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PubMed1995

[Analysis of changes in MGE localization of Drosophila after selection and temperature treatment using Southern blot-hydridization].

For five heterogeneous lines of Drosophila melanogaster (riC, riSN, riSP, riT113, and riT149), patterns of DNA restriction fragments, containing different mobile genetic elements (MGE), were obtained by means of Southern blot hybridization. Using densitometry of gel radioautographs, differences between patterns were estimated and distance matrices and similarity dendrograms constructed. Judging by these dendrograms, lines riSN (selected in negative direction) and riT113 (treated with temperature) are most similar both for patterns of MGEs Dm412, I-3', and jockey; and for the expression of the quantitative character radius incompletus. The similarity in MGE patterns was shown to be determined mainly by more similar spectra of acquisition and loss of bands (fragments), than in the control line (riC). Earlier, the same results were obtained for MGEs Dm412, MDG1, and copia, using in situ hybridization. It is assumed that during selection, a consensus pattern of the selected line is largely formed by transpositions and excisions of MGE, which either modify the expression of adjacent polygenes or mark adjacent polygenes with large effect. Under temperature stress, non-random induced transpositions and excisions generate hot sites and site haplotypes. If they affect polygene expression, they also fall into consensus patterns of contrasting "temperature" lines and form correlation between the character expression and MGE localization pattern.

Animals↗

PubMed1995

Genetic and environmental sources of fibrinogen variability in Israeli families: the Kibbutzim Family Study.

Genetic and environmental determinants of plasma fibrinogen were investigated in a sample of 82 kindreds residing in kibbutz settlements in Israel. The sample included 223 males and 229 females ages 15-97 years. Fibrinogen levels were first adjusted for variability in sex and age. There was a significant familial aggregation of adjusted fibrinogen levels, as indicated by inter- and intraclass correlation coefficients significantly different from zero. Commingling analysis implied that in this population a mixture of two normal distributions fit the adjusted fibrinogen levels better than did a single normal distribution. Complex segregation analysis was first applied to these sex- and age-adjusted data. Heterogeneous etiologies for individual differences were suggested. There was evidence for a nontransmitted environmental major factor in addition to polygenic genes that explained the mixture of distributions. In parallel, a single recessive locus with a major effect that explained the adjusted variation in fibrinogen could not be rejected. However, when the regression model for sex and age allowed coefficients to be ousiotype (class)-specific, the recessive genetic model was rejected and the mixed environmental one was not. These results suggested that particular ousiotypes determined by the major environmental factor are associated with a steeper increase of fibrinogen with age. While at the age of 20 years, the major environmental factor contributed 10% to fibrinogen variability, and 48% was explained by polygenic loci, at 80 years of age, the major factor explained 64% and only approximately 20% was explained by polygenic factors.

Adolescent↗

PubMed1993

Conclusions of segregation analysis for family data generated under two-locus models.

Susceptibility to a disease may involve the interactive effect of two genes. What conclusions will be drawn by segregation analysis in such a case? To answer this question, we considered a set of two-locus models and the corresponding exact distribution for 300 families. We investigated the conclusions and parameter estimations obtained for this sample, by comparing the likelihood expectations of the unified model and of more restricted models. In many cases, segregation analysis leads to the conclusion of a major gene effect, with or without a polygenic component--usually without a polygenic component in multiplicative models (i.e., where two genes have a multiplicative effect) and with such a component in nonmultiplicative models. For all the models considered, existence of a major gene effect is supported by transmission probability tests; there is evidence for transmission and agreement with the hypothesis of Mendelian transmission. Accordingly, there is no means of detecting that the effect of a major gene, with or without a polygenic component, does not correspond to the correct model. In addition, the parameter estimates for the major gene do not correspond to the characteristics of either of the two genes of the true model. This may substantially affect further linkage analysis.

Alleles↗

PubMed1993

[Genetics of bronchial asthma with reference to allergy].

No uniform opinion exists to date in respect of the transmission of a genetic disposition to asthma bronchiale and atopy. Literature references discuss both monogenic, autosomal dominant or recessive and multifactorial-polygenic heredity. The following contribution discusses the results of an own study on the occurrence of atopy and asthma bronchiale in 153 families. Multifactorial-polygenic heredity with threshold value range is most suitable for the interpretation of our findings, even though an autosomal dominant heredity with reduced penetrance and variable expressivity might well be the basis for the transmission of a disposition to atopy and asthma bronchiale. In multifactorial-polygenic heredity with threshold value range, empirical risk data are important for predicting the disease risk. Such data can be obtained only on the basis of extensive family research and apply only to the population for which they were obtained. The risk of occurrence of atopy or asthma bronchiale in families already affected by the increases, in our experience, with the number of the patients already suffering from the disease and with the closeness of relationship with the patients concerned. We found a recurrence risk for further children of 40-45% for atopy and of 5-10% for asthma bronchiale in those marriages where both one parent and already one child are suffering from the disease.

Asthma↗

PubMed1997

[Advances in the research on Alzheimer's disease--overview].

The number of patients suffering from dementia in Japan has been estimated to exceed 1,250,000 and is expected to increase rapidly in the near future. It is quickly becoming a serious medical and social issue. Alzheimer's disease (AD) is a leading cause of dementia, and can be classified into two genetic categories: single-gene and polygenic diseases. Familial Alzheimer's disease (FAD) is classified as a single-gene disease, while sporadic AD is classified as a polygenic disease which involves multiple genetic and environmental factors. Using positional cloning, most of the genes which lead to FAD have recently been identified e.g., the amyloid precursor protein (APP) gene on chromosome 21, presenilin I on chromosome 14 and presenilin II on chromosome 1. Recent studies indicate that mutations in these genes can result in either overproduction of A beta or in production of A beta 1-42. Although the accumulation of A beta has been suggested to be the "primary cause" not only in FAD but also in sporadic AD, it remains unclear how neurodegeneration in AD is related to the accumulation of A beta. The discovery of ApoE4 as a major genetic risk factor for AD has created a new step of research on AD as a polygenic disease. Although it is confirmed that the presence of the ApoE4 allele greatly accelerates age at onset of AD, the role of ApoE4 as a risk factor for AD remains to be fully elucidated. Now that major genes involved in the pathogenesis of AD have been identified, future research should be directed toward elucidation of the molecular mechanisms of how these gene products are involved in the pathogenesis of AD on protein as well as cellular levels.

Alzheimer Disease↗

PubMed2026

Shared genetic architecture between DTI-ALPS traits and neurodegenerative diseases.

INTRODUCTION: Diffusion tensor image analysis along the perivascular space (DTI-ALPS) index is associated with neurodegenerative diseases (NDDs), but its shared genetic basis with NDDs remains unclear. METHODS: By integrating genome-wide association datasets for three DTI-ALPS traits and seven NDDs, we quantified polygenic overlap using MiXeR, identified shared loci using conditional and conjunctional false discovery rate analyses, and performed gene mapping, enrichment, temporal expression, and transcriptome-wide association analyses. RESULTS: DTI-ALPS traits showed widespread but heterogeneous polygenic overlap with NDDs. We identified 22 shared loci, including novel associations implicating GAK and SIAH3, with the strongest convergence at 17q21.31. Shared loci mapped to 183 protein-coding genes enriched in the endolysosomal system and microtubule cytoskeleton. These genes showed similar temporal expression patterns, and 45 were associated with both DTI-ALPS traits and NDDs. DISCUSSION: These findings reveal a shared genetic architecture between DTI-ALPS traits and NDDs, highlighting mechanisms that may contribute to their overlap.

Neurodegenerative Diseases↗

PubMed2026

Genetic determinants of obesity: mechanisms, clinical implications, and targeted therapies.

PURPOSE: Obesity is a major global health crisis with rising prevalence in both pediatric and adult populations, leading to an increased risk of cardiovascular, metabolic, and other chronic complications affecting all organ systems. A clear understanding of the genetic contributors to polygenic, syndromic, and monogenic obesity is essential for early diagnosis and targeted management. METHODS: Advances in genome-wide association studies (GWAS) and sequencing technologies have greatly expanded our understanding of the genetic alterations underlying this multifaceted disease and have helped in delivering personalized treatment. RESULTS: The pathogenesis of common, polygenic obesity is related to a complex interplay between genetic susceptibility and environmental factors. Syndromic obesity, a less common form, is characterized by early-onset accompanied by additional features such as developmental delay, dysmorphic traits, and various organ system involvement. The rarest form, monogenic obesity, is characterized by severe early-onset non-syndromic obesity caused by mutations in single genes regulating appetite within the hypothalamus. These monogenic obesity cases, though infrequent, have been instrumental in elucidating key pathways involved in hunger and satiety. CONCLUSION: This review provides a comprehensive summary of the most recent findings on the genetic basis of obesity across all age groups, highlighting clinical implications and emerging therapeutic opportunities.

Humans↗

PubMed2025

Leveraging local ancestry and cross-ancestry genetic architecture to improve genetic prediction of complex traits in admixed populations.

The broader application of polygenic risk score (PRS) is hindered by the limited transferability of PRS developed in Europeans to non-European populations. While many statistical methods have been developed to improve the performance of PRS in non-European populations, most of them focused on discrete genetic ancestry clusters and did not consider admixed individuals. Admixed individuals pose a unique challenge for PRS calculation due to the complexity of local ancestry and cross-ancestry effect sizes. Here, we present a statistical method called SDPR_admix for calculating PRS in admixed individuals. SDPR_admix characterizes the joint distribution of the effect sizes of a genetic variant with two ancestries to be both zero, ancestry enriched, or shared with correlation. SDPR_admix outperformed other methods in simulations and improved the prediction of real traits in European-African admixed individuals in UK Biobank when trained on the Population Architecture using Genomics and Epidemiology (PAGE) dataset (N = 13,000). Deployment of SDPR_admix on All of Us (N = 52,000) further increased the prediction accuracy by approximately 5-fold on average compared with training on PAGE. This enhancement was achieved with manageable computational time and cost, demonstrating the feasibility of training PRS models on large-scale All of Us data. We provided several examples demonstrating that both ancestral-enriched and shared effects, as included in the SDPR_admix prediction model, are helpful for improving polygenic prediction in admixed populations. We also applied SDPR_admix to construct PRS for admixed Americans with mixture of European and Amerindigenous ancestries and showed that SDPR_admix overall outperformed other methods.

Humans↗

PubMed2025

Dissecting the shared genetic architecture of schizophrenia with ventricular subregion volumes.

Schizophrenia is characterized by cerebral ventricular enlargement as an early and consistent structural anomaly. While genetic factors significantly influence both schizophrenia and cerebral ventricular enlargement, the shared genetic etiology between them requires further investigation. Using summary statistics from recent large genome-wide association studies on schizophrenia and 9 ventricular subregion volumes phenotypes. Gaussian causal mixture modeling was applied to characterize the genetic architecture and overlap between schizophrenia and ventricular subregion volumes phenotypes. Local genetic correlation was investigated with Local Analysis of Variant Association. The conjunctional false discovery rate framework was used to identify the specific shared genetic loci, annotated with FUMA. Gaussian causal mixture modeling estimated schizophrenia to be more polygenic more polygenic (9574 trait-influencing variants) than ventricular subregion volumes phenotypes (157-1267 trait-influencing variants). Conjunctional false discovery rate analysis identified 42 shared genetic loci, 17 loci were identified as novel for both schizophrenia and the ventricular subregion volumes phenotypes. Local Analysis of Variant Association revealed that 11 distinct loci demonstrated significant differences, among which 4 loci were situated in the Major Histocompatibility Complex region. Annotated genes in shared loci were enriched in molecular signaling pathways involved in inflammation and the brain structure. The shared loci between them were annotated and enriched in Major Histocompatibility Complex and inflammation-related pathways, highlighting new opportunities for future investigation.

Schizophrenia↗

PubMed2025

Genome-wide Parallelism Underlies Rapid Freshwater Adaptation Fueled by Standing Genetic Variation in a Wild Fish.

A fundamental focus of ecological and evolutionary biology is determining how natural populations adapt to environmental changes. Rapid parallel phenotypic evolution can be leveraged to uncover the genetics of adaptation. Using population genomic approaches, we investigated the genetic architecture underlying rapid parallel freshwater adaptation of Neosalanx brevirostris by comparing four freshwater-resident populations with their common ancestral anadromous population. We demonstrated that the rapid parallel adaptation to freshwater followed a complex polygenic architecture and was characterized by genomic-level parallelism, which proceeded predominantly through repeated selection on the preexisting standing genetic variations. Frequencies of the genome-wide adaptive standing variations were moderate in the ancestral anadromous population, which had pre-adapted to fluctuating salinities. Relatively large allele frequency shifts were observed at some adaptive single-nucleotide polymorphisms (SNPs) during parallel adaptation to freshwater environments, with a large fraction of freshwater-favored alleles being fixed or nearly fixed. These adaptive SNPs were involved in multiple biological functions associated with osmoregulation, immunoregulation, locomotion, metabolism, etc., which were highly consistent with the polygenic architecture of adaptive divergence between the two ecotypes involving multiple complex physiological and behavioral traits. This work provides insight into the mechanisms by which natural populations rapidly evolve to changes in the environment and highlights the importance of standing genetic variation for the evolutionary potential of populations facing global environmental changes.

Animals↗

PubMed2026

Consistent and idiosyncratic pleiotropy in shaping genetic correlations.

Pleiotropy, the phenomenon where a single mutation influences multiple phenotypic traits, creates genetic correlations that can constrain evolutionary trajectories. Yet genetic correlations differ in their persistence: some remain stable over long evolutionary timescales, whereas others change rapidly across generations or environments. One explanation is that similar values of genetic correlation, rG, can arise from different pleiotropic architectures: broadly aligned effects across many loci, or disproportionate covariance contributions from a few large effect loci. Motivated by the distinction between vertical and horizontal pleiotropy, here, we develop a bivariate marker effect framework for recombinant mapping populations that separates candidate large covariance contributors from the polygenic background correlation, rD. We define rD as the correlation among marker effects after trimming markers with unusually large covariance contributions. rD is a trait-pair summary of how consistently small and moderate effect markers align across the genome; high rD is expected when many perturbations propagate through shared developmental, physiological, causal, or geometric structure. Applying this framework to high-dimensional yeast single-cell morphology, we show that trait pairs with similar rG can differ substantially in rD, and that a small number of candidate outlier regions can strongly influence some marker effect correlations. We then test whether rD predicts the environmental stability of genetic correlations under geldanamycin-mediated Hsp90 perturbation. Trait pairs with stronger rD show smaller absolute changes in rG. These results suggest that genetic correlations supported by a strong polygenic marker effect background are more environmentally stable than correlations shaped primarily by a few large covariance contributors.

Genetic Pleiotropy↗

PubMed2025

Genetic prediction of early adolescent chronotype: effects of sex and pubertal status.

STUDY OBJECTIVES: Adolescence is characterized by later sleep onset and wake times, indicating a shift to an evening chronotype. Genome-wide association studies (GWAS) in adults show chronotype is polygenic and causally linked to depression, schizophrenia, and cognitive function. Yet, the impact of genetics on adolescent chronotype remains largely unexplored, and biological factors influencing the predictive relationship between genetics and chronotype have not been well-defined. This study aims to assess the utility of polygenic scores (PGS) derived from adult GWAS in predicting adolescent chronotype, mental health, and cognition while considering sex- and puberty-dependent effects. METHODS: Generalized linear models were used to assess the relationship between PGS for chronotype and self-reported chronotype, mental health, and cognition in 2411 youths of European ancestry aged 10-13 years. Interaction terms assessed whether the genotype-phenotype relationships varied by sex or pubertal development. Statistical significance was determined using a likelihood ratio test. RESULTS: Significant sex- and puberty-dependent effects were observed. Higher PGS for morningness concordantly predicted earlier self-reported chronotype, but in female youth only. Follow-up analyses showed that sex-specific effects were mediated by the interaction between PGS and pubertal status. Greater genetic predisposition for morningness was negatively associated with somnolence and cognition in males and negatively associated with psychotic-like experiences in females. CONCLUSIONS: The influence of genetic predisposition for early versus late chronotype on adolescent sleep-wake behavior emerges as puberty progresses. These findings suggest puberty is a critical transition when genetic variants associated with chronotype in adults become relevant to pediatric cohorts.

Humans↗

PubMed2026

Climate-Driven Niche Tracking and Genomic Resilience Shape Future Distribution of a Widespread Agricultural Weed.

Understanding how agriculturally important species respond to environmental change is critical for maintaining productivity, mitigating agroecosystem threats and sustaining resilience. While crops have traditionally been the focus in agroecosystems, agricultural weeds are integral components that often face even stronger selective pressures, making them powerful models for investigating ecological and evolutionary responses to climatic and human-mediated challenges. Insights from how weeds adapt rapidly under these pressures can inform strategies to improve agricultural outcomes, since both pests and crops evolve under the same multivariate selective pressures. Here, we integrate two centuries of distribution records with whole-genome sequencing from natural populations of the most damaging weed in Europe-Alopecurus myosuroides (blackgrass) - to examine its ecological and evolutionary responses in agroecosystems. Blackgrass largely maintained its historical climatic niche, expanding its range primarily by tracking environments analogous to those it historically occupied. Genome-wide analyses revealed a polygenic basis of environmental responses, with most loci linked to single environmental variables and a subset showing limited environmental pleiotropy, indicating modular adaptation to the complex selective pressures of managed agricultural landscapes. Coupling these genomic-environment relationships with projected climate change and genomic offset analyses indicated that most blackgrass populations will remain well aligned with future conditions. Our findings show that ecological niche tracking and polygenic adaptation allow agricultural weeds like blackgrass to persist under rapid environmental change, offering insights relevant not only for weed management but also for designing resilient cropping systems under future climates.

Plant Weeds↗

PubMed2026

Divergent autoimmune genetic landscapes in diabetic and non-diabetic individuals.

BACKGROUND: Type 2 diabetes (T2D) and autoimmune diseases are complex disorders shaped by genetic, immunological, and environmental factors. However, differences in genetic susceptibility to autoimmune disorders between diabetic and non-diabetic individuals remain poorly understood, particularly within the Indian population. This study aimed to compare polygenic susceptibility to multiple autoimmune diseases between individuals with and without T2D from Gujarat, India. RESULTS: Polygenic risk scores were evaluated for eleven autoimmune diseases in 474 individuals, including 99 diabetics and 375 non-diabetics. Significant differences were observed for systemic lupus erythematosus and rheumatoid arthritis. Individuals with diabetes showed a higher genetic risk for systemic lupus erythematosus, whereas non-diabetic individuals exhibited a higher genetic risk for rheumatoid arthritis. Pathway enrichment analysis of disease-associated genetic variants revealed significant involvement of immune-related pathways, including antigen processing and presentation, T-helper cell differentiation, and immune responses to viral infections. CONCLUSIONS: The findings reveal disease-specific differences in genetic susceptibility to autoimmune disorders between diabetic and non-diabetic individuals. These results highlight the complex immunogenetic relationship between type 2 diabetes and autoimmune diseases and provide insight into shared and distinct immune pathways within an Indian population. Such information may support future efforts in risk stratification and precision medicine approaches for immune-related comorbidities in diabetes.

Humans↗

PubMed2026

Shared genetic architecture between ADHD and intelligence varies across ADHD subtypes.

BACKGROUND: Attention-deficit/hyperactivity disorder (ADHD) is a heterogeneous neurodevelopmental condition frequently accompanied by cognitive difficulties. Although previous genetic studies have demonstrated substantial overlap between ADHD and intelligence, most have treated ADHD as a single phenotype. However, whether this shared genetic architecture differs across ADHD subtypes remains unclear. METHODS: We conducted a genome-wide cross-trait analysis integrating large-scale genome-wide association study (GWAS) datasets of overall ADHD, its subtypes-childhood ADHD, persistent ADHD, and late-diagnosed ADHD-and intelligence (total N > 300,000). Genome-wide genetic correlations, polygenic overlap, local genetic correlations, and variant-level associations between ADHD phenotypes and intelligence were evaluated to characterize their shared genetic architecture. Shared variants were identified through cross-trait enrichment analyses and subsequently mapped to genes for functional annotation and gene-set enrichment. Bidirectional associations were evaluated using two-sample Mendelian randomization with sensitivity analyses. Additional GWAS datasets were used to validate the robustness of shared loci by assessing the consistency of effect directions. RESULTS: All ADHD phenotypes showed significant negative genetic correlations with intelligence (rg ranging from -0.3442 to -0.4205). Despite these modest genome-wide correlations, cross-trait analyses revealed substantial genetic overlap, including polygenic overlap, local genetic correlations, and variant-level associations. We identified 184 loci jointly associated with ADHD traits and intelligence, including 64 novel loci, whereas no shared loci were detected for persistent ADHD under the current analysis. Functional annotation revealed biologically distinct enrichment patterns across subtypes: childhood ADHD loci were linked to early neurodevelopmental processes, while late-diagnosed ADHD loci were enriched in synapse-related and neuronal signaling pathways. Mendelian randomization analyses suggested bidirectional associations, with stronger evidence supporting a directional association from intelligence to ADHD risk. Furthermore, these shared loci showed largely consistent effect directions across additional GWAS datasets, providing support for the robustness of the findings. CONCLUSIONS: The shared genetic architecture between ADHD and intelligence varies across ADHD subtypes, highlighting distinct biological pathways underlying cognitive heterogeneity in ADHD. These findings suggest that the relationship between ADHD liability and general cognitive ability is not uniform across ADHD subtypes and may inform future research on risk stratification and early identification in child and adolescent psychiatry.

Humans↗

PubMed2024

Prediction of metabolic syndrome using machine learning approaches based on genetic and nutritional factors: a 14-year prospective-based cohort study.

INTRODUCTION: Metabolic syndrome is a chronic disease associated with multiple comorbidities. Over the last few years, machine learning techniques have been used to predict metabolic syndrome. However, studies incorporating demographic, clinical, laboratory, dietary, and genetic factors to predict the incidence of metabolic syndrome in Koreans are limited. In the present study, we propose a genome-wide polygenic risk score for the prediction of metabolic syndrome, along with other factors, to improve the prediction accuracy of metabolic syndrome. METHODS: We developed 7 machine learning-based models and used Cox multivariable regression, deep neural network (DNN), support vector machine (SVM), stochastic gradient descent (SGD), random forest (RAF), Naïve Bayes (NBA) classifier, and AdaBoost (ADB) to predict the incidence of metabolic syndrome at year 14 using the dataset from the Korean Genome and Epidemiology Study (KoGES) Ansan and Ansung. RESULTS: Of the 5440 patients, 2,120 were considered to have new-onset metabolic syndrome. The AUC values of model, which included sex, age, alcohol intake, energy intake, marital status, education status, income status, smoking status, dried laver intake, and genome-wide polygenic risk score (gPRS) Z-score based on 344,447 SNPs (p-value < 1.0), were the highest for RAF (0.994 [95% CI 0.985, 1.000]) and ADB (0.994 [95% CI 0.986, 1.000]). CONCLUSIONS: Incorporating both gPRS and demographic, clinical, laboratory, and seaweed data led to enhanced metabolic syndrome risk prediction by capturing the distinct etiologies of metabolic syndrome development. The RAF- and ADB-based models predicted metabolic syndrome more accurately than the NBA-based model for the Korean population.

Humans↗

PubMed2026

Stratifying the risk of transition to adult-onset psychiatric disorders in adolescents with anxiety.

BACKGROUND: Escalating mental health service demands have created a need to better identify young people most likely to require continued support from mental health services at the transition between childhood and adulthood. Anxiety is the most common adolescent mental health condition, yet its clinical significance and prognosis are not well understood. We aimed to examine the risk of young adult-onset psychiatric disorders in individuals with an adolescent anxiety disorder, and identify stratifiers of risk of subsequent psychiatric disorders in this group. METHODS: Individuals from the Norwegian Mother, Father, and Child Cohort Study (MoBa) with linked health records and aged 18 or over as of the 31st December 2023 were included. Those diagnosed with any ICD-10 anxiety disorder when aged 10-17 years were defined as having an adolescent anxiety disorder (n=2107, controls n=47,582). Polygenic scores (PGS) for psychiatric and neurodevelopmental conditions were calculated using LDpred2. Anxiety, comorbidities, and parental psychiatric history were defined through linked ICD-10 diagnoses. Sex was defined through linked records. Individuals were defined as having a young adult-onset psychiatric disorder if they first received any new psychiatric diagnosis aged 18-24. RESULTS: Adolescent anxiety diagnosis was associated with increased risk of all adult-onset psychiatric disorders (HR= 2.33-8.65). Post-traumatic stress disorder PGS, parental history of severe mental illness, and female sex were associated with increased risk of transition to a young adult-onset psychiatric disorder in people with an adolescent anxiety disorder. CONCLUSIONS: Adolescent anxiety greatly increases the risk of a psychiatric disorder during the transition to adult life. Clinicians should consider female sex and parental psychiatric history when prioritising young people with anxiety for adult mental health service support. Future research needs to further consider whether polygenic scores would aid risk stratification in clinical practice.

Norwegian Mother Father and Child Cohort Study↗

PubMed1992

Usefulness of serum apolipoprotein B levels for screening children with primary dyslipoproteinemias.

OBJECTIVE: To assess the use of serum apolipoprotein B levels for screening children with primary dyslipoproteinemia (those with elevated levels of low-density lipoprotein cholesterol [LDL-C]) and to know the types of dyslipoproteinemias we can identify. DESIGN: Criterion standard. SETTING: Referral center. PARTICIPANTS: We have studied 267 children. Of these, 31 had parents with dyslipoproteinemia, 38 had parents with ischemic heart disease, and 43 had hypercholesterolemia detected by routine analyses. One hundred fifty-five were considered healthy children and comprised the control group. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: Sensitivity was 87% for total serum cholesterol levels and 73% for serum apolipoprotein B levels. Of the children studied, 31 had elevated levels of serum LDL-C. The types of dyslipoproteinemia in children with both elevated levels of serum LDL-C and apolipoprotein B consisted of heterozygous familial hypercholesterolemia, found in 12 (50%) of 24 patients; familial combined hyperlipidemia, found in 11 (46%) of 24 patients; and polygenic hypercholesterolemia, found in one (4%) of 24 patients. CONCLUSIONS: Serum apolipoprotein B level appears to be a good tool for screening children with elevated levels of LDL-C and is equivalent to using total serum cholesterol levels. In children with elevated serum LDL-C and apolipoprotein B levels, we can identify not only patients with heterozygous familial hypercholesterolemia but also those with familial combined hyperlipidemia or polygenic hypercholesterolemia.

Adolescent↗