ABSTRACT
Genome-wide association studies (GWASs) have focused primarily on populations of European descent, but it is essential that diverse populations become better represented. Increasing diversity among study participants will advance our understanding of genetic architecture in all populations and ensure that genetic research is broadly applicable. To facilitate and promote research in multi-ancestry and admixed cohorts, we outline key methodological considerations and highlight opportunities, challenges, solutions, and areas in need of development. Despite the perception that analyzing genetic data from diverse populations is difficult, it is scientifically and ethically imperative, and there is an expanding analytical toolbox to do it well.
Subject(s)
Genome-Wide Association Study/methods , Genotyping Techniques/methods , Human Genetics/methods , Data Accuracy , Genetic Variation , Genetics, Population/methods , Genetics, Population/standards , Genome-Wide Association Study/standards , Genotyping Techniques/standards , Human Genetics/standards , Humans , PedigreeABSTRACT
BACKGROUND: Women experience major depression and post-traumatic stress disorder (PTSD) approximately twice as often as men. Estrogen is thought to contribute to sex differences in these disorders, and reduced estrogen is also known to be a key driver of menopause symptoms such as hot flashes. Moreover, estrogen is used to treat menopause symptoms. In order to test for potential shared genetic influences between menopause symptoms and psychiatric disorders, we conducted a genome-wide association study (GWAS) of estrogen medication use (as a proxy for menopause symptoms) in the UK Biobank. METHODS: The analysis included 232 993 women aged 39-71 in the UK Biobank. The outcome variable for genetic analyses was estrogen medication use, excluding women using hormonal contraceptives. Trans-ancestry GWAS meta-analyses were conducted along with genetic correlation analyses on the European ancestry GWAS results. Hormone usage was also tested for association with depression and PTSD. RESULTS: GWAS of estrogen medication use (compared to non-use) identified a locus in the TACR3 gene, which was previously linked to hot flashes in menopause [top rs77322567, odds ratio (OR) = 0.78, p = 7.7 × 10-15]. Genetic correlation analyses revealed shared genetic influences on menopause symptoms and depression (rg = 0.231, s.e.= 0.055, p = 2.8 × 10-5). Non-genetic analyses revealed higher psychiatric symptoms scores among women using estrogen medications. CONCLUSIONS: These results suggest that menopause symptoms have a complex genetic etiology which is partially shared with genetic influences on depression. Moreover, the TACR3 gene identified here has direct clinical relevance; antagonists for the neurokinin 3 receptor (coded for by TACR3) are effective treatments for hot flashes.
Subject(s)
Depression , Hot Flashes , Female , Humans , Male , Hot Flashes/genetics , Depression/genetics , Genome-Wide Association Study , Menopause/genetics , Estrogens/therapeutic useABSTRACT
Large-scale reference data sets of human genetic variation are critical for the medical and functional interpretation of DNA sequence changes. Here we describe the aggregation and analysis of high-quality exome (protein-coding region) DNA sequence data for 60,706 individuals of diverse ancestries generated as part of the Exome Aggregation Consortium (ExAC). This catalogue of human genetic diversity contains an average of one variant every eight bases of the exome, and provides direct evidence for the presence of widespread mutational recurrence. We have used this catalogue to calculate objective metrics of pathogenicity for sequence variants, and to identify genes subject to strong selection against various classes of mutation; identifying 3,230 genes with near-complete depletion of predicted protein-truncating variants, with 72% of these genes having no currently established human disease phenotype. Finally, we demonstrate that these data can be used for the efficient filtering of candidate disease-causing variants, and for the discovery of human 'knockout' variants in protein-coding genes.
Subject(s)
Exome/genetics , Genetic Variation/genetics , DNA Mutational Analysis , Datasets as Topic , Humans , Phenotype , Proteome/genetics , Rare Diseases/genetics , Sample SizeABSTRACT
Eating disorders and substance use disorders frequently co-occur. Twin studies reveal shared genetic variance between liabilities to eating disorders and substance use, with the strongest associations between symptoms of bulimia nervosa and problem alcohol use (genetic correlation [rg ], twin-based = 0.23-0.53). We estimated the genetic correlation between eating disorder and substance use and disorder phenotypes using data from genome-wide association studies (GWAS). Four eating disorder phenotypes (anorexia nervosa [AN], AN with binge eating, AN without binge eating, and a bulimia nervosa factor score), and eight substance-use-related phenotypes (drinks per week, alcohol use disorder [AUD], smoking initiation, current smoking, cigarettes per day, nicotine dependence, cannabis initiation, and cannabis use disorder) from eight studies were included. Significant genetic correlations were adjusted for variants associated with major depressive disorder and schizophrenia. Total study sample sizes per phenotype ranged from ~2400 to ~537 000 individuals. We used linkage disequilibrium score regression to calculate single nucleotide polymorphism-based genetic correlations between eating disorder- and substance-use-related phenotypes. Significant positive genetic associations emerged between AUD and AN (rg = 0.18; false discovery rate q = 0.0006), cannabis initiation and AN (rg = 0.23; q < 0.0001), and cannabis initiation and AN with binge eating (rg = 0.27; q = 0.0016). Conversely, significant negative genetic correlations were observed between three nondiagnostic smoking phenotypes (smoking initiation, current smoking, and cigarettes per day) and AN without binge eating (rgs = -0.19 to -0.23; qs < 0.04). The genetic correlation between AUD and AN was no longer significant after co-varying for major depressive disorder loci. The patterns of association between eating disorder- and substance-use-related phenotypes highlights the potentially complex and substance-specific relationships among these behaviors.
Subject(s)
Feeding and Eating Disorders/genetics , Substance-Related Disorders/genetics , Alcoholism/genetics , Depressive Disorder, Major/genetics , Genome-Wide Association Study , Humans , Linkage Disequilibrium , Phenotype , Polymorphism, Single Nucleotide , Risk Factors , Schizophrenia/genetics , Tobacco Use Disorder/geneticsABSTRACT
Schizophrenia is a common disease with a complex aetiology, probably involving multiple and heterogeneous genetic factors. Here, by analysing the exome sequences of 2,536 schizophrenia cases and 2,543 controls, we demonstrate a polygenic burden primarily arising from rare (less than 1 in 10,000), disruptive mutations distributed across many genes. Particularly enriched gene sets include the voltage-gated calcium ion channel and the signalling complex formed by the activity-regulated cytoskeleton-associated scaffold protein (ARC) of the postsynaptic density, sets previously implicated by genome-wide association and copy-number variation studies. Similar to reports in autism, targets of the fragile X mental retardation protein (FMRP, product of FMR1) are enriched for case mutations. No individual gene-based test achieves significance after correction for multiple testing and we do not detect any alleles of moderately low frequency (approximately 0.5 to 1 per cent) and moderately large effect. Taken together, these data suggest that population-based exome sequencing can discover risk alleles and complements established gene-mapping paradigms in neuropsychiatric disease.
Subject(s)
Multifactorial Inheritance/genetics , Mutation/genetics , Schizophrenia/genetics , Autistic Disorder/genetics , Calcium Channels/genetics , Cytoskeletal Proteins/genetics , DNA Copy Number Variations/genetics , Disks Large Homolog 4 Protein , Female , Fragile X Mental Retardation Protein/metabolism , Genome-Wide Association Study , Humans , Intellectual Disability/genetics , Intracellular Signaling Peptides and Proteins/genetics , Male , Membrane Proteins/genetics , Nerve Tissue Proteins/genetics , Receptors, N-Methyl-D-Aspartate/geneticsABSTRACT
PURPOSE OF REVIEW: This review highlights recent research on sex- and gender-related factors in the prevalence, symptom expression, and treatment of PTSD. Further discoveries about the underlying mechanisms of sex and gender effects have the potential to shape innovative directions for research. RECENT FINDINGS: The prevalence of PTSD is substantially higher among women, but women show a modest advantage with respect to treatment response. There is evidence of greater heritability among females. Women are more likely to experience sexual and intimate violence, childhood trauma exposure, and repeated trauma exposures. Specific characteristics of social contexts act as gender-linked risks for PTSD. Among individuals diagnosed with PTSD, men and women are similar in phenotypic expression. Though research has yet to fully account for the factors that explain sex- and gender- related effects on PTSD, emerging research suggests these effects occur across multiple levels. Shared risk factors for trauma exposure and PTSD merit further investigation. Both social and biological contexts merit investigation to understand sex-linked differences in heritability.
Subject(s)
Stress Disorders, Post-Traumatic/genetics , Stress Disorders, Post-Traumatic/psychology , Adverse Childhood Experiences/statistics & numerical data , Domestic Violence/statistics & numerical data , Humans , Prevalence , Risk Factors , Sex Characteristics , Sex Factors , Stress Disorders, Post-Traumatic/therapyABSTRACT
PURPOSE OF REVIEW: The purpose of this review is to contextualize findings from the first 25 years of PTSD genetics research, focusing on the most robust findings and interpreting results in light of principles that have emerged from modern genetics studies. RECENT FINDINGS: Genome-wide association studies (GWAS) encompassing tens of thousands of participants enabled the first molecular genetic heritability and genetic correlation estimates for PTSD in 2017. In 2018, highly promising loci for PTSD were reported, including variants in and near the CAMKV, KANSL1, and TCF4 genes. Twin studies from 25 years ago established that PTSD is genetically influenced and foreshadowed the molecular genetic findings of today. Discoveries that were impossible with smaller studies have been achieved via collaborative/team-science efforts. Most promisingly, individual genomic loci offer entirely novel clues about PTSD etiology, providing the raw material for transformative discoveries, and the future of PTSD research is bright.
Subject(s)
Genetic Research , Genome-Wide Association Study , Stress Disorders, Post-Traumatic/genetics , Genetic Predisposition to Disease , Genomics , HumansABSTRACT
The original version of this article contained an error in the title. The correct title should read "Robust Findings From 25 Years of PTSD Genetics Research" as shown above. The original article has been corrected.
ABSTRACT
Prioritizing missense variants for further experimental investigation is a key challenge in current sequencing studies for exploring complex and Mendelian diseases. A large number of in silico tools have been employed for the task of pathogenicity prediction, including PolyPhen-2, SIFT, FatHMM, MutationTaster-2, MutationAssessor, Combined Annotation Dependent Depletion, LRT, phyloP, and GERP++, as well as optimized methods of combining tool scores, such as Condel and Logit. Due to the wealth of these methods, an important practical question to answer is which of these tools generalize best, that is, correctly predict the pathogenic character of new variants. We here demonstrate in a study of 10 tools on five datasets that such a comparative evaluation of these tools is hindered by two types of circularity: they arise due to (1) the same variants or (2) different variants from the same protein occurring both in the datasets used for training and for evaluation of these tools, which may lead to overly optimistic results. We show that comparative evaluations of predictors that do not address these types of circularity may erroneously conclude that circularity confounded tools are most accurate among all tools, and may even outperform optimized combinations of tools.
Subject(s)
Computational Biology/methods , Mutation, Missense , Software , Datasets as Topic , Humans , Internet , Reproducibility of Results , Web BrowserABSTRACT
OBJECTIVE: Prior investigations consistently indicate that personality pathology is a risk factor for recurrence of major depressive disorder (MDD). Lack of emipircal support, however, for the Diagnostic and Statistical Manual of Mental Disorders (DSM) Fourth Edition organization of Axis II disorders supports the investigation of empirically derived factors of personality pathology as predictors of recurrence. METHOD: A sample of 130 previously depressed emerging adults (80% female; aged 18 to 21 years) were assessed for personality disorder symptoms at baseline. Participants were then followed for 18 months to identify MDD recurrence during the first 2 years of college. RESULTS: Based on a previous factor analysis of DSM personality disorder criteria, eight personality pathology factors were examined as predictors of MDD recurrence. Survival analysis indicated that factors of interpersonal hypersensitivity, antisocial conduct, and social anxiety were associated with increased risk of MDD recurrence. CONCLUSIONS: These findings suggest that an empirically based approach to personality pathology organization may yield useful predictors of MDD recurrence during emerging adulthood.
Subject(s)
Depressive Disorder, Major/diagnosis , Personality Disorders/diagnosis , Adolescent , Comorbidity , Depressive Disorder, Major/prevention & control , Depressive Disorder, Major/psychology , Diagnostic and Statistical Manual of Mental Disorders , Factor Analysis, Statistical , Female , Humans , Male , Personality Assessment/statistics & numerical data , Personality Disorders/prevention & control , Personality Disorders/psychology , Psychometrics/statistics & numerical data , Psychotherapy, Group , Recurrence , Risk Factors , Young AdultABSTRACT
Psychiatric diseases are strongly influenced by genetics, but genetically guided treatments have been slow to develop, and precise molecular mechanisms remain mysterious. Although individual locations in the genome tend to not contribute powerfully to psychiatric disease incidence, genome-wide association studies (GWAS) have now successfully linked hundreds of specific genetic loci to psychiatric disorders [1-3]. Here, building upon results from well-powered GWAS of four phenotypes relevant to psychiatry, we motivate an exploratory workflow leading from GWAS screening, through causal testing in animal models using methods such as optogenetics, to new therapies in human beings. We focus on schizophrenia and the dopamine D2 receptor (DRD2), hot flashes and the neurokinin B receptor (TACR3), cigarette smoking and receptors bound by nicotine (CHRNA5, CHRNA3, CHRNB4), and alcohol use and enzymes that help to break down alcohol (ADH1B, ADH1C, ADH7). A single genomic locus may not powerfully determine disease at the level of the population, but the same locus may nevertheless represent a potent treatment target suitable for population-wide therapeutic approaches.
Subject(s)
Brain Diseases , Receptors, Nicotinic , Humans , Genetic Predisposition to Disease , Genome-Wide Association Study , Genetic Loci , Phenotype , Receptors, Nicotinic/genetics , Polymorphism, Single NucleotideABSTRACT
Females are twice as likely to experience PTSD as compared to males. Although sex differences in prevalence are well-established, little is known about why such sex differences occur. Biological factors that vary with sex, including sex hormone production, may contribute to these differences. Considerable evidence links sex hormones, such as testosterone, to PTSD risk though less is known about the shared genetic underpinnings. The objective of the present study was to test for genetic relationships between testosterone and PTSD. To do so, we used summary statistics from large, publicly available genetic consortia to conduct linkage disequilibrium score regression to estimate the genetic correlations between PTSD and testosterone in males and females, and two-sample, bi-directional Mendelian randomization to examine potential causal relationships of testosterone on PTSD and the reverse. Heritability estimates of testosterone were significantly higher in males (0.17, SE = 0.02) than females (0.11, SE = 0.01; z = 2.46, p = 00.01). The correlation between testosterone and PTSD was negative in males (rg = -0.11, SE = 0.02, p = 6.7 x 10-6), but not significant in females (rg = 0.002, SE = 0.03, p = 0.95). MR analyses found no evidence of a causal effect of testosterone on PTSD or the reverse. Findings are consistent with phenotypic literature suggesting a relationship between testosterone and PTSD that may be sex-specific. This work provides early evidence of a relationship between testosterone and PTSD genotypically and suggests an avenue for future research that will enable a better understanding of disparities in PTSD.
Subject(s)
Stress Disorders, Post-Traumatic , Testosterone , Humans , Stress Disorders, Post-Traumatic/genetics , Stress Disorders, Post-Traumatic/blood , Male , Testosterone/blood , Female , Sex Characteristics , Linkage Disequilibrium , Genetic Predisposition to Disease , Polymorphism, Single Nucleotide , Mendelian Randomization AnalysisABSTRACT
BACKGROUND: The hypothalamic pituitary adrenal (HPA) axis is a system involved in stress and pregnancy regulation, and hair cortisol concentration (HCC) is a promising biomarker of its activity. Assessing factors that influence HCC in the prenatal period is critical to understand whether and how HPA axis (dys-)regulation influences maternal health and child development, particularly in high-risk populations from low- and middle-income countries (LMICs). AIMS: This study aimed at characterizing preconception and pregnancy HCC with respect to multiple sociodemographic, pregnancy-related, and hair-related factors. METHODS: In a sample of N = 2581 pregnant women in Perú, participants from two cohort studies provided a 6â¯cm scalp hair sample at three prenatal timepoints. Each hair sample was cut into two segments of 3â¯cm that represent cortisol secretion at four times: preconception, first-, second- and third trimester of pregnancy. Hair cortisol was extracted using liquid chromatography tandem mass spectrometry (LC-MS/MS). Spearman correlations, paired t-tests, and ANOVA were used to assess differences in log-transformed values of HCC (logHCC) across maternal sociodemographic, pregnancy-related, and hair-related factors. Multivariable linear regressions were used to examine independent associations of HCCs with selected correlates. RESULTS: Mean logHCC values showed an increase across the four prenatal periods. Preconception BMI was consistently associated with HCC in all three trimesters, while difficulty accessing basic foods, education, hair dyeing, and infant sex showed time-specific associations with HCCs. In sensitivity analyses, we detected no substantial segment effects in the associations of HCCs with maternal characteristics. CONCLUSION: This study is the largest to characterize HCC in pregnant women from a LMIC. Our findings provide a foundation for the use of HCC as a biomarker of prenatal HPA axis activity for future studies. This foundation may contribute to finding valid biomarkers of stress-response systems to promote maternal and child health.
Subject(s)
Hair , Hydrocortisone , Hypothalamo-Hypophyseal System , Pituitary-Adrenal System , Humans , Female , Hair/chemistry , Hair/metabolism , Hydrocortisone/analysis , Hydrocortisone/metabolism , Pregnancy , Adult , Hypothalamo-Hypophyseal System/metabolism , Pituitary-Adrenal System/metabolism , Young Adult , Biomarkers/analysis , Biomarkers/metabolism , Cohort Studies , Stress, Psychological/metabolismABSTRACT
Post-traumatic stress disorder (PTSD) genetics are characterized by lower discoverability than most other psychiatric disorders. The contribution to biological understanding from previous genetic studies has thus been limited. We performed a multi-ancestry meta-analysis of genome-wide association studies across 1,222,882 individuals of European ancestry (137,136 cases) and 58,051 admixed individuals with African and Native American ancestry (13,624 cases). We identified 95 genome-wide significant loci (80 new). Convergent multi-omic approaches identified 43 potential causal genes, broadly classified as neurotransmitter and ion channel synaptic modulators (for example, GRIA1, GRM8 and CACNA1E), developmental, axon guidance and transcription factors (for example, FOXP2, EFNA5 and DCC), synaptic structure and function genes (for example, PCLO, NCAM1 and PDE4B) and endocrine or immune regulators (for example, ESR1, TRAF3 and TANK). Additional top genes influence stress, immune, fear and threat-related processes, previously hypothesized to underlie PTSD neurobiology. These findings strengthen our understanding of neurobiological systems relevant to PTSD pathophysiology, while also opening new areas for investigation.
Subject(s)
Genetic Predisposition to Disease , Genome-Wide Association Study , Polymorphism, Single Nucleotide , Stress Disorders, Post-Traumatic , Humans , Stress Disorders, Post-Traumatic/genetics , White People/genetics , Neurobiology , Genetic LociABSTRACT
Functional impairment is one of the most enduring, intractable consequences of psychiatric disorders and is both familial and heritable. Previous studies have suggested that variation in functional impairment can be independent of symptom severity. Here we report the first genome-wide association study (GWAS) of functional impairment in the context of major mental illness. Participants of European-American descent (N = 2,246) were included from three large treatment studies of bipolar disorder (STEP-BD) (N = 765), major depressive disorder (STAR*D) (N = 1091), and schizophrenia (CATIE) (N = 390). At study entry, participants completed the SF-12, a widely used measure of health-related quality of life. We performed a GWAS and pathway analysis of the mental and physical components of health-related quality of life across diagnosis (â¼1.6 million single nucleotide polymorphisms), adjusting for psychiatric symptom severity. Psychiatric symptom severity was a significant predictor of functional impairment, but it accounted for less than one-third of the variance across disorders. After controlling for diagnostic category and symptom severity, the strongest evidence of genetic association was between variants in ADAMTS16 and physical functioning (P = 5.87 × 10(-8) ). Pathway analysis did not indicate significant enrichment after correction for gene clustering and multiple testing. This study illustrates a phenotypic framework for examining genetic contributions to functional impairment across psychiatric disorders.
Subject(s)
Bipolar Disorder/genetics , Depressive Disorder, Major/genetics , Genetic Predisposition to Disease , Genome-Wide Association Study , Resilience, Psychological , Schizophrenia/genetics , ADAM Proteins/genetics , ADAMTS Proteins , Bipolar Disorder/physiopathology , Depressive Disorder, Major/physiopathology , Genetic Loci , Humans , Phenotype , Polymorphism, Single Nucleotide/genetics , Risk Factors , Schizophrenia/physiopathologyABSTRACT
The XXth World Congress of Psychiatric Genetics (WCPG), sponsored by The International Society of Psychiatric Genetics (ISPG) took place in Hamburg, Germany on October 14-18, 2012. Approximately 600 participants gathered to discuss the latest findings in this rapidly advancing field. The following report was written by student travel awardees. Each was assigned sessions as rapporteurs. This manuscript represents topics covered in most, but not all, oral presentations during the conference, and some of the major notable new findings reported at this 2012 WCPG.
Subject(s)
Mental Disorders/genetics , Animals , Brain/pathology , Disease Models, Animal , Drug Discovery , Endophenotypes , Epigenesis, Genetic , Genetic Testing , Genetic Variation , Genome, Human/genetics , Genome-Wide Association Study , Germany , Humans , Inheritance Patterns/genetics , Magnetic Resonance Imaging , Mice , Sequence Analysis, DNAABSTRACT
A new era of human postmortem tissue research has emerged thanks to the development of 'omics technologies that measure genes, proteins, and spatial parameters in unprecedented detail. Also newly possible is the ability to construct polygenic scores, individual-level metrics of genetic risk (also known as polygenic risk scores/PRS), based on genome-wide association studies, GWAS. Here, we report on clinical, educational, and brain gene expression correlates of polygenic scores in ancestrally diverse samples from the Human Brain Collection Core (HBCC). Genotypes from 1418 donors were subjected to quality control filters, imputed, and used to construct polygenic scores. Polygenic scores for schizophrenia predicted schizophrenia status in donors of European ancestry (p = 4.7 × 10-8, 17.2%) and in donors with African ancestry (p = 1.6 × 10-5, 10.4% of phenotypic variance explained). This pattern of higher variance explained among European ancestry samples was also observed for other psychiatric disorders (depression, bipolar disorder, substance use disorders, anxiety disorders) and for height, body mass index, and years of education. For a subset of 223 samples, gene expression from dorsolateral prefrontal cortex (DLPFC) was available through the CommonMind Consortium. In this subgroup, schizophrenia polygenic scores also predicted an aggregate gene expression score for schizophrenia (European ancestry: p = 0.0032, African ancestry: p = 0.15). Overall, polygenic scores performed as expected in ancestrally diverse samples, given historical biases toward use of European ancestry samples and variable predictive power of polygenic scores across phenotypes. The transcriptomic results reported here suggest that inherited schizophrenia genetic risk influences gene expression, even in adulthood. For future research, these and additional polygenic scores are being made available for analyses, and for selecting samples, using postmortem tissue from the Human Brain Collection Core.
Subject(s)
Bipolar Disorder , Schizophrenia , Humans , Genome-Wide Association Study , Schizophrenia/genetics , Bipolar Disorder/genetics , Multifactorial Inheritance , Brain , Genetic Predisposition to Disease/geneticsABSTRACT
The cerebellum contains most of the neurons in the human brain, and exhibits unique modes of development, malformation, and aging. For example, granule cells-the most abundant neuron type-develop unusually late and exhibit unique nuclear morphology. Here, by developing our high-resolution single-cell 3D genome assay Dip-C into population-scale (Pop-C) and virus-enriched (vDip-C) modes, we were able to resolve the first 3D genome structures of single cerebellar cells, create life-spanning 3D genome atlases for both human and mouse, and jointly measure transcriptome and chromatin accessibility during development. We found that while the transcriptome and chromatin accessibility of human granule cells exhibit a characteristic maturation pattern within the first year of postnatal life, 3D genome architecture gradually remodels throughout life into a non-neuronal state with ultra-long-range intra-chromosomal contacts and specific inter-chromosomal contacts. This 3D genome remodeling is conserved in mice, and robust to heterozygous deletion of chromatin remodeling disease-associated genes (Chd8 or Arid1b). Together these results reveal unexpected and evolutionarily-conserved molecular processes underlying the unique development and aging of the mammalian cerebellum.
ABSTRACT
The cerebellum contains most of the neurons in the human brain and exhibits distinctive modes of development and aging. In this work, by developing our single-cell three-dimensional (3D) genome assay-diploid chromosome conformation capture, or Dip-C-into population-scale (Pop-C) and virus-enriched (vDip-C) modes, we resolved the first 3D genome structures of single cerebellar cells, created life-spanning 3D genome atlases for both humans and mice, and jointly measured transcriptome and chromatin accessibility during development. We found that although the transcriptome and chromatin accessibility of cerebellar granule neurons mature in early postnatal life, 3D genome architecture gradually remodels throughout life, establishing ultra-long-range intrachromosomal contacts and specific interchromosomal contacts that are rarely seen in neurons. These results reveal unexpected evolutionarily conserved molecular processes that underlie distinctive features of neural development and aging across the mammalian life span.
Subject(s)
Cellular Senescence , Cerebellum , Chromatin Assembly and Disassembly , Genome , Neurons , Animals , Humans , Mice , Cerebellum/cytology , Cerebellum/growth & development , Neurons/metabolism , Imaging, Three-Dimensional , Single-Cell Analysis , Atlases as TopicABSTRACT
Assessing factors that influence chronic stress biomarkers like hair cortisol concentrations (HCCs) in pregnancy is critical to prevent adverse pregnancy outcomes. Thus, we aimed to identify correlates of HCC preconception and during pregnancy. 2,581 pregnant women participated in the study. HCC was available at four time periods: pre-pregnancy (0-3 months preconception, n = 1,023), and in the first (1-12 weeks, n = 1,734), second (13-24 weeks, n = 1,534), and third (25-36 weeks, n = 835) trimesters. HCC was assessed using liquid chromatography tandem mass spectrometry (LC-MS/MS). Sociodemographic, pregnancy- and hair-related characteristics, and measures of psychosocial stress, were interrogated as potential correlates of HCC. Spearman correlations, paired t-tests, and ANOVA were used to assess differences in log-transformed values of HCC (logHCC) across maternal characteristics. Multivariable linear regressions were used to identify the correlates of HCCs after adjusting for confounders. Mean logHCC values increased across the four prenatal periods (P < 0.001). In multivariable analyses, pre-pregnancy BMI was consistently associated with all HCCs, while gestational age, economic hardship, hair dyeing, and depression, showed time-specific associations with HCC. In conclusion, this study showed evidence of factors influencing HCC levels before and during pregnancy. The most consistent association was seen with pre-pregnancy BMI. Depression was also associated with HCC concentrations.