Rare variant associations with birth weight identify genes involved in adipose tissue regulation, placental function and insulin-like growth factor signalling.

Investigating the genetic factors influencing human birth weight may lead to biological insights into fetal growth and long-term health. Genome-wide association studies of birth weight have highlighted associated variants in more than 200 regions of the genome, but the causal genes are mostly unknown. Rare genetic variants with robust evidence of association are more likely to point to causal genes, but to date, only a few rare variants are known to influence birth weight. We aimed to identify genes that harbour rare variants that impact birth weight when carried by either the fetus or the mother, by analysing whole exome sequence data in UK Biobank participants. We annotated rare (minor allele frequency <0.1%) protein-truncating or high impact missense variants on whole exome sequence data in up to 234,675 participants with data on their own birth weight (fetal variants), and up to 181,883 mothers who reported the birth weight of their first child (maternal variants). Variants within each gene were collapsed to perform gene burden tests and for each associated gene, we compared the observed fetal and maternal effects. We identified 8 genes with evidence of rare fetal variant effects on birth weight, of which 2 also showed maternal effects. One additional gene showed evidence of maternal effects only. We observed 10/11 directionally concordant associations in an independent sample of up to 45,622 individuals (sign test P=0.01). Of the genes identified, IGF1R and PAPPA2 (fetal and maternal-acting) have known roles in insulin-like growth factor bioavailability and signalling. PPARG, INHBE and ACVR1C (all fetal-acting) have known roles in adipose tissue regulation and rare variants in the latter two also showed associations with favourable adiposity patterns in adults. We highlight the dual role of PPARG in both adipocyte differentiation and placental angiogenesis. NOS3, NRK, and ADAMTS8 (fetal and maternal-acting) have been implicated in both placental function and hypertension. Analysis of rare coding variants has identified regulators of fetal adipose tissue and fetoplacental angiogenesis as determinants of birth weight, as well as further evidence for the role of insulin-like growth factors.

Integrative common and rare variant analyses provide insights into the genetic architecture of liver cirrhosis.

We report a multi-ancestry genome-wide association study on liver cirrhosis and its associated endophenotypes, alanine aminotransferase (ALT) and γ-glutamyl transferase. Using data from 12 cohorts, including 18,265 cases with cirrhosis, 1,782,047 controls, up to 1 million individuals with liver function tests and a validation cohort of 21,689 cases and 617,729 controls, we identify and validate 14 risk associations for cirrhosis. Many variants are located near genes involved in hepatic lipid metabolism. One of these, PNPLA3 p.Ile148Met, interacts with alcohol intake, obesity and diabetes on the risk of cirrhosis and hepatocellular carcinoma (HCC). We develop a polygenic risk score that associates with the progression from cirrhosis to HCC. By focusing on prioritized genes from common variant analyses, we find that rare coding variants in GPAM associate with lower ALT, supporting GPAM as a potential target for therapeutic inhibition. In conclusion, this study provides insights into the genetic underpinnings of cirrhosis.

GWAS meta-analysis reveals key risk loci in essential tremor pathogenesis.

Essential tremor (ET) is a prevalent neurological disorder with a largely unknown underlying biology. In this genome-wide association study meta-analysis, comprising 16,480 ET cases and 1,936,173 controls from seven datasets, we identify 12 sequence variants at 11 loci. Evaluating mRNA expression, splicing, plasma protein levels, and coding effects, we highlight seven putative causal genes at these loci, including CA3 and CPLX1. CA3 encodes Carbonic Anhydrase III and carbonic anhydrase inhibitors have been shown to decrease tremors. CPLX1, encoding Complexin-1, regulates neurotransmitter release. Through gene-set enrichment analysis, we identify a significant association with specific cell types, including dopaminergic and GABAergic neurons, as well as biological processes like Rho GTPase signaling. Genetic correlation analyses reveals a positive association between ET and Parkinson's disease, depression, and anxiety-related phenotypes. This research uncovers risk loci, enhancing our knowledge of the complex genetics of this common but poorly understood disorder, and highlights CA3 and CPLX1 as potential therapeutic targets.

Genome-wide analyses identify 21 infertility loci and over 400 reproductive hormone loci across the allele frequency spectrum.

Genome-wide association studies (GWASs) may help inform treatments for infertility, whose causes remain unknown in many cases. Here we present GWAS meta-analyses across six cohorts for male and female infertility in up to 41,200 cases and 687,005 controls. We identified 21 genetic risk loci for infertility (P≤5E-08), of which 12 have not been reported for any reproductive condition. We found positive genetic correlations between endometriosis and all-cause female infertility (rg=0.585, P=8.98E-14), and between polycystic ovary syndrome and anovulatory infertility (rg=0.403, P=2.16E-03). The evolutionary persistence of female infertility-risk alleles in EBAG9 may be explained by recent directional selection. We additionally identified up to 269 genetic loci associated with follicle-stimulating hormone (FSH), luteinising hormone, oestradiol, and testosterone through sex-specific GWAS meta-analyses (N=6,095-246,862). While hormone-associated variants near FSHB and ARL14EP colocalised with signals for anovulatory infertility, we found no rg between female infertility and reproductive hormones (P>0.05). Exome sequencing analyses in the UK Biobank (N=197,340) revealed that women carrying testosterone-lowering rare variants in GPC2 were at higher risk of infertility (OR=2.63, P=1.25E-03). Taken together, our results suggest that while individual genes associated with hormone regulation may be relevant for fertility, there is limited genetic evidence for correlation between reproductive hormones and infertility at the population level. We provide the first comprehensive view of the genetic architecture of infertility across multiple diagnostic criteria in men and women, and characterise its relationship to other health conditions.

Predicting the presence of coronary plaques featuring high-risk characteristics using polygenic risk scores and targeted proteomics in patients with suspected coronary artery disease.

BACKGROUND: The presence of coronary plaques with high-risk characteristics is strongly associated with adverse cardiac events beyond the identification of coronary stenosis. Testing by coronary computed tomography angiography (CCTA) enables the identification of high-risk plaques (HRP). Referral for CCTA is presently based on pre-test probability estimates including clinical risk factors (CRFs); however, proteomics and/or genetic information could potentially improve patient selection for CCTA and, hence, identification of HRP. We aimed to (1) identify proteomic and genetic features associated with HRP presence and (2) investigate the effect of combining CRFs, proteomics, and genetics to predict HRP presence. METHODS: Consecutive chest pain patients (n = 1462) undergoing CCTA to diagnose obstructive coronary artery disease (CAD) were included. Coronary plaques were assessed using a semi-automatic plaque analysis tool. Measurements of 368 circulating proteins were obtained with targeted Olink panels, and DNA genotyping was performed in all patients. Imputed genetic variants were used to compute a multi-trait multi-ancestry genome-wide polygenic score (GPSMult). HRP presence was defined as plaques with two or more high-risk characteristics (low attenuation, spotty calcification, positive remodeling, and napkin ring sign). Prediction of HRP presence was performed using the glmnet algorithm with repeated fivefold cross-validation, using CRFs, proteomics, and GPSMult as input features. RESULTS: HRPs were detected in 165 (11%) patients, and 15 input features were associated with HRP presence. Prediction of HRP presence based on CRFs yielded a mean area under the receiver operating curve (AUC) ± standard error of 73.2 ± 0.1, versus 69.0 ± 0.1 for proteomics and 60.1 ± 0.1 for GPSMult. Combining CRFs with GPSMult increased prediction accuracy (AUC 74.8 ± 0.1 (P = 0.004)), while the inclusion of proteomics provided no significant improvement to either the CRF (AUC 73.2 ± 0.1, P = 1.00) or the CRF + GPSMult (AUC 74.6 ± 0.1, P = 1.00) models, respectively. CONCLUSIONS: In patients with suspected CAD, incorporating genetic data with either clinical or proteomic data improves the prediction of high-risk plaque presence. TRIAL REGISTRATION: https://clinicaltrials.gov/ct2/show/NCT02264717 (September 2014).

A comparison of methods for detecting DNA methylation from long-read sequencing of human genomes.

BACKGROUND: Long-read sequencing can enable the detection of base modifications, such as CpG methylation, in single molecules of DNA. The most commonly used methods for long-read sequencing are nanopore developed by Oxford Nanopore Technologies (ONT) and single molecule real-time (SMRT) sequencing developed by Pacific Bioscience (PacBio). In this study, we systematically compare the performance of CpG methylation detection from long-read sequencing. RESULTS: We demonstrate that CpG methylation detection from 7179 nanopore-sequenced DNA samples is highly accurate and consistent with 132 oxidative bisulfite-sequenced (oxBS) samples, isolated from the same blood draws. We introduce quality filters for CpGs that further enhance the accuracy of CpG methylation detection from nanopore-sequenced DNA, while removing at most 30% of CpGs. We evaluate the per-site performance of CpG methylation detection across different genomic features and CpG methylation rates and demonstrate how the latest R10.4 flowcell chemistry and base-calling algorithms improve methylation detection from nanopore sequencing. Additionally, we show how the methylation detection of 50 SMRT-sequenced genomes compares to nanopore sequencing and oxBS. CONCLUSIONS: This study provides the first systematic comparison of CpG methylation detection tools for long-read sequencing methods. We compare two commonly used computational methods for the detection of CpG methylation in a large number of nanopore genomes, including samples sequenced using the latest R10.4 nanopore flowcell chemistry and 50 SMRT sequenced samples. We provide insights into the strengths and limitations of each sequencing method as well as recommendations for standardization and evaluation of tools designed for genome-scale modified base detection using long-read sequencing.

Variant in the synaptonemal complex protein SYCE2 associates with pregnancy loss through effect on recombination.

Two-thirds of all human conceptions are lost, in most cases before clinical detection. The lack of detailed understanding of the causes of pregnancy losses constrains focused counseling for future pregnancies. We have previously shown that a missense variant in synaptonemal complex central element protein 2 (SYCE2), in a key residue for the assembly of the synaptonemal complex backbone, associates with recombination traits. Here we show that it also increases risk of pregnancy loss in a genome-wide association analysis on 114,761 women with reported pregnancy loss. We further show that the variant associates with more random placement of crossovers and lower recombination rate in longer chromosomes but higher in the shorter ones. These results support the hypothesis that some pregnancy losses are due to failures in recombination. They further demonstrate that variants with a substantial effect on the quality of recombination can be maintained in the population.

Polygenic liability for antipsychotic dosage and polypharmacy - a real-world registry and biobank study.

Genomic prediction of antipsychotic dose and polypharmacy has been difficult, mainly due to limited access to large cohorts with genetic and drug prescription data. In this proof of principle study, we investigated if genetic liability for schizophrenia is associated with high dose requirements of antipsychotics and antipsychotic polypharmacy, using real-world registry and biobank data from five independent Nordic cohorts of a total of N = 21,572 individuals with psychotic disorders (schizophrenia, bipolar disorder, and other psychosis). Within regression models, a polygenic risk score (PRS) for schizophrenia was studied in relation to standardized antipsychotic dose as well as antipsychotic polypharmacy, defined based on longitudinal prescription registry data as well as health records and self-reported data. Meta-analyses across the five cohorts showed that PRS for schizophrenia was significantly positively associated with prescribed (standardized) antipsychotic dose (beta(SE) = 0.0435(0.009), p = 0.0006) and antipsychotic polypharmacy defined as taking ≥2 antipsychotics (OR = 1.10, CI = 1.05-1.21, p = 0.0073). The direction of effect was similar in all five independent cohorts. These findings indicate that genotypes may aid clinically relevant decisions on individual patients´ antipsychotic treatment. Further, the findings illustrate how real-world data have the potential to generate results needed for future precision medicine approaches in psychiatry.

How Real-World Data Can Facilitate the Development of Precision Medicine Treatment in Psychiatry.

Precision medicine has the ambition to improve treatment response and clinical outcomes through patient stratification and holds great potential for the treatment of mental disorders. However, several important factors are needed to transform current practice into a precision psychiatry framework. Most important are 1) the generation of accessible large real-world training and test data including genomic data integrated from multiple sources, 2) the development and validation of advanced analytical tools for stratification and prediction, and 3) the development of clinically useful management platforms for patient monitoring that can be integrated into health care systems in real-life settings. This narrative review summarizes strategies for obtaining the key elements-well-powered samples from large biobanks integrated with electronic health records and health registry data using novel artificial intelligence algorithms-to predict outcomes in severe mental disorders and translate these models into clinical management and treatment approaches. Key elements are massive mental health data and novel artificial intelligence algorithms. For the clinical translation of these strategies, we discuss a precision medicine platform for improved management of mental disorders. We use cases to illustrate how precision medicine interventions could be brought into psychiatry to improve the clinical outcomes of mental disorders.

Polygenic risk scores associate with blood pressure traits across the lifespan.

AIMS: Hypertension is a major modifiable cause of morbidity and mortality that affects over 1 billion people worldwide. Blood pressure (BP) traits have a strong genetic component that can be quantified with polygenic risk scores (PRSs). To date, the performance of BP PRSs has mainly been assessed in adults, and less is known about polygenic hypertension risk in childhood. METHODS AND RESULTS: Multiple PRSs for systolic BP (SBP), diastolic BP (DBP), and pulse pressure were developed using either genome-wide significant weights, pruning and thresholding, or Bayesian regression. Among 87 total PRSs, the top performer for each trait was applied in independent cohorts of children and adult to assess genotype-phenotype associations and disease risk across the lifespan. Differences between those with low (1st decile), average (2nd-9th decile), and high (10th decile) PRS emerge in the first years of life and are maintained throughout adulthood. These diverging BP trajectories also seem to affect cardiovascular and renal disease risk, with increased risk observed among those in the top decile and reduced risk among those in the bottom decile of the polygenic risk distribution compared with the rest of the population. CONCLUSION: Genetic risk factors are associated with BP traits across the lifespan, beginning in the first years of life. Given the importance of exposure time in disease pathogenesis and the early rise in BP levels among those genetically susceptible, PRSs may help identify high-risk individuals prior to hypertension onset, facilitate primordial prevention, and reduce the burden of this public health challenge.

A high genetic risk of elevated blood pressure (BP) is associated with increased BP from early childhood and throughout the lifespan. Inherited predispositions also affect the risk of cardiovascular morbidity and mortality, yet this appears to be modified by the absence or presence of hypertension, indicating that genetic hypertension risk is not deterministic, and that controlling BP can and should be done across the polygenic risk distribution. Given that differences in BP emerge early in life as a function of genetic risk, polygenic risk scores have the potential to reduce the duration of exposure to high BP by identifying high-risk individuals from birth, and thereby attenuate lifelong disease risk.

Multi-polygenic scores in psychiatry: From disorder specific to transdiagnostic perspectives.

The dense co-occurrence of psychiatric disorders questions the categorical classification tradition and motivates efforts to establish dimensional constructs with neurobiological foundations that transcend diagnostic boundaries. In this study, we examined the genetic liability for eight major psychiatric disorder phenotypes under both a disorder-specific and a transdiagnostic framework. The study sample (n = 513) was deeply phenotyped, consisting of 452 patients from tertiary care with mood disorders, anxiety disorders (ANX), attention-deficit/hyperactivity disorder (ADHD), autism spectrum disorders, and/or substance use disorders (SUD) and 61 unaffected comparison individuals. We computed subject-specific polygenic risk score (PRS) profiles and assessed their associations with psychiatric diagnoses, comorbidity status, as well as cross-disorder behavioral dimensions derived from a rich battery of psychopathology assessments. High PRSs for depression were unselectively associated with the diagnosis of SUD, ADHD, ANX, and mood disorders (p < 1e-4). In the dimensional approach, four distinct functional domains were uncovered, namely the negative valence, social, cognitive, and regulatory systems, closely matching the major functional domains proposed by the Research Domain Criteria (RDoC) framework. Critically, the genetic predisposition for depression was selectively reflected in the functional aspect of negative valence systems (R2 = 0.041, p = 5e-4) but not others. This study adds evidence to the ongoing discussion about the misalignment between current psychiatric nosology and the underlying psychiatric genetic etiology and underscores the effectiveness of the dimensional approach in both the functional characterization of psychiatric patients and the delineation of the genetic liability for psychiatric disorders.

A population-based survey of FBN1 variants in Iceland reveals underdiagnosis of Marfan syndrome.

Marfan syndrome (MFS) is an autosomal dominant condition characterized by aortic aneurysm, skeletal abnormalities, and lens dislocation, and is caused by variants in the FBN1 gene. To explore causes of MFS and the prevalence of the disease in Iceland we collected information from all living individuals with a clinical diagnosis of MFS in Iceland (n = 32) and performed whole-genome sequencing of those who did not have a confirmed genetic diagnosis (27/32). Moreover, to assess a potential underdiagnosis of MFS in Iceland we attempted a genotype-based approach to identify individuals with MFS. We interrogated deCODE genetics' database of 35,712 whole-genome sequenced individuals to search for rare sequence variants in FBN1. Overall, we identified 15 pathogenic or likely pathogenic variants in FBN1 in 44 individuals, only 22 of whom were previously diagnosed with MFS. The most common of these variants, NM_000138.4:c.8038 C > T p.(Arg2680Cys), is present in a multi-generational pedigree, and was found to stem from a single forefather born around 1840. The p.(Arg2680Cys) variant associates with a form of MFS that seems to have an enrichment of abdominal aortic aneurysm, suggesting that this may be a particularly common feature of p.(Arg2680Cys)-associated MFS. Based on these combined genetic and clinical data, we show that MFS prevalence in Iceland could be as high as 1/6,600 in Iceland, compared to 1/10,000 based on clinical diagnosis alone, which indicates underdiagnosis of this actionable genetic disorder.

Variants at the Interleukin 1 Gene Locus and Pericarditis.

Importance: Recurrent pericarditis is a treatment challenge and often a debilitating condition. Drugs inhibiting interleukin 1 cytokines are a promising new treatment option, but their use is based on scarce biological evidence and clinical trials of modest sizes, and the contributions of innate and adaptive immune processes to the pathophysiology are incompletely understood. Objective: To use human genomics, transcriptomics, and proteomics to shed light on the pathogenesis of pericarditis. Design, Setting, and Participants: This was a meta-analysis of genome-wide association studies of pericarditis from 5 countries. Associations were examined between the pericarditis-associated variants and pericarditis subtypes (including recurrent pericarditis) and secondary phenotypes. To explore mechanisms, associations with messenger RNA expression (cis-eQTL), plasma protein levels (pQTL), and CpG methylation of DNA (ASM-QTL) were assessed. Data from Iceland (deCODE genetics, 1983-2020), Denmark (Copenhagen Hospital Biobank/Danish Blood Donor Study, 1977-2022), the UK (UK Biobank, 1953-2021), the US (Intermountain, 1996-2022), and Finland (FinnGen, 1970-2022) were included. Data were analyzed from September 2022 to August 2023. Exposure: Genotype. Main Outcomes and Measures: Pericarditis. Results: In this genome-wide association study of 4894 individuals with pericarditis (mean [SD] age at diagnosis, 51.4 [17.9] years, 2734 [67.6%] male, excluding the FinnGen cohort), associations were identified with 2 independent common intergenic variants at the interleukin 1 locus on chromosome 2q14. The lead variant was rs12992780 (T) (effect allele frequency [EAF], 31%-40%; odds ratio [OR], 0.83; 95% CI, 0.79-0.87; P = 6.67 × 10-16), downstream of IL1B and the secondary variant rs7575402 (A or T) (EAF, 45%-55%; adjusted OR, 0.89; 95% CI, 0.85-0.93; adjusted P = 9.6 × 10-8). The lead variant rs12992780 had a smaller odds ratio for recurrent pericarditis (0.76) than the acute form (0.86) (P for heterogeneity = .03) and rs7575402 was associated with CpG methylation overlapping binding sites of 4 transcription factors known to regulate interleukin 1 production: PU.1 (encoded by SPI1), STAT1, STAT3, and CCAAT/enhancer-binding protein ß (encoded by CEBPB). Conclusions and Relevance: This study found an association between pericarditis and 2 independent sequence variants at the interleukin 1 gene locus. This finding has the potential to contribute to development of more targeted and personalized therapy of pericarditis with interleukin 1-blocking drugs.

Obesity variants in the GIPR gene do not associate with risk of fracture or bone mineral density.

OBJECTIVE: The objective of this study was to investigate the risk of fracture and bone mineral density (BMD) of sequence variants in GIPR that reduce the activity of the GIPR receptor and have been associated with reduced body mass index (BMI). METHODS: We analysed the association of three missense variants in GIPR, a common variant, rs1800437 (p.Glu354Gln), and two rare variants, rs139215588 (p.Arg190Gln) and rs143430880 (p.Glu288Gly), as well as a burden of predicted loss of function (LoF) variants with risk of fracture and with BMD in a large meta-analysis of up to 1.2 million participants. We analysed associations with fractures at different skeletal sites in the general population; any fractures, hip fractures, vertebral fractures and forearm fractures, and specifically non-vertebral and osteoporotic fractures in postmenopausal women. We also evaluated associations with BMD at the lumbar spine, femoral neck, and total body measured with dual-energy X-ray absorptiometry (DXA), and with BMD estimated from heel ultrasound (eBMD). RESULTS: None of the three missense variants in GIPR associated significantly with increased risk of fractures or with lower BMD. Burden of LoF variants in GIPR were not associated with fractures or with BMD measured with clinically validated DXA, but associated with eBMD. CONCLUSION: Missense variants in GIPR, or burden of LoF variants in the gene, do not associate with risk of fractures or with lower BMD.

Predicting ADHD in alcohol dependence using polygenic risk scores for ADHD.

Attention deficit hyperactivity disorder (ADHD) is a neurodevelopmental disorder with a high degree of comorbidity, including substance misuse. We aimed to assess whether ADHD polygenic risk scores (PRS) could predict ADHD diagnosis in alcohol dependence (AD). ADHD PRS were generated for 1223 AD subjects with ADHD diagnosis information and 1818 healthy controls. ADHD PRS distributions were compared to evaluate the differences between healthy controls and AD cases with and without ADHD. We found increased ADHD PRS means in the AD cohort with ADHD (mean 0.30, standard deviation (SD) 0.92; p = 3.9 × 10-6 ); and without ADHD (mean - 0.00, SD 1.00; p = 5.2 × 10-5 ) compared to the healthy control subjects (mean - 0.17, SD 0.99). The ADHD PRS means differed within the AD group with a higher ADHD PRS mean in those with ADHD, odds ratio (OR) 1.34, confidence interval (CI) 1.10 to 1.65; p = 0.002. This study showed a positive relationship between ADHD PRS and risk of ADHD in individuals with co-occurring AD indicating that ADHD PRS may have utility in identifying individuals that are at a higher or lower risk of ADHD. Further larger studies need to be conducted to confirm the reliability of the results before ADHD PRS can be considered as a robust biomarker for diagnosis.

Genetics and epidemiology of mutational barcode-defined clonal hematopoiesis.

Clonal hematopoiesis (CH) arises when a substantial proportion of mature blood cells is derived from a single hematopoietic stem cell lineage. Using whole-genome sequencing of 45,510 Icelandic and 130,709 UK Biobank participants combined with a mutational barcode method, we identified 16,306 people with CH. Prevalence approaches 50% in elderly participants. Smoking demonstrates a dosage-dependent impact on risk of CH. CH associates with several smoking-related diseases. Contrary to published claims, we find no evidence that CH is associated with cardiovascular disease. We provide evidence that CH is driven by genes that are commonly mutated in myeloid neoplasia and implicate several new driver genes. The presence and nature of a driver mutation alters the risk profile for hematological disorders. Nevertheless, most CH cases have no known driver mutations. A CH genome-wide association study identified 25 loci, including 19 not implicated previously in CH. Splicing, protein and expression quantitative trait loci were identified for CD164 and TCL1A.

Actionable Genotypes and Their Association with Life Span in Iceland.

BACKGROUND: In 2021, the American College of Medical Genetics and Genomics (ACMG) recommended reporting actionable genotypes in 73 genes associated with diseases for which preventive or therapeutic measures are available. Evaluations of the association of actionable genotypes in these genes with life span are currently lacking. METHODS: We assessed the prevalence of coding and splice variants in genes on the ACMG Secondary Findings, version 3.0 (ACMG SF v3.0), list in the genomes of 57,933 Icelanders. We assigned pathogenicity to all reviewed variants using reported evidence in the ClinVar database, the frequency of variants, and their associations with disease to create a manually curated set of actionable genotypes (variants). We assessed the relationship between these genotypes and life span and further examined the specific causes of death among carriers. RESULTS: Through manual curation of 4405 sequence variants in the ACMG SF v3.0 genes, we identified 235 actionable genotypes in 53 genes. Of the 57,933 participants, 2306 (4.0%) carried at least one actionable genotype. We found shorter median survival among persons carrying actionable genotypes than among noncarriers. Specifically, we found that carrying an actionable genotype in a cancer gene was associated with survival that was 3 years shorter than that among noncarriers, with causes of death among carriers attributed primarily to cancer-related conditions. Furthermore, we found evidence of association between carrying an actionable genotype in certain genes in the cardiovascular disease group and a reduced life span. CONCLUSIONS: On the basis of the ACMG SF v3.0 guidelines, we found that approximately 1 in 25 Icelanders carried an actionable genotype and that carrying such a genotype was associated with a reduced life span. (Funded by deCODE Genetics-Amgen.).

An atlas of genetic determinants of forearm fracture.

Osteoporotic fracture is among the most common and costly of diseases. While reasonably heritable, its genetic determinants have remained elusive. Forearm fractures are the most common clinically recognized osteoporotic fractures with a relatively high heritability. To establish an atlas of the genetic determinants of forearm fractures, we performed genome-wide association analyses including 100,026 forearm fracture cases. We identified 43 loci, including 26 new fracture loci. Although most fracture loci associated with bone mineral density, we also identified loci that primarily regulate bone quality parameters. Functional studies of one such locus, at TAC4, revealed that Tac4-/- mice have reduced mechanical bone strength. The strongest forearm fracture signal, at WNT16, displayed remarkable bone-site-specificity with no association with hip fractures. Tall stature and low body mass index were identified as new causal risk factors for fractures. The insights from this atlas may improve fracture prediction and enable therapeutic development to prevent fractures.

Testing for pharmacogenomic predictors of ppRNFL thinning in individuals exposed to vigabatrin.

Background: The anti-seizure medication vigabatrin (VGB) is effective for controlling seizures, especially infantile spasms. However, use is limited by VGB-associated visual field loss (VAVFL). The mechanisms by which VGB causes VAVFL remains unknown. Average peripapillary retinal nerve fibre layer (ppRNFL) thickness correlates with the degree of visual field loss (measured by mean radial degrees). Duration of VGB exposure, maximum daily VGB dose, and male sex are associated with ppRNFL thinning. Here we test the hypothesis that common genetic variation is a predictor of ppRNFL thinning in VGB exposed individuals. Identifying pharmacogenomic predictors of ppRNFL thinning in VGB exposed individuals could potentially enable safe prescribing of VGB and broader use of a highly effective drug. Methods: Optical coherence topography (OCT) and GWAS data were processed from VGB-exposed individuals (n = 71) recruited through the EpiPGX Consortium. We conducted quantitative GWAS analyses for the following OCT measurements: (1) average ppRNFL, (2) inferior quadrant, (3) nasal quadrant, (4) superior quadrant, (5) temporal quadrant, (6) inferior nasal sector, (7) nasal inferior sector, (8) superior nasal sector, and (9) nasal superior sector. Using the summary statistics from the GWAS analyses we conducted gene-based testing using VEGAS2. We conducted nine different PRS analyses using the OCT measurements. To determine if VGB-exposed individuals were predisposed to having a thinner RNFL, we calculated their polygenic burden for retinal thickness. PRS alleles for retinal thickness were calculated using published summary statistics from a large-scale GWAS of inner retinal morphology using the OCT images of UK Biobank participants. Results: The GWAS analyses did not identify a significant association after correction for multiple testing. Similarly, the gene-based and PRS analyses did not reveal a significant association that survived multiple testing. Conclusion: We set out to identify common genetic predictors for VGB induced ppRNFL thinning. Results suggest that large-effect common genetic predictors are unlikely to exist for ppRNFL thinning (as a marker of VAVFL). Sample size was a limitation of this study. However, further recruitment is a challenge as VGB is rarely used today because of this adverse reaction. Rare variants may be predictors of this adverse drug reaction and were not studied here.