Burden re-analysis of neurodevelopmental disorder cohorts for prioritization of candidate genes.

This study aimed to uncover novel genes associated with neurodevelopmental disorders (NDD) by leveraging recent large-scale de novo burden analysis studies to enhance a virtual gene panel used in a diagnostic setting. We re-analyzed historical trio-exome sequencing data from 745 individuals with NDD according to the most recent diagnostic standards, resulting in a cohort of 567 unsolved individuals. Next, we designed a virtual gene panel containing candidate genes from three large de novo burden analysis studies in NDD and prioritized candidate genes by stringent filtering for ultra-rare de novo variants with high pathogenicity scores. Our analysis revealed an increased burden of de novo variants in our selected candidate genes within the unsolved NDD cohort and identified qualifying de novo variants in seven candidate genes: RIF1, CAMK2D, RAB11FIP4, AGO3, PCBP2, LEO1, and VCP. Clinical data were collected from six new individuals with de novo or inherited LEO1 variants and three new individuals with de novo PCBP2 variants. Our findings add additional evidence for LEO1 as a risk gene for autism and intellectual disability. Furthermore, we prioritize PCBP2 as a candidate gene for NDD associated with motor and language delay. In summary, by leveraging de novo burden analysis studies, employing a stringent variant filtering pipeline, and engaging in targeted patient recruitment, our study contributes to the identification of novel genes implicated in NDDs.

Start codon variant in LAG3 is associated with decreased LAG-3 expression and increased risk of autoimmune thyroid disease.

Autoimmune thyroid disease (AITD) is a common autoimmune disease. In a GWAS meta-analysis of 110,945 cases and 1,084,290 controls, 290 sequence variants at 225 loci are associated with AITD. Of these variants, 115 are previously unreported. Multiomics analysis yields 235 candidate genes outside the MHC-region and the findings highlight the importance of genes involved in T-cell regulation. A rare 5'-UTR variant (rs781745126-T, MAF = 0.13% in Iceland) in LAG3 has the largest effect (OR = 3.42, P = 2.2 × 10-16) and generates a novel start codon for an open reading frame upstream of the canonical protein translation initiation site. rs781745126-T reduces mRNA and surface expression of the inhibitory immune checkpoint LAG-3 co-receptor on activated lymphocyte subsets and halves LAG-3 levels in plasma among heterozygotes. All three homozygous carriers of rs781745126-T have AITD, of whom one also has two other T-cell mediated diseases, that is vitiligo and type 1 diabetes. rs781745126-T associates nominally with vitiligo (OR = 5.1, P = 6.5 × 10-3) but not with type 1 diabetes. Thus, the effect of rs781745126-T is akin to drugs that inhibit LAG-3, which unleash immune responses and can have thyroid dysfunction and vitiligo as adverse events. This illustrates how a multiomics approach can reveal potential drug targets and safety concerns.

Biallelic variants in POPDC2 cause a novel autosomal recessive syndrome presenting with cardiac conduction defects and variable hypertrophic cardiomyopathy.

POPDC2 encodes for the Popeye domain-containing protein 2 which has an important role in cardiac pacemaking and conduction, due in part to its cAMP-dependent binding and regulation of TREK-1 potassium channels. Loss of Popdc2 in mice results in sinus pauses and bradycardia and morpholino knockdown of popdc2 in zebrafish results in atrioventricular (AV) block. We identified bi-allelic variants in POPDC2 in 4 families that presented with a phenotypic spectrum consisting of sinus node dysfunction, AV conduction defects and hypertrophic cardiomyopathy. Using homology modelling we show that the identified POPDC2 variants are predicted to diminish the ability of POPDC2 to bind cAMP. In in vitro electrophysiological studies we demonstrated that, while co-expression of wild-type POPDC2 with TREK-1 increased TREK-1 current density, POPDC2 variants found in the patients failed to increase TREK-1 current density. While patient muscle biopsy did not show clear myopathic disease, it showed significant reduction of the expression of both POPDC1 and POPDC2, suggesting that stability and/or membrane trafficking of the POPDC1-POPDC2 complex is impaired by pathogenic variants in any of the two proteins. Single-cell RNA sequencing from human hearts demonstrated that co-expression of POPDC1 and 2 was most prevalent in AV node, AV node pacemaker and AV bundle cells. Sinoatrial node cells expressed POPDC2 abundantly, but expression of POPDC1 was sparse. Together, these results concur with predisposition to AV node disease in humans with loss-of-function variants in POPDC1 and POPDC2 and presence of sinus node disease in POPDC2, but not in POPDC1 related disease in human. Using population-level genetic data of more than 1 million individuals we showed that none of the familial variants were associated with clinical outcomes in heterozygous state, suggesting that heterozygous family members are unlikely to develop clinical manifestations and therefore might not necessitate clinical follow-up. Our findings provide evidence for POPDC2 as the cause of a novel Mendelian autosomal recessive cardiac syndrome, consistent with previous work showing that mice and zebrafish deficient in functional POPDC2 display sinus and AV node dysfunction.

The rate and nature of mitochondrial DNA mutations in human pedigrees.

We examined the rate and nature of mitochondrial DNA (mtDNA) mutations in humans using sequence data from 64,806 contemporary Icelanders from 2,548 matrilines. Based on 116,663 mother-child transmissions, 8,199 mutations were detected, providing robust rate estimates by nucleotide type, functional impact, position, and different alleles at the same position. We thoroughly document the true extent of hypermutability in mtDNA, mainly affecting the control region but also some coding-region variants. The results reveal the impact of negative selection on viable deleterious mutations, including rapidly mutating disease-associated 3243A>G and 1555A>G and pre-natal selection that most likely occurs during the development of oocytes. Finally, we show that the fate of new mutations is determined by a drastic germline bottleneck, amounting to an average of 3 mtDNA units effectively transmitted from mother to child.

PSMD11 loss-of-function variants correlate with a neurobehavioral phenotype, obesity, and increased interferon response.

Primary proteasomopathies have recently emerged as a new class of rare early-onset neurodevelopmental disorders (NDDs) caused by pathogenic variants in the PSMB1, PSMC1, PSMC3, or PSMD12 proteasome genes. Proteasomes are large multi-subunit protein complexes that maintain cellular protein homeostasis by clearing ubiquitin-tagged damaged, misfolded, or unnecessary proteins. In this study, we have identified PSMD11 as an additional proteasome gene in which pathogenic variation is associated with an NDD-causing proteasomopathy. PSMD11 loss-of-function variants caused early-onset syndromic intellectual disability and neurodevelopmental delay with recurrent obesity in 10 unrelated children. Our findings demonstrate that the cognitive impairment observed in these individuals could be recapitulated in Drosophila melanogaster with depletion of the PMSD11 ortholog Rpn6, which compromised reversal learning. Our investigations in subject samples further revealed that PSMD11 loss of function resulted in impaired 26S proteasome assembly and the acquisition of a persistent type I interferon (IFN) gene signature, mediated by the integrated stress response (ISR) protein kinase R (PKR). In summary, these data identify PSMD11 as an additional member of the growing family of genes associated with neurodevelopmental proteasomopathies and provide insights into proteasomal biology in human health.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

Obesity Variants in the GIPR Gene Are not Associated With Risk of Fracture or Bone Mineral Density.

CONTEXT: It is not clear if antagonizing the GIP (glucose-dependent insulinotropic polypeptide) receptor (GIPR) for treatment of obesity is likely to increase the risk of fractures, or to lower bone mineral density (BMD) beyond what is expected with rapid weight loss. OBJECTIVE: The objective of this study was to investigate the risk of fracture and BMD of sequence variants in GIPR that reduce the activity of the GIP receptor and have been associated with reduced body mass index (BMI). METHODS: We analyzed the association of 3 missense variants in GIPR, a common variant, rs1800437 (p.Glu354Gln), and 2 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 analyzed associations with fractures at different skeletal sites in the general population: any fractures, hip fractures, vertebral fractures and forearm fractures, and specifically nonvertebral 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 3 missense variants in GIPR was significantly associated with increased risk of fractures or with lower BMD. Burden of LoF variants in GIPR was not associated with fractures or with BMD measured with clinically validated DXA, but was associated with eBMD. CONCLUSION: Missense variants in GIPR, or burden of LoF variants in the gene, are not associated with risk of fractures or with lower BMD.