scholarly journals Heritability of pubertal timing: detailed evaluation of specific milestones in healthy boys and girls

2020 ◽  
Vol 183 (1) ◽  
pp. 13-20
Author(s):  
Alexander S Busch ◽  
Casper P Hagen ◽  
Anders Juul
Keyword(s):  
Genetic Heterogeneity ◽  
Large Scale ◽  
Pubertal Timing ◽  
Association Studies ◽  
Genetic Correlations ◽  
Genetic Data ◽  
Genome Wide Association Studies ◽  
Facial Hair ◽  
Timing Of Menarche ◽  
Relative Category

Objective Pubertal timing is highly heritable. Observational studies were inconclusive concerning a potential sex-specific difference in the parental contribution, while genome-wide association studies highlighted a heterogeneity in the genetic architecture of pubertal timing between sexes. Our objectives were to evaluate the association of timing of pubertal milestones in offspring with parental pubertal timing and to identify the genetic basis of the heterogeneity. Design (1.) Population-based mixed cross-sectional/longitudinal cohort (2006–2014, COPENHAGEN Puberty Study) comprising 1381 healthy Danish children including their parents. (2.) UK Biobank-based summary statistics of genetic data on timing of menarche (n = 188 644), voice-break (n = 154 459) and facial hair (n = 161 470). Methods (1.) Participants underwent clinical examination(s) including blood sampling. Parental pubertal timing was obtained by questionnaire. Timing of milestones were analyzed using SAS-lifereg. (2.) Genetic correlations between pubertal outcomes were estimated using LD Score regression. Genetic heterogeneity was analyzed using METAL. Results We observed significant associations of relative parental pubertal timing with timing of pubertal milestones in offspring of concordant sex, that is, fathers/sons (e.g. testicular enlargement: P = 0.004, β = 0.34 years per relative category) and mothers/daughters (e.g. thelarche: P < 0.001, β = 0.45 years per relative category). Fewer milestones were associated with relative parental pubertal timing in offspring of discordant sex compared to concordant sex. Large-scale genetic data highlight both moderate to strong genetic correlations between timing of menarche, voice-break and facial hair. Out of 434 lead single-nucleotide polymorphisms significantly associated with at least one outcome, 39 exhibited a significant genetic heterogeneity between sexes (P < 1.15 × 10−4). Conclusion Our results highlight a distinct genetic heterogeneity of pubertal timing between sexes.

scholarly journals The Genetic Basis of Delayed Puberty

2017 ◽  
Vol 106 (3) ◽  
pp. 283-291 ◽  
Author(s):  
Sasha R. Howard ◽  
Leo Dunkel
Keyword(s):  
Genetic Control ◽  
Large Scale ◽  
Pubertal Timing ◽  
Association Studies ◽  
Genetic Regulation ◽  
Psychosocial Health ◽  
Delayed Puberty ◽  
Genome Wide Association Studies ◽  
Fetal Life ◽  
Mineral Density

The genetic control of puberty remains an important but mostly unanswered question. Late pubertal timing affects over 2% of adolescents and is associated with adverse health outcomes including short stature, reduced bone mineral density, and compromised psychosocial health. Self-limited delayed puberty (DP) is a highly heritable trait, which often segregates in an autosomal dominant pattern; however, its neuroendocrine pathophysiology and genetic regulation remain unclear. Some insights into the genetic mutations that lead to familial DP have come from sequencing genes known to cause gonadotropin-releasing hormone (GnRH) deficiency, most recently via next-generation sequencing, and others from large-scale genome-wide association studies in the general population. Investigation of the genetic control of DP is complicated by the fact that this trait is not rare and that the phenotype is likely to represent a final common pathway, with a variety of different pathogenic mechanisms affecting the release of the puberty “brake.” These include abnormalities of GnRH neuronal development and function, GnRH receptor and luteinizing hormone/follicle-stimulating hormone abnormalities, metabolic and energy homeostatic derangements, and transcriptional regulation of the hypothalamic-pituitary-gonadal axis. Thus, genetic control of pubertal timing can range from early fetal life via development of the GnRH network to those factors directly influencing the puberty brake during mid-childhood.

scholarly journals Comment on ‘Large-Scale Cognitive GWAS Meta-Analysis Reveals Tissue-Specific Neural Expression and Potential Nootropic Drug Targets’ by Lam et al.

2018 ◽  
Vol 21 (2) ◽  
pp. 84-88 ◽  
Author(s):  
W. David Hill
Keyword(s):  
Genetic Information ◽  
Drug Targets ◽  
Large Scale ◽  
Association Studies ◽  
Meta Analysis ◽  
Genetic Correlations ◽  
Data Sets ◽  
Genome Wide Association Studies ◽  
Nootropic Drug ◽  
Genome Wide

Intelligence and educational attainment are strongly genetically correlated. This relationship can be exploited by Multi-Trait Analysis of GWAS (MTAG) to add power to Genome-wide Association Studies (GWAS) of intelligence. MTAG allows the user to meta-analyze GWASs of different phenotypes, based on their genetic correlations, to identify association's specific to the trait of choice. An MTAG analysis using GWAS data sets on intelligence and education was conducted by Lam et al. (2017). Lam et al. (2017) reported 70 loci that they described as ‘trait specific’ to intelligence. This article examines whether the analysis conducted by Lam et al. (2017) has resulted in genetic information about a phenotype that is more similar to education than intelligence.

scholarly journals Large-scale cognitive GWAS Meta-Analysis Reveals Tissue-Specific Neural Expression and Potential Nootropic Drug Targets

2017 ◽  
Author(s):  
Max Lam ◽  
Joey W. Trampush ◽  
Jin Yu ◽  
Emma Knowles ◽  
Gail Davies ◽  
...  
Keyword(s):  
Cognitive Ability ◽  
Large Scale ◽  
Association Studies ◽  
Genetic Correlations ◽  
Adult Brain ◽  
Specific Gene ◽  
Age At First Birth ◽  
Genome Wide Association Studies ◽  
Tissue Specific ◽  
Brain Expression

AbstractNeurocognitive ability is a fundamental readout of brain function, and cognitive deficits are a critical component of neuropsychiatric disorders, yet neurocognition is poorly understood at the molecular level. In the present report, we present the largest genome-wide association studies (GWAS) of cognitive ability to date (N=107,207), and further enhance signal by combining results with a large-scale GWAS of educational attainment. We identified 70 independent genomic loci associated with cognitive ability, 34 of which were novel. A total of 350 genes were implicated, and this list showed significant enrichment for genes associated with Mendelian disorders with an intellectual disability phenotype. Competitive pathway analysis of gene results implicated the biological process of neurogenesis, as well as the gene targets of two pharmacologic agents: cinnarizine, a T-type calcium channel blocker; and LY97241, a potassium channel inhibitor. Transcriptome-wide analysis revealed that the implicated genes were strongly expressed in neurons, but not astrocytes or oligodendrocytes, and were more strongly associated with fetal brain expression than adult brain expression. Several tissue-specific gene expression relationships to cognitive ability were observed (for example, DAG1 levels in the hippocampus). Finally, we report novel genetic correlations between cognitive ability and disparate phenotypes such as maternal age at first birth and number of children, as well as several autoimmune disorders.

Genetic correlations between subcortical brain volumes and psychiatric disorders

2020 ◽  
Vol 216 (5) ◽  
pp. 280-283
Author(s):  
Kazutaka Ohi ◽  
Takamitsu Shimada ◽  
Yuzuru Kataoka ◽  
Toshiki Yasuyama ◽  
Yasuhiro Kawasaki ◽  
...  
Keyword(s):  
Psychiatric Disorders ◽  
Genetic Variants ◽  
Large Scale ◽  
Association Studies ◽  
Genetic Correlations ◽  
Intracranial Volume ◽  
Genome Wide Association Studies ◽  
Brain Volumes ◽  
Subcortical Brain ◽  
Genome Wide

SummaryPsychiatric disorders as well as subcortical brain volumes are highly heritable. Large-scale genome-wide association studies (GWASs) for these traits have been performed. We investigated the genetic correlations between five psychiatric disorders and the seven subcortical brain volumes and the intracranial volume from large-scale GWASs by linkage disequilibrium score regression. We revealed weak overlaps between the genetic variants associated with psychiatric disorders and subcortical brain and intracranial volumes, such as in schizophrenia and the hippocampus and bipolar disorder and the accumbens. We confirmed shared aetiology and polygenic architecture across the psychiatric disorders and the specific subcortical brain and intracranial volume.

scholarly journals Genetic heterogeneity and subtypes of major depression

2021 ◽  
Author(s):  
Thuy-Dung Nguyen ◽  
Arvid Harder ◽  
Ying Xiong ◽  
Kaarina Kowalec ◽  
Sara Hägg ◽  
...  
Keyword(s):  
Major Depression ◽  
Genetic Heterogeneity ◽  
Association Studies ◽  
Age At Onset ◽  
Genetic Correlations ◽  
Genome Wide Association Studies ◽  
Atypical Symptoms ◽  
Specific Effects ◽  
Phenotypic Complexity ◽  
Comparison Groups

ABSTRACTBackgroundMajor depression (MD) is a heterogeneous disorder; however, the extent to which genetic factors distinguish MD patient subgroups (genetic heterogeneity) remains uncertain. This study sought evidence for genetic heterogeneity in MD.MethodsUsing UK Biobank cohort, the authors defined 16 MD subtypes within eight comparison groups (vegetative symptoms, symptom severity, comorbid anxiety disorder, age at onset, recurrence, suicidality, impairment and postpartum depression; N∼3,000-47,000). To compare genetic architecture of these subtypes, subtype-specific genome-wide association studies were performed to estimate SNP-heritability, and genetic correlations within subtype comparison and with other related disorders or traits.ResultsMD subtypes were divergent in their SNP-heritability, and genetic correlations both within subtype comparisons and with other related disorders/traits. Three subtype comparisons (age at onset, suicidality, and impairment) showed significant differences in SNP-heritability; while genetic correlations within subtypes comparisons ranged from 0.55 to 0.86, suggesting genetic profiles are only partially shared among MD subtypes. Furthermore, subtypes that are more clinically challenging, e.g., early-onset, recurrent, suicidal, more severely impaired, had stronger genetic correlations with other psychiatric disorders. MD with atypical features showed a positive genetic correlation (+0.40) with BMI while a negative correlation (−0.09) was found in those with non-atypical symptoms. Novel genomic loci with subtype-specific effects were identified.ConclusionsThese results provide the most comprehensive evidence to date for genetic heterogeneity within MD, and suggest that the phenotypic complexity of MD can be effectively reduced by studying the subtypes which share partially distinct etiologies.

scholarly journals The genetic etiology of childhood insomnia: Longitudinal gene-brain-behavior associations in the ABCD study

2020 ◽  
Author(s):  
Leanna M. Hernandez ◽  
Minsoo Kim ◽  
Cristian Hernandez ◽  
Wesley Thompson ◽  
Chun Chieh Fan ◽  
...  
Keyword(s):  
Sleep Disturbances ◽  
Large Scale ◽  
Sleep Problems ◽  
Association Studies ◽  
Genetic Correlations ◽  
Externalizing Disorders ◽  
Risk Scores ◽  
Genome Wide Association Studies ◽  
Brain Surface ◽  
Brain Behavior

AbstractChildhood sleep problems are common and frequently comorbid with neurodevelopmental, psychiatric disorders. However, little is known about the genetic contributions to sleep-related traits in childhood, their potential relationship with brain development and psychiatric outcomes, or their association with adult sleep disturbance. Using data from the Adolescent Brain and Cognitive Development study, we performed a comprehensive characterization of the genetic and phenotypic relationships between childhood sleep disturbances (SDs; insomnia, arousal, breathing, somnolence, hyperhidrosis, sleep-wake transitions), global and regional measures of brain structure, and multiple dimensions of psychiatric symptomology in 9-10-year-old youth (discovery/replication N=4,428). Among the six SDs assessed, only insomnia showed significant SNP-based heritability (h2=0.15) and had replicable associations with smaller brain surface area (SA). Furthermore, insomnia showed significant positive phenotypic and genetic correlations with externalizing disorders (e.g., attention-deficit/hyperactivity disorder [ADHD]). Polygenic risk scores (PRS) calculated from genome-wide association studies (GWAS) of ADHD predicted insomnia and externalizing symptoms longitudinally, as well as decreased SA at baseline. In contrast, PRS trained using the largest adult insomnia GWAS did not predict childhood insomnia. Together, these findings demonstrate a distinct genetic architecture between childhood and adult SD, and indicate that childhood insomnia should be considered along the dimensional axis of ADHD and externalizing traits. These results highlight the importance of developmental context when interpreting gene-brain-behavior relationships and underscore the need for further large-scale genetic investigations of psychiatric phenotypes in pediatric populations.

scholarly journals Heterogeneity and Polygenicity in Psychiatric Disorders: A Genome-Wide Perspective

2020 ◽  
Vol 4 ◽  
pp. 247054702092484 ◽  
Author(s):  
Frank R. Wendt ◽  
Gita A. Pathak ◽  
Daniel S. Tylee ◽  
Aranyak Goswami ◽  
Renato Polimanti
Keyword(s):  
Psychiatric Disorders ◽  
Large Scale ◽  
Association Studies ◽  
Genetic Data ◽  
Autism Spectrum ◽  
Genome Wide Association Studies ◽  
Compulsive Disorder ◽  
Genome Wide ◽  
A Genome ◽  
Chronic Tic Disorder

Genome-wide association studies (GWAS) have been performed for many psychiatric disorders and revealed a complex polygenic architecture linking mental and physical health phenotypes. Psychiatric diagnoses are often heterogeneous, and several layers of trait heterogeneity may contribute to detection of genetic risks per disorder or across multiple disorders. In this review, we discuss these heterogeneities and their consequences on the discovery of risk loci using large-scale genetic data. We primarily highlight the ways in which sex and diagnostic complexity contribute to risk locus discovery in schizophrenia, bipolar disorder, attention deficit hyperactivity disorder, autism spectrum disorder, posttraumatic stress disorder, major depressive disorder, obsessive-compulsive disorder, Tourette’s syndrome and chronic tic disorder, anxiety disorders, suicidality, feeding and eating disorders, and substance use disorders. Genetic data also have facilitated discovery of clinically relevant subphenotypes also described here. Collectively, GWAS of psychiatric disorders revealed that the understanding of heterogeneity, polygenicity, and pleiotropy is critical to translate genetic findings into treatment strategies.

scholarly journals Investigation of convergent and divergent genetic influences underlying schizophrenia and alcohol use disorder

2021 ◽  
pp. 1-9
Author(s):  
Emma C. Johnson ◽  
Manav Kapoor ◽  
Alexander S. Hatoum ◽  
Hang Zhou ◽  
Renato Polimanti ◽  
...  
Keyword(s):  
Alcohol Use ◽  
Alcohol Use Disorder ◽  
Large Scale ◽  
Association Studies ◽  
Genetic Correlations ◽  
Genome Wide Association Studies ◽  
Nucleotide Polymorphisms ◽  
Genetic Covariance ◽  
Specific Effects ◽  
Genome Wide

Abstract Background Alcohol use disorder (AUD) and schizophrenia (SCZ) frequently co-occur, and large-scale genome-wide association studies (GWAS) have identified significant genetic correlations between these disorders. Methods We used the largest published GWAS for AUD (total cases = 77 822) and SCZ (total cases = 46 827) to identify genetic variants that influence both disorders (with either the same or opposite direction of effect) and those that are disorder specific. Results We identified 55 independent genome-wide significant single nucleotide polymorphisms with the same direction of effect on AUD and SCZ, 8 with robust effects in opposite directions, and 98 with disorder-specific effects. We also found evidence for 12 genes whose pleiotropic associations with AUD and SCZ are consistent with mediation via gene expression in the prefrontal cortex. The genetic covariance between AUD and SCZ was concentrated in genomic regions functional in brain tissues (p = 0.001). Conclusions Our findings provide further evidence that SCZ shares meaningful genetic overlap with AUD.

scholarly journals A Large-Scale Genetic Correlation Scan Between Intelligence and Brain Imaging Phenotypes

2020 ◽  
Vol 30 (7) ◽  
pp. 4197-4203
Author(s):  
Shiqiang Cheng ◽  
Cuiyan Wu ◽  
Xin Qi ◽  
Li Liu ◽  
Mei Ma ◽  
...  
Keyword(s):  
Brain Imaging ◽  
Large Scale ◽  
Association Studies ◽  
Pearson Correlation ◽  
Genetic Correlations ◽  
Correlation Coefficients ◽  
Functional Brain Imaging ◽  
Genome Wide Association Studies ◽  
Uk Biobank ◽  
Individual Level

Abstract Limited efforts have been paid to evaluate the potential relationships between structural and functional brain imaging and intelligence until now. We performed a two-stage analysis to systematically explore the relationships between 3144 brain image-derived phenotypes (IDPs) and intelligence. First, by integrating genome-wide association studies (GWAS) summaries data of brain IDPs and two GWAS summary datasets of intelligence, we systematically scanned the relationship between each of the 3144 brain IDPs and intelligence through linkage disequilibrium score regression (LDSC) analysis. Second, using the individual-level genotype and intelligence data of 160 124 subjects derived from UK Biobank datasets, polygenetic risk scoring (PRS) analysis was performed to replicate the common significant associations of the first stage. In the first stage, LDSC identified 6 and 2 significant brain IDPs significantly associated with intelligence dataset1 and dataset2, respectively. It is interesting that NET100_0624 showed genetic correlations with intelligence in the two datasets of intelligence. After adjusted for age and sex as the covariates, NET100_0624 (P = 5.26 × 10−20, Pearson correlation coefficients = −0.02) appeared to be associated with intelligence by PRS analysis of UK Biobank samples. Our findings may help to understand the genetic mechanisms of the effects of brain structure and function on the development of intelligence.

166 Livestock Resiliency: Concepts and Approaches

2021 ◽  
Vol 99 (Supplement_3) ◽  
pp. 89-90
Author(s):  
Christine F Baes ◽  
Filippo Miglior ◽  
Flavio S Schenkel ◽  
Ellen Goddard ◽  
Gerrit Kistemaker ◽  
...  
Keyword(s):  
Genomic Selection ◽  
Large Scale ◽  
Association Studies ◽  
Genetic Correlations ◽  
Performance Testing ◽  
Breeding Value ◽  
Estimation Methods ◽  
Genome Wide Association Studies ◽  
Breeding Programs ◽  
Fertility Traits

Abstract Genetic improvement of health, welfare, efficiency, and fertility traits is challenging due to expensive and fuzzy phenotypes, the polygenic nature of traits, antagonistic genetic correlations to production traits and low heritabilities. Nevertheless, many organizations have introduced large-scale genetic evaluations for such traits in routine selection indexes. Medium and high-density arrays can be applied in genomic selection strategies to improve breeding value accuracy, and also in genome-wide association studies (GWAS) to identify causative mutations responsible for economically important traits. Genomic information is particularly helpful when traits have low heritability. The objective here is to provide a framework for including health, welfare, efficiency, and fertility traits taken from large-scale genetic and genomic analyses and identifying areas of potential improvement in terms of trait definition and performance testing. General tendencies between trait groups confirmed that a number of moderate unfavourable correlations (+/-0.20 or higher) exist between economically important trait complexes and health, welfare, and fertility traits. A number of trait complexes were identified in which “closer-to-biology” phenotypes could provide clear improvements to routine genetic and genomic selection programs. Here we outline development of these phenotypes and describe their collection. While conventional variance component estimation methods have underpinned the genomic component of some traits of economic interest, performance testing for health, welfare, efficiency, and fertility traits remains an elusive goal for breeding programs. Although our results are encouraging, there is much to be done in terms of trait definition and obtaining better measures of physiological parameters for wide-scale application in breeding programs. Close collaboration between veterinarians, physiologists, and geneticists is necessary to attain meaningful advancement in such areas. We would like to acknowledge the support and funding from all national and international partners involved in the RDGP project through the Large Scale Applied Research Project program from Genome Canada

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