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Fontanillas, P.

Publications and source records attributed to Fontanillas, P..

16 recordsLinked to original sources

Analysis of 3.6 million individuals yields minimal evidence of pairwise genetic interactions for height

Adult height is a highly heritable polygenic trait with heritability attributable to thousands of independent variants. Large-scale studies have been able to detect genetic variants with contributions to height in the range of approximately 1.2 millimetre per allele copy on average. Non-additive genetic interactions may, in part, account for the difference between broad-sense and narrow-sense heritability estimates. However, prior studies have failed to identify variants with non-additive effects, possibly due to the lack of statistical power. Leveraging 3.6M individuals of European genetic ancestry in the 23andMe research cohort, we performed a genome-wide analysis study (GWAS) to select 1,063 independent common SNPs associated with height (p-value < 5e-8), and then screened for evidence of non-additive effects by analysing 564,453 models including a pairwise SNP-SNP interaction term. We identified 69 pairwise models with suggestive evidence of SNP-SNP interaction (p-value < 1e-4) and, for each SNP pair, we evaluated a fully saturated model including additive, dominant, and epistatic (additive-by-additive, additive-by-dominance and dominance-by-dominance) terms. We tested for the presence of epistatic interactions by comparing models with and without epistatic terms using a likelihood ratio test. Assuming a strict Bonferroni-corrected threshold of 8.9e-8 (0.05/564,453), we found no evidence of epistatic interactions (Likelihood ratio test (LRT) p-value < 9e-07 for all models). Our analysis rules out the existence of epistatic interactions between alleles of >1% frequency with effect sizes larger than 2.42mm. Our large-scale analysis provides further evidence of the minimal contribution of non-additivity in the genetic architecture of adult human height.

genomics↗

The shared genetic architecture and evolution of human language and musical rhythm

Rhythm and language-related traits are phenotypically correlated, but their genetic overlap is largely unknown. Here, we leveraged two large-scale genome-wide association studies performed to shed light on the shared genetics of rhythm (N=606,825) and dyslexia (N=1,138,870). Our results reveal an intricate shared genetic and neurobiological architecture, and lay groundwork for resolving longstanding debates about the potential co-evolution of human language and musical traits.

genomics↗

The Latent Genetic Structure of Impulsivity and its Relation to Internalizing Psychopathology

Factor analyses suggest that impulsivity traits that capture tendencies to act prematurely or take risks tap partially distinct constructs. We applied genomic structure equation modeling to evaluate the genetic factor structure of two well-established impulsivity questionnaires, using published genome-wide association study statistics from up to 22,861 participants. We also tested the hypotheses that delay discounting would be genetically separable from other impulsivity factors, and that emotionally-triggered facets of impulsivity (urgency) would be those most strongly genetically correlated with an internalizing latent factor. A five-factor model best fit the impulsivity data. Delay discounting was genetically distinct from these five factors. As expected, the two urgency subscales were most strongly related to an Internalizing Psychopathology latent factor. These findings provide empirical genetic evidence that impulsivity can be disarticulated into distinct categories of differential relevance for internalizing psychopathology. They also demonstrate how measured genetic markers can be used to inform theories of psychology/personality.

genetics↗

Genome-wide association study of pain sensitivity assessed by questionnaire and the cold pressor test

Altered pain sensitivity is believed to play an important role in the development of chronic pain, a common debilitating condition affecting an estimated 1 in 5 adults. Pain sensitivity varies broadly between individuals, and it is notoriously difficult to measure at scale in large populations. Although pain sensitivity is known to be moderately heritable, only a small number of genetic studies have been published and they have had limited success in identifying the genetic architecture of pain sensitivity. In this study, we deployed an online pain sensitivity questionnaire (PSQ) and an at-home version of the cold pressor test (CPT) in a large genotyped cohort. We performed genome-wide association studies (GWAS) on the PSQ score (n = 25,321) and CPT duration (n = 6,853). Despite a reasonably large sample size, we identified only one genome-wide significant locus associated with the PSQ score, which was located in the TSSC1 gene (rs58194899, OR = 0.950 [0.933-0.967], P-value = 1.9*10-8). This gene is responsible for intracellular cell trafficking and it could modulate pain sensitivity via changes in neuroplasticity. PSQ score is genetically correlated with chronic and acute pain, including chronic neck and shoulder pain (rg = 0.71), fracture (0.71), rheumatoid arthritis (0.68), osteoarthritis (0.38), and pneumothorax (0.82). PSQ score was also genetically correlated with known risk factors, such as the length of working week (0.65), noisy workplace (0.41), smoking (0.36), or extreme BMI (0.23). Gene-based analysis followed by pathway analysis showed that GWAS results were enriched for genes expressed in the brain, predominantly in the frontal cortex and basal ganglia, and enriched for genes involved in neuronal development and glutamatergic synapse signaling pathways. Finally, we confirmed that females with red hair were more sensitive to pain and found that genetic variation in the MC1R gene was associated with an increase in pain sensitivity as assessed by the PSQ. Overall, we detailed the genetic background of pain sensitivity using scalable at-home procedures that may serve as a blueprint for larger genetic studies. Author SummaryDespite decades of research and many advances in our understanding of the physical, emotional, and psychological aspects, the genetic contribution to pain sensitivity is still largely unknown. We administered a pain sensitivity questionnaire in parallel with an experimental cold pressor test in a large, genotyped cohort of 31,000 research participants, and found a novel genome-wide genetic association in TSSC1. This gene is responsible for intracellular cell trafficking and it could modulate pain sensitivity via changes in neuroplasticity. Overall, the pain sensitivity measurements revealed strong positive genetic correlations with chronic and acute pain conditions, as well as with unhealthy traits and behaviors, such as obesity, smoking, or difficult working conditions. The genetic association results also suggested, perhaps unsurprisingly, that only the brain tissues could be relevant for pain sensitivity, and identified enrichments for glutamatergic synapse pathways. Despite the complexity of pain sensitivity, our study demonstrated that it is now possible to deploy sophisticated pain questionnaires online and perform experimental medicine tests in at-home settings to further study the genetic architecture of pain sensitivity.

genetics↗

Genetic risk for major depressive disorder and loneliness in gender-specific associations with coronary artery disease

ImportanceEpidemiological evidence indicates that major depressive disorder (MDD) and loneliness both reduce life expectancies, but mechanisms underlying the excess morbidity are unclear. Electronic health records (EHRs) linked to genetic data offer new opportunities to address this knowledge gap.\n\nObjectiveTo determine the medical morbidity pattern associated with genetic risk factors for MDD and loneliness, two common psychological traits with adverse health outcomes.\n\nDesignPhenome-wide association study using EHRs spanning 1990 to 2017 from the Vanderbilt University Medical Center biobank, BioVU. Top associations with coronary artery disease (CAD) were replicated in the Atherosclerosis Risk in Communities (ARIC) cohort.\n\nSettingHospital-based EHR study, with replication in a population-based cohort study.\n\nParticipants18,385 genotyped adult patients in BioVU. Replication in ARIC included 7,197 genotyped participants. All participants were of European ancestry.\n\nExposuresPolygenic scores for MDD and loneliness were developed for each individual using previously published meta-GWAS summary statistics.\n\nMain Outcomes and MeasuresThe phenome-wide association study included 882 clinical diagnoses ascertained via billing codes in the EHR. ARIC included 1598 incident CAD cases.\n\nResultsBioVU patients had a median EHR length of 9.91 years. In the phenome-wide association study, polygenic scores for MDD and loneliness were significantly associated with psychiatric and cardiac phenotypes. Targeted analyses of CAD in 3,893 cases and 4,197 controls in BioVU found odds ratios of 1.11 (95% CI, 1.04-1.18; P=8.43x10-4) and 1.13 (95% CI, 1.07-1.20; P=4.51x10-6) per 1-SD increase in the polygenic scores for MDD and loneliness, respectively. Comparable hazard ratios in ARIC were 1.07 (95% CI, 0.99-1.14; P=0.07) and 1.07 (1.01-1.15; P=0.03). Across both studies, the increased risk persisted in women after adjusting for multiple conventional risk factors, a polygenic score for CAD, and psychiatric symptoms (available in BioVU). Controlling for genetic risk factors shared between MDD and loneliness, the polygenic score for loneliness conditioned on MDD remained associated with CAD risk, but the polygenic score for MDD conditioned on loneliness did not.\n\nConclusions and RelevanceGenetic risk factors for MDD and loneliness act pleiotropically to increase CAD risk in women. Continued research into the biological and clinical connections between the heart and mind is warranted.

genetics↗

Phenome-wide investigation of health outcomes associated with genetic predisposition to loneliness

AO_SCPLOWBSTRACTC_SCPLOWHumans are social animals that experience intense suffering when they perceive a lack of social connection. Modern societies are experiencing an epidemic of loneliness. While the experience of loneliness is universally human, some people report experiencing greater loneliness than others. Loneliness is more strongly associated with mortality than obesity, emphasizing the need to understand the nature of the relationship between loneliness and health. While it is intuitive that circumstantial factors such as marital status and age influence loneliness, there is also compelling evidence of a genetic predisposition towards loneliness. To better understand the genetic architecture of loneliness and its relationship with associated outcomes, we conducted a genome-wide association (GWAS) meta-analysis of loneliness (N=475,661), report 12 associated loci (two novel) and significant genetic correlations with 34 other complex traits. The polygenic basis for loneliness was significantly enriched for evolutionary constrained genes and genes expressed in specific brain tissues: (frontal) cortex, cerebellum, anterior cingulate cortex, and substantia nigra. We built polygenic scores based on this GWAS meta-analysis to explore the genetic association between loneliness and health outcomes in an independent sample of 18,498 individuals for whom electronic health records were available. A genetic predisposition towards loneliness predicted cardiovascular, psychiatric, and metabolic disorders, and triglycerides and high-density lipoproteins. Mendelian randomization analyses showed evidence of a causal, increasing, effect of body fat on loneliness, and a similar weaker causal effect of BMI. Our results provide a framework for ongoing studies of the genetic basis of loneliness and its role in mental and physical health.

genetics↗

Genome-wide association studies of impulsive personality traits (BIS-11 and UPPSP) and drug experimentation in up to 22,861 adult research participants

BackgroundImpulsive personality traits are complex heritable traits that are governed by frontal-subcortical circuits and are associated with numerous neuropsychiatric disorders, particularly drug abuse.\n\nMethodsIn collaboration with the genetics company 23andMe, Inc., we performed several genome-wide association studies (GWAS) on measures of impulsive personality traits (the short version of the UPPSP Impulsive Behavior Scale, and the Barratt Impulsiveness Scale [BIS-11]) and drug experimentation (the number of drug classes an individual has tried in their lifetime) in up to 22,861 male and female adult research participants of European ancestry.\n\nResultsImpulsive personality traits and drug experimentation showed SNP-heritabilities that ranged from 5 to 11%. Genetic variants in the CADM2 locus were significantly associated with the UPPSP Sensation Seeking subscale (P = 8.3 x 10-9, rs139528938) and showed a suggestive association with drug experimentation (P = 3.0 x 10-7, rs2163971; r2 = 0.68 with rs139528938); CADM2 has been previously associated with measures of risky behaviors and self-reported risk tolerance, cannabis initiation, alcohol consumption, as well as information speed processing, body mass index (BMI) variation and obesity. Furthermore, genetic variants in the CACNA1I locus were significantly associated with the UPPSP Negative Urgency subscale (P = 3.8 x 10-8, rs199694726). Multiple subscales from both UPPSP and BIS showed strong genetic correlations (>0.5) with drug experimentation and other substance use traits measured in independent cohorts, including smoking initiation, and lifetime cannabis use. Several UPPSP and BIS subscales were genetically correlated with attention-deficit/hyperactivity disorder (rg = 0.30-0.51, p < 8.69 x 10-3), supporting their validity as endophenotypes.\n\nConclusionsOur findings demonstrate a role for common genetic contributions to individual differences in impulsivity. Furthermore, our study is the first to provide a genetic dissection of the relationship between different types of impulsive personality traits and various psychiatric disorders.

genetics↗

Genome-wide association studies on endometriosis and endometriosis-related infertility

Endometriosis affects [~]10% of women of reproductive age. It is characterized by the growth of endometrial-like tissue outside the uterus and is frequently associated with severe pain and infertility. We performed the largest endometriosis genome-wide association study (GWAS) to date, with 37,183 cases and 251,258 controls. All women were of European ancestry. We also performed the first GWAS of endometriosis-related infertility, including 2,969 cases and 3,770 controls. Our endometriosis GWAS study replicated, at genome-wide significance, seven loci identified in previous endometriosis GWASs (CELA3A-CDC42, SYNE1, KDR, FSHB-ARL14EP, GREB1, ID4, and CEP112) and identified seven new candidate loci with genome-wide significance (NGF, ATP1B1-F5, CD109, HEY2, OSR2-VPS13B, WT1, and TEX11-SLC7A3). No loci demonstrated genome-wide significance for endometriosis-related infertility, however, the three most strongly associated loci (MCTP1, EPS8L3-CSF1, and LPIN1) were in or near genes associated with female fertility or embryonic lethality in model organisms. These results reveal new candidate genes with potential involvement in the pathophysiology of endometriosis and endometriosis-related infertility.

genetics↗

Large-scale genome-wide association meta-analysis of endometriosis reveals 13 novel loci and genetically-associated comorbidity with other pain conditions

Endometriosis is a common complex inflammatory condition characterised by the presence of endometrium-like tissue outside the uterus, mainly in the pelvic area. It is associated with chronic pelvic pain and infertility, and its pathogenesis remains poorly understood. The disease is typically classified according to the revised American Fertility Society (rAFS) 4-stage surgical assessment system, although stage does not correlate well with symptomatology or prognosis. Previously identified genetic variants mainly are associated with stage III/IV disease, highlighting the need for further phenotype-stratified analysis that requires larger datasets. We conducted a meta-analysis of 15 genome-wide association studies (GWAS) and a replication analysis, including 58,115 cases and 733,480 controls in total, and sub-phenotype analyses of stage I/II, stage III/IV and infertility-associated endometriosis cases. This revealed 27 genetic loci associated with endometriosis at the genome-wide p-value threshold (P<5x10-8), 13 of which are novel and an additional 8 novel genes identified from gene-based association analyses. Of the 27 loci, 21 (78%) had greater effect sizes in stage III/IV disease compared to stage I/II, 1 (4%) had greater effect size in stage I/II compared to stage III/IV and 17 (63%) had greater effect sizes when restricted to infertility-associated endometriosis cases compared to overall endometriosis. These results suggest that specific variants may confer risk for different sub-types of endometriosis through distinct pathways. Analyses of genetic variants underlying different pain symptoms reported in the UK Biobank showed that 7/9 had positive significant (p<1.28x103) positive genetic correlations with endometriosis, suggesting a genetic basis for sensitivity to pain in general. Additional conditions with significant positive genetic correlations with endometriosis included uterine fibroids, excessive and irregular menstrual bleeding, osteoarthritis, diabetes as well as menstrual cycle length and age at menarche. These results provide a basis for fine-mapping of the causal variants at these 27 loci, and for functional follow-up to understand their contribution to endometriosis and its potential subtypes.

genomics↗

Trans-ancestral GWAS of alcohol dependence reveals common genetic underpinnings with psychiatric disorders

Liability to alcohol dependence (AD) is heritable, but little is known about its complex polygenic architecture or its genetic relationship with other disorders. To discover loci associated with AD and characterize the relationship between AD and other psychiatric and behavioral outcomes, we carried out the largest GWAS to date of DSM - IV diagnosed AD. Genome - wide data on 14,904 individuals with AD and 37,944 controls from 28 case / control and family - based studies were meta - analyzed, stratified by genetic ancestry (European, N = 46,568; African; N = 6,280). Independent, genome - wide significant effects of different ADH1B variants were identified in European (rs1229984; p = 9.8E - 13) and African ancestries (rs2066702; p = 2.2E - 9). Significant genetic correlations were observed with schizophrenia, ADHD, depression, and use of cigarettes and cannabis. There was only modest genetic correlation with alcohol consumption and inconsistent associations with problem drinking. The genetic underpinnings of AD only partially overlap with those for alcohol consumption, underscoring the genetic distinction between pathological and non - pathological drinking behaviors.

genetics↗

Genome-wide association study meta-analysis of the Alcohol Use Disorder Identification Test (AUDIT) in two population-based cohorts (N=141,958)

Alcohol use disorders (AUD) are common conditions that have enormous social and economic consequences. We obtained quantitative measures using the Alcohol Use Disorder Identification Test (AUDIT) from two population-based cohorts of European ancestry: UK Biobank (UKB; N=121,604) and 23andMe (N=20,328) and performed a genome-wide association study (GWAS) meta-analysis. We also performed GWAS for AUDIT items 1-3, which focus on consumption (AUDIT-C), and for items 4-10, which focus on the problematic consequences of drinking (AUDIT-P). The GWAS meta-analysis of AUDIT total score identified 10 associated risk loci. Novel associations localized to genes including JCAD and SLC39A13; we also replicated previously identified signals in the genes ADH1B, ADH1C, KLB, and GCKR. The dimensions of AUDIT showed positive genetic correlations with alcohol consumption (rg=0.76-0.92) and Diagnostic and Statistical Manual of Mental Disorders (DSM-IV) alcohol dependence (rg=0.33-0.63). AUDIT-P and AUDIT-C showed significantly different patterns of association across a number of traits, including psychiatric disorders. AUDIT-P was positively genetically correlated with schizophrenia (rg=0.22, p=3.0x10-10), major depressive disorder (rg=0.26, p=5.6x10-3), and attention-deficit/hyperactivity disorder (ADHD; rg=0.23, p=1.1x10-5), whereas AUDIT-C was negatively genetically correlated with major depressive disorder (rg=-0.24, p=3.7x10-3) and ADHD (rg=-0.10, p=1.8x10-2). We also used the AUDIT data in the UKB to identify thresholds for dichotomizing AUDIT total score that optimize genetic correlations with DSM-IV alcohol dependence. Coding individuals with AUDIT total score of [&le;]4 as controls and [&ge;]12 as cases produced a high genetic correlation with DSM-IV alcohol dependence (rg=0.82, p=3.2x10-6) while retaining most subjects. We conclude that AUDIT scores ascertained in population-based cohorts can be used to explore the genetic basis of both alcohol consumption and AUD.

genetics↗

The Parkinson’s Phenome: Traits Associated with Parkinson’s Disease in a Large and Deeply Phenotyped Cohort

BackgroundObservational studies have begun to characterize the wide spectrum of phenotypes associated with Parkinsons disease (PD), but recruiting large numbers of PD cases and assaying a diversity of phenotypes has often been difficult. Here, we set out to systematically describe the PD phenome using a cross-sectional case-control design in a large database.\n\nMethodsWe analyzed the association between PD and 840 phenotypes derived from online surveys. For each phenotype, we ran a logistic regression using an average of 5,141 PD cases and 65,459 age- and sex-matched controls. We selected uncorrelated phenotypes, determined statistical significance after correcting for multiple testing, and systematically assessed the novelty of each significant association. We tested whether significant phenotypes were also associated with disease duration in PD cases.\n\nFindingsPD diagnosis was associated with 149 independent phenotypes. We replicated 32 known associations and discovered 49 associations that have not previously been reported. We found that migraine, obsessive-compulsive disorder, seasonal allergies, and anemia were associated with PD, but were not significantly associated with PD duration, and tend to occur decades before the average age of diagnosis for PD. Further work is needed to determine whether these phenotypes are PD risk factors or whether they share common disease mechanisms.\n\nInterpretationWe used a systematic approach in a single large dataset to assess the spectrum of traits that were associated with PD. Some of these traits may be risk factors for PD, features of the pre-diagnostic phase of disease, or manifestations of PD pathology. The model outputs from all 840 logistic regressions are available to the research community and may be used to generate hypotheses regarding PD etiology.\n\nFundingThe Michael J. Fox Foundation, Parkinsons UK, Barts Charity, National Institute on Aging, and 23andMe, Inc.\n\nResearch in ContextO_ST_ABSEvidence before this studyC_ST_ABSWe used PubMed to perform a MEDLINE database search for review articles published up to January 21st, 2018 that contained the keywords \"Parkinson\" and \"epidemiology\" in the title or abstract. We performed additional MEDLINE searches for each phenotype that was significantly associated with PD. Although dozens of phenotypes have been tested for an association with PD, only a few associations have been consistently repeatable (e.g. pesticide exposure, coffee consumption).\n\nAdded value of this studyWe systematically tested for an association between PD and 840 phenotypes using up to 13,546 cases and 1{middle dot}3 million controls, making this one of the largest PD epidemiology studies ever conducted. We discovered 49 novel associations that will need to be replicated or validated. We found 44 associations for phenotypes that have previously been studied in relation to PD, but for which an association has not been consistently demonstrated.\n\nImplications of all the available evidenceTaken together with results from previous studies, this series of case-control analyses adds evidence for associations between PD and many phenotypes that are not currently thought to be part of the canonical PD phenome. This work paves the way for future studies to assess whether any of these phenotypes represent PD risk factors and whether any of these risk factors are modifiable.

epidemiology↗

Genome-wide study identifies 611 loci associated with risk tolerance and risky behaviors

Humans vary substantially in their willingness to take risks. In a combined sample of over one million individuals, we conducted genome-wide association studies (GWAS) of general risk tolerance, adventurousness, and risky behaviors in the driving, drinking, smoking, and sexual domains. We identified 611 approximately independent genetic loci associated with at least one of our phenotypes, including 124 with general risk tolerance. We report evidence of substantial shared genetic influences across general risk tolerance and risky behaviors: 72 of the 124 general risk tolerance loci contain a lead SNP for at least one of our other GWAS, and general risk tolerance is moderately to strongly genetically correlated ([Formula] to 0.50) with a range of risky behaviors. Bioinformatics analyses imply that genes near general-risk-tolerance-associated SNPs are highly expressed in brain tissues and point to a role for glutamatergic and GABAergic neurotransmission. We find no evidence of enrichment for genes previously hypothesized to relate to risk tolerance.

genetics↗

Genome-wide association analysis of lifetime cannabis use (N=184,765) identifies new risk loci, genetic overlap with mental health, and a causal influence of schizophrenia on cannabis use

Cannabis use is a heritable trait [1] that has been associated with adverse mental health outcomes. To identify risk variants and improve our knowledge of the genetic etiology of cannabis use, we performed the largest genome-wide association study (GWAS) meta-analysis for lifetime cannabis use (N=184,765) to date. We identified 4 independent loci containing genome-wide significant SNP associations. Gene-based tests revealed 29 genome-wide significant genes located in these 4 loci and 8 additional regions. All SNPs combined explained 10% of the variance in lifetime cannabis use. The most significantly associated gene, CADM2, has previously been associated with substance use and risk-taking phenotypes [2-4]. We used S-PrediXcan to explore gene expression levels and found 11 unique eGenes. LD-score regression uncovered genetic correlations with smoking, alcohol use and mental health outcomes, including schizophrenia and bipolar disorder. Mendelian randomisation analysis provided evidence for a causal positive influence of schizophrenia risk on lifetime cannabis use.

genetics↗

Genome-wide association study of Alcohol Use Disorder Identification Test (AUDIT) scores in 20,328 research participants of European ancestry

Genetic factors contribute to the risk for developing alcohol use disorder (AUD). In collaboration with the genetics company 23andMe, Inc., we performed a genome-wide association (GWAS) study of the Alcohol Use Disorder Identification Test (AUDIT), an instrument designed to screen for alcohol misuse over the past year. Our final sample consisted of 20,328 research participants of European ancestry (55.3% females; mean age = 53.8, SD = 16.1) who reported ever using alcohol. Our results showed that the chip-heritability of AUDIT score, when treated as a continuous phenotype, was 12%. No loci reached genome-wide significance. The gene ADH1C, which has been previously implicated in AUD, was among our most significant associations (4.4 x 10-7; rs141973904). We also detected a suggestive association on chromosome 1 (2.1 x 10-7; rs182344113) near the gene KCNJ9, which has been implicated in mouse models of high ethanol drinking. Using LD score regression, we identified positive genetic correlations between AUDIT score and AUD, high alcohol consumption, and cigarette smoking. We also observed an unexpected positive genetic correlation between AUDIT and educational attainment, and additional unexpected negative correlations with BMI/obesity and attention-deficit/hyperactivity disorder (ADHD). We conclude that conducting a genetic study using data from a population unselected for AUD and responding to an online questionnaire may represent a cost-effective strategy for elucidating the etiology of AUD.

genetics↗

Genetics of the Research Domain Criteria (RDoC): genome-wide association study of delay discounting

Delay discounting (DD), which is the tendency to discount the value of delayed versus current rewards, is elevated in a constellation of diseases and behavioral conditions. We performed a genome-wide association study of DD using 23,127 research participants of European ancestry. The most significantly associated SNP was rs6528024 (P = 2.40 x 10-8), which is located in an intron of the gene GPM6B. We also showed that 12% of the variance in DD was accounted for by genotype, and that the genetic signature of DD overlapped with attention-deficit/hyperactivity disorder, schizophrenia, major depression, smoking, personality, cognition, and body weight.

genetics↗