Genome-wide association analyses identify 95 risk loci and provide insights into the neurobiology of post-traumatic stress disorder

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.

Shared genetic architectures of educational attainment in East Asian and European populations

Educational attainment (EduYears), a heritable trait often used as a proxy for cognitive ability, is associated with various health and social outcomes. Previous genome-wide association studies (GWASs) on EduYears have been focused on samples of European (EUR) genetic ancestries. Here we present the first large-scale GWAS of EduYears in people of East Asian (EAS) ancestry (n = 176,400) and conduct a cross-ancestry meta-analysis with EduYears GWAS in people of EUR ancestry (n = 766,345). EduYears showed a high genetic correlation and power-adjusted transferability ratio between EAS and EUR. We also found similar functional enrichment, gene expression enrichment and cross-trait genetic correlations between two populations. Cross-ancestry fine-mapping identified refined credible sets with a higher posterior inclusion probability than single population fine-mapping. Polygenic prediction analysis in four independent EAS and EUR cohorts demonstrated transferability between populations. Our study supports the need for further research on diverse ancestries to increase our understanding of the genetic basis of educational attainment.

Whole-exome sequencing in UK Biobank reveals rare genetic architecture for depression

Nearly two hundred common-variant depression risk loci have been identified by genome-wide association studies (GWAS). However, the impact of rare coding variants on depression remains poorly understood. Here, we present whole-exome sequencing analyses of depression with seven different definitions based on survey, questionnaire, and electronic health records in 320,356 UK Biobank participants. We showed that the burden of rare damaging coding variants in loss-of-function intolerant genes is significantly associated with risk of depression with various definitions. We compared the rare and common genetic architecture across depression definitions by genetic correlation and showed different genetic relationships between definitions across common and rare variants. In addition, we demonstrated that the effects of rare damaging coding variant burden and polygenic risk score on depression risk are additive. The gene set burden analyses revealed overlapping rare genetic variant components with developmental disorder, autism, and schizophrenia. Our study provides insights into the contribution of rare coding variants, separately and in conjunction with common variants, on depression with various definitions and their genetic relationships with neurodevelopmental disorders.

Blood-based DNA methylation and exposure risk scores predict PTSD with high accuracy in military and civilian cohorts

Background

Incorporating genomic data into risk prediction has become an increasingly useful approach for rapid identification of individuals most at risk for complex disorders such as PTSD. Our goal was to develop and validate Methylation Risk Scores (MRS) using machine learning to distinguish individuals who have PTSD from those who do not.

Methods

Elastic Net was used to develop three risk score models using a discovery dataset (n = 1226; 314 cases, 912 controls) comprised of 5 diverse cohorts with available blood-derived DNA methylation (DNAm) measured on the Illumina Epic BeadChip. The first risk score, exposure and methylation risk score (eMRS) used cumulative and childhood trauma exposure and DNAm variables; the second, methylation-only risk score (MoRS) was based solely on DNAm data; the third, methylation-only risk scores with adjusted exposure variables (MoRSAE) utilized DNAm data adjusted for the two exposure variables. The potential of these risk scores to predict future PTSD based on pre-deployment data was also assessed. External validation of risk scores was conducted in four independent cohorts.

Results

The eMRS model showed the highest accuracy (92%), precision (91%), recall (87%), and f1-score (89%) in classifying PTSD using 3730 features. While still highly accurate, the MoRS (accuracy = 89%) using 3728 features and MoRSAE (accuracy = 84%) using 4150 features showed a decline in classification power. eMRS significantly predicted PTSD in one of the four independent cohorts, the BEAR cohort (beta = 0.6839, p-0.003), but not in the remaining three cohorts. Pre-deployment risk scores from all models (eMRS, beta = 1.92; MoRS, beta = 1.99 and MoRSAE, beta = 1.77) displayed a significant (p < 0.001) predictive power for post-deployment PTSD.

Conclusion

Results, especially those from the eMRS, reinforce earlier findings that methylation and trauma are interconnected and can be leveraged to increase the correct classification of those with vs. without PTSD. Moreover, our models can potentially be a valuable tool in predicting the future risk of developing PTSD. As more data become available, including additional molecular, environmental, and psychosocial factors in these scores may enhance their accuracy in predicting the condition and, relatedly, improve their performance in independent cohorts.

Large-Scale Mendelian Randomization Study Reveals Circulating Blood-based Proteomic Biomarkers for Psychopathology and Cognitive Task Performance

Background

Research on peripheral (e.g., blood-based) biomarkers for psychiatric illness has typically been low-throughput in terms of both the number of subjects and the range of assays performed. Moreover, traditional case-control studies examining blood-based biomarkers are subject to potential confounds of treatment and other exposures common to patients with psychiatric illnesses. Our research addresses these challenges by leveraging large-scale, high-throughput proteomics data and Mendelian Randomization (MR) to examine the causal impact of circulating proteins on psychiatric phenotypes and cognitive task performance.

Methods

We utilized plasma proteomics data from the UK Biobank (3,072 proteins assayed in 34,557 European-ancestry individuals) and deCODE Genetics (4,719 proteins measured across 35,559 Icelandic individuals). Significant proteomic quantitative trait loci (both cis-pQTLs and trans-pQTLs) served as MR instruments, with the most recent GWAS for schizophrenia, bipolar disorder, major depressive disorder, and cognitive task performance (all excluding overlapping UK Biobank participants) as phenotypic outcomes.

Results

MR revealed 109 Bonferroni-corrected causal associations (44 novel) involving 88 proteins across the four phenotypes. Several immune-related proteins, including interleukins and complement factors, stood out as pleiotropic across multiple outcome phenotypes. Drug target enrichment analysis identified several novel potential pharmacologic repurposing opportunities, including anti-inflammatory agents for schizophrenia and bipolar disorder and duloxetine for cognitive performance.

Conclusions

Identification of causal effects for these circulating proteins suggests potential biomarkers for these conditions and offers insights for developing innovative therapeutic strategies. The findings also indicate substantial evidence for the pleiotropic effects of many proteins across different phenotypes, shedding light on the shared etiology among psychiatric conditions and cognitive ability.

Relationship between mood disorders and substance involvement and the shared genetic liabilities: A population-based study in Taiwan

BACKGROUND

This study explored the phenotypic association of mood disorders, including major depressive disorder (MDD) and bipolar disorder (BPD), with a range of substance involvement, including lifetime experience and age at initiation of tobacco, alcohol, and betel nut use. Additionally, we elucidated polygenic risk score (PRS) association.

METHODS

In total, 132,615 community participants were recruited from the Taiwan Biobank. Genome-wide genotyping data were available for 106,806 unrelated individuals, and the PRS for MDD and BPD was calculated. The significance of mood disorders and PRSs associated with substance involvement were evaluated using a linear/logistic regression model with adjustment for potential confounders. Sex differences were assessed.

RESULTS

MDD and BPD were associated with regular alcohol consumption, drinking cessation, tobacco smoking, smoking cessation, betel nut chewing, and earlier onset of drinking. BPD was associated with an earlier onset of smoking. MDD PRS was associated with regular alcohol use (odds ratio [OR] per standard deviation increase in PRS = 1.03, p = 0.018), alcohol cessation (OR = 1.05, p = 0.03), regular tobacco use (OR = 1.08, p < 0.0001), and betel nut chewing (OR = 1.06, p < 0.0001), whereas BPD PRS was not associated with substance use. Phenotypic association strengths between MDD/BPD and regular drinking/smoking and the polygenic association between MDD PRS and regular smoking were larger in females than in males.

LIMITATIONS

Retrospective self-reported MDD/BPD diagnoses and substance involvement.

CONCLUSIONS

Mood disorders were associated with a range of substance involvement. Shared genetic architecture contributed to the co-occurrence of MDD and substance involvement. These findings may help design prevention and cessation strategies for substance use.

The accuracy of polygenic score models for anthropometric traits and Type II Diabetes in the Native Hawaiian Population

Polygenic scores (PGS) are promising in stratifying individuals based on the genetic susceptibility to complex diseases or traits. However, the accuracy of PGS models, typically trained in European- or East Asian-ancestry populations, tend to perform poorly in other ethnic minority populations, and their accuracies have not been evaluated for Native Hawaiians. Using body mass index, height, and type-2 diabetes as examples of highly polygenic traits, we evaluated the prediction accuracies of PGS models in a large Native Hawaiian sample from the Multiethnic Cohort with up to 5,300 individuals. We evaluated both publicly available PGS models or genome-wide PGS models trained in this study using the largest available GWAS. We found evidence of lowered prediction accuracies for the PGS models in some cases, particularly for height. We also found that using the Native Hawaiian samples as an optimization cohort during training did not consistently improve PGS performance. Moreover, even the best performing PGS models among Native Hawaiians would have lowered prediction accuracy among the subset of individuals most enriched with Polynesian ancestry. Our findings indicate that factors such as admixture histories, sample size and diversity in GWAS can influence PGS performance for complex traits among Native Hawaiian samples. This study provides an initial survey of PGS performance among Native Hawaiians and exposes the current gaps and challenges associated with improving polygenic prediction models for underrepresented minority populations.

[Clinical analysis of 86 cases of acute fatty liver of pregnancy]

Objective: To investigate the clinical characteristics and maternal and fetal prognosis of pregnant women with acute fatty liver of pregnancy (AFLP). Methods: The clinical data of 86 AFLP pregnant women admitted to the Third Affiliated Hospital of Guangzhou Medical University from September 2017 to August 2022 were collected, and their general data, clinical characteristics, laboratory tests and maternal and fetal outcomes were retrospectively analyzed. Results: (1) General information: the age of the 86 pregnant women with AFLP was (30.8±5.4) years, and the body mass index was (21.0±2.5) kg/m2. There were 50 primiparas (58.1%, 50/86) and 36 multiparas (41.9%, 36/86). There were 64 singleton pregnancies (74.4%, 64/86) and 22 twin pregnancies (25.6%, 22/86). (2) Clinical characteristics: the main complaints of AFLP pregnant women were gastrointestinal symptoms, including epigastric pain (68.6%, 59/86), nausea (47.7%, 41/86), anorexia (46.5%, 40/86), vomiting (39.5%, 34/86). The main non-gastrointestinal symptoms were jaundice of skin and/or scleral (54.7%, 47/86), edema (38.4%, 33/86), fatigue (19.8%, 17/86), bleeding tendency (16.3%, 14/86), polydipsia or polyuria (14.0%, 12/86), skin itching (8.1%, 7/86), and 17.4% (15/86) AFLP pregnant women had no obvious symptoms. (3) Laboratory tests: the incidence of liver and kidney dysfunction and abnormal coagulation function in AFLP pregnant women was high, and the levels of blood ammonia, lactate dehydrogenase and lactic acid were increased, and the levels of hemoglobin, platelet and albumin decreased. However, only 24 cases (27.9%, 24/86) of AFLP pregnant women showed fatty liver by imageology examination. (4) Pregnancy outcomes: ① AFLP pregnant women had a high incidence of pregnancy complications, mainly including renal insufficiency (95.3%, 82/86), preterm birth (46.5%, 40/86), hypertensive disorders in pregnancy (30.2%, 26/86), gestational diabetes mellitus (36.0%, 31/86), fetal distress (24.4%, 21/86), pulmonary infection (23.3%, 20/86), disseminated intravascular coagulation (16.3%, 14/86), multiple organ dysfunction syndrome (16.3%, 14/86), hepatic encephalopathy (9.3%, 8/86), and intrauterine fetal death (2.3%, 2/86). ② Treatment and outcome of AFLP pregnant women: the intensive care unit transfer rate of AFLP pregnant women was 66.3% (57/86). 82 cases were improved and discharged after treatment, 2 cases were transferred to other hospitals for follow-up treatment, and 2 cases (2.3%, 2/86) died. ③ Neonatal outcomes: except for 2 cases of intrauterine death, a total of 106 neonates were delivered, including 39 cases (36.8%, 39/106) of neonatal asphyxia, 63 cases (59.4%, 63/106) of neonatal intensive care unit admission, and 3 cases (2.8%, 3/106) of neonatal death. Conclusions: AFLP is a severe obstetric complication, which is harmful to mother and fetus. In the process of clinical diagnosis and treatment, attention should be paid to the clinical manifestations and laboratory tests of pregnant women, early diagnosis and active treatment, so as to improve maternal and fetal outcomes.

Analysis across Taiwan Biobank, Biobank Japan, and UK Biobank identifies hundreds of novel loci for 36 quantitative traits

Genome-wide association studies (GWASs) have identified tens of thousands of genetic loci associated with human complex traits. However, the majority of GWASs were conducted in individuals of European ancestries. Failure to capture global genetic diversity has limited genomic discovery and has impeded equitable delivery of genomic knowledge to diverse populations. Here we report findings from 102,900 individuals across 36 human quantitative traits in the Taiwan Biobank (TWB), a major biobank effort that broadens the population diversity of genetic studies in East Asia. We identified 968 novel genetic loci, pinpointed novel causal variants through statistical fine-mapping, compared the genetic architecture across TWB, Biobank Japan, and UK Biobank, and evaluated the utility of cross-phenotype, cross-population polygenic risk scores in disease risk prediction. These results demonstrated the potential to advance discovery through diversifying GWAS populations and provided insights into the common genetic basis of human complex traits in East Asia.

A neotropical perspective on the uniqueness of the Holocene among interglacials

Understanding how tropical systems have responded to large-scale climate change, such as glacial-interglacial oscillations, and how human impacts have altered those responses is key to current and future ecology. A sedimentary record recovered from Lake Junín, in the Peruvian Andes (4085 m elevation) spans the last 670,000 years and represents the longest continuous and empirically-dated record of tropical vegetation change to date. Spanning seven glacial-interglacial oscillations, fossil pollen and charcoal recovered from the core showed the general dominance of grasslands, although during the warmest times some Andean forest trees grew above their modern limits near the lake. Fire was very rare until the last 12,000 years, when humans were in the landscape. Here we show that, due to human activity, our present interglacial, the Holocene, has a distinctive vegetation composition and ecological trajectory compared with six previous interglacials. Our data reinforce the view that modern vegetation assemblages of high Andean grasslands and the presence of a defined tree line are aspects of a human-modified landscape.

Causal influence of sleeping phenotypes on the risk of coronary artery disease and sudden cardiac arrest: A Mendelian randomization analysis

OBJECTIVES

To assess the causal influence of sleep and circadian traits on coronary artery disease and sudden cardiac arrest with adjustment for obesity through a two-sample Mendelian randomization study.

METHODS

We used summary statistics of 5 sleep and circadian traits for genome-wide association studies, including chronotype, sleep duration, long sleep (≥9 h a day), short sleep (<7 h a day), and insomnia (sample size range: 237,622-651,295). Coronary artery disease genome-wide association studies with 60,801 cases and 123,504 controls, sudden cardiac arrest genome-wide association studies with 3939 cases and 25,989 controls, and obesity genome-wide association studies with 806,834 individuals were also used. Multivariable Mendelian randomization was performed to estimate the causality.

RESULTS

After adjusting for obesity, genetically predicted short sleep (odds ratio = 1.87 and p = .02), and genetically predicted insomnia (odds ratio = 1.17 and p = .001) were causally associated with increased odds of coronary artery disease. Genetically predicted long sleep (odds ratio = 0.06 and p = .02) and genetically predicted longer sleep duration (odds ratio = 0.36 for per-hour increase in sleep duration and p = .0006) were causally associated with decreased odds of sudden cardiac arrest.

CONCLUSIONS

The findings of this Mendelian randomization study indicate that insomnia and short sleep contribute to the development of coronary artery disease, whereas a longer sleep duration protects from sudden cardiac arrest, independent of the influence of obesity. The mechanisms underlying these associations warrant further investigation.

Plasma proteomic associations with genetics and health in the UK Biobank

The Pharma Proteomics Project is a precompetitive biopharmaceutical consortium characterizing the plasma proteomic profiles of 54,219 UK Biobank participants. Here we provide a detailed summary of this initiative, including technical and biological validations, insights into proteomic disease signatures, and prediction modelling for various demographic and health indicators. We present comprehensive protein quantitative trait locus (pQTL) mapping of 2,923 proteins that identifies 14,287 primary genetic associations, of which 81% are previously undescribed, alongside ancestry-specific pQTL mapping in non-European individuals. The study provides an updated characterization of the genetic architecture of the plasma proteome, contextualized with projected pQTL discovery rates as sample sizes and proteomic assay coverages increase over time. We offer extensive insights into trans pQTLs across multiple biological domains, highlight genetic influences on ligand-receptor interactions and pathway perturbations across a diverse collection of cytokines and complement networks, and illustrate long-range epistatic effects of ABO blood group and FUT2 secretor status on proteins with gastrointestinal tissue-enriched expression. We demonstrate the utility of these data for drug discovery by extending the genetic proxied effects of protein targets, such as PCSK9, on additional endpoints, and disentangle specific genes and proteins perturbed at loci associated with COVID-19 susceptibility. This public-private partnership provides the scientific community with an open-access proteomics resource of considerable breadth and depth to help to elucidate the biological mechanisms underlying proteo-genomic discoveries and accelerate the development of biomarkers, predictive models and therapeutics1.

[To compare the efficacy and incidence of severe hematological adverse events of flumatinib and imatinib in patients newly diagnosed with chronic phase chronic myeloid leukemia]

Objective: To analyze and compare therapy responses, outcomes, and incidence of severe hematologic adverse events of flumatinib and imatinib in patients newly diagnosed with chronic phase chronic myeloid leukemia (CML) . Methods: Data of patients with chronic phase CML diagnosed between January 2006 and November 2022 from 76 centers, aged ≥18 years, and received initial flumatinib or imatinib therapy within 6 months after diagnosis in China were retrospectively interrogated. Propensity score matching (PSM) analysis was performed to reduce the bias of the initial TKI selection, and the therapy responses and outcomes of patients receiving initial flumatinib or imatinib therapy were compared. Results: A total of 4 833 adult patients with CML receiving initial imatinib (n=4 380) or flumatinib (n=453) therapy were included in the study. In the imatinib cohort, the median follow-up time was 54 [interquartile range (IQR), 31-85] months, and the 7-year cumulative incidences of CCyR, MMR, MR(4), and MR(4.5) were 95.2%, 88.4%, 78.3%, and 63.0%, respectively. The 7-year FFS, PFS, and OS rates were 71.8%, 93.0%, and 96.9%, respectively. With the median follow-up of 18 (IQR, 13-25) months in the flumatinib cohort, the 2-year cumulative incidences of CCyR, MMR, MR(4), and MR(4.5) were 95.4%, 86.5%, 58.4%, and 46.6%, respectively. The 2-year FFS, PFS, and OS rates were 80.1%, 95.0%, and 99.5%, respectively. The PSM analysis indicated that patients receiving initial flumatinib therapy had significantly higher cumulative incidences of CCyR, MMR, MR(4), and MR(4.5) and higher probabilities of FFS than those receiving the initial imatinib therapy (all P<0.001), whereas the PFS (P=0.230) and OS (P=0.268) were comparable between the two cohorts. The incidence of severe hematologic adverse events (grade≥Ⅲ) was comparable in the two cohorts. Conclusion: Patients receiving initial flumatinib therapy had higher cumulative incidences of therapy responses and higher probability of FFS than those receiving initial imatinib therapy, whereas the incidence of severe hematologic adverse events was comparable between the two cohorts.

Discovery of 95 PTSD loci provides insight into genetic architecture and neurobiology of trauma and stress-related disorders

Posttraumatic 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 novel). Convergent multi-omic approaches identified 43 potential causal genes, broadly classified as neurotransmitter and ion channel synaptic modulators (e.g., GRIA1, GRM8, CACNA1E ), developmental, axon guidance, and transcription factors (e.g., FOXP2, EFNA5, DCC ), synaptic structure and function genes (e.g., PCLO, NCAM1, PDE4B ), and endocrine or immune regulators (e.g., ESR1, TRAF3, 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.

[Clinical presentation and prognosis in children over 10-year-old with primary nephrotic syndrome]

Objective: To summary the clinical presentation and prognosis of primary nephrotic syndrome (PNS) in teenagers. Methods: The clinical data, renal pathological types and prognosis of 118 children over 10-year-old with PNS treated in the Department of Nephrology of the Children's Hospital Affiliated to Capital Institute of Pediatrics from January 2010 to December 2020 were retrospectively analyzed, with 408 children ≤10-year-old as control group synchronously. Chi-square test was used to compare the difference of clinical types, pathologic types, response to steroids and tubulointerstitial changes between the groups. The teenagers with steroid resistant nephrotic syndrome (SRNS) were divided into initial non-responder group and late non-responder group. Kaplan-Meier method was used to compare the difference of persistent proteinuria, and Fisher's exact test for the histological types. Results: There were 118 children >10-year-old, including 74 males and 44 females, with the onset age of 12.1 (10.8, 13.4) years; and 408 children ≤10-year-old with the onset age of 4.5 (3.2, 6.8) years. The proportion of SRNS was significantly higher in patients >10-year-old than those ≤10-year-old (24.6% (29/118) vs. 15.9% (65/408), χ²=4.66, P=0.031). There was no statistical difference in the pathological types between >10-year-old and ≤10-year-old (P>0.05), with minimal change disease the most common type (56.0% (14/25) vs. 60.5% (26/43)). The percentage of cases with renal tubulointerstitial lesions was significantly higher in children >10-year-old compared to those ≤10-year-old (60.0% (15/25) vs. 23.3% (10/43), χ²=9.18, P=0.002). There were 29 cases presented with SRNS in PNS over 10-year-old, including 19 initial non-responders and 10 late non-responders. Analyzed by Kaplan-Meier curve, it was shown that the percentage of persistent proteinuria after 6 months of immunosuppressive treatments was significantly higher in initial non-responders than those of the late non-responders ((22±10)% vs. 0, χ²=14.68, P<0.001); the percentage of minimal change disease was significantly higher in patients of late non-responders than those of the initial non-responders (5/6 vs. 3/13, P=0.041). Of the 63 >10-year-old with steroid-sensitive nephrotic syndrome followed up more than one year, 38 cases (60.3%) had relapse, and 14 cases (22.2%) were frequent relapse nephrotic syndrome and steroid dependent nephrotic syndrome. Among the 45 patients followed up over 18-year-old, 22 cases (48.9%) had recurrent proteinuria continued to adulthood, 3 cases of SRNS progressed to kidney insufficiency, and one of them developed into end stage kidney disease and was administrated with hemodialysis. Conclusions: Cases over 10-year-old with PNS tend to present with SRNS and renal tubulointerstitial lesions. They have a favorable prognosis, but are liable to relapse in adulthood.

Fine-mapping across diverse ancestries drives the discovery of putative causal variants underlying human complex traits and diseases

Genome-wide association studies (GWAS) of human complex traits or diseases often implicate genetic loci that span hundreds or thousands of genetic variants, many of which have similar statistical significance. While statistical fine-mapping in individuals of European ancestries has made important discoveries, cross-population fine-mapping has the potential to improve power and resolution by capitalizing on the genomic diversity across ancestries. Here we present SuSiEx, an accurate and computationally efficient method for cross-population fine-mapping, which builds on the single-population fine-mapping framework, Sum of Single Effects (SuSiE). SuSiEx integrates data from an arbitrary number of ancestries, explicitly models population-specific allele frequencies and LD patterns, accounts for multiple causal variants in a genomic region, and can be applied to GWAS summary statistics. We comprehensively evaluated SuSiEx using simulations, a range of quantitative traits measured in both UK Biobank and Taiwan Biobank, and schizophrenia GWAS across East Asian and European ancestries. In all evaluations, SuSiEx fine-mapped more association signals, produced smaller credible sets and higher posterior inclusion probability (PIP) for putative causal variants, and captured population-specific causal variants.

Rare genetic variants impact muscle strength

Muscle strength is highly heritable and predictive for multiple adverse health outcomes including mortality. Here, we present a rare protein-coding variant association study in 340,319 individuals for hand grip strength, a proxy measure of muscle strength. We show that the exome-wide burden of rare protein-truncating and damaging missense variants is associated with a reduction in hand grip strength. We identify six significant hand grip strength genes, KDM5B, OBSCN, GIGYF1, TTN, RB1CC1, and EIF3J. In the example of the titin (TTN) locus we demonstrate a convergence of rare with common variant association signals and uncover genetic relationships between reduced hand grip strength and disease. Finally, we identify shared mechanisms between brain and muscle function and uncover additive effects between rare and common genetic variation on muscle strength.

The impact of rare protein coding genetic variation on adult cognitive function

Compelling evidence suggests that human cognitive function is strongly influenced by genetics. Here, we conduct a large-scale exome study to examine whether rare protein-coding variants impact cognitive function in the adult population (n = 485,930). We identify eight genes (ADGRB2, KDM5B, GIGYF1, ANKRD12, SLC8A1, RC3H2, CACNA1A and BCAS3) that are associated with adult cognitive function through rare coding variants with large effects. Rare genetic architecture for cognitive function partially overlaps with that of neurodevelopmental disorders. In the case of KDM5B we show how the genetic dosage of one of these genes may determine the variability of cognitive, behavioral and molecular traits in mice and humans. We further provide evidence that rare and common variants overlap in association signals and contribute additively to cognitive function. Our study introduces the relevance of rare coding variants for cognitive function and unveils high-impact monogenic contributions to how cognitive function is distributed in the normal adult population.

[Clinical and genetic characteristics of young patients with myeloproliferative neoplasms]

Objectives: To investigate the clinical and genetic features of young Chinese patients with myeloproliferative neoplasms (MPN). Methods: In this cross-sectional study, anonymous questionnaires were distributed to patients with MPN patients nationwide. The respondents were divided into 3 groups based on their age at diagnosis: young (≤40 years) , middle-aged (41-60 years) , and elderly (>60 years) . We compared the clinical and genetic characteristics of three groups of MPN patients. Results: 1727 assessable questionnaires were collected. There were 453 (26.2%) young respondents with MPNs, including 274 with essential thrombocythemia (ET) , 80 with polycythemia vera (PV) , and 99 with myelofibrosis. Among the young group, 178 (39.3%) were male, and the median age was 31 (18-40) years. In comparison to middle-aged and elderly respondents, young respondents with MPN were more likely to present with a higher proportion of unmarried status (all P<0.001) , a higher education level (all P<0.001) , less comorbidity (ies) , fewer medications (all P<0.001) , and low-risk stratification (all P<0.001) . Younger respondents experienced headache (ET, P<0.001; PV, P=0.007; MF, P=0.001) at diagnosis, had splenomegaly at diagnosis (PV, P<0.001) , and survey (ET, P=0.052; PV, P=0.063) . Younger respondents had fewer thrombotic events at diagnosis (ET, P<0.001; PV, P=0.011) and during the survey (ET, P<0.001; PV, P=0.003) . JAK2 mutations were found in fewer young people (ET, P<0.001; PV, P<0.001; MF, P=0.013) ; however, CALR mutations were found in more young people (ET, P<0.001; MF, P=0.015) . Furthermore, mutations in non-driver genes (ET, P=0.042; PV, P=0.043; MF, P=0.004) and high-molecular risk mutations (ET, P=0.024; PV, P=0.023; MF, P=0.001) were found in fewer young respondents. Conclusion: Compared with middle-aged and elderly patients, young patients with MPN had unique clinical and genetic characteristics.

Brain expression quantitative trait locus and network analyses reveal downstream effects and putative drivers for brain-related diseases

Identification of therapeutic targets from genome-wide association studies (GWAS) requires insights into downstream functional consequences. We harmonized 8,613 RNA-sequencing samples from 14 brain datasets to create the MetaBrain resource and performed cis- and trans-expression quantitative trait locus (eQTL) meta-analyses in multiple brain region- and ancestry-specific datasets (n ≤ 2,759). Many of the 16,169 cortex cis-eQTLs were tissue-dependent when compared with blood cis-eQTLs. We inferred brain cell types for 3,549 cis-eQTLs by interaction analysis. We prioritized 186 cis-eQTLs for 31 brain-related traits using Mendelian randomization and co-localization including 40 cis-eQTLs with an inferred cell type, such as a neuron-specific cis-eQTL (CYP24A1) for multiple sclerosis. We further describe 737 trans-eQTLs for 526 unique variants and 108 unique genes. We used brain-specific gene-co-regulation networks to link GWAS loci and prioritize additional genes for five central nervous system diseases. This study represents a valuable resource for post-GWAS research on central nervous system diseases.

GWAS quality score for evaluating associated regions in GWAS analyses

MOTIVATION

The number of significantly associated regions reported in genome-wide association studies (GWAS) for polygenic traits typically increases with sample size. A traditional tool for quality control and identification of significant regions has been a visual inspection of how significant and correlated genetic variants cluster within a region. However, while inspecting hundreds of regions, this subjective method can misattribute significance to some loci or neglect others that are significant.

RESULTS

The GWAS quality score (GQS) identifies suspicious regions and prevents erroneous interpretations with an objective, quantitative and automated method. The GQS assesses all measured single nucleotide polymorphisms (SNPs) that are linked by inheritance to each other [linkage disequilibrium (LD)] and compares the significance of trait association of each SNP to its LD value for the reported index SNP. A GQS value of 1.0 ascribes a high level of confidence to the entire region and its underlying gene(s), while GQS values <1.0 indicate the need to closely inspect the outliers. We applied the GQS to published and non-published genome-wide summary statistics and report suspicious regions requiring secondary inspection while supporting the majority of reported regions from large-scale published meta-analyses.

AVAILABILITY AND IMPLEMENTATION

The GQS code/scripts can be cloned from GitHub (https://github.com/Xswapnil/GQS/). The analyst can use whole-genome summary statistics to estimate GQS for each defined region. We also provide an online tool (http://35.227.18.38/) that gives access to the GQS. The quantitative measure of quality attributes by GQS and its visualization is an objective method that enhances the confidence of each genomic hit.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Associations of polygenic risks, depression, and obesity-related traits in Taiwan Biobank

BACKGROUND

The comorbidity of obesity and major depressive disorder (MDD) may be attributable to a bidirectional relationship and shared genetic influence. We aimed to examine the polygenic associations between obesity and MDD and to characterize their corresponding impacts on the obesity mechanism.

METHODS

Genome-wide genotyping was available in 106,604 unrelated individuals from Taiwan Biobank. Polygenic risk score (PRS) for body mass index (BMI) and MDD was derived to evaluate their effects on obesity-related traits. Stratified analyses were performed for the modified effect of depression on the polygenic associations.

RESULTS

The MDD PRS was positively associated with waistline (beta in per SD increase in PRS = 0.12), hipline (beta = 0.08), waist-hip ratio (WHR) (beta = 0.05), body fat rate (beta = 0.08), BMI (beta = 0.05), overweight (OR = 1.02 for BMI ≥ 25), and obesity (OR = 1.05 for BMI ≥ 30). For the synergism between depression and BMI PRS, the presence of active depression symptoms defined by the PHQ-4 (p for interaction < 0.05 for waistline, WHR, and BMI) was more salient than lifetime MDD.

LIMITATIONS

Limitations include recall bias for MDD due to a retrospective self-reporting questionnaire, a low response rate of the PHQ-4 for evaluating active psychological symptoms, and limited generalizability to non-Taiwanese ancestries.

CONCLUSIONS

The shared genetic etiology of obesity and depression was demonstrated. The amplified effect of BMI polygenic effect on obesity for individuals with active depressive symptoms was also characterized. The study may be helpful for designing public health interventions to reduce the disease burden caused by obesity and depression.

FinnGen provides genetic insights from a well-phenotyped isolated population

Population isolates such as those in Finland benefit genetic research because deleterious alleles are often concentrated on a small number of low-frequency variants (0.1% ≤ minor allele frequency < 5%). These variants survived the founding bottleneck rather than being distributed over a large number of ultrarare variants. Although this effect is well established in Mendelian genetics, its value in common disease genetics is less explored^1,2. FinnGen aims to study the genome and national health register data of 500,000 Finnish individuals. Given the relatively high median age of participants (63 years) and the substantial fraction of hospital-based recruitment, FinnGen is enriched for disease end points. Here we analyse data from 224,737 participants from FinnGen and study 15 diseases that have previously been investigated in large genome-wide association studies (GWASs). We also include meta-analyses of biobank data from Estonia and the United Kingdom. We identified 30 new associations, primarily low-frequency variants, enriched in the Finnish population. A GWAS of 1,932 diseases also identified 2,733 genome-wide significant associations (893 phenome-wide significant (PWS), P < 2.6 × 10^-11) at 2,496 (771 PWS) independent loci with 807 (247 PWS) end points. Among these, fine-mapping implicated 148 (73 PWS) coding variants associated with 83 (42 PWS) end points. Moreover, 91 (47 PWS) had an allele frequency of <5% in non-Finnish European individuals, of which 62 (32 PWS) were enriched by more than twofold in Finland. These findings demonstrate the power of bottlenecked populations to find entry points into the biology of common diseases through low-frequency, high impact variants.

Collective genomic segments with differential pleiotropic patterns between cognitive dimensions and psychopathology

Cognitive deficits are known to be related to most forms of psychopathology. Here, we perform local genetic correlation analysis as a means of identifying independent segments of the genome that show biologically interpretable pleiotropic associations between cognitive dimensions and psychopathology. We identify collective segments of the genome, which we call "meta-loci", showing differential pleiotropic patterns for psychopathology relative to either cognitive task performance (CTP) or performance on a non-cognitive factor (NCF) derived from educational attainment. We observe that neurodevelopmental gene sets expressed during the prenatal-early childhood period predominate in CTP-relevant meta-loci, while post-natal gene sets are more involved in NCF-relevant meta-loci. Further, we demonstrate that neurodevelopmental gene sets are dissociable across CTP meta-loci with respect to their spatial distribution across the brain. Additionally, we find that GABA-ergic, cholinergic, and glutamatergic genes drive pleiotropic relationships within dissociable meta-loci.

Taiwan Biobank: A rich biomedical research database of the Taiwanese population

The Taiwan Biobank (TWB) is an ongoing prospective study of >150,000 individuals aged 20-70 in Taiwan. A comprehensive list of phenotypes was collected for each consented participant at recruitment and follow-up visits through structured interviews and physical measurements. Biomarkers and genetic data were generated from blood and urine samples. We present here an overview of TWB's genetic data quality, population structure, and familial relationship, which consists of predominantly Han Chinese ancestry, and highlight its important attributes and genetic findings thus far. A linkage to Taiwan's National Health Insurance database of >25 years and other registries is underway to enrich the phenotypic spectrum and enable deep and longitudinal genetic investigations. TWB provides one of the largest biobank resources for biomedical and public health research in East Asia that will contribute to our understanding of the genetic basis of health and disease in global populations through collaborative studies with other biobanks.

[Effect of P311 microspheres-loaded thermosensitive chitosan hydrogel on the wound healing of full-thickness skin defects in rats]

Objective: To explore the effect of P311 microspheres-loaded thermosensitive chitosan hydrogel on the wound healing of full-thickness skin defects in rats. Methods: The method of experimental study was adopted. The polyvinyl alcohol/sodium alginate microspheres (simple microspheres), P311 microspheres, and bovine serum albumin labeled with fluorescein isothiocyanate (FITC-BSA) microspheres were prepared by water-in-oil emulsification, and then their morphology was observed under a light microscope/inverted fluorescence microscope. Chitosan solution was prepared, chitosan solution and β-glycerol phosphate disodium hydrate were mixed to prepare simple thermosensitive hydrogels, and thermosensitive hydrogels loaded with simple microspheres or P311 microspheres were prepared by adding corresponding substances in simple thermosensitive hydrogels. The morphological changes of the prepared four liquids in the state of tilt was observed at 37 ℃. After being freeze-dried, the micromorphology of the prepared four liquids was observed under a scanning electron microscope. Eighteen 3-4-week-old male Sprague-Dawley rats were divided into normal group without any treatment, dressing group, chitosan group, hydrogel alone group, simple microspheres-loaded hydrogel group, and P311 microspheres-loaded hydrogel group, which were inflicted with one full-thickness skin defect wound on both sides of the back spine and were dealt correspondingly, with 3 rats in each group. Rats with full-thickness skin defects in the five groups were collected, the wound healing was observed on post injury day (PID) 0 (immediately), 5, 10, and 15, and the wound healing rates on PID 5, 10, and 15 were calculated. The wound and wound margin tissue of rats with full-thickness skin defects in the five groups on PID 15 and normal skin tissue in the same site of rats in normal group were collected, hematoxylin and eosin staining was conducted to observe the histological changes, immunohistochemical staining was performed to observe the expressions of CD31 and vascular endothelial growth factor (VEGF), and Western blotting was conducted to detect the protein expressions of CD31 and VEGF. The number of samples was all three. Data were statistically analyzed with one-way analysis of variance, analysis of variance for repeated measurement, and Bonferroni correction. Results: Simple microspheres were spherical, with loose and porous surface. The surfaces of P311 microspheres and FITC-BSA microspheres were smooth without pores, and the FITC-BSA microspheres emitted uniform green fluorescence. The diameters of the three microspheres were basically consistent, being 33.1 to 37.7 μm. Compared with chitosan solution and simple thermosensitive hydrogel, the structures of the two microspheres-loaded hydrogels were more stable in the state of tilt at 37 ℃. The two microspheres-loaded hydrogels had denser network structures than those of chitosan solution and simple thermosensitive hydrogel, and in the cross section of which microspheres with a diameter of about 30 μm could be seen. Within PID 15, the wounds of rats in the five groups were healed to different degrees, and the wound healing of rats in P311 microspheres-loaded hydrogel group was the best. On PID 5, 10, and 15, the wound healing rates of rats in dressing group and chitosan group were (26.6±2.4)%, (38.5±3.1)%, (50.9±1.5)%, (47.6±2.0)%, (58.5±3.6)%, and (66.7±4.1)%, respectively, which were significantly lower than (59.3±4.8)%, (87.6±3.2)%, (97.2±1.0)% in P311 microspheres-loaded hydrogel group (P<0.05 or P<0.01). The wound healing rates of rats in hydrogel alone group on PID 10 and 15, and in simple microspheres-loaded hydrogel group on PID 15 were (76.0±3.3)%, (84.5±3.6)%, and (88.0±2.6)%, respectively, which were significantly lower than those in P311 microspheres-loaded hydrogel group (P<0.05). The epidermis, hair follicles, and sebaceous glands could be seen in the normal skin of rats in normal group, without positive expressions of CD31 or VEGF. The wounds of rats in P311 microspheres-loaded hydrogel group on PID 15 were almost completely epithelialized, with more blood vessels, hair follicles, sebaceous glands, and positive expressions of CD31 and VEGF in the wounds than those of rats with full-thickness skin defects in the other four groups, and more protein expressions of CD31 and VEGF than those of rats in the other five groups. Conclusions: The P311 microspheres-loaded thermosensitive chitosan hydrogel can release the encapsulated drug slowly, prolong the drug action time, and promote wound healing in rats with full-thickness skin defects by promoting wound angiogenesis and re-epithelialization.

Global Biobank Meta-analysis Initiative: Powering genetic discovery across human disease

Biobanks facilitate genome-wide association studies (GWASs), which have mapped genomic loci across a range of human diseases and traits. However, most biobanks are primarily composed of individuals of European ancestry. We introduce the Global Biobank Meta-analysis Initiative (GBMI)-a collaborative network of 23 biobanks from 4 continents representing more than 2.2 million consented individuals with genetic data linked to electronic health records. GBMI meta-analyzes summary statistics from GWASs generated using harmonized genotypes and phenotypes from member biobanks for 14 exemplar diseases and endpoints. This strategy validates that GWASs conducted in diverse biobanks can be integrated despite heterogeneity in case definitions, recruitment strategies, and baseline characteristics. This collaborative effort improves GWAS power for diseases, benefits understudied diseases, and improves risk prediction while also enabling the nomination of disease genes and drug candidates by incorporating gene and protein expression data and providing insight into the underlying biology of human diseases and traits.

Legacy effects of infection in patients with heart failure: a national cohort study of 31,318 patients in Taiwan

Background

Although infection is a common cause of hospitalization in patients (pts) with heart failure (HF), the long-term cardiovascular (CV) prognosis in HF after infection is not well studied.

Methods and results

From 2009 to 2015, 310,485 pts with their first HF admissions and survival to discharge were identified from the National Health Insurance Research Database. Among the pts, 103,505 (33.3%) were readmitted within 1 year after HF discharge for infection, including pneumonia (44.2%), urinary tract infection (UTI) (37.9%), skin and soft tissue infections (9.7%), and others (8.1%). Those without admission for any infection were controls. We compared the primary composite endpoint, including all-cause death, acute myocardial infarction (AMI), stroke, and hospitalization for HF (HHF) between the 2 groups after the infection episode. After propensity score matching, the clinical characteristics (age 71.7±13.9 years, male 52.0%) and treatment were similar between the groups (n=15,659 in each group). In a mean follow-up time of 4.3±2.9 years, 86.2% pts with a history of infection admission and 63.6% pts in the control group met the primary endpoint. Multivariate Cox proportional hazards analysis showed the infection group had a higher risk of the primary composite endpoint (HR 1.760, 95% CI 1.714–1.807), including all-cause death (HR 1.587, 95% CI: 1.540–1.636), HHF (HR 1.993, 95% CI 1.922–2.066), AMI (HR 1.332, 95% CI 1.224–1.450), and stroke (HR 1.769, 95% CI 1.664–1.882). In infection group, HHF was the earliest outcome event with a mean time of 17.5 months and mortality is the second early event with a mean time of 23 months after discharge from the infection episode. Pneumonia carried a higher risk than UTI for the primary composite endpoint (HR 1.140, 95% CI 1.104–1.178).

Conclusions

One-third of HF pts discharged from the hospital experienced acute infection that required readmission. The pts had worse CV prognosis after readmission for infectious disease compared to those without infection

Funding Acknowledgement

Type of funding sources: Private hospital(s). Main funding source(s): This study is supported by National Cheng Kung University Hospital and Tainan Hospital, Ministry of Health and Welfare, Taiwan.

Evaluation of the causal relationship between smoking and schizophrenia in East Asia

Cigarette smoking has been suggested to be associated with the risk of schizophrenia in observational studies. A significant causal effect of smoking on schizophrenia has been reported in European populations using the Mendelian randomization approach; however, no evidence of causality was found in participants from East Asia. Using Taiwan Biobank (TWBB), we conducted genome-wide association studies (GWAS) to identify susceptibility loci for smoking behaviors, including smoking initiation (N = 79,989) and the onset age (N = 15,582). We then meta-analyzed GWAS from TWBB and Biobank Japan (BBJ) with the total sample size of 245,425 for smoking initiation and 46,000 for onset age of smoking. The GWAS for schizophrenia was taken from the East Asia Psychiatric Genomics Consortium, which included 22,778 cases and 35,362 controls. We performed a two-sample Mendelian randomization to estimate the causality of smoking behaviors on schizophrenia in East Asia. In TWBB, we identified one locus that met genome-wide significance for onset age. In a meta-analysis of TWBB and BBJ, we identified two loci for smoking initiation. In Mendelian randomization, genetically predicted smoking initiation (odds ratio (OR) = 4.00, 95% confidence interval (CI) = 0.89–18.01, P = 0.071) and onset age (OR for a per-year increase = 0.96, 95% CI = 0.91–1.01, P = 0.098) were not significantly associated with schizophrenia; the direction of effect was consistent with European Ancestry samples, which had higher statistical power. These findings provide tentative evidence consistent with a causal role of smoking on the development of schizophrenia in East Asian populations.

Causality of abdominal obesity on cognition: a trans-ethnic Mendelian randomization study

BACKGROUND

Obesity has been associated with cognition in observational studies; however, whether its effect is confounding or a reverse causality remains inconclusive. This study aimed to investigate the causal relationships of overall obesity, measured by body mass index (BMI), and abdominal adiposity, measured by waist-hip ratio adjusted for BMI (WHRadjBMI), and cognition across European and Asian populations using Mendelian randomization (MR) analysis.

METHODS

We used publicly available genome-wide association study (GWAS) summary data of European ancestry, including BMI (n = 322,154) and WHRadjBMI (n = 210,088) from the GIANT consortium, and cognition performance (n = 257,828) from the UK Biobank and COGENT consortium. Data for individuals of Asian ancestry were retrieved from Taiwan Biobank to perform GWAS for BMI (n = 65,689), WHRadjBMI (n = 65,683), and Mini-Mental State Examination (MMSE, n = 21,273). MR analysis was carried out using the inverse-variance weighted method for the main results. Further, we examined the overall pleiotropy by MR-Egger intercept, and detected and adjusted for possible outliers using MR PRESSO.

RESULTS

No causal effect of BMI on cognition performance (beta [95% CI] = 0.00 [-0.07, 0.07], p value = 0.91) was found for Europeans; however, a 1-SD increase in WHRadjBMI was associated with a 0.07 standardized score decrease in cognition performance (beta [95% CI] = -0.07 [-0.12, -0.02], p value = 0.006). Further, no causal effect of BMI on MMSE (beta [95% CI] = 0.01 [-0.08, 0.10], p = 0.91) was found for Asians; however, a 1-SD increase in WHRadjBMI was associated with a 0.17 standardized score decrease in MMSE (beta [95% CI] = -0.17 [-0.30, -0.03], p = 0.02). In both populations, overall pleiotropy was not detected, and outliers did not affect the robustness of the main findings.

CONCLUSIONS

This trans-ethnic MR study reveals that abdominal adiposity, as measured by WHR adjusted for BMI, impairs cognition, whereas weak evidence suggests that BMI impairs cognition.

Development and validation of a trans-ancestry polygenic risk score for type 2 diabetes in diverse populations

BACKGROUND

Type 2 diabetes (T2D) is a worldwide scourge caused by both genetic and environmental risk factors that disproportionately afflicts communities of color. Leveraging existing large-scale genome-wide association studies (GWAS), polygenic risk scores (PRS) have shown promise to complement established clinical risk factors and intervention paradigms, and improve early diagnosis and prevention of T2D. However, to date, T2D PRS have been most widely developed and validated in individuals of European descent. Comprehensive assessment of T2D PRS in non-European populations is critical for equitable deployment of PRS to clinical practice that benefits global populations.

METHODS

We integrated T2D GWAS in European, African, and East Asian populations to construct a trans-ancestry T2D PRS using a newly developed Bayesian polygenic modeling method, and assessed the prediction accuracy of the PRS in the multi-ethnic Electronic Medical Records and Genomics (eMERGE) study (11,945 cases; 57,694 controls), four Black cohorts (5137 cases; 9657 controls), and the Taiwan Biobank (4570 cases; 84,996 controls). We additionally evaluated a post hoc ancestry adjustment method that can express the polygenic risk on the same scale across ancestrally diverse individuals and facilitate the clinical implementation of the PRS in prospective cohorts.

RESULTS

The trans-ancestry PRS was significantly associated with T2D status across the ancestral groups examined. The top 2% of the PRS distribution can identify individuals with an approximately 2.5-4.5-fold of increase in T2D risk, which corresponds to the increased risk of T2D for first-degree relatives. The post hoc ancestry adjustment method eliminated major distributional differences in the PRS across ancestries without compromising its predictive performance.

CONCLUSIONS

By integrating T2D GWAS from multiple populations, we developed and validated a trans-ancestry PRS, and demonstrated its potential as a meaningful index of risk among diverse patients in clinical settings. Our efforts represent the first step towards the implementation of the T2D PRS into routine healthcare.

Profiled polyethylene terephthalate filaments that incorporate collagen and calcium phosphate enhance ligamentisation and bone formation

Polyethylene terephthalate (PET) artificial ligaments offer an unlimited source of ligaments without donor-site-related morbidity and with good mechanical properties for a rapid return to sporting activities. Developing PET artificial ligaments with excellent ligamentisation and ligament-bone healing is still a considerable challenge. This study aimed to investigate the effects of the profiled PET/collagen/calcium phosphate (PET/C/CaP) ligament upon cell growth, ligamentisation and ligament-bone healing in vitro and in vivo. Profiled PET/C/CaP filaments were made by melt-spinning process with 2 % CaP hybrid spinning and collagen coating. Rat mesenchymal stem cells (MSCs) were cultured on the profiled PET/C filaments for cytotoxicity, viability, scanning electron microscopy (SEM) and ligament-related gene expression analysis. MSCs' osteogenic capacity on the profiled PET/CaP filaments was identified by detecting osteogenic gene expression and alizarin red S staining. For in vivo verification, an animal study was performed to evaluate the effect of the profiled PET/C/CaP ligament in a rabbit knee medial collateral ligament reinforcement reconstruction model. The graft ligamentisation and bone formation were investigated by SEM, histology, microcomputed tomography and mechanical tests. The profiled PET/C filaments enhanced MSC proliferation and ligament-related gene expression. Furthermore, they enhanced osteogenic gene expression, alkaline phosphatase activity and mineralisation of MSCs. The in vivo study indicated that the profiled PET/C/CaP ligament enhanced ligamentous matrix remodelling and bone formation. Therefore, their use is an effective strategy for promoting MSCs' ligamentous and osteogenic potential in vitro and enhancing ligamentous matrix remodelling and bone formation in vivo.

Familial aggregation and shared genetic loading for major psychiatric disorders and type 2 diabetes

AIMS/HYPOTHESIS

Psychiatric disorders, such as schizophrenia (SCZ), major depressive disorder (MDD) and bipolar disorder (BPD), are highly comorbid with type 2 diabetes. However, the mechanisms underlying such comorbidity are understudied. This study explored the familial aggregation of common psychiatric disorders and type 2 diabetes by testing family history association, and investigated the shared genetic loading between them by testing the polygenic risk score (PRS) association.

METHODS

A total of 105,184 participants were recruited from the Taiwan Biobank, and genome-wide genotyping data were available for 95,238 participants. The Psychiatric Genomics Consortium-derived PRS for SCZ, MDD and BPD was calculated. Logistic regression was used to estimate the OR with CIs between a family history of SCZ/MDD/BPD and a family history of type 2 diabetes, and between the PRS and the risk of type 2 diabetes.

RESULTS

A family history of type 2 diabetes was associated with a family history of SCZ (OR 1.23, 95% CI 1.08, 1.40), MDD (OR 1.19, 95% CI 1.13, 1.26) and BPD (OR 1.26, 95% CI 1.15, 1.39). Compared with paternal type 2 diabetes, maternal type 2 diabetes was associated with a higher risk of a family history of SCZ. SCZ PRS was negatively associated with type 2 diabetes in women (OR 0.92, 95% CI 0.88, 0.97), but not in men; the effect of SCZ PRS reduced after adjusting for BMI. MDD PRS was positively associated with type 2 diabetes (OR 1.04, 95% CI 1.00, 1.07); the effect of MDD PRS reduced after adjusting for BMI or smoking. BPD PRS was not associated with type 2 diabetes.

CONCLUSIONS/INTERPRETATION

The comorbidity of type 2 diabetes with psychiatric disorders may be explained by shared familial factors. The shared polygenic loading between MDD and type 2 diabetes implies not only pleiotropy but also a shared genetic aetiology for the mechanism behind the comorbidity. The negative correlation between polygenic loading for SCZ and type 2 diabetes implies the role of environmental factors.

Mapping genomic loci implicates genes and synaptic biology in schizophrenia

Schizophrenia has a heritability of 60-80%1, much of which is attributable to common risk alleles. Here, in a two-stage genome-wide association study of up to 76,755 individuals with schizophrenia and 243,649 control individuals, we report common variant associations at 287 distinct genomic loci. Associations were concentrated in genes that are expressed in excitatory and inhibitory neurons of the central nervous system, but not in other tissues or cell types. Using fine-mapping and functional genomic data, we identify 120 genes (106 protein-coding) that are likely to underpin associations at some of these loci, including 16 genes with credible causal non-synonymous or untranslated region variation. We also implicate fundamental processes related to neuronal function, including synaptic organization, differentiation and transmission. Fine-mapped candidates were enriched for genes associated with rare disruptive coding variants in people with schizophrenia, including the glutamate receptor subunit GRIN2A and transcription factor SP4, and were also enriched for genes implicated by such variants in neurodevelopmental disorders. We identify biological processes relevant to schizophrenia pathophysiology; show convergence of common and rare variant associations in schizophrenia and neurodevelopmental disorders; and provide a resource of prioritized genes and variants to advance mechanistic studies.

The burden of rare protein-truncating genetic variants on human lifespan

Genetic predisposition has been shown to contribute substantially to the age at which we die. Genome-wide association studies (GWASs) have linked more than 20 loci to phenotypes related to human lifespan¹. However, little is known about how lifespan is impacted by gene loss of function. Through whole-exome sequencing of 352,338 UK Biobank participants of European ancestry, we assessed the relevance of protein-truncating variant (PTV) gene burden on individual and parental survival. We identified four exome-wide significant (P < 4.2 × 10^-7) human lifespan genes, BRCA1, BRCA2, ATM and TET2. Gene and gene-set, PTV-burden, phenome-wide association studies support known roles of these genes in cancer to impact lifespan at the population level. The TET2 PTV burden was associated with a lifespan through somatic mutation events presumably due to clonal hematopoiesis. The overlap between PTV burden and common variant-based lifespan GWASs was modest, underscoring the value of exome sequencing in well-powered biobank cohorts to complement GWASs for identifying genes underlying complex traits.

Enhancing Discovery of Genetic Variants for Posttraumatic Stress Disorder Through Integration of Quantitative Phenotypes and Trauma Exposure Information

BACKGROUND

Posttraumatic stress disorder (PTSD) is heritable and a potential consequence of exposure to traumatic stress. Evidence suggests that a quantitative approach to PTSD phenotype measurement and incorporation of lifetime trauma exposure (LTE) information could enhance the discovery power of PTSD genome-wide association studies (GWASs).

METHODS

A GWAS on PTSD symptoms was performed in 51 cohorts followed by a fixed-effects meta-analysis (N = 182,199 European ancestry participants). A GWAS of LTE burden was performed in the UK Biobank cohort (N = 132,988). Genetic correlations were evaluated with linkage disequilibrium score regression. Multivariate analysis was performed using Multi-Trait Analysis of GWAS. Functional mapping and annotation of leading loci was performed with FUMA. Replication was evaluated using the Million Veteran Program GWAS of PTSD total symptoms.

RESULTS

GWASs of PTSD symptoms and LTE burden identified 5 and 6 independent genome-wide significant loci, respectively. There was a 72% genetic correlation between PTSD and LTE. PTSD and LTE showed largely similar patterns of genetic correlation with other traits, albeit with some distinctions. Adjusting PTSD for LTE reduced PTSD heritability by 31%. Multivariate analysis of PTSD and LTE increased the effective sample size of the PTSD GWAS by 20% and identified 4 additional loci. Four of these 9 PTSD loci were independently replicated in the Million Veteran Program.

CONCLUSIONS

Through using a quantitative trait measure of PTSD, we identified novel risk loci not previously identified using prior case-control analyses. PTSD and LTE have a high genetic overlap that can be leveraged to increase discovery power through multivariate methods.

Sex-Dependent Shared and Nonshared Genetic Architecture Across Mood and Psychotic Disorders

BACKGROUND

Sex differences in incidence and/or presentation of schizophrenia (SCZ), major depressive disorder (MDD), and bipolar disorder (BIP) are pervasive. Previous evidence for shared genetic risk and sex differences in brain abnormalities across disorders suggest possible shared sex-dependent genetic risk.

METHODS

We conducted the largest to date genome-wide genotype-by-sex (G×S) interaction of risk for these disorders using 85,735 cases (33,403 SCZ, 19,924 BIP, and 32,408 MDD) and 109,946 controls from the PGC (Psychiatric Genomics Consortium) and iPSYCH.

RESULTS

Across disorders, genome-wide significant single nucleotide polymorphism-by-sex interaction was detected for a locus encompassing NKAIN2 (rs117780815, p = 3.2 × 10-8), which interacts with sodium/potassium-transporting ATPase (adenosine triphosphatase) enzymes, implicating neuronal excitability. Three additional loci showed evidence (p < 1 × 10-6) for cross-disorder G×S interaction (rs7302529, p = 1.6 × 10-7; rs73033497, p = 8.8 × 10-7; rs7914279, p = 6.4 × 10-7), implicating various functions. Gene-based analyses identified G×S interaction across disorders (p = 8.97 × 10-7) with transcriptional inhibitor SLTM. Most significant in SCZ was a MOCOS gene locus (rs11665282, p = 1.5 × 10-7), implicating vascular endothelial cells. Secondary analysis of the PGC-SCZ dataset detected an interaction (rs13265509, p = 1.1 × 10-7) in a locus containing IDO2, a kynurenine pathway enzyme with immunoregulatory functions implicated in SCZ, BIP, and MDD. Pathway enrichment analysis detected significant G×S interaction of genes regulating vascular endothelial growth factor receptor signaling in MDD (false discovery rate-corrected p < .05).

CONCLUSIONS

In the largest genome-wide G×S analysis of mood and psychotic disorders to date, there was substantial genetic overlap between the sexes. However, significant sex-dependent effects were enriched for genes related to neuronal development and immune and vascular functions across and within SCZ, BIP, and MDD at the variant, gene, and pathway levels.

Response to comment on "Evaluating the cardiovascular safety of sclerostin inhibition using evidence from meta-analysis of clinical trials and human genetics"

Triangulation of evidence from clinical trials and human genetics suggests a potential excess risk of cardiovascular disease events arising from therapeutic inhibition of sclerostin.

Pairwise effects between lipid GWAS genes modulate lipid plasma levels and cellular uptake

Complex traits are characterized by multiple genes and variants acting simultaneously on a phenotype. However, studying the contribution of individual pairs of genes to complex traits has been challenging since human genetics necessitates very large population sizes, while findings from model systems do not always translate to humans. Here, we combine genetics with combinatorial RNAi (coRNAi) to systematically test for pairwise additive effects (AEs) and genetic interactions (GIs) between 30 lipid genome-wide association studies (GWAS) genes. Gene-based burden tests from 240,970 exomes show that in carriers with truncating mutations in both, APOB and either PCSK9 or LPL ("human double knock-outs") plasma lipid levels change additively. Genetics and coRNAi identify overlapping AEs for 12 additional gene pairs. Overlapping GIs are observed for TOMM40/APOE with SORT1 and NCAN. Our study identifies distinct gene pairs that modulate plasma and cellular lipid levels primarily via AEs and nominates putative drug target pairs for improved lipid-lowering combination therapies.

Thrombosis and major bleeding risk after primary percutaneous coronary intervention among patients with multi-vessels coronary artery disease

Background and aims

The present study aimed to develop and validate separate risk prediction models for thrombosis events (TEs) and major bleeding (MB) in patients with multi-vessel coronary artery lesions who had undergone primary percutaneous coronary intervention (PCI).

Methods and results

TEs were defined as the composite of myocardial infarction recurrence or ischemic cerebrovascular events, whereas MB was defined as the occurrence of bleeding academic research consortium (BARC) 3 or 5 bleeding. The derivation and validation cohorts comprised 2976 patients who underwent primary PCI between January 2010 and June 2017. At a median follow-up of 3.07 years (1122 days), TEs and MB occurred in 167 and 98 patients, respectively. Independent predictors of TEs were older age, prior PCI, non-ST elevated MI (NSTEMI), and stent thrombosis (ST). Independent predictors of MB were triple therapy at discharge, coronary artery bifurcation lesions, lesion restenosis, target lesion of the left main coronary artery, and PTCA. In the derivation and validation cohorts, the areas under the curve were 0.817 and 0.820 for thrombosis and 0.886 and 0.976 for bleeding, respectively. In the derivation cohort, high thrombotic risk (n=755) was associated with a higher 3-year incidence of TEs, major adverse cardiovascular events (MACEs), and all-cause death, compared to low risk (n=1275) (p=0.0022, 0.019, 0.012, respectively). High bleeding risk (n=1675) was associated with a higher incidence of bleeding, MACEs, cardiac death, compared to low risk (n=355) (p&lt;0.0001).

Conclusion

Simple risk scores can be useful in predicting the risks of ischemic and bleeding events after primary PCI, thereby stratifying thrombotic or MB risks and facilitating clinical decisions.

Funding Acknowledgement

Type of funding sources: Foundation. Main funding source(s): This study was supported by the Chinese Academy of Medical Sciences Innovation Fund for Medical Sciences (2016-I2M-1–009), National Natural Science Funds (number: 81970308) and the Fund of “Sanming” Project of Medicine in Shenzhen (number: SZSM201911017). Figure 2Figure 3

Phenotypic and genetic correlations of pork myoglobin content with meat colour and other traits in an eight breed-crossed heterogeneous population

Meat colour is one of the most important meat quality traits affecting consumption desire. Genetic improvement for meat colour traits is not so easy because pigs can be phenotyped only after slaughter. Besides the parameters from the optical instrument, other indexes that reflect the material basis of meat colour should be measured accurately and used in the genomic analysis. Myoglobin (Mb) is the main chemical component determining meat colour. However, to what extent the Mb content contributes to meat colour, and whether it can be used as a trait for pig breeding to improve meat colour, and the correlations of Mb content with complex porcine traits are largely unknown. To address these questions, we measured the muscle Mb content in 624 pigs from the 7th generation of a specially designed eight breed-crossed pig heterogeneous population, evaluated its phenotypic and genetic correlations with longissimus thoracis colour score at 24 h after slaughter. More than that, we also systematically phenotyped more than 100 traits on these animals to evaluate the potential correlations between muscle Mb content and economically important traits. Our results showed that the average muscle Mb content in the 624 pigs was 1.00 mg/g, ranging from 0.51 to 2.17 mg/g. We found that higher Mb content usually correlated with favourable meat colour, higher marbling score, less moisture content, and less drip loss. Genetic correlation analysis between muscle Mb content and 101 traits measured in this study shows that Mb content is also significantly correlated with 31 traits, including marbling, shear force, firmness, and juiciness. To our knowledge, this is one of the largest studies about the correlations of muscle Mb content with as many as 100 various traits in a large-scale genetically diversified population. Our results showed that the Mb content could be a selection parameter for the genetic improvement of meat colour. The selection for higher Mb content will also benefit marbling, shear force, firmness, and overall liking but might not affect the growth, carcass, and fat deposition traits.

Identifying nootropic drug targets via large-scale cognitive GWAS and transcriptomics

Broad-based cognitive deficits are an enduring and disabling symptom for many patients with severe mental illness, and these impairments are inadequately addressed by current medications. While novel drug targets for schizophrenia and depression have emerged from recent large-scale genome-wide association studies (GWAS) of these psychiatric disorders, GWAS of general cognitive ability can suggest potential targets for nootropic drug repurposing. Here, we (1) meta-analyze results from two recent cognitive GWAS to further enhance power for locus discovery; (2) employ several complementary transcriptomic methods to identify genes in these loci that are credibly associated with cognition; and (3) further annotate the resulting genes using multiple chemoinformatic databases to identify "druggable" targets. Using our meta-analytic data set (N = 373,617), we identified 241 independent cognition-associated loci (29 novel), and 76 genes were identified by 2 or more methods of gene identification. Actin and chromatin binding gene sets were identified as novel pathways that could be targeted via drug repurposing. Leveraging our transcriptomic and chemoinformatic databases, we identified 16 putative genes targeted by existing drugs potentially available for cognitive repurposing.

CgPBA1 may be involved in nuclear degradation during secretory cavity formation by programmed cell death in Citrus grandis 'Tomentosa' fruits

Caspase-3 is the crucial executor caspase of apoptosis in mammalian cells, which is essential for chromatin condensation and DNA fragmentation. Although plants have no caspase-3 homologs, PBA1 acts as a plant caspase-3-like enzyme in plant programmed cell death (PCD). PCD occurs during the formation of secretory cavities in Citrus fruits; hence, secretory cavities could be utilized as a new cell biology model for investigating the regulatory mechanisms of plant PCD. To further study the association between PBA1 and PCD during secretory cavity development in Citrus fruits, CgPBA1 was identified in the fruit of Citrus grandis 'Tomentosa'. The temporal and spatial expression of CgPBA1 during secretory cavity development were analyzed using quantitative real-time PCR and in situ hybridization, and the morphological changes in the apoptotic cell nuclei were observed using TUNEL assay and ultra-thin section technology. The results revealed that the full-length cDNA of CgPBA1 contains a 711 bp ORF that encodes a putative protein containing 236 amino acid with a proteasome-β-6 functional domain that belongs to the Ntn hydrolase super family. CgPBA1 was predominantly expressed in the secretory cavities; its expression changes coincided with the morphological changes and DNA fragmentation in apoptotic cell nuclei. The green fluorescent fusion protein of CgPBA1 is also located in the nucleus of tobacco epidermal cells. Based on previous research and the findings of the present study, we speculate that CgPBA1 is a highly functional conserved protein in plants, and it might be involved in nuclear degradation during PCD for secretory cavity formation in C. grandis 'Tomentosa' fruits.

Identifying drug targets for neurological and psychiatric disease via genetics and the brain transcriptome

Discovering drugs that efficiently treat brain diseases has been challenging. Genetic variants that modulate the expression of potential drug targets can be utilized to assess the efficacy of therapeutic interventions. We therefore employed Mendelian Randomization (MR) on gene expression measured in brain tissue to identify drug targets involved in neurological and psychiatric diseases. We conducted a two-sample MR using cis-acting brain-derived expression quantitative trait loci (eQTLs) from the Accelerating Medicines Partnership for Alzheimer’s Disease consortium (AMP-AD) and the CommonMind Consortium (CMC) meta-analysis study (n = 1,286) as genetic instruments to predict the effects of 7,137 genes on 12 neurological and psychiatric disorders. We conducted Bayesian colocalization analysis on the top MR findings (using P<6x10^-7 as evidence threshold, Bonferroni-corrected for 80,557 MR tests) to confirm sharing of the same causal variants between gene expression and trait in each genomic region. We then intersected the colocalized genes with known monogenic disease genes recorded in Online Mendelian Inheritance in Man (OMIM) and with genes annotated as drug targets in the Open Targets platform to identify promising drug targets. 80 eQTLs showed MR evidence of a causal effect, from which we prioritised 47 genes based on colocalization with the trait. We causally linked the expression of 23 genes with schizophrenia and a single gene each with anorexia, bipolar disorder and major depressive disorder within the psychiatric diseases and 9 genes with Alzheimer’s disease, 6 genes with Parkinson’s disease, 4 genes with multiple sclerosis and two genes with amyotrophic lateral sclerosis within the neurological diseases we tested. From these we identified five genes (ACE, GPNMB, KCNQ5, RERE and SUOX) as attractive drug targets that may warrant follow-up in functional studies and clinical trials, demonstrating the value of this study design for discovering drug targets in neuropsychiatric diseases.

Genetic association studies have been successful in identifying many genetic variants associated with disease risk, but it has been far more challenging to determine the genes through which these act. This is important, because such genes may encode effective drug targets for these diseases. We used Mendelian randomization (MR) and colocalization, two methods which in combination exploit these genetic variants to estimate the causal effects of individual genes. We applied this approach to 12 neurological and psychiatric diseases using data from the AMP-AD and CMC brain expression quantitative locus dataset, which is large enough to provide robust evidence for the relationship between genetic variants and gene expression. We found a causal relationship between the change in expression of 47 genes and increased disease risk across the 12 diseases we tested. As drug targets with human genetic evidence are far more likely to be approved in clinical trials, these findings provide a valuable list of potential therapeutic targets, including the ACE, GPNMB, KCNQ5, RERE and SUOX genes.

[A new strategy for non-invasive diagnosis of liver diseases: DSA-FACE technology based-glycomics method]

Chronic liver disease has gradually become a serious health problem worldwide. Liver biopsy is the current gold standard to assess liver lesions; however, it is an invasive procedure that may cause severe complications. Therefore, there is an urgent need for an economical and rapid non-invasive detection method that can be used in clinic for diagnosis. In the past decade, protein glycosylation has become a research hotspot, and the concept of changes in serum proteoglycans structure has gradually been accepted by many researchers as an indication of liver injury. At the same time, N-linked glycans via DNA sequencing equipment-Fluorophore Assisted Carbohydrate Electrophoresis (DSA-FACE) has also brought high sensitivity and specificity diagnostic models (GlycoHepatoTest) for various chronic liver diseases, which is a new strategy for non-invasive diagnosis of liver diseases.

[Application of serum N -glycan profiling diagnostic model in evaluation of liver fibrosis in patients with hepatitis C]

Objective: To study the changes of serum N-glycan abundance in patients with liver fibrosis at different stages of hepatitis C, and to establish and evaluate the diagnostic model for clinical application value. Methods: Data of 169 hepatitis C virus-infected cases with liver fibrosis were enrolled. Nine kinds of serum N-glycans were detected and analyzed using DNA sequencer-assisted fluorophore-assisted capillary electrophoresis technology. A binary logistics regression method was used to establish a diagnostic model based on the changes in the relative content of N-glycans in each stage of liver fibrosis. Receiver operating characteristic curve was used to evaluate and compare the diagnostic efficacy with other liver fibrosis diagnostic models. Results: N-glycan diagnostic model (B and C) had highest AUROC= 0.776, 0.827 for distinguishing fibrosis S1~S2 to S3~S4 and S1~S3 to S4 than GlycoFibroTest (AUROC = 0.760, 0.807), GlycoCirrhoTest (AUROC = 0.722, 0.787), aspartate aminotransferase to platelet ratio index (AUROC = 0.755, 0.751), FIB-4 index (AUROC = 0.730, 0.774), and S-index (AUROC = 0.707, 0.744). However, the diagnostic efficacy of model A (AUROC = 0.752) for distinguishing fibrosis S1 with S2~S4 had lower diagnostic potency than that of the aspartate aminotransferase to platelet ratio index (AUROC = 0.807). Diagnostic efficiency was improved when the N-glycan profiling and the aspartate aminotransferase to platelet ratio index were combined to diagnose liver fibrosis in each stage, and the area under the receiver operating characteristic curve was 0.839, 0.825, and 0.837, respectively. Conclusion: The serum N-glycan profiling diagnostic model has potential clinical application value in the diagnosis of liver fibrosis in patients with hepatitis C.