European Ancestry Research Articles

Neurocognitive correlates of polygenic risk for bipolar disorder among youth with and without bipolar disorder

IntroductionThere is well-established evidence of reduced neurocognitive performance in adults and youth with bipolar disorder (BD). However, little is known about the polygenic underpinnings of neurocognition in individuals with BD, particularly in youth. The current study aimed to examine the association between polygenic risk score for BD (BD-PRS) and neurocognition among youth with BD and healthy controls (HC). Methods129 youth of European ancestry (72 BD, 57 HC), ages 13–20 years, were included. Six neurocognitive tasks within the Cambridge Neuropsychological Test Automated Battery were assessed. General linear models were used to examine the association between BD-PRS and neurocognitive composite scores, controlling for age, sex, IQ, and two genetic principal components. ResultsIn the overall sample, higher BD-PRS was associated with significantly poorer affective processing (β = −0.25, p = 0.01), decision-making (β = −0.23, p = 0.02), and sustained attention (β = −0.28, p = 0.002). Secondary analyses revealed that higher BD-PRS was associated with significantly poorer sustained attention within the BD group (β = −0.27, p = 0.04), and with significantly poorer affective processing within the HC group (β = −0.29, p = 0.04). LimitationsCross-sectional design. Modest sample size may have reduced power to detect smaller effect sizes. ConclusionThe current study found that higher BD-PRS generated based on adult GWAS was associated with poorer neurocognitive performance in youth with BD and HC. Future longitudinal studies incorporating repeated neurocognitive assessments would further inform whether the associations of BD-PRS with neurocognition vary from youth to adulthood, and whether BD-PRS is associated with differential neurodevelopmental trajectories in individuals with and without BD.

The prevalence of hyperlipoproteinemia(a) in outpatient cardiology clinic patients of European ancestry: results from a STAR-Lp(a) cross-sectional study.

Elevated lipoprotein(a) [Lp(a)] is independently associated with an increased risk of cardiovascular disease (CVD). Evaluating the levels of Lp(a) among patients of European ancestry referred to outpatient cardiology clinics. We included 2475 consecutive patients referred to outpatient cardiology clinics between March 2022 and January 2024. We excluded all patients with atherosclerotic cardiovascular disease, heart failure, significant valve disease, and aortic aneurysm. The median age of the 2475 study participants (of which 1724 [69.7%] were women) was 66.0 years [53.0-73.0 years]). An Lp(a) level of ≥30 mg/dL (≥75 nmol/L) was recorded in 21.5% and a level of ≥50 mg/dL (≥125 nmol/L) was recorded in 13.5% of patients. In univariable analysis the level of Lp(a) was significantly associated with hypertension, sleep apnea, migraine, polycystic ovary syndrome, physical activity, fasting blood glucose, HbA1c, LDL, and non-HDL cholesterol. Being female (β±SE 0.06±0.02), atrial fibrillation (0.05±0.02), HbA1c (0.14±0.02), and LDL cholesterol (0.09±0.02) were independently related to the level of Lp(a). Atrial fibrillation (odds ratio [OR] 1.80, 95%CI:1.01-3.19), migraine (0.51, 0.32-0.83) and hyperlipidemia (1.56, 1.22-1.99) were related to Lp(a) ≥30 mg/dL (≥75 nmol/L), while being female (1.46, 1.10-1.92), hyperlipidemia (1.49, 1.12-1.97), hypertension (1.42, 1.10-1.84) and HbA1c (0.84, 0.72-0.96) were related to Lp(a) ≥50 mg/dL (≥125 nmol/L). The prevalence of increased Lp(a) concentration among patients of European ancestry consulting with cardiologists is 21.5%. Being female, hypertension, atrial fibrillation, migraine, LDL-C, and HbA1c concentration are independently related to the level of Lp(a) in this population.

Genetically-predicted effects of lifestyle factors on frailty: Evidence from Mendelian randomization study

ObjectiveTo evaluate the causal relationships between genetically predicted lifestyle factors and frailty using Mendelian randomization(MR). MethodsWe extracted summary data from genome-wide association studies conducted among individuals of European ancestry, examining lifestyle factors such as smoking, alcohol consumption, physical activity, and sedentary behaviors. The outcomes were assessed using Fried Frailty Score (FFS) and Frailty Index (FI). We conducted 2-sample single-variable Mendelian randomization (SVMR) and multivariable Mendelian randomization (MVMR) to simultaneously assess the independent causal effects were primarily estimated using inverse variance weighted methods. Multiple sensitivity and validation analyzes were used. ResultsThe IVW analyzes indicated that smoking increased frailty risk (FFS: β = 0.107, 95 % CI = 0.057 to 0.156, P < 0.001; FI: β = 0.899, 95 % CI = 0.016 to 0.191, P = 0.020.), this effect was amplified in the MVMR analysis after adjusting for alcohol consumption. Strenuous sports or other exercise(SSOE) reduced frailty risk (FFS: β = -0.473, 95 % CI = -0.646 to -0.299, P < 0.001; FI: β = -0.423, 95 % CI = -0.692 to -0.154, P = 0.002). Vigorous and moderate-to-vigorous physical activities were significantly related to lower FFS, although no effects were observed on FI. Increased television watching was linked to higher frailty incidence (FFS: β = 0.227, 95 % CI = 0.197 to 0.257, P < 0.001; FI: β = 0.297, 95 % CI = 0.249 to 0.346, P < 0.001), the impact remained persistent in MVMR adjusting for driving and computer use. ConclusionThis study suggests that modifications in smoking, alcohol consumption, and physical activity may help prevent or manage frailty.

Identification of Potential Causal Genes for Neurodegenerative Diseases by Mitochondria-Related Genome-Wide Mendelian Randomization.

Current research lacks comprehensive investigations into the potential causal link between mitochondrial-related genes and the risk of neurodegenerative diseases (NDDs). We aimed to identify potential causative genes for five NDDs through an examination of mitochondrial-related gene expression levels. Through the integration of summary statistics from expression quantitative trait loci (eQTL) datasets (human blood and brain tissue), mitochondrial DNA copy number (mtDNA-CN), and genome-wide association studies (GWAS) datasets of five NDDs from European ancestry, we conducted a Mendelian randomization (MR) analysis to explore the potential causal relationship between mitochondrial-related genes and Alzheimer's disease (AD), Parkinson's disease (PD), amyotrophic lateral sclerosis (ALS), frontotemporal dementia (FTD), and Lewy body dementia (LBD). Sensitivity analysis and Bayesian colocalization were employed to validate this causal relationship. Through MR analysis, we have identified potential causal relationships between 12 mitochondria-related genes and AD, PD, ALS, and FTD overlapping with motor neuron disease (FTD_MND) in human blood or brain tissue. Bayesian colocalization analysis further confirms 9 causal genes, including NDUFS2, EARS2, and MRPL41 for AD; NDUFAF2, MALSU1, and METTL8 for PD; MYO19 and MRM1 for ALS; and FASTKD1 for FTD_MND. Importantly, in both human blood and brain tissue, NDUFS2 exhibits a significant pathogenic effect on AD, while NDUFAF2 demonstrates a robust protective effect on PD. Additionally, the mtDNA-CN plays a protected role in LBD (OR = 0.62, p = 0.031). This study presents evidence establishing a causal relationship between mitochondrial dysfunction and NDDs. Furthermore, the identified candidate genes may serve as potential targets for drug development aimed at preventing NDDs.

Genetic liability to higher frailty index may increase the risk of ophthalmic disease.

Frailty and age-related eye diseases are common in older people; however, whether there is a causal link remains unknown. We aimed to explore the causal associations between the frailty index (FI) and ophthalmic traits and identify modifiable mediators. Linkage disequilibrium score regression and two-sample Mendelian randomization were applied to identify genetic correlations and causal associations between FI and ophthalmic traits. Summary data for FI was obtained from a genome-wide association study that included 175,226 individuals of European ancestry. Summary-level statistics for ophthalmic traits were obtained from relative GWASs. Summary-level data for cardiovascular risk factors, inflammatory biomarkers, and the central nervous system were used to identify the possible mediators. FI had a significant genetic correlation with 10 ophthalmic traits. Per SD increment of FI, the odds ratio was 1.329 (95% CI, 1.123, 1.573; P = 9.5 × 10-4) for cataracts, 1.825 (95% CI, 1.115, 2.986; P = 0.016) for keratitis, 1.798 (95% CI, 1.039, 3.11; P = 0.036) for disorders of vitreous body and 1.478 (95% CI, 1.005, 2.173; P = 0.046) for disorders of sclera, cornea, iris and ciliary body. The MR effect estimates of FI on ophthalmic traits were attenuated after adjusting for mental disorders, type 2 diabetes, triglyceride, and interleukin-8 (IL-8) levels. This study reports a genetic correlation and causal association between FI and ophthalmic traits, in which mental disorders, type 2 diabetes, triglycerides, and IL-8 may play a mediating role. These findings highlight a possible method to reduce the risk of FI-related ophthalmic diseases.

Causal effects of serum calcium, phosphate, and 25-hydroxyvitamin D on kidney function: a genetic correlation, pleiotropic analysis, and Mendelian randomization study.

Existing studies investigating the impact of serum calcium (Ca), phosphate (P), 25 hydroxyvitamin D (25[OH]D), and parathyroid hormone (PTH) levels on kidney function have produced inconsistent results. Further research is needed to establish the direct causal relationship between these factors and kidney function. The study used genome-wide association study datasets for exposure and outcome, mainly derived from the UK Biobank and CKDGen Consortium, with sample sizes ranging from 3,310 to 480,699 individuals of European ancestry. Heritability and genetic correlations among these phenotypes were assessed using linkage disequilibrium score regression (LDSC) and phenotypes with a heritability z-score <4 were excluded from further analyses. Pleiotropic analyses were performed to identify potential horizontal pleiotropic variants at gene and LD-independent locus levels. Mendelian randomization (MR) analysis, using instrumental variables (IVs) based on two distinct selection criteria, was conducted to investigate the potential causal relationships between serum Ca, P, 25(OH)D, PTH, and kidney function. PTH was excluded from further analysis due to a heritability z-score < 4. Genetic correlations were observed between serum Ca and urine albumin-to-creatinine ratio (UACR) (rg = 0.202, P-value = 5.0E-04), between serum 25(OH)D and estimated glomerular filtration rate using serum creatinine (eGFRcrea) (rg = -0.094; P-value = 1.4E-05), and between serum 25(OH)D and blood urea nitrogen (BUN) (rg = 0.127; P-value = 1.7E-06). In univariable MR analysis using IVs based on two different selection criteria, it consistently demonstrated that genetically predicted serum Ca consistently showed an increase in UACR (beta 0.11, P-value 2.0E-03; beta 0.13, P-value 2.0E-04). Similarly, serum P was associated with a decrease in eGFRcrea (beta -0.01, P-value 2.0E-04; beta -0.005, P-value 2.0E-03) and an increase in BUN (beta 0.02, P-value 3.0E-03; beta 0.02, P-value 7.5E-07). The influence of serum P on kidney function was further supported in multivariable MR analysis. However, genetically predicted 25(OH)D did not have a significant impact on kidney function. Elevated serum Ca or P levels could both impair kidney function, whereas 25(OH)D has no impact on renal function.

Proteome-wide mendelian randomization identifies novel therapeutic targets for chronic kidney disease.

There is an urgent need to pinpoint novel targets for drug discovery in the context of chronic kidney disease (CKD), and the proteome represents a significant pool of potential therapeutic targets. To address this, we performed proteome-wide analyses using Mendelian randomization (MR) and colocalization techniques to uncover potential targets for CKD. We extracted summary-level data from the ARIC study, focusing on 7213 European American (EA) individuals and 4657 plasma proteins. To broaden our analysis, we incorporated genetic association data from Icelandic cohorts, thereby enhancing our investigation into the correlations with chronic kidney disease (CKD), creatinine-based estimated glomerular filtration rate (eGFRcrea), and estimated glomerular filtration rate (eGFR). We utilized genetic association data from the GWAS Catalog, including CKD (765,348, 625,219 European ancestry and 140,129 non-European ancestry), eGFRcrea (1,004,040, European ancestry), and eGFR (567,460, European ancestry). Employing MR analysis, we estimated the associations between proteins and CKD risk. Additionally, we conducted colocalization analysis to evaluate the existence of shared causal variants between the identified proteins and CKD. We detected notable correlations between levels predicted based on genetics of three circulating proteins and CKD, eGFRcrea, and eGFR. Notably, our colocalization analysis provided robust evidence supporting these associations. Specifically, genetically predicted levels of Transcription elongation factor A protein 2 (TCEA2) and Neuregulin-4 (NRG4) exhibited an inverse relationship with CKD risk, while Glucokinase regulatory protein (GCKR) showed an increased risk of CKD. Furthermore, our colocalization analysis also supported the associations of TCEA2, NRG4, and GCKR with the risk of eGFRcrea and eGFR.

Whole genome sequencing analysis identifies sex differences of familial pattern contributing to phenotypic diversity in autism

BackgroundWhole-genome sequencing (WGS) analyses have found higher genetic burden in autistic females compared to males, supporting higher liability threshold in females. However, genomic evidence of sex differences has been limited to European ancestry to date and little is known about how genetic variation leads to autism-related traits within families across sex.MethodsTo address this gap, we present WGS data of Korean autism families (n = 2255) and a Korean general population sample (n = 2500), the largest WGS data of East Asian ancestry. We analyzed sex differences in genetic burden and compared with cohorts of European ancestry (n = 15,839). Further, with extensively collected family-wise Korean autism phenotype data (n = 3730), we investigated sex differences in phenotypic scores and gene-phenotype associations within family.ResultsWe observed robust female enrichment of de novo protein-truncating variants in autistic individuals across cohorts. However, sex differences in polygenic burden varied across cohorts and we found that the differential proportion of comorbid intellectual disability and severe autism symptoms mainly drove these variations. In siblings, males of autistic females exhibited the most severe social communication deficits. Female siblings exhibited lower phenotypic severity despite the higher polygenic burden than male siblings. Mothers also showed higher tolerance for polygenic burden than fathers, supporting higher liability threshold in females.ConclusionsOur findings indicate that genetic liability in autism is both sex- and phenotype-dependent, expanding the current understanding of autism’s genetic complexity. Our work further suggests that family-based assessments of sex differences can help unravel underlying sex-differential liability in autism.

Causal relationship between allergic rhinitis and otitis media: A Mendelian randomization study.

Otitis media and allergic rhinitis are prevalent conditions. Some data posit a significant association between the 2 ailments, proposing mechanisms such as allergic rhinitis-induced Eustachian tube dysfunction or concurrent allergic pathophysiology affecting both the nasal and aural cavities. Observational studies hint at an association between allergic rhinitis (AR) and nonsuppurative otitis media, yet definitive causality remains elusive. Thus, to elucidate the causal impact of AR on otitis media, a 2-sample Mendelian randomization study was undertaken. Data on AR, acute suppurative otitis media, chronic suppurative otitis media, and nonsuppurative otitis media were sourced from the Genome for Extensive Association Study, encompassing individuals of European ancestry. Single nucleotide polymorphisms linked with AR were utilized as instrumental variables. The inverse-variance weighting (IVW) method, alongside sensitivity analyses employing the weighted median and Mendelian randomization-Egger methods, was employed to assess causal effects. Our analysis revealed a significant causal effect of AR on nonsuppurative otitis media (IVW, odds ratio [OR] = 12.22, 95% confidence interval, 1.38-107.93, P = .024) and indicated an association with acute suppurative otitis media (IVW, OR = 6.95, 95% confidence interval, 0.80-60.35, P = .078). However, no causal effect of AR on chronic suppurative otitis media was discerned. Our findings delineate a measurable causal link between AR and nonsuppurative otitis media (OR = 12.22) and suggest an association with acute suppurative otitis media (OR = 6.95), though lacking evidence for a causal effect on chronic suppurative otitis media. These results underscore the propensity of AR to correlate with diverse forms of otitis media and furnish high-quality causal evidence pertinent to clinical management.

Causal effects of pediatric asthma on psychiatric disorders: a bidirectional Mendelian randomization study

Background Previous studies have suggested a potential link between pediatric asthma and psychiatric disorders. However, the causal relationship between pediatric asthma and psychiatric disorders is unclear. Therefore, we used Mendelian randomization to explore causal relationships between pediatric asthma and depression, anxiety disorders, and attention deficit and hyperactivity disorder (ADHD). Methods Genome-wide association studies (GWAS) meta-analyses with the largest possible sample size and independent individuals from European ancestry were selected. The genetic data for depression and anxiety are from FinnGen consortium, while the genetic data for ADHD is from the Psychiatric Genomics Consortium. Inverse variance weighted (IVW) was the main analysis method. The heterogeneity of the instrumental variables (IVs) was assessed using IVW, and the horizontal pleiotropy of the IVs was assessed using MR-Egger. Result The IVW results showed a significant causal relationship between pediatric asthma and depression (OR = 1.08, 95% CI = 1.02–1.15; p = 0.013). However, there is no evidence to suggest a causal relationship between pediatric asthma, anxiety, and ADHD. Reverse MR suggests a significant causal relationship (OR = 1.27, 95% CI [1.14–1.41], p = 9.64E − 06) between ADHD and pediatric asthma using the IVW method. Conclusions Our findings suggest a causal relationship between pediatric asthma and an increased risk of depression. Additionally, we found that ADHD is significantly associated with a higher risk of pediatric asthma.

Multi-ancestry population attributable risk assessment of common genetic variation in Alzheimer's and Parkinson's diseases.

Multiple scientific studies, mostly performed within European populations, have unraveled many of the genetic factors associated with Alzheimer's disease (AD) and Parkinson's disease (PD) etiologies, improving our understanding of the molecular pathways implicated in the pathogenesis of these conditions. However, there is increasing evidence that the genetic architecture of these diseases differs across ancestral populations. This raises concerns about the efficacy of therapeutic interventions crafted around genetic targets prevalent only in European ancestry populations. Such interventions neglect potentially distinctive etiological profiles, including Latino, Black/African American, and East Asian populations. In the current study, we explore Population Attributable Risk (PAR) in AD and PD etiologies and assess the proportion of disease attributed to specific genetic factors across diverse populations. Leveraging data from genome-wide association studies across four ancestries, we explore distinct and universal therapeutic targets across diverse populations. Multi-ancestral genetics research is critical to the development of successful therapeutics and treatments for neurodegenerative diseases. By offering insights into genetic disparities, we aim to inform more inclusive and effective therapeutic strategies, advancing personalized healthcare.

Causality of genetically determined serum metabolites on lower back pain or/and sciatica: a comprehensive Mendelian randomized study.

There is an urgent need to confirm biomarkers reflecting the pathogenesis and targeted drugs of lower back pain or/and sciatica in clinical practice. This study aimed to conduct a two sample bidirectional Mendelian randomization (MR) analysis to explore the causal link between 486 serum metabolites and lower back pain or/and sciatica. All data come from two public shared databases of European ancestry and single nucleotide polymorphisms (SNPs) for lower back pain or/and sciatica acted as instrumental variables. The traditional inverse variance weighting (IVW) method, weighted-median method, MR-Egger methodand other methods were used to estimate causality. The horizontal pleiotropy, heterogeneities were also verified through the MR-Egger intercept test, Cochran's Q test, MR-PRESSO test and the leave-one-out sensitivity analysis. Reverse MR analysis was employed to evaluate the direct impact of metabolites on lower back pain or/and sciatica. Additionally, we conducted the colocalization analysis to reflect the causality deeply. Furthermore, metabolic pathway analysis was performed. 28 metabolites (18 known metabolites, 1 identified metabolites and 9 unknown metabolites) relevant to the risk of sciatica or/and lower back pain after using genetic variants as probes at PIVW < 0.05 were identifed. Among them, 8 serum metabolites decreased risk of sciatica or/and lower back pain significantly (P < 0.05), and 14 serum metabolites increased risk of sciatica or/and lower back pain significantly (P < 0.05). No reverse causal association was found between 28 metabolites and sciatica or/and lower back pain. Colocalization analysis results showed that the associations between sciatica or/and lower back pain and the 28 identified metabolites were not due to shared causal variant sites. Moreover, pathway enrichment analysis identifed 11 signifcant metabolic pathways, which are mainly involved in the pathological mechanism of sciatica or/and lower back pain (P < 0.05). There was no horizontal pleiotropy or heterogeneity in the other analyses. Our analyses provided robust evidence of causal associations between blood metabolites on sciatica or/and lower back pain. However, the underlying mechanisms remain to be further investigated.

The Causal Effect of Urate Level on Female Infertility: A Mendelian Randomization Study.

This study aimed to investigate the causal relationship between urate level and female infertility using Mendelian randomization (MR) analysis. To identify instrumental variables, we selected independent genetic loci associated with serum urate levels in individuals of European ancestry, utilizing data from large-scale genome-wide association studies (GWAS). The GWAS dataset included information on serum urate levels from 288,649 CKDGen participants. Female infertility data, including different etiologic classifications, consisted of 13,142 female infertility patients and 107,564 controls. We employed four MR methods, namely inverse variance weighted (IVW), MR-Egger, weighted median, and weighted model, to investigate the causal relationship between urate levels and female infertility. The Cochran Q-test was used to assess heterogeneity among single nucleotide polymorphisms (SNPs), and the MR-Egger intercept test was employed to evaluate the presence of horizontal pleiotropy. Additionally, a "leave-one-out" sensitivity analysis was conducted to examine the influence of individual SNPs on the MR study. The IVW analysis demonstrated that elevated serum urate levels increased the risk of female infertility (odds ratio [OR] = 1.18, 95% confidence interval [CI]: 1.07-1.33). Furthermore, serum urate levels were found to be associated with infertility due to cervical, vaginal, or other unknown causes (OR = 1.16, 95% CI: 1.06-1.26), also confirmed by other methods. Heterogeneity among instrumental variables was assessed using Cochran's Q-test (p < 0.05), so a random-effects IVW approach was employed in the effects model. The MR-Egger intercept test indicated no presence of horizontal pleiotropy. A "leave-one-out" sensitivity analysis was conducted, demonstrating that no individual SNP had a substantial impact on the overall findings. In the European population, the urate level is significantly and causally associated with an increased risk of female infertility.

Polymorphisms within autophagy-related genes as susceptibility biomarkers for pancreatic cancer: A meta-analysis of three large European cohorts and functional characterization.

Pancreatic ductal adenocarcinoma (PDAC) is one of the most lethal cancers with patients having unresectable or metastatic disease at diagnosis, with poor prognosis and very short survival. Given that genetic variation within autophagy-related genes influences autophagic flux and susceptibility to solid cancers, we decided to investigate whether 55,583 single nucleotide polymorphisms (SNPs) within 234 autophagy-related genes could influence the risk of developing PDAC in three large independent cohorts of European ancestry including 12,754 PDAC cases and 324,926 controls. The meta-analysis of these populations identified, for the first time, the association of the BIDrs9604789 variant with an increased risk of developing the disease (ORMeta = 1.31, p = 9.67 × 10-6). We also confirmed the association of TP63rs1515496 and TP63rs35389543 variants with PDAC risk (OR = 0.89, p = 6.27 × 10-8 and OR = 1.16, p = 2.74 × 10-5). Although it is known that BID induces autophagy and TP63 promotes cell growth, cell motility and invasion, we also found that carriers of the TP63rs1515496G allele had increased numbers of FOXP3+ Helios+ T regulatory cells and CD45RA+ T regulatory cells (p = 7.67 × 10-4 and p = 1.56 × 10-3), but also decreased levels of CD4+ T regulatory cells (p = 7.86 × 10-4). These results were in agreement with research suggesting that the TP63rs1515496 variant alters binding sites for FOXA1 and CTCF, which are transcription factors involved in modulating specific subsets of regulatory T cells. In conclusion, this study identifies BID as new susceptibility locus for PDAC and confirms previous studies suggesting that the TP63 gene is involved in the development of PDAC. This study also suggests new pathogenic mechanisms of the TP63 locus in PDAC.

Leveraging the Genetics of Psychiatric Disorders to Prioritize Potential Drug Targets and Compounds.

Genetics has the potential to inform biologically relevant drug treatment and repurposing which may ultimately improve patient care. In this study, we combine methods which leverage the genetics of psychiatric disorders to prioritize potential drug targets and compounds. We used the largest available genome-wide association studies, in European ancestry, of four psychiatric disorders [i.e., attention deficit hyperactivity disorder (ADHD), bipolar disorder, depression, and schizophrenia] along with genes encoding drug targets. With this data, we conducted drug enrichment analyses incorporating the novel and biologically specific GSA-MiXeR tool. We then conducted a series of molecular trait analyses using large-scale transcriptomic and proteomic datasets sampled from brain and blood tissue. This included the novel use of the UK Biobank proteomic data for a proteome-wide association study of psychiatric disorders. With the accumulated evidence, we prioritize potential drug targets and compounds for each disorder. We reveal candidate drug targets shared across multiple disorders as well as disorder-specific targets. Drug prioritization indicated genetic support for several currently used psychotropic medications including the antipsychotic paliperidone as the top ranked drug for schizophrenia. We also observed genetic support for other commonly used psychotropics (e.g., clozapine, risperidone, duloxetine, lithium, and valproic acid). Opportunities for drug repurposing were revealed such as cholinergic drugs for ADHD, estrogens for depression, and gabapentin enacarbil for schizophrenia. Our findings also indicate the genetic liability to schizophrenia is associated with reduced brain and blood expression of CYP2D6, a gene encoding a metabolizer of drugs and neurotransmitters, suggesting a genetic risk for poor drug response and altered neurotransmission. Here we present a series of complimentary and comprehensive analyses that highlight the utility of genetics for informing drug development and repurposing for psychiatric disorders. Our findings present novel opportunities for refining psychiatric treatment.

Proteogenomic analysis integrated with electronic health records data reveals disease-associated variants in Black Americans.

Most genome wide association studies (GWAS) of plasma proteomics have focused on White individuals of European ancestry, limiting biological insight from other ancestry enriched protein quantitative loci (pQTL). We conducted a discovery GWAS of ~3,000 plasma proteins measured by the antibody based Olink platform in 1,054 Black adults from the Jackson Heart Study (JHS), and validated our findings in the Multi-Ethnic Study of Atherosclerosis (MESA). The genetic architecture of identified pQTLs were further explored through fine mapping and admixture association analysis. Finally, using our pQTL findings, we performed a phenome wide association study (PheWAS) across two large multi-ethnic electronic health record (EHR) systems in All of Us and BioMe. We identified 1002 pQTLs for 925 proteins. Fine mapping and admixture analyses suggested allelic heterogeneity of the plasma proteome across diverse populations. We identified associations for variants enriched in African ancestry, many in diseases that lack precise biomarkers, including cis-pQTLs for Cathepsin L (CTSL) and Siglec-9 that were linked with sarcoidosis and non-Hodgkin's lymphoma, respectively. We found concordant associations across clinical diagnoses and laboratory measurements, elucidating disease pathways, including a cis-pQTL associated with circulating CD58, white blood cell count, and multiple sclerosis. Our findings emphasize the value of leveraging diverse populations to enhance biological insights from proteomics GWAS, and we have made this resource readily available as an interactive web portal.

Germline Variants in Patients Affected by Both Uveal and Cutaneous Melanoma.

Uveal melanoma (UM) and nonacral cutaneous melanoma (CM) are distinct entities with varied genetic landscapes despite both arising from melanocytes. There are, however, similarities in that they most frequently affect people of European ancestry, and high penetrance germline variants in BAP1, POT1 and CDKN2A have been shown to predispose to both UM and CM. This study aims to further explore germline variants in patients affected by both UM and CM, shedding light on the underlying genetic mechanism causing these diseases. Using exome sequencing we analysed germline DNA samples from a cohort of 83 Australian patients diagnosed with both UM and CM. Eight (10%) patients were identified that carried pathogenic mutations in known melanoma predisposition genes POT1, MITF, OCA2, SLC45A2 and TYR. Three (4%) patients carried pathogenic variants in genes previously linked with other cancer syndromes (ATR, BRIP1 and MSH6) and another three cases carried monoallelic pathogenic variants in recessive cancer genes (xeroderma pigmentosum and Fanconi anaemia), indicating that reduced penetrance of phenotype in these individuals may contribute to the development of both UM and CM. These findings highlight the need for further studies characterising the role of these genes in melanoma susceptibility.

Integrated clinical risk prediction of type 2 diabetes with a multifactorial polygenic risk score.

Combining information from multiple GWASs for a disease and its risk factors has proven a powerful approach for development of polygenic risk scores (PRSs). This may be particularly useful for type 2 diabetes (T2D), a highly polygenic and heterogeneous disease where the additional predictive value of a PRS is unclear. Here, we use a meta-scoring approach to develop a metaPRS for T2D that incorporated genome-wide associations from both European and non-European genetic ancestries and T2D risk factors. We evaluated the performance of this metaPRS and benchmarked it against existing genome-wide PRS in 620,059 participants and 50,572 T2D cases amongst six diverse genetic ancestries from UK Biobank, INTERVAL, the All of Us Research Program, and the Singapore Multi-Ethnic Cohort. We show that our metaPRS was the most powerful PRS for predicting T2D in European population-based cohorts and had comparable performance to the top ancestry-specific PRS, highlighting its transferability. In UK Biobank, we show the metaPRS had stronger predictive power for 10-year risk than all individual risk factors apart from BMI and biomarkers of dysglycemia. The metaPRS modestly improved T2D risk stratification of QDiabetes risk scores for 10-year risk prediction, particularly when prioritising individuals for blood tests of dysglycemia. Overall, we present a highly predictive and transferrable PRS for T2D and demonstrate that the potential for PRS to incrementally improve T2D risk prediction when incorporated into UK guideline-recommended screening and risk prediction with a clinical risk score.

Ancestry and somatic profile predict acral melanoma origin and prognosis.

Acral melanoma, which is not ultraviolet (UV)-associated, is the most common type of melanoma in several low- and middle-income countries including Mexico. Latin American samples are significantly underrepresented in global cancer genomics studies, which directly affects patients in these regions as it is known that cancer risk and incidence may be influenced by ancestry and environmental exposures. To address this, here we characterise the genome and transcriptome of 128 acral melanoma tumours from 96 Mexican patients, a population notable because of its genetic admixture. Compared with other studies of melanoma, we found fewer frequent mutations in classical driver genes such as BRAF, NRAS or NF1. While most patients had predominantly Amerindian genetic ancestry, those with higher European ancestry had increased frequency of BRAF mutations and a lower number of structural variants. These BRAF-mutated tumours have a transcriptional profile similar to cutaneous non-volar melanocytes, suggesting that acral melanomas in these patients may arise from a distinct cell of origin compared to other tumours arising in these locations. KIT mutations were found in a subset of these tumours, and transcriptional profiling defined three expression clusters; these characteristics were associated with overall survival. We highlight novel low-frequency drivers, such as SPHKAP, which correlate with a distinct genomic profile and clinical characteristics. Our study enhances knowledge of this understudied disease and underscores the importance of including samples from diverse ancestries in cancer genomics studies.

Cross-population enhancement of PrediXcan predictions with a gnomAD-based east Asian reference framework.

Over the past decade, genome-wide association studies have identified thousands of variants significantly associated with complex traits. For each locus, gene expression levels are needed to further explore its biological functions. To address this, the PrediXcan algorithm leverages large-scale reference data to impute the gene expression level from single nucleotide polymorphisms, and thus the gene-trait associations can be tested to identify the candidate causal genes. However, a challenge arises due to the fact that most reference data are from subjects of European ancestry, and the accuracy and robustness of predicted gene expression in subjects of East Asian (EAS) ancestry remains unclear. Here, we first simulated a variety of scenarios to explore the impact of the level of population diversity on gene expression. Population differentiated variants were estimated by using the allele frequency information from The Genome Aggregation Database. We found that the weights of a variants was the main factor that affected the gene expression predictions, and that ~70% of variants were significantly population differentiated based on proportion tests. To provide insights into this population effect on gene expression levels, we utilized the allele frequency information to develop a gene expression reference panel, Predict Asian-Population (PredictAP), for EAS ancestry. PredictAP can be viewed as an auxiliary tool for PrediXcan when using genotype data from EAS subjects.