ABSTRACT
Family history is the standard indirect measure of inherited susceptibility in clinical care, whereas polygenic risk scores (PRSs) have more recently demonstrated potential for more directly capturing genetic risk in many diseases. Few studies have systematically compared how these overlap and complement each other across common diseases. Within FinnGen (N = 306,418), we leverage family relationships, up to 50 years of nationwide registries, and genome-wide genotyping to examine the interplay of family history and genome-wide PRSs. We explore the dynamic for three types of family history across 24 common diseases: first- and second-degree family history and parental causes of death. Covering a large proportion of the burden of non-communicable diseases in adults, we show that family history and PRS are independent and not interchangeable measures, but instead provide complementary information on inherited disease susceptibility. The PRSs explained on average 10% of the effect of first-degree family history, and first-degree family history 3% of PRSs, and PRS effects were independent of both early- and late-onset family history. The PRS stratified the risk similarly in individuals with and without family history. In most diseases, including coronary artery disease, glaucoma, and type 2 diabetes, a positive family history with a high PRS was associated with a considerably elevated risk, whereas a low PRS compensated completely for the risk implied by positive family history. This study provides a catalogue of risk estimates for both family history of disease and PRSs and highlights opportunities for a more comprehensive way of assessing inherited disease risk across common diseases.
Subject(s)
Diabetes Mellitus, Type 2 , Genome-Wide Association Study , Adult , Humans , Diabetes Mellitus, Type 2/genetics , Multifactorial Inheritance/genetics , Genetic Predisposition to Disease , Medical History Taking , Risk FactorsABSTRACT
Lipidomic data often exhibit missing data points, which can be categorized as missing completely at random (MCAR), missing at random, or missing not at random (MNAR). In order to utilize statistical methods that require complete datasets or to improve the identification of potential effects in statistical comparisons, imputation techniques can be employed. In this study, we investigate commonly used methods such as zero, half-minimum, mean, and median imputation, as well as more advanced techniques such as k-nearest neighbor and random forest imputation. We employ a combination of simulation-based approaches and application to real datasets to assess the performance and effectiveness of these methods. Shotgun lipidomics datasets exhibit high correlations and missing values, often due to low analyte abundance, characterized as MNAR. In this context, k-nearest neighbor approaches based on correlation and truncated normal distributions demonstrate best performance. Importantly, both methods can effectively impute missing values independent of the type of missingness, the determination of which is nearly impossible in practice. The imputation methods still control the type I error rate.
Subject(s)
Lipidomics , Lipidomics/methods , Humans , Algorithms , Lipids/analysis , Data Interpretation, StatisticalABSTRACT
BACKGROUND: Hereditary factors, including single genetic variants and family history, can be used for targeting colorectal cancer (CRC) screening, but limited data exist on the impact of polygenic risk scores (PRS) on risk-based CRC screening. METHODS: Using longitudinal health and genomics data on 453,733 Finnish individuals including 8801 CRC cases, we estimated the impact of a genome-wide CRC PRS on CRC screening initiation age through population-calibrated incidence estimation over the life course in men and women. RESULTS: Compared to the cumulative incidence of CRC at age 60 in Finland (the current age for starting screening in Finland), a comparable cumulative incidence was reached 5 and 11 years earlier in persons with high PRS (80-99% and >99%, respectively), while those with a low PRS (< 20%) reached comparable incidence 7 years later. The PRS was associated with increased risk of post-colonoscopy CRC after negative colonoscopy (hazard ratio 1.76 per PRS SD, 95% CI 1.54-2.01). Moreover, the PRS predicted colorectal adenoma incidence and improved incident CRC risk prediction over non-genetic risk factors. CONCLUSIONS: Our findings demonstrate that a CRC PRS can be used for risk stratification of CRC, with further research needed to optimally integrate the PRS into risk-based screening.
Subject(s)
Colorectal Neoplasms , Genetic Risk Score , Male , Humans , Female , Middle Aged , Early Detection of Cancer , Colorectal Neoplasms/diagnosis , Colorectal Neoplasms/epidemiology , Colorectal Neoplasms/genetics , Risk , Colonoscopy , Risk FactorsABSTRACT
Susceptibility to schizophrenia is inversely correlated with general cognitive ability at both the phenotypic and the genetic level. Paradoxically, a modest but consistent positive genetic correlation has been reported between schizophrenia and educational attainment, despite the strong positive genetic correlation between cognitive ability and educational attainment. Here we leverage published genome-wide association studies (GWASs) in cognitive ability, education, and schizophrenia to parse biological mechanisms underlying these results. Association analysis based on subsets (ASSET), a pleiotropic meta-analytic technique, allowed jointly associated loci to be identified and characterized. Specifically, we identified subsets of variants associated in the expected ("concordant") direction across all three phenotypes (i.e., greater risk for schizophrenia, lower cognitive ability, and lower educational attainment); these were contrasted with variants that demonstrated the counterintuitive ("discordant") relationship between education and schizophrenia (i.e., greater risk for schizophrenia and higher educational attainment). ASSET analysis revealed 235 independent loci associated with cognitive ability, education, and/or schizophrenia at p < 5 × 10-8. Pleiotropic analysis successfully identified more than 100 loci that were not significant in the input GWASs. Many of these have been validated by larger, more recent single-phenotype GWASs. Leveraging the joint genetic correlations of cognitive ability, education, and schizophrenia, we were able to dissociate two distinct biological mechanisms-early neurodevelopmental pathways that characterize concordant allelic variation and adulthood synaptic pruning pathways-that were linked to the paradoxical positive genetic association between education and schizophrenia. Furthermore, genetic correlation analyses revealed that these mechanisms contribute not only to the etiopathogenesis of schizophrenia but also to the broader biological dimensions implicated in both general health outcomes and psychiatric illness.
Subject(s)
Cognition Disorders/physiopathology , Cognition/physiology , Educational Status , Neurodevelopmental Disorders/etiology , Polymorphism, Single Nucleotide , Schizophrenia/physiopathology , Synaptic Transmission , Adult , Genetic Predisposition to Disease , Genome-Wide Association Study , Humans , Neurodevelopmental Disorders/pathologyABSTRACT
Hill (Twin Research and Human Genetics, Vol. 21, 2018, 84-88) presented a critique of our recently published paper in Cell Reports entitled 'Large-Scale Cognitive GWAS Meta-Analysis Reveals Tissue-Specific Neural Expression and Potential Nootropic Drug Targets' (Lam et al., Cell Reports, Vol. 21, 2017, 2597-2613). Specifically, Hill offered several interrelated comments suggesting potential problems with our use of a new analytic method called Multi-Trait Analysis of GWAS (MTAG) (Turley et al., Nature Genetics, Vol. 50, 2018, 229-237). In this brief article, we respond to each of these concerns. Using empirical data, we conclude that our MTAG results do not suffer from 'inflation in the FDR [false discovery rate]', as suggested by Hill (Twin Research and Human Genetics, Vol. 21, 2018, 84-88), and are not 'more relevant to the genetic contributions to education than they are to the genetic contributions to intelligence'.
Subject(s)
Genome-Wide Association Study , Nootropic Agents , Cognition , Genetic Predisposition to Disease , Humans , Polymorphism, Single NucleotideABSTRACT
Variants in the growth factor receptor-bound protein 10 (GRB10) gene were in a GWAS meta-analysis associated with reduced glucose-stimulated insulin secretion and increased risk of type 2 diabetes (T2D) if inherited from the father, but inexplicably reduced fasting glucose when inherited from the mother. GRB10 is a negative regulator of insulin signaling and imprinted in a parent-of-origin fashion in different tissues. GRB10 knock-down in human pancreatic islets showed reduced insulin and glucagon secretion, which together with changes in insulin sensitivity may explain the paradoxical reduction of glucose despite a decrease in insulin secretion. Together, these findings suggest that tissue-specific methylation and possibly imprinting of GRB10 can influence glucose metabolism and contribute to T2D pathogenesis. The data also emphasize the need in genetic studies to consider whether risk alleles are inherited from the mother or the father.
Subject(s)
GRB10 Adaptor Protein/genetics , GRB10 Adaptor Protein/metabolism , Islets of Langerhans/metabolism , Alleles , Diabetes Mellitus, Type 2 , Fasting/metabolism , Genome-Wide Association Study/methods , Glucose/genetics , Glucose/metabolism , Humans , Insulin/genetics , Insulin/metabolism , Insulin Resistance/genetics , Male , Middle Aged , Polymorphism, Single Nucleotide/genetics , Receptor, Insulin/genetics , Receptor, Insulin/metabolism , Signal Transduction/geneticsABSTRACT
Variation in plasma levels of cortisol, an essential hormone in the stress response, is associated in population-based studies with cardio-metabolic, inflammatory and neuro-cognitive traits and diseases. Heritability of plasma cortisol is estimated at 30-60% but no common genetic contribution has been identified. The CORtisol NETwork (CORNET) consortium undertook genome wide association meta-analysis for plasma cortisol in 12,597 Caucasian participants, replicated in 2,795 participants. The results indicate that <1% of variance in plasma cortisol is accounted for by genetic variation in a single region of chromosome 14. This locus spans SERPINA6, encoding corticosteroid binding globulin (CBG, the major cortisol-binding protein in plasma), and SERPINA1, encoding α1-antitrypsin (which inhibits cleavage of the reactive centre loop that releases cortisol from CBG). Three partially independent signals were identified within the region, represented by common SNPs; detailed biochemical investigation in a nested sub-cohort showed all these SNPs were associated with variation in total cortisol binding activity in plasma, but some variants influenced total CBG concentrations while the top hit (rs12589136) influenced the immunoreactivity of the reactive centre loop of CBG. Exome chip and 1000 Genomes imputation analysis of this locus in the CROATIA-Korcula cohort identified missense mutations in SERPINA6 and SERPINA1 that did not account for the effects of common variants. These findings reveal a novel common genetic source of variation in binding of cortisol by CBG, and reinforce the key role of CBG in determining plasma cortisol levels. In turn this genetic variation may contribute to cortisol-associated degenerative diseases.
Subject(s)
Genome-Wide Association Study , Hydrocortisone/blood , Transcortin/genetics , alpha 1-Antitrypsin/genetics , Adolescent , Adult , Aged , Aged, 80 and over , Cohort Studies , Exome/genetics , Female , Humans , Male , Middle Aged , Mutation , Polymorphism, Single Nucleotide/genetics , Protein Binding , Transcortin/metabolism , alpha 1-Antitrypsin/metabolismABSTRACT
The scientific advances in the past few years have enabled individualized prevention and treatment of diseases on the basis of genome-wide information. For example, dozens of genomic regions affecting the risk for coronary artery disease have been identified. Both Finnish and international longitudinal studies show that the risk assessment of coronary artery disease can be significantly improved if the estimate is based both on the newly discovered hereditary risk factors and the long-recognized traditional risk factors, e.g. age, gender, smoking, blood pressure, and serum lipid levels. In this review, by using coronary artery disease as an example, we present recent research aiming at enhancing the use of genome information in combination with traditional risk factors for the assessment of the risk for common disease of public health importance. We introduce the KardioKompassi tool, developed by us, which comprehensively utilizes the genetic profile of an individual in combination with conventional health information to assess the risk for coronary artery disease. We also discuss the prospects and opportunities provided by the newly developed next-generation risk prediction tools to promote health."
Subject(s)
Coronary Artery Disease/genetics , Genetic Testing/methods , Genomics , Finland , Humans , Precision Medicine , Risk Assessment , Risk FactorsABSTRACT
Little is known about genes regulating male puberty. Further, while many identified pubertal timing variants associate with age at menarche, a late manifestation of puberty, and body mass, little is known about these variants' relationship to pubertal initiation or tempo. To address these questions, we performed genome-wide association meta-analysis in over 11 000 European samples with data on early pubertal traits, male genital and female breast development, measured by the Tanner scale. We report the first genome-wide significant locus for male sexual development upstream of myocardin-like 2 (MKL2) (P = 8.9 × 10(-9)), a menarche locus tagging a developmental pathway linking earlier puberty with reduced pubertal growth (P = 4.6 × 10(-5)) and short adult stature (p = 7.5 × 10(-6)) in both males and females. Furthermore, our results indicate that a proportion of menarche loci are important for pubertal initiation in both sexes. Consistent with epidemiological correlations between increased prepubertal body mass and earlier pubertal timing in girls, body mass index (BMI)-increasing alleles correlated with earlier breast development. In boys, some BMI-increasing alleles associated with earlier, and others with delayed, sexual development; these genetic results mimic the controversy in epidemiological studies, some of which show opposing correlations between prepubertal BMI and male puberty. Our results contribute to our understanding of the pubertal initiation program in both sexes and indicate that although mechanisms regulating pubertal onset in males and females may largely be shared, the relationship between body mass and pubertal timing in boys may be complex and requires further genetic studies.
Subject(s)
Body Mass Index , Genetic Loci , Menarche/physiology , Puberty/genetics , Sexual Maturation/genetics , Adiposity/genetics , Adolescent , Breast/growth & development , Child , Chromosomes, Human, Pair 16 , Female , Genitalia, Male/growth & development , Genome-Wide Association Study , Genotype , Humans , Male , Menarche/genetics , Polymorphism, Single Nucleotide , Sex Factors , Transcription Factors/genetics , White PeopleABSTRACT
BACKGROUND: The cardiac sodium channel Nav 1.5, encoded by the gene SCN5A, is associated with a wide spectrum of hereditary arrhythmias. The gain-of-function mutation p.I141V in SCN5A was identified in a large multigenerational family with exercise-induced polymorphic ventricular arrhythmias. The purpose of this study was to evaluate the molecular and clinical effects of flecainide administration on patients with this syndrome. METHODS: Eleven p.I141V carriers who exhibited frequent multiformic premature ventricular complexes (PVCs) during exercise were subjected to exercise stress tests, both before and after intravenous infusion of 2 mg/kg flecainide. The in vitro effects of flecainide were evaluated using the patch-clamp technique with HEK293 cells expressing the Nav 1.5 channel. RESULTS: The flecainide treatment significantly reduced the frequency of PVCs during and after exercise. Next, the sensitivity of the p.I141V mutant channel to flecainide was compared to that of the wild type channel. Perfusion of flecainide inhibited the peak and window currents in both groups. CONCLUSION: The clinical investigations of the affected patients, as well as the molecular and pharmacological characterization of the SCN5A p.I141V mutation, provide new evidence supporting the association of this mutation with exercise-induced polymorphic ventricular arrhythmias. These data also demonstrate that flecainide may serve as an effective treatment for the defect in Nav 1.5 that leads to an increased sodium window current.
Subject(s)
Anti-Arrhythmia Agents/therapeutic use , Flecainide/therapeutic use , NAV1.5 Voltage-Gated Sodium Channel/genetics , Ventricular Premature Complexes/drug therapy , Adult , Aged , Electrocardiography , Exercise Test , Female , HEK293 Cells , Humans , Male , Middle Aged , Mutation , Patch-Clamp TechniquesABSTRACT
Although genome-wide association studies (GWAS) have identified hundreds of complex trait loci, the pathomechanisms of most remain elusive. Studying the genetics of risk factors predisposing to disease is an attractive approach to identify targets for functional studies. Intracranial aneurysms (IA) are rupture-prone pouches at cerebral artery branching sites. IA is a complex disease for which GWAS have identified five loci with strong association and a further 14 loci with suggestive association. To decipher potential underlying disease mechanisms, we tested whether there are IA loci that convey their effect through elevating blood pressure (BP), a strong risk factor of IA. We performed a meta-analysis of four population-based Finnish cohorts (n(FIN)â = â11 266) not selected for IA, to assess the association of previously identified IA candidate loci (n â=â 19) with BP. We defined systolic BP (SBP), diastolic BP, mean arterial pressure, and pulse pressure as quantitative outcome variables. The most significant result was further tested for association in the ICBP-GWAS cohort of 200 000 individuals. We found that the suggestive IA locus at 5q23.2 in PRDM6 was significantly associated with SBP in individuals of European descent (p(FIN) â=â 3.01E-05, p(ICBP-GWAS) â= â0.0007, p(ALL)â = â8.13E-07). The risk allele of IA was associated with higher SBP. PRDM6 encodes a protein predominantly expressed in vascular smooth muscle cells. Our study connects a complex disease (IA) locus with a common risk factor for the disease (SBP). We hypothesize that common variants in PRDM6 can contribute to altered vascular wall structure, hence increasing SBP and predisposing to IA. True positive associations often fail to reach genome-wide significance in GWAS. Our findings show that analysis of traditional risk factors as intermediate phenotypes is an effective tool for deciphering hidden heritability. Further, we demonstrate that common disease loci identified in a population isolate may bear wider significance.
Subject(s)
Blood Pressure , Genome-Wide Association Study , Intracranial Aneurysm/genetics , Zinc Fingers/genetics , Adult , Blood Pressure/genetics , Chromosomes, Human, Pair 5/genetics , Cohort Studies , Female , Finland , Genetic Predisposition to Disease , Humans , Male , Middle Aged , Muscle Proteins/genetics , Myocytes, Smooth Muscle/metabolism , Polymorphism, Single Nucleotide , Risk Factors , Transcription Factors/geneticsABSTRACT
Cognitive deficits and reduced educational achievement are common in psychiatric illness; understanding the genetic basis of cognitive and educational deficits may be informative about the etiology of psychiatric disorders. A recent, large genome-wide association study (GWAS) reported a genome-wide significant locus for years of education, which subsequently demonstrated association to general cognitive ability ("g") in overlapping cohorts. The current study was designed to test whether GWAS hits for educational attainment are involved in general cognitive ability in an independent, large-scale collection of cohorts. Using cohorts in the Cognitive Genomics Consortium (COGENT; up to 20,495 healthy individuals), we examined the relationship between g and variants associated with educational attainment. We next conducted meta-analyses with 24,189 individuals with neurocognitive data from the educational attainment studies, and then with 53,188 largely independent individuals from a recent GWAS of cognition. A SNP (rs1906252) located at chromosome 6q16.1, previously associated with years of schooling, was significantly associated with g (P = 1.47 × 10(-4) ) in COGENT. The first joint analysis of 43,381 non-overlapping individuals for this a priori-designated locus was strongly significant (P = 4.94 × 10(-7) ), and the second joint analysis of 68,159 non-overlapping individuals was even more robust (P = 1.65 × 10(-9) ). These results provide independent replication, in a large-scale dataset, of a genetic locus associated with cognitive function and education. As sample sizes grow, cognitive GWAS will identify increasing numbers of associated loci, as has been accomplished in other polygenic quantitative traits, which may be relevant to psychiatric illness.
Subject(s)
Cognition Disorders/genetics , Cognition/physiology , Genetic Predisposition to Disease , Polymorphism, Single Nucleotide/genetics , Adult , Aged , Female , Genetic Loci , Genome-Wide Association Study , Humans , Male , Middle AgedABSTRACT
BACKGROUND: Estimates of the heritability of plasma fibrinogen concentration, an established predictor of cardiovascular disease, range from 34% to 50%. Genetic variants so far identified by genome-wide association studies explain only a small proportion (<2%) of its variation. METHODS AND RESULTS: We conducted a meta-analysis of 28 genome-wide association studies including >90 000 subjects of European ancestry, the first genome-wide association meta-analysis of fibrinogen levels in 7 studies in blacks totaling 8289 samples, and a genome-wide association study in Hispanics totaling 1366 samples. Evaluation for association of single-nucleotide polymorphisms with clinical outcomes included a total of 40 695 cases and 85 582 controls for coronary artery disease, 4752 cases and 24 030 controls for stroke, and 3208 cases and 46 167 controls for venous thromboembolism. Overall, we identified 24 genome-wide significant (P<5×10(-8)) independent signals in 23 loci, including 15 novel associations, together accounting for 3.7% of plasma fibrinogen variation. Gene-set enrichment analysis highlighted key roles in fibrinogen regulation for the 3 structural fibrinogen genes and pathways related to inflammation, adipocytokines, and thyrotrophin-releasing hormone signaling. Whereas lead single-nucleotide polymorphisms in a few loci were significantly associated with coronary artery disease, the combined effect of all 24 fibrinogen-associated lead single-nucleotide polymorphisms was not significant for coronary artery disease, stroke, or venous thromboembolism. CONCLUSIONS: We identify 23 robustly associated fibrinogen loci, 15 of which are new. Clinical outcome analysis of these loci does not support a causal relationship between circulating levels of fibrinogen and coronary artery disease, stroke, or venous thromboembolism.
Subject(s)
Cardiovascular Diseases/ethnology , Cardiovascular Diseases/genetics , Fibrinogen/genetics , Fibrinogen/metabolism , Genetic Loci/genetics , Genome-Wide Association Study , Adolescent , Adult , Aged , Aged, 80 and over , Black People/genetics , Black People/statistics & numerical data , Cardiovascular Diseases/metabolism , Coronary Artery Disease/ethnology , Coronary Artery Disease/genetics , Coronary Artery Disease/metabolism , Female , Genetic Predisposition to Disease/ethnology , Hispanic or Latino/genetics , Hispanic or Latino/statistics & numerical data , Humans , Male , Middle Aged , Myocardial Infarction/ethnology , Myocardial Infarction/genetics , Myocardial Infarction/metabolism , Polymorphism, Single Nucleotide/genetics , Risk Factors , Stroke/ethnology , Stroke/genetics , Stroke/metabolism , Venous Thromboembolism/ethnology , Venous Thromboembolism/genetics , Venous Thromboembolism/metabolism , White People/genetics , White People/statistics & numerical data , Young AdultABSTRACT
Sleep duration is genetically regulated, but the genetic variants are largely unknown. We aimed to identify such genes using a genome-wide association study (GWAS) combined with RNA expression at the population level, and with experimental verification. A GWAS was performed in a Finnish sample (n = 1941), and variants with suggestive association (P < 5 × 10(-5) ) were tested in a follow-up sample from the same population with sleep duration (n = 6834) and time in bed (n = 1720). Variants with pointwise association of P < 0.05 in the follow-up sample were analysed further. First, we correlated genotypes with transcript expression levels with sleep duration (n = 207). The expression levels of significant transcripts were further studied in experimental sleep restriction. Of the 31 variants with P < 5 × 10(-5) in the discovery sample, three variants showed nominal allelic association (P < 0.05) in the follow-up sample: rs10914351, near PTPRU (P = 0.049), rs1037079 in PCDH7-CENTD1 (P = 0.011) and rs2031573 near KLF6 (P = 0.044). The risk alleles for shorter sleep (rs2031573 and rs1037079) were also associated with higher KLF6 and PCDH7 expression levels (P < 0.05). Experimental sleep restriction increased the expression of KLF6 (P < 0.01). These data suggest that rs2031573 near KLF6 or related loci and rs1037079 between PCDH7-CENTD1 or related loci may contribute to the regulation of sleep duration via gene expression. These results illustrate the utility of combining different analytical approaches to identify genetic determinants for traits related to sleep physiology. However, additional studies are needed in order to understand the roles of KLF6 and PCDH7 in sleep regulation.
Subject(s)
Genome-Wide Association Study , Polymorphism, Single Nucleotide/genetics , Sleep/genetics , Sleep/physiology , Adult , Aged , Aged, 80 and over , Alleles , Female , Genotype , Humans , Male , Middle Aged , Phenotype , Quantitative Trait Loci , RNA/analysis , RNA/genetics , Sleep Deprivation/genetics , Time Factors , White People/geneticsABSTRACT
PURPOSE: Family history (FH) and pathogenic variants (PVs) are used for guiding risk surveillance in selected high-risk women but little is known about their impact for breast cancer screening on population level. In addition, polygenic risk scores (PRSs) have been shown to efficiently stratify breast cancer risk through combining information about common genetic factors into one measure. METHODS: In longitudinal real-life data, we evaluate PRS, FH, and PVs for stratified screening. Using FinnGen (N = 117,252), linked to the Mass Screening Registry for breast cancer (1992-2019; nationwide organized biennial screening for age 50-69 years), we assessed the screening performance of a breast cancer PRS and compared its performance with FH of breast cancer and PVs in moderate- (CHEK2)- to high-risk (PALB2) susceptibility genes. RESULTS: Effect sizes for FH, PVs, and high PRS (>90th percentile) were comparable in screening-aged women, with similar implications for shifting age at screening onset. A high PRS identified women more likely to be diagnosed with breast cancer after a positive screening finding (positive predictive value [PPV], 39.5% [95% CI, 37.6 to 41.5]). Combinations of risk factors increased the PPVs up to 45% to 50%. A high PRS conferred an elevated risk of interval breast cancer (hazard ratio [HR], 2.78 [95% CI, 2.00 to 3.86] at age 50 years; HR, 2.48 [95% CI, 1.67 to 3.70] at age 60 years), and women with a low PRS (<10th percentile) had a low risk for both interval- and screen-detected breast cancers. CONCLUSION: Using real-life screening data, this study demonstrates the effectiveness of a breast cancer PRS for risk stratification, alone and combined with FH and PVs. Further research is required to evaluate their impact in a prospective risk-stratified screening program, including cost-effectiveness.
Subject(s)
Breast Neoplasms , Early Detection of Cancer , Genetic Predisposition to Disease , Humans , Breast Neoplasms/genetics , Breast Neoplasms/diagnosis , Female , Middle Aged , Early Detection of Cancer/methods , Aged , Risk Assessment , Risk FactorsABSTRACT
Nightmares are vivid, extended, and emotionally negative or negative dreams that awaken the dreamer. While sporadic nightmares and bad dreams are common and generally harmless, frequent nightmares often reflect underlying pathologies of emotional regulation. Indeed, insomnia, depression, anxiety, or alcohol use have been associated with nightmares in epidemiological and clinical studies. However, the connection between nightmares and their comorbidities are poorly understood. Our goal was to examine the genetic risk factors for nightmares and estimate correlation or causality between nightmares and comorbidities. We performed a genome-wide association study (GWAS) in 45,255 individuals using a questionnaire-based assessment on the frequency of nightmares during the past month and genome-wide genotyping data. While the GWAS did not reveal individual risk variants, heritability was estimated at 5%. In addition, the genetic correlation analysis showed a robust correlation (rg > 0.4) of nightmares with anxiety (rg = 0.671, p = 7.507e-06), depressive (rg = 0.562, p = 1.282e-07) and posttraumatic stress disorders (rg = 0.4083, p = 0.0152), and personality trait neuroticism (rg = 0.667, p = 4.516e-07). Furthermore, Mendelian randomization suggested causality from insomnia to nightmares (beta = 0.027, p = 0.0002). Our findings suggest that nightmares share genetic background with psychiatric traits and that insomnia may increase an individual's liability to experience frequent nightmares. Given the significant correlations with psychiatric and psychological traits, it is essential to grow awareness of how nightmares affect health and disease and systematically collect information about nightmares, especially from clinical samples and larger cohorts.
Subject(s)
Dreams , Sleep Initiation and Maintenance Disorders , Humans , Dreams/psychology , Sleep Initiation and Maintenance Disorders/genetics , Genome-Wide Association Study , Anxiety Disorders , Risk FactorsABSTRACT
Gestational diabetes mellitus (GDM) is a common metabolic disorder affecting more than 16 million pregnancies annually worldwide1,2. GDM is related to an increased lifetime risk of type 2 diabetes (T2D)1-3, with over a third of women developing T2D within 15 years of their GDM diagnosis. The diseases are hypothesized to share a genetic predisposition1-7, but few studies have sought to uncover the genetic underpinnings of GDM. Most studies have evaluated the impact of T2D loci only8-10, and the three prior genome-wide association studies of GDM11-13 have identified only five loci, limiting the power to assess to what extent variants or biological pathways are specific to GDM. We conducted the largest genome-wide association study of GDM to date in 12,332 cases and 131,109 parous female controls in the FinnGen study and identified 13 GDM-associated loci, including nine new loci. Genetic features distinct from T2D were identified both at the locus and genomic scale. Our results suggest that the genetics of GDM risk falls into the following two distinct categories: one part conventional T2D polygenic risk and one part predominantly influencing mechanisms disrupted in pregnancy. Loci with GDM-predominant effects map to genes related to islet cells, central glucose homeostasis, steroidogenesis and placental expression.
Subject(s)
Diabetes Mellitus, Type 2 , Diabetes, Gestational , Islets of Langerhans , Pregnancy , Female , Humans , Diabetes Mellitus, Type 2/genetics , Diabetes, Gestational/genetics , Genome-Wide Association Study , PlacentaABSTRACT
We have studied the largely unknown genetic underpinnings of height growth by using a unique resource of longitudinal childhood height data available in Finnish population cohorts. After applying GWAS mapping of potential genes influencing pubertal height growth followed by further characterization of the genetic effects on complete postnatal growth trajectories, we have identified strong association between variants near LIN28B and pubertal growth (rs7759938; female p = 4.0 x 10(-9), male p = 1.5 x 10(-4), combined p = 5.0 x 10(-11), n = 5038). Analysis of growth during early puberty confirmed an effect on the timing of the growth spurt. Correlated SNPs have previously been implicated as influencing both adult stature and age at menarche, the same alleles associating with taller height and later age of menarche in other studies as with later pubertal growth here. Additionally, a partially correlated LIN28B SNP, rs314277, has been associated previously with final height. Testing both rs7759938 and rs314277 (pairwise r(2) = 0.29) for independent effects on postnatal growth in 8903 subjects indicated that the pubertal timing-associated marker rs7759938 affects prepubertal growth in females (p = 7 x 10(-5)) and final height in males (p = 5 x 10(-4)), whereas rs314277 has sex-specific effects on growth (p for interaction = 0.005) that were distinct from those observed at rs7759938. In conclusion, partially correlated variants at LIN28B tag distinctive, complex, and sex-specific height-growth-regulating effects, influencing the entire period of postnatal growth. These findings imply a critical role for LIN28B in the regulation of human growth.
Subject(s)
Body Height , DNA-Binding Proteins/genetics , Growth/physiology , Menarche/physiology , White People/genetics , Adolescent , Adult , Female , Humans , Infant, Newborn , Male , Polymorphism, Single Nucleotide , RNA-Binding ProteinsABSTRACT
Cardiovascular diseases (CVD) are the leading cause of death worldwide for both men and women, but their prevalence and burden show marked sex differences. The existing knowledge gaps in research, prevention, and treatment for women emphasize the need for understanding the biological mechanisms contributing to the sex differences in CVD. Sex differences in the plasma lipids that are well-known risk factors and predictors of CVD events have been recognized and are believed to contribute to the known disparities in CVD manifestations in men and women. However, the current understanding of sex differences in lipids has mainly come from the studies on routinely measured standard lipids- low-density lipoprotein cholesterol (LDL-C), high-density lipoprotein cholesterol (HDL-C), total triglycerides, and total cholesterol, which have been the mainstay of the lipid profiling. Sex differences in individual lipid species, collectively called the lipidome, have until recently been less explored due to the technological challenges and analytic costs. With the technological advancements in the last decade and growing interest in understanding mechanisms of sexual dimorphism in metabolic disorders, many investigators utilized metabolomics and lipidomics based platforms to examine the effect of biological sex on detailed lipidomic profiles and individual lipid species. This review presents an overview of the research on sex differences in the concentrations of circulating lipid species, focusing on findings from the metabolome- and lipidome-wide studies. We also discuss the potential contribution of genetic factors including sex chromosomes and sex-specific physiological factors such as menopause and sex hormones to the sex differences in lipidomic profiles.