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PubMed2023

Low and differential polygenic score generalizability among African populations due largely to genetic diversity.

African populations are vastly underrepresented in genetic studies but have the most genetic variation and face wide-ranging environmental exposures globally. Because systematic evaluations of genetic prediction had not yet been conducted in ancestries that span African diversity, we calculated polygenic risk scores (PRSs) in simulations across Africa and in empirical data from South Africa, Uganda, and the United Kingdom to better understand the generalizability of genetic studies. PRS accuracy improves with ancestry-matched discovery cohorts more than from ancestry-mismatched studies. Within ancestrally and ethnically diverse South African individuals, we find that PRS accuracy is low for all traits but varies across groups. Differences in African ancestries contribute more to variability in PRS accuracy than other large cohort differences considered between individuals in the United Kingdom versus Uganda. We computed PRS in African ancestry populations using existing European-only versus ancestrally diverse genetic studies; the increased diversity produced the largest accuracy gains for hemoglobin concentration and white blood cell count, reflecting large-effect ancestry-enriched variants in genes known to influence sickle cell anemia and the allergic response, respectively. Differences in PRS accuracy across African ancestries originating from diverse regions are as large as across out-of-Africa continental ancestries, requiring commensurate nuance.

Humans↗
PubMed2000

General equations for Pt, Ps, and the power of the TDT and the affected-sib-pair test.

Several equations are highlighted here, whose algebraic symmetries and generality make them very useful for understanding and comparing the properties of the transmission disequilibrium test (TDT) and affected sib-pair test. Methods using the equations are also presented that yield precise estimates of sample sizes needed for genome scans or for testing a single candidate gene, and these power methods are shown to compare favorably with alternative approaches recently described by Knapp (1999) and by Tu and Whittemore (1999). Simple relationships are also noted that summarize the relative sample sizes required for equivalent power to detect association by the TDT or case-control designs. As single-nucleotide polymorphism (SNP) maps revolutionize the search for disease-causing genes, the equations should prove useful for planning and evaluating studies of linkage and association across a broad range of possible disease models and relationships between markers and linked disease loci.

Alleles↗
PubMed1975

Sex-linked familial reflux.

A family is described in which all 3 brothers and the maternal grandfather had vesicoureteral reflux, whereas the father, mother and 3 daughters were urologically normal. This pedigree strongly suggests and X-linked mode of genetic transmission. Nevertheless, available evidence indicates that familial reflux is usually transmitted by multifactorial polygenic inheritance. Hundreds of additional pedigrees will have to be studied before the methods of inheritance are firmly established.

Adolescent↗
PubMed2001

Genetic dissection of complex traits: an overview.

Genetic dissection of even simple Mendelian traits has been sufficiently challenging. Complex traits are proving to be much more challenging and frustrating than previously thought. The concepts, methods, and strategies discussed in this volume emphasize the critical importance of study design, appropriate methods of analysis, including relatively newer and emerging methods, and issues relating to the interpretation of results from genome scans; some thoughts on the future the new millennium holds are offered, as well. This chapter overviews the key steps involved in the study of complex traits, which are discussed in detail in subsequent chapters. It is suggested that a combination of lumping and splitting strategies is more appropriate for the analysis of complex traits, and large-scale collaborations should make this possible. For example, by pooling data and/or results from multiple studies on a given disease/trait, one may attain a sample size large enough to permit the division of the data into multiple relatively more homogeneous subgroups. The sample size of the subgroups may still be sufficiently large sample, but the genetic dissection within each subgroup should be much less daunting. The expectation is that analyses within subgroups will enhance gene finding, especially when any interacting determinants are taken into account at the time of dividing the data into subgroups. Perhaps the methods are not yet optimum, but the future holds much promise. In the meantime, the cutting-edge methods discussed in this volume by leading experts should help. There is an increasing healthy tendency for investigators to collaborate by pooling materials and results across studies, with the goal of increasing the sample size and thus the power. We believe that such efforts are essential for the genetic dissection of complex traits and should contribute to greater success, especially if there is a real commitment to meaningful collaboration. After all, for most complex traits, the question is not whether there are genes, only when and how they might be found.

Genetic Variation↗
PubMed2001

Familial resemblance and heritability.

Familial resemblance, which arises when members within families are more similar than are unrelated pairs of individuals, may be estimated in terms of correlations (or covariances) among family members. The magnitudes of such correlations generally reflect both the extent of environmental sharing and the degree of biological relationship between the relatives. Heritability, or more appropriately multifactorial heritability or generalized heritability, quantifies the strength of the familial resemblance and represents the percentage of variance ina trait that is due to all additive familial effects including additive genetic effects and those of the familial environment. However, the traditional concept of heritability, which may be more appropriately called the genetic heritability, represents only the percentage of phenotypic variance due to additive genetic effects. Resolving the sources of familial resemblance entails other issues. For example, there may be major gene effects that may be largely or entirely nonadditive, temporal or developmental trends, and gene-gene (epistasis) and gene-environment interactions. The design of a family study determines which of these sources are resolvable. For example, in intact nuclear families consisting of parents and offspring, the genetic and familial environmental effects are not resolvable because these relatives share both genes and environments. However, extended pedigrees and twin and adoption study designs allow separation of the heritable effects and, possibly, more complex etiologies, including interactions. Various factors affect the estimation and interpretability of heritability, for example, assumptions regarding linearity and additivity of the effects, assortative mating, and the underlying distribution of the data. Nonnormality of the data can lead to errors in hypothesis testing, although it yields reasonably unbiased estimates. Fortunately, these and other complications can be directly modeled in many of the sophisticated software packages available today in genetic epidemiology.

Adoption↗
PubMed2000

Etiology and pathophysiology of stroke as a complex trait.

Stroke (brain attack) is currently the third leading cause of death in Western societies. Recent advances in molecular genetics have finally demonstrated what has long been suggested by the clinical observation, that is, stroke is not only the complication of major pathologic conditions such as atherosclerosis, hypertension, or cardiac diseases, but rather it represents a complex trait itself. Thus, the pathogenesis of stroke is often the result of the combined effects of genes exerting a direct contributory role and of their interactions with several environmental determinants. A genetic dissection of stroke has been attempted in suitable animal models and in humans. With this approach, the genetic defects underlying monogenic disorders associated with stroke were identified. Moreover, important findings have recently highlighted the contribution of genes encoding cardiovascular hormones, such as the atrial natriuretic peptide, for the pathogenesis of multifactorial, polygenic forms of stroke. A more thorough understanding of the fine mechanisms, dependent from mutations within stroke susceptibility genes and underlying the disease pathogenesis, may help to introduce new specific tools to achieve better prevention and treatment of stroke.

Animals↗
PubMed1998

Genetics of the hydrophilic surfactant proteins A and D.

The use of candidate genes has increased the ability to identify genetic factors involved in diseases with complex and multifactorial etiology. The surfactant proteins (SP) A and D are involved in host defense and inflammatory processes of the lung, which are often components of pulmonary disease. Therefore, the SP-A and SP-D genes make particularly good candidates to study factors contributing to pulmonary disease etiopathogenesis. Moreover, SP-A also plays a role in the surface tension lowering abilities of pulmonary surfactant, which is essential for normal lung function. Although genetic variability at the SP-D locus may exist among humans, allelic variants have not yet been characterized. On the other hand, the human SP-A genes (SP-A1 and SP-A2) are characterized by genetically dependent splice variants at the 5' untranslated region and allelic variants. The polymorphisms that give rise to SP-A1 and SP-A2 alleles are contained within coding regions, potentially having an effect on protein function. There appears to be a correlation between SP-A genotype and SP-A mRNA content. Furthermore, one SP-A2 allele (1A0) shown to associate with low SP-A mRNA levels is found with higher frequency in a subgroup with respiratory distress syndrome. The evidence gathered thus far indicates that SP-A, possibly by interacting with other surfactant components, may play a role (e.g. be a susceptibility factor) in the development of respiratory disease.

Alternative Splicing↗
PubMed2000

Power of quantitative trait locus mapping for polygenic binary traits using generalized and regression interval mapping in multi-family half-sib designs.

A generalized interval mapping (GIM) method to map quantitative trait loci (QTL) for binary polygenic traits in a multi-family half-sib design is developed based on threshold theory and implemented using a Newton-Raphson algorithm. Statistical power and bias of QTL mapping for binary traits by GIM is compared with linear regression interval mapping (RIM) using simulation. Data on 20 paternal half-sib families were simulated with two genetic markers that bracketed an additive QTL. Data simulated and analysed were: (1) data on the underlying normally distributed liability (NDL) scale, (2) binary data created by truncating NDL data based on three thresholds yielding data sets with three different incidences, and (3) NDL data with polygenic and QTL effects reduced by a proportion equal to the ratio of the heritabilities on the binary versus NDL scale (reduced-NDL). Binary data were simulated with and without systematic environmental (herd) effects in an unbalanced design. GIM and RIM gave similar power to detect the QTL and similar estimates of QTL location, effects and variances. Presence of fixed effects caused differences in bias between RIM and GIM, where GIM showed smaller bias which was affected less by incidence. The original NDL data had higher power and lower bias in QTL parameter estimates than binary and reduced-NDL data. RIM for reduced-NDL and binary data gave similar power and estimates of QTL parameters, indicating that the impact of the binary nature of data on QTL analysis is equivalent to its impact on heritability.

Algorithms↗
PubMed1999

Quantitative genetics in conservation biology.

Most of the major genetic concerns in conservation biology, including inbreeding depression, loss of evolutionary potential, genetic adaptation to captivity and outbreeding depression, involve quantitative genetics. Small population size leads to inbreeding and loss of genetic diversity and so increases extinction risk. Captive populations of endangered species are managed to maximize the retention of genetic diversity by minimizing kinship, with subsidiary efforts to minimize inbreeding. There is growing evidence that genetic adaptation to captivity is a major issue in the genetic management of captive populations of endangered species as it reduces reproductive fitness when captive populations are reintroduced into the wild. This problem is not currently addressed, but it can be alleviated by deliberately fragmenting captive populations, with occasional exchange of immigrants to avoid excessive inbreeding. The extent and importance of outbreeding depression is a matter of controversy. Currently, an extremely cautious approach is taken to mixing populations. However, this cannot continue if fragmented populations are to be adequately managed to minimize extinctions. Most genetic management recommendations for endangered species arise directly, or indirectly, from quantitative genetic considerations.

Animals↗
PubMed1999

Clines in polygenic traits.

This article outlines theoretical models of clines in additive polygenic traits, which are maintained by stabilizing selection towards a spatially varying optimum. Clines in the trait mean can be accurately predicted, given knowledge of the genetic variance. However, predicting the variance is difficult, because it depends on genetic details. Changes in genetic variance arise from changes in allele frequency, and in linkage disequilibria. Allele frequency changes dominate when selection is weak relative to recombination, and when there are a moderate number of loci. With a continuum of alleles, gene flow inflates the genetic variance in the same way as a source of mutations of small effect. The variance can be approximated by assuming a Gaussian distribution of allelic effects; with a sufficiently steep cline, this is accurate even when mutation and selection alone are better described by the 'House of Cards' approximation. With just two alleles at each locus, the phenotype changes in a similar way: the mean remains close to the optimum, while the variance changes more slowly, and over a wider region. However, there may be substantial cryptic divergence at the underlying loci. With strong selection and many loci, linkage disequilibria are the main cause of changes in genetic variance. Even for strong selection, the infinitesimal model can be closely approximated by assuming a Gaussian distribution of breeding values. Linkage disequilibria can generate a substantial increase in genetic variance, which is concentrated at sharp gradients in trait means.

Alleles↗
PubMed1999

Estimating genetic correlations in natural populations.

Information on the genetic correlation between traits provides fundamental insight into the constraints on the evolutionary process. Estimates of such correlations are conventionally obtained by raising individuals of known relatedness in artificial environments. However, many species are not readily amenable to controlled breeding programmes, and considerable uncertainty exists over the extent to which estimates derived under benign laboratory conditions reflect the properties of populations in natural settings. Here, non-invasive methods that allow the estimation of genetic correlations from phenotypic measurements derived from individuals of unknown relatedness are introduced. Like the conventional approach, these methods demand large sample sizes in order to yield reasonably precise estimates, and special precautions need to be taken to eliminate bias from shared environmental effects. Provided the sample consists of at least 20% or so relatives, informative estimates of the genetic correlation are obtainable with sample sizes of several hundred individuals, particularly if supplemental information on relatedness is available from polymorphic molecular markers.

Animals↗
PubMed2026

Polygenic risk factors for comorbid diagnoses in individuals with substance use disorders: A phenome-wide survival analysis.

OBJECTIVE: Persons with substance use disorders (SUD) often suffer from additional comorbidities. Researchers have explored this overlap via phenome-wide association studies (PheWASs). However, PheWASs are largely cross-sectional, limiting our understanding of whether diagnoses predate the development of an SUD. We characterize whether polygenic scores (PGSs) are associated with time to comorbid diagnoses in electronic health records (EHR) after the first documented SUD diagnosis. METHODS: Using data from All of Us (N&#xa0;=&#xa0;393,596), we explored: (1) whether social determinants of health (SDoHs) are associated with lifetime risk of SUD (N cases&#xa0;=&#xa0;42,568) and (2) within a subset those with a diagnosed SUD and available genetic data SUD (N&#xa0;=&#xa0;21,357), whether PGS for alcohol use disorders, cannabis use disorders, depression, externalizing, posttraumatic stress disorder, and schizophrenia were associated with subsequent diagnoses via a phenome-wide survival analysis. RESULTS: Multiple SDoHs were associated with lifetime SUD diagnosis, with annual household income having the largest overall associations (e.g. <$10&#xa0;K annually vs $100&#xa0;K-$150&#xa0;K annually: OR&#xa0;=&#xa0;4.18; 95% CI&#xa0;=&#xa0;3.92, 4.45). There were 86 phenome-wide significant PGS associations with subsequent diagnoses across various bodily systems. PGSs for alcohol use disorders, posttraumatic stress disorder, and schizophrenia were each associated with time to their respective diagnoses. CONCLUSIONS: Social determinants, especially those related to income, have profound associations with lifetime SUD risk. Additionally, PGSs for psychiatric conditions are associated with multiple post-SUD diagnoses within those with a SUD, suggesting PGS may capture information beyond lifetime risk, including timing and severity of comorbidities related to SUD.

Humans↗
PubMed2026

Unravelling sex differences in the genetic architecture of anxiety.

BACKGROUND: Anxiety disorders show striking sex differences in prevalence, symptoms, and clinical characteristics, shaping how they manifest and are experienced. METHODS: Here, we report the first sex-specific meta-analysis of genome-wide association studies (GWAS) of anxiety, leveraging two of the largest biobank datasets, UK Biobank and All of Us, comprising 85,042 female cases with 196,789 controls and 36,732 male cases with 136,924 controls. Functional annotation, sex-specific polygenic scores (PGS), and genetic correlations were performed to assess genetic differences and functional implications. RESULTS: In females, 21 lead SNPs were significantly associated with anxiety, compared to five in males. Although the genetic correlation between sexes was high, it was significantly different from one, indicating partially distinct genetic architectures. In addition, both the SNP-based observed and liability-scale heritabilities (assuming a 2:1 female-to-male prevalence ratio) were significantly higher in females. Gene-based tests and functional prioritization identified different genes associated with anxiety in females and males. Moreover, genetic correlation analyses revealed stronger associations of female anxiety with attention-deficit/hyperactivity disorder (ADHD) and body mass index (BMI), whereas male anxiety showed stronger correlations with waist-hip-ratio-adjusted BMI. CONCLUSIONS: While the overall genetic architecture of anxiety is largely shared, our findings reveal distinct sex-specific genetic associations and correlations, highlighting the value of analyzing the sexes separately to uncover genetic signals that may be masked in sex-combined samples.

Female↗
PubMed1998

Etiology of Balkan endemic nephropathy: a multifactorial disease?

Balkan endemic nephropathy (BEN) is of great clinical importance in the restricted areas of Bulgaria, Rumania, Croatia, Serbia, Bosnia and Herzegovina. So far, studies on the etiological factors for BEN have not discovered any single environmental causative agent of this puzzling disease. These data reject the possibility of a purely environmental causation of BEN. The pattern of BEN transmission in the risk families is not typical for single gene disorders. Extensive epidemiological and genetic studies disclose characteristics of multifactorial (polygenic) inheritance of BEN. The evidences of 'familial tendency', variation of the risk for BEN depending on the number of sick parents and the degree of relatedness; the development of BEN in individuals from at-risk families who were born in non-endemic areas; the data that disease is not found in the gypsy population and the expressions of 3q25 cytogenetic marker suggest that the genetic factors play an important role as causative factors in BEN development. The possible impact of environmental triggers on individuals genetically predisposed to BEN could be supposed by the following data: the cytogenetic results of the increased frequency of folate sensitive Fra sites, spontaneous or radiation-induced aberrations in several bands in BEN patients, the data from the detailed analysis of breaks in BEN patients and controls that generate structural chromosome aberrations; the occurrence of BEN in immigrants. Genetical epidemiological approaches to etiology and prevention of BEN are proposed. The predisposing genes for BEN could be genes localized in a region between 3q25-3q26; transforming growth factor-beta (TGF-beta), genetic heterogeneity of xenobiotic-metabolizing enzymes; defects in the host's immune system. The predisposing genes for BEN patients with urinary tract tumors could be germline mutations in tumor suppressor genes and acquired somatic mutations in oncogenes.

Balkan Nephropathy↗
PubMed2000

Genetic polymorphism and clinical outcome: identification of individuals at risk of a poor clinical outcome.

Susceptibility and outcome in complex disorders such as asthma and cancer appear to be determined, at least in part, by genetic polymorphism. However, while our ability to identify new allelic variants and study them in case and control populations has greatly improved, considerable difficulties remain in elucidating how many genes determine particular clinical phenotypes. This is because most studies have concentrated on study of single genes in relatively small study groups. The important issues of gene-gene interactions (epistasis) and high-risk subgroups have not yet been adequately addressed. We now describe a general approach, using patients with head and neck cancers as an example. Our purpose is to demonstrate candidate gene selection, statistical approaches, and identification of patient subgroups.

Genetic Predisposition to Disease↗
PubMed1999

Aicardi-Goutières syndrome: monogenic recessive disease, genetically heterogeneous disease, or multifactorial disease?

Aicardi-Goutières syndrome (AGS) is a severe progressive familial encephalopathy, which is usually diagnosed shortly after birth. Using the principle of homozygosity mapping, genome-wide screening of five consanguineous families was performed to search for a homozygous region shared by all affected individuals. A total of 364 markers with an average spacing of 9.9 cM were genotyped, but no homozygous region common to all affected individuals could be found. Regions of homozygosity in affected sibs could only be identified within each family individually. This may reflect genetic heterogeneity, possibly related to clinical heterogeneity, since several syndromes are clinically difficult to distinguish from AGS. Involvement of a small number of genes and/or of an external factor, such as infection, may also explain the absence of a homozygous region common to all affected individuals.

Abnormalities, Multiple↗
PubMed2000

A multivariate analysis of 59 candidate genes in personality traits: the temperament and character inventory.

Cloninger (Cloninger CR. Neurogenetic adaptive mechanisms in alcoholism. Science 1987: 236: 410-416) proposed three basic personality dimensions for temperament: novelty seeking, harm avoidance, and reward dependence. He suggested that novelty seeking primarily utilized dopamine pathways, harm avoidance utilized serotonin pathways, and reward dependence utilized norepinephrine pathways. Subsequently, one additional temperament dimension (persistence) and three character dimensions (cooperativeness, self-directedness, and self-transcendence) were added to form the temperament and character inventory (TCI). We have utilized a previously described multivariate analysis technique (Comings DE, Gade-Andavolu R, Gonzalez N et al. Comparison of the role of dopamine, serotonin, and noradrenergic genes in ADHD, ODD and conduct disorder. Multivariate regression analysis of 20 genes. Clin Genet 2000: 57: 178-196; Comings DD, Gade-Andavolu R, Gonzalez N et al. Multivariate analysis of associations of 42 genes in ADHD, ODD and conduct disorder. Clin Genet 2000: in press) to examine the relative role of 59 candidate genes in the seven TCI traits and test the hypothesis that specific personality traits were associated with specific genes. While there was some tendency for this to be true, a more important trend was the involvement of different ratios of functionally related groups of genes, and of different genotypes of the same genes, for different traits.

Adult↗