings suggest that g functions as both a reflective and formative entity.

Incorporating genetic data from diverse populations is crucial for understanding genetic contributions to diseases and ensuring health equity in healthcare practices. However, existing reference panels either capture a limited number of populations or have small sample sizes. We examine the UK Biobank's performance as a reference for clustering genetically similar individuals. Leveraging data from participants of diverse origins, we aim to improve population representation and mitigate bias caused by the limited number of populations in other reference panels. We combined countries of birth and ethnic backgrounds data fields from the UK Biobank and genetic information to infer genetically similar population labels. A random forest model was then trained on genetic principal components to identify each individual's most genetically similar population. The model's performance was validated using the 1000 Genomes and the CARTaGENE biobank data. We identified more diverse reference populations than present in datasets such as 1000 Genomes, covering 19 populations worldwide. Our model achieved medium to high precision and recall for most labeled populations, although lower rates were observed in closely related groups. For instance, we identified 519 people in CARTaGENE most genetically similar to the Middle Eastern reference sample derived in the UK Biobank (there are no Middle Eastern samples in 1000 Genomes), yielding an 81.1% precision and a 97.0% recall rate compared to demographic-based information. This practical approach of clustering genetically similar individuals utilizing existing biobank data may facilitate downstream analyses, such as genomewide association studies or polygenic risk scores in underrepresented populations in genetic studies.

Since the 1970s, twin birth rates have increased sharply in developed countries. In Africa, where the rate is the highest globally, its evolution and variation are poorly understood. This article aims to estimate the twinning rate in sub-Saharan African (SSA) countries throughout 1986-2016 and analyze its spatial, temporal, and ethnic variations. It also seeks to identify social and demographic factors associated with a high probability of twin births and outline a forecast of the twinning rate. We used data from 174 Demographic and Health Surveys from 42 countries. We supplemented them with the UN World Population Prospects (WPP). The twinning rate was calculated by reporting the number of twin births per thousand total births. We used logistic regression to analyze the factors associated with twin births. We projected the twinning rate based on WPP. The overall SSA twinning rate is 17.4 per 1000, but it has changed very little over time, and we expect it will grow a little between 2015 and 2050, increasing at most from 17.4 per 1000 to 18.4 per 1000. We also show significant differences in the twinning rate in SSA according to mother ethnicity. Most ethnic groups with high twinning rates belong to the large Bantu ethnic family. SSA remains the 'land of twins', with the twinning rate changing slowly. However, specific health policies must target twin births in SSA to address the public health challenges they present.

The objective of this study was to to describe perinatal outcomes in monochorionic twin pregnancies after selective fetal reduction using bipolar cord coagulation (BCC) or interstitial laser ablation (ILA). This retrospective cohort study included monochorionic twin pregnancies requiring selective fetal reduction between 2008 and 2023 at a referral center in Spain. Maternal and perinatal data were collected and analyzed to compare outcomes between BCC and ILA techniques. The primary outcome was the survival of the co-twin, while secondary outcomes included gestational age at delivery, the incidence of PPROM, birth weight and long-term neurodevelopmental outcomes. Eighty-four procedures were performed (30 ILA, 54 BCC). The overall co-twin survival rate was 80%, with BCC showing a higher survival rate (87%) compared to ILA (67%, p = .026). Fetal death before 24 weeks was more common in ILA (30%) than BCC (7.4%, p = .010). The mean gestational age at delivery was lower in BCC (36.6 weeks) than ILA (38.6 weeks, p = .021), and preterm delivery was more frequent in BCC (50%) compared to ILA (14%, p = .005). BCC seems to have a better overall survival than ILA in complicated monochorionic twins' selective terminations. However, we could not clarify whether this difference was due to the technique itself or the different gestational age at the time of the procedure as well as the specific indication.

Although financial stressors are implicated as risk factors for suicidal behavior, these associations might be confounded by other factors. Furthermore, a move toward high-risk subgroup definition is necessary. The authors used Swedish national registry data to examine the associations between receipt of social welfare, unemployment benefits, or early retirement (N = 627,745-2,260,753) with suicidal behavior in Cox proportional hazards models. They applied co-relative models to improve causal inference, and examined interactions with aggregate genetic risk for suicidality. All three exposures were associated with elevated suicidal behavior risk. Initial hazard ratios for suicide attempt ranged from 1.37-3.86, were similar for suicide death, and declined after controlling for psychopathology and time elapsed after exposure. Age at registration differentially impacted risk of suicidal behavior. Aggregate genetic liability for suicidality was associated with risk, but its effect was not moderated by financial stress. Financial stressors are associated with suicidal behavior risk even after controlling for psychopathology. Associations are attributable in part to familial confounding, though a potentially causal pathway was observed in most cases. Suicidality risk varied as a function of sex and age at exposure; these findings could be used to identify subgroups at high risk who warrant targeted prevention.

Most twin registries have not systematically collected the data required to determine gender identity, which has limited opportunities to evaluate potential familial contributors to gender diversity. This study addresses this gap by analyzing responses to gender identity questions introduced in Twins Research Australia's 2023 survey. Among 4475 respondents (mean age 52.2 years, SD = 15.3), 36 (0.8%) indicated a transgender or gender diverse identity, which is consistent with population-based estimates of gender diversity internationally. Gender diversity co-occurred in 2/19 monozygotic pairs and 0/8 dizygotic pairs, giving rise to tetrachoric correlations of 0.62 (95% CI [0.33, 0.87]) and 0.00 (95% CI [0.00, 0.88]), respectively. These results broadly align with previous concordance estimates from twin studies that were specifically focused on gender identity. Although limited by a small sample size, these findings demonstrate the feasibility and utility of systematically collecting gender identity data through routine twin registry surveys.