Expanding OBSL1 Mutation Phenotype: Disproportionate Short Stature, Barrel Chest, Thoracic Kyphoscoliosis, Hypogonadism, and Hypospadias.

We present a Pakistani kinship afflicted with a syndrome with features including short stature, reduced sitting height, orofacial symptoms including prominent forehead and thick eyebrows, short and broad thorax, and variable features such as long philtrum, short broad neck, barrel chest, thoracic kyphoscoliosis, hypogonadism, and hypospadias. Phenotypic variation even within different sibships was considerable. The unique combination of the phenotypic characteristics prompted us to determine the shared homozygosity regions in patient genomes and the pathogenic variants by next generation technologies like single nucleotide polymorphism (SNP) genotyping and whole exome sequencing (WES). Through these analyses, we detected homozygous OBSL1 c.848delG (p.Gly283AlafsTer54) as the causal variant. Biallelic variants in OBSL1 are known to cause Three M Syndrome 2 (3M2), a rare disorder of growth retardation with characteristic facial dysmorphism and musculoskeletal abnormalities. Affected members of the family do not have the 3M2 hallmark features of dolichocephaly, hypoplastic midface, anteverted nares, low nasal bridge, pectus excavatum, sacral hyperlordosis, spina bifida occulta, anterior wedging of thoracic vertebrae, prominent heels, and prominent talus. Moreover, they have some variable features not typical for the syndrome such as round face, disproportionate short stature, barrel chest, thoracic kyphoscoliosis, hypogonadism, and hypospadias. Our study facilitated genetic diagnosis in the family, expanded the clinical phenotype for 3M2, and unraveled the considerable clinical variation within the same kinship. We conclude that unbiased molecular analyses such as WES should be more integrated into healthcare, particularly in populations with high parental consanguinity, given the potential of such analyses to facilitate diagnosis.

Detection and characterization of male sex chromosome abnormalities in the UK Biobank study.

PURPOSE: The study aimed to systematically ascertain male sex chromosome abnormalities, 47,XXY (Klinefelter syndrome [KS]) and 47,XYY, and characterize their risks of adverse health outcomes. METHODS: We analyzed genotyping array or exome sequence data in 207,067 men of European ancestry aged 40 to 70 years from the UK Biobank and related these to extensive routine health record data. RESULTS: Only 49 of 213 (23%) of men whom we identified with KS and only 1 of 143 (0.7%) with 47,XYY had a diagnosis of abnormal karyotype on their medical records or self-report. We observed expected associations for KS with reproductive dysfunction (late puberty: risk ratio [RR] = 2.7; childlessness: RR = 4.2; testosterone concentration: RR = -3.8 nmol/L, all P < 2 × 10-8), whereas XYY men appeared to have normal reproductive function. Despite this difference, we identified several higher disease risks shared across both KS and 47,XYY, including type 2 diabetes (RR = 3.0 and 2.6, respectively), venous thrombosis (RR = 6.4 and 7.4, respectively), pulmonary embolism (RR = 3.3 and 3.7, respectively), and chronic obstructive pulmonary disease (RR = 4.4 and 4.6, respectively) (all P < 7 × 10-6). CONCLUSION: KS and 47,XYY were mostly unrecognized but conferred substantially higher risks for metabolic, vascular, and respiratory diseases, which were only partially explained by higher levels of body mass index, deprivation, and smoking.

The first adolescent case of Fraser syndrome 3, with a novel nonsense variant in GRIP1.

Fraser syndrome is characterized by cryptophthalmos, syndactyly and other autopod defects, and abnormalities of the respiratory and urogenital tracts. Biallelic variants in GRIP1 can cause Fraser syndrome 3 (FRASRS3), and five unrelated FRASRS3 cases have been reported to date. Four cases are fetuses with homozygous truncating variants. The remaining case is an almost 9-year-old Turkish girl compound heterozygous for a truncation variant and a possibly frame-shift intragenic deletion. We present a 15.5-year old Pakistani boy with homozygous truncating variant c.1774C>T (p.Gln592Ter). Of the hallmarks of the disease, the boy has cryptophthalmia, midface retrusion, very low anterior hairline, hair growth on temples extending to the supraorbital line and also on alae nasi, agenesis of right kidney, and cutaneous syndactyly of fingers and toes but no symptoms in any other organs, including lungs, anorectal system, genitalia, and umbilical system. This case is the oldest known individual with FRASRS3, and our findings show that a homozygous GRIP1 truncating variant can manifest with a non-lethal phenotype than in the reported cases with such variants, expanding the phenotypic and mutational spectrum of GRIP1.

Biallelic ZNF407 mutations in a neurodevelopmental disorder with ID, short stature and variable microcephaly, hypotonia, ocular anomalies and facial dysmorphism.

We describe five members of a consanguineous Pakistani family (Family I) plus two affected children from families of different ethnic origins presenting with neurodevelopmental disorders with overlapping features. All affected individuals from families have intellectual disability (ID), ranging from mild to profound, and reduced motor and cognitive skills plus variable features including short stature, microcephaly, developmental delay, hypotonia, dysarthria, deafness, visual problems, enuresis, encopresis, behavioural anomalies, delayed pubertal onset and facial dysmorphism. We first mapped the disease locus in the large family (Family I), and by exome sequencing identified homozygous ZNF407 c.2814_2816dup (p.Val939dup) in four affected members where DNA samples were available. By exome sequencing we detected homozygous c.2405G>T (p.Gly802Val) in the affected member of Family II and compound heterozygous variants c.2884C>G (p.Arg962Gly) and c.3642G>C (p.Lys1214Asn) in the affected member of Family III. Homozygous c.5054C>G (p.Ser1685Trp) has been reported in two brothers with an ID syndrome. Affected individuals we present did not exhibit synophrys, midface hypoplasia, kyphosis, 5th finger camptodactyly, short 4th metatarsals or limited knee mobility observed in the reported family.

Proteomic prediction of diverse incident diseases: a machine learning-guided biomarker discovery study using data from a prospective cohort study.

BACKGROUND: Broad-capture proteomic technologies have the potential to improve disease prediction, enabling targeted prevention and management, but studies have so far been limited to very few selected diseases and have not evaluated predictive performance across multiple conditions. We aimed to evaluate the potential of serum proteins to improve risk prediction over and above health-derived information and polygenic risk scores across a diverse set of 24 outcomes. METHODS: We designed multiple case-cohorts nested in the EPIC-Norfolk prospective study, from participants with available serum samples and genome-wide genotype data, with more than 32 974 person-years of follow-up. Participants were middle-aged individuals (aged 40-79 years at baseline) of European ancestry who were recruited from the general population of Norfolk, England, between March, 1993 and December, 1997. We selected participants who developed one of ten less common diseases within 10 years of follow-up; we also subsampled a randomly drawn control subcohort, which also served to investigate 14 more common outcomes (n>70), including all-cause premature mortality (death before the age of 75 years; case numbers 71-437; controls 608-1556). Individuals were excluded from the current study owing to failed genotyping or proteomic quality control, relatedness, or missing information on age, sex, BMI, or smoking status. We used a machine learning framework to derive sparse predictive protein models for the onset of the the 23 individual diseases and all-cause premature mortality, and to derive a single common sparse multimorbidity signature that was predictive across multiple diseases from 2923 serum proteins. FINDINGS: Participants who developed one of ten less common diseases within 10 years of follow-up included 482 women and 507 men, with a mean age at baseline of 64·56 years (8·08). The random subcohort included 990 women and 769 men, with a mean age of 58·79 years (9·31). As few as five proteins alone outperformed polygenic risk scores for 17 of 23 outcomes (median dfference in concordance index [C-index] 0·13 [0·10-0·17]) and improved predictive performance when added over basic patient-derived information models for seven outcomes, achieving a median C-index of 0·82 (IQR 0·77-0·82). This included diseases with poor prognosis such as lung cancer (C-index 0·85 [+/- cross-validation error 0·83-0·87]), for which we identified unreported biomarkers such as C-X-C motif chemokine ligand 17. A sparse multimorbidity signature of ten proteins improved prediction across seven outcomes over patient-derived information models, achieving performances (median C-index 0·81 [IQR 0·80-0·82]) similar to those of disease-specific signatures. INTERPRETATION: We show the value of broad-capture proteomic biomarker discovery studies across multiple diseases of diverse causes, pointing to those that might benefit the most from proteomic approaches, and the potential to derive common sparse biomarker panels for prediction of multiple diseases at once. This framework could enable follow-up studies to explore the generalisability of proteomic models and to benchmark these against clinical assays, which are required to understand the translational potential of these findings. FUNDING: Medical Research Council, Health Data Research UK, UK Research and Innovation-National Institute for Health and Care Research, Cancer Research UK, and Wellcome Trust.

Identifying proteomic risk factors for overall, aggressive, and early onset prostate cancer using Mendelian Randomisation and tumour spatial transcriptomics.

BACKGROUND: Understanding the role of circulating proteins in prostate cancer risk can reveal key biological pathways and identify novel targets for cancer prevention. METHODS: We investigated the association of 2002 genetically predicted circulating protein levels with risk of prostate cancer overall, and of aggressive and early onset disease, using cis-pQTL Mendelian randomisation (MR) and colocalisation. Findings for proteins with support from both MR, after correction for multiple-testing, and colocalisation were replicated using two independent cancer GWAS, one of European and one of African ancestry. Proteins with evidence of prostate-specific tissue expression were additionally investigated using spatial transcriptomic data in prostate tumour tissue to assess their role in tumour aggressiveness. Finally, we mapped risk proteins to drug and ongoing clinical trials targets. FINDINGS: We identified 20 proteins genetically linked to prostate cancer risk (14 for overall [8 specific], 7 for aggressive [3 specific], and 8 for early onset disease [2 specific]), of which the majority replicated where data were available. Among these were proteins associated with aggressive disease, such as PPA2 [Odds Ratio (OR) per 1 SD increment = 2.13, 95% CI: 1.54-2.93], PYY [OR = 1.87, 95% CI: 1.43-2.44] and PRSS3 [OR = 0.80, 95% CI: 0.73-0.89], and those associated with early onset disease, including EHPB1 [OR = 2.89, 95% CI: 1.99-4.21], POGLUT3 [OR = 0.76, 95% CI: 0.67-0.86] and TPM3 [OR = 0.47, 95% CI: 0.34-0.64]. We confirmed an inverse association of MSMB with prostate cancer overall [OR = 0.81, 95% CI: 0.80-0.82], and also found an inverse association with both aggressive [OR = 0.84, 95% CI: 0.82-0.86] and early onset disease [OR = 0.71, 95% CI: 0.68-0.74]. Using spatial transcriptomics data, we identified MSMB as the genome-wide top-most predictive gene to distinguish benign regions from high grade cancer regions that comparatively had five-fold lower MSMB expression. Additionally, ten proteins that were associated with prostate cancer risk also mapped to existing therapeutic interventions. INTERPRETATION: Our findings emphasise the importance of proteomics for improving our understanding of prostate cancer aetiology and of opportunities for novel therapeutic interventions. Additionally, we demonstrate the added benefit of in-depth functional analyses to triangulate the role of risk proteins in the clinical aggressiveness of prostate tumours. Using these integrated methods, we identify a subset of risk proteins associated with aggressive and early onset disease as priorities for investigation for the future prevention and treatment of prostate cancer. FUNDING: This work was supported by Cancer Research UK (grant no. C8221/A29017).

Identifying therapeutic targets for cancer among 2074 circulating proteins and risk of nine cancers.

Circulating proteins can reveal key pathways to cancer and identify therapeutic targets for cancer prevention. We investigate 2,074 circulating proteins and risk of nine common cancers (bladder, breast, endometrium, head and neck, lung, ovary, pancreas, kidney, and malignant non-melanoma) using cis protein Mendelian randomisation and colocalization. We conduct additional analyses to identify adverse side-effects of altering risk proteins and map cancer risk proteins to drug targets. Here we find 40 proteins associated with common cancers, such as PLAUR and risk of breast cancer [odds ratio per standard deviation increment: 2.27, 1.88-2.74], and with high-mortality cancers, such as CTRB1 and pancreatic cancer [0.79, 0.73-0.85]. We also identify potential adverse effects of protein-altering interventions to reduce cancer risk, such as hypertension. Additionally, we report 18 proteins associated with cancer risk that map to existing drugs and 15 that are not currently under clinical investigation. In sum, we identify protein-cancer links that improve our understanding of cancer aetiology. We also demonstrate that the wider consequence of any protein-altering intervention on well-being and morbidity is required to interpret any utility of proteins as potential future targets for therapeutic prevention.

Proteogenomic links to human metabolic diseases.

Studying the plasma proteome as the intermediate layer between the genome and the phenome has the potential to identify new disease processes. Here, we conducted a cis-focused proteogenomic analysis of 2,923 plasma proteins measured in 1,180 individuals using antibody-based assays. We (1) identify 256 unreported protein quantitative trait loci (pQTL); (2) demonstrate shared genetic regulation of 224 cis-pQTLs with 575 specific health outcomes, revealing examples for notable metabolic diseases (such as gastrin-releasing peptide as a potential therapeutic target for type 2 diabetes); (3) improve causal gene assignment at 40% (n = 192) of overlapping risk loci; and (4) observe convergence of phenotypic consequences of cis-pQTLs and rare loss-of-function gene burden for 12 proteins, such as TIMD4 for lipoprotein metabolism. Our findings demonstrate the value of integrating complementary proteomic technologies with genomics even at moderate scale to identify new mediators of metabolic diseases with the potential for therapeutic interventions.

Identifying proteomic risk factors for overall, aggressive and early onset prostate cancer using Mendelian randomization and tumor spatial transcriptomics.

Background: Understanding the role of circulating proteins in prostate cancer risk can reveal key biological pathways and identify novel targets for cancer prevention. Methods: We investigated the association of 2,002 genetically predicted circulating protein levels with risk of prostate cancer overall, and of aggressive and early onset disease, using cis-pQTL Mendelian randomization (MR) and colocalization. Findings for proteins with support from both MR, after correction for multiple-testing, and colocalization were replicated using two independent cancer GWAS, one of European and one of African ancestry. Proteins with evidence of prostate-specific tissue expression were additionally investigated using spatial transcriptomic data in prostate tumor tissue to assess their role in tumor aggressiveness. Finally, we mapped risk proteins to drug and ongoing clinical trials targets. Results: We identified 20 proteins genetically linked to prostate cancer risk (14 for overall [8 specific], 7 for aggressive [3 specific], and 8 for early onset disease [2 specific]), of which a majority were novel and replicated. Among these were proteins associated with aggressive disease, such as PPA2 [Odds Ratio (OR) per 1 SD increment = 2.13, 95% CI: 1.54-2.93], PYY [OR = 1.87, 95% CI: 1.43-2.44] and PRSS3 [OR = 0.80, 95% CI: 0.73-0.89], and those associated with early onset disease, including EHPB1 [OR = 2.89, 95% CI: 1.99-4.21], POGLUT3 [OR = 0.76, 95% CI: 0.67-0.86] and TPM3 [OR = 0.47, 95% CI: 0.34-0.64]. We confirm an inverse association of MSMB with prostate cancer overall [OR = 0.81, 95% CI: 0.80-0.82], and also find an inverse association with both aggressive [OR = 0.84, 95% CI: 0.82-0.86] and early onset disease [OR = 0.71, 95% CI: 0.68-0.74]. Using spatial transcriptomics data, we identified MSMB as the genome-wide top-most predictive gene to distinguish benign regions from high grade cancer regions that had five-fold lower MSMB expression. Additionally, ten proteins that were associated with prostate cancer risk mapped to existing therapeutic interventions. Conclusion: Our findings emphasize the importance of proteomics for improving our understanding of prostate cancer etiology and of opportunities for novel therapeutic interventions. Additionally, we demonstrate the added benefit of in-depth functional analyses to triangulate the role of risk proteins in the clinical aggressiveness of prostate tumors. Using these integrated methods, we identify a subset of risk proteins associated with aggressive and early onset disease as priorities for investigation for the future prevention and treatment of prostate cancer.

Elevated plasma complement factor H related 5 protein is associated with venous thromboembolism.

Venous thromboembolism (VTE) is a common, multi-causal disease with potentially serious short- and long-term complications. In clinical practice, there is a need for improved plasma biomarker-based tools for VTE diagnosis and risk prediction. Here we show, using proteomics profiling to screen plasma from patients with suspected acute VTE, and several case-control studies for VTE, how Complement Factor H Related 5 protein (CFHR5), a regulator of the alternative pathway of complement activation, is a VTE-associated plasma biomarker. In plasma, higher CFHR5 levels are associated with increased thrombin generation potential and recombinant CFHR5 enhanced platelet activation in vitro. GWAS analysis of ~52,000 participants identifies six loci associated with CFHR5 plasma levels, but Mendelian randomization do not demonstrate causality between CFHR5 and VTE. Our results indicate an important role for the regulation of the alternative pathway of complement activation in VTE and that CFHR5 represents a potential diagnostic and/or risk predictive plasma biomarker.

KERATIN 17-related recessive atypical pachyonychia congenita with variable hair and tooth anomalies.

We present the first pachyonychia congenita (PC) to involve all ectodermal derivatives and the first recessive KRT17-related PC in total seven members of two consanguineous Pakistani families. This atypical PC is characterized by an unusual combination of pachyonychia, plantar keratoderma, folliculitis, alopecia, sparse eyebrows, dental anomalies and variable acanthosis nigricans of neck, dry skin, palmoplantar hyperhidrosis, recurrent blisters on soles and/or arms, rough sparse hair on scalp and keratosis pilaris. By exome sequencing we detected homozygous KRT17 c.281G>A (p.(Arg94His)) in affected individuals, and linkage mapping indicated a single locus. Heterozygous variants in KRT17 cause PC2 (PC-K17) with main characteristics of pachyonychia, subungual keratosis, palmoplantar keratoderma, hyperhidrosis, oral leukokeratosis and epidermal cysts, or steatocystoma multiplex, both with dominant inheritance. The causative variant has been reported in heterozygous state in a family afflicted with severe steatocystoma multiplex and in a sporadic PC2 case, and thus we also define a third phenotype related to the variant. Both exome sequencing and linkage mapping demonstrated recessive inheritance whereas Sanger sequencing indicated heterozygosity for the causal variant, reiterating caution for simple targeted sequencing for genetic testing. Testing parents for variants found in sibs could uncover recessive inheritance also in other KRT genes.

Identification of Rare Loss-of-Function Genetic Variation Regulating Body Fat Distribution.

CONTEXT: Biological and translational insights from large-scale, array-based genetic studies of fat distribution, a key determinant of metabolic health, have been limited by the difficulty in linking predominantly noncoding variants to specific gene targets. Rare coding variant analyses provide greater confidence that a specific gene is involved, but do not necessarily indicate whether gain or loss of function (LoF) would be of most therapeutic benefit. OBJECTIVE: This work aimed to identify genes/proteins involved in determining fat distribution. METHODS: We combined the power of genome-wide analysis of array-based rare, nonsynonymous variants in 450 562 individuals in the UK Biobank with exome-sequence-based rare LoF gene burden testing in 184 246 individuals. RESULTS: The data indicate that the LoF of 4 genes (PLIN1 [LoF variants, P = 5.86 × 10-7], INSR [LoF variants, P = 6.21 × 10-7], ACVR1C [LoF + moderate impact variants, P = 1.68 × 10-7; moderate impact variants, P = 4.57 × 10-7], and PDE3B [LoF variants, P = 1.41 × 10-6]) is associated with a beneficial effect on body mass index-adjusted waist-to-hip ratio and increased gluteofemoral fat mass, whereas LoF of PLIN4 (LoF variants, P = 5.86 × 10-7 adversely affects these parameters. Phenotypic follow-up suggests that LoF of PLIN1, PDE3B, and ACVR1C favorably affects metabolic phenotypes (eg, triglycerides [TGs] and high-density lipoprotein [HDL] cholesterol concentrations) and reduces the risk of cardiovascular disease, whereas PLIN4 LoF has adverse health consequences. INSR LoF is associated with lower TG and HDL levels but may increase the risk of type 2 diabetes. CONCLUSION: This study robustly implicates these genes in the regulation of fat distribution, providing new and in some cases somewhat counterintuitive insight into the potential consequences of targeting these molecules therapeutically.

CRADD and USP44 mutations in intellectual disability, mild lissencephaly, brain atrophy, developmental delay, strabismus, behavioural problems and skeletal anomalies.

In a consanguineous Pakistani kinship afflicted with mild to moderate intellectual disability (ID), mild lissencephaly, brain atrophy and skeletal anomalies, we detected homozygous CRADD c.2T > G (p.Met1?) and USP44 c.873_886delinsT (p.Leu291Phefs*8), two good candidates 1.85-Mb apart that segregated with the disorder. Biallelic damaging variants in CRADD cause recessive mental retardation-34 (MRT34; MIM 614499) with mild to moderate ID, "thin" lissencephaly, and variable megalencephaly and seizures. For USP44, only a single ID family has been reported with a homozygous deleterious variant, which is the same as the variant we detected. In affected individuals we present, at ages 29-32 years, clinical findings are similar yet not fully concordant with phenotypes for either gene considering the skeletal findings, and ID is not as severe as would be expected for defects in two genes with additive effect. Some variable CRADD-related features such as language impairment and seizures are not observed in the presented family. The presence of the two variants in the family is a very rare example of familial linked homozygous variants, and whether the damaging USP44 variant contributed to the disease in the family we present is not clear. As for the skeletal findings, facial dysmorphism and digestive problems, we did not find a candidate variant. This study is an example of both clinical variation and difficulty in variant detection and evaluation. Our findings highlight that even an extensive exome sequence analysis can fail to fully uncover the complex molecular basis of a syndrome even if potentially causative variants are identified.

GIGYF1 loss of function is associated with clonal mosaicism and adverse metabolic health.

Mosaic loss of chromosome Y (LOY) in leukocytes is the most common form of clonal mosaicism, caused by dysregulation in cell-cycle and DNA damage response pathways. Previous genetic studies have focussed on identifying common variants associated with LOY, which we now extend to rarer, protein-coding variation using exome sequences from 82,277 male UK Biobank participants. We find that loss of function of two genes-CHEK2 and GIGYF1-reach exome-wide significance. Rare alleles in GIGYF1 have not previously been implicated in any complex trait, but here loss-of-function carriers exhibit six-fold higher susceptibility to LOY (OR = 5.99 [3.04-11.81], p = 1.3 × 10-10). These same alleles are also associated with adverse metabolic health, including higher susceptibility to Type 2 Diabetes (OR = 6.10 [3.51-10.61], p = 1.8 × 10-12), 4 kg higher fat mass (p = 1.3 × 10-4), 2.32 nmol/L lower serum IGF1 levels (p = 1.5 × 10-4) and 4.5 kg lower handgrip strength (p = 4.7 × 10-7) consistent with proposed GIGYF1 enhancement of insulin and IGF-1 receptor signalling. These associations are mirrored by a common variant nearby associated with the expression of GIGYF1. Our observations highlight a potential direct connection between clonal mosaicism and metabolic health.

Synergistic insights into human health from aptamer- and antibody-based proteomic profiling.

Affinity-based proteomics has enabled scalable quantification of thousands of protein targets in blood enhancing biomarker discovery, understanding of disease mechanisms, and genetic evaluation of drug targets in humans through protein quantitative trait loci (pQTLs). Here, we integrate two partly complementary techniques-the aptamer-based SomaScan® v4 assay and the antibody-based Olink assays-to systematically assess phenotypic consequences of hundreds of pQTLs discovered for 871 protein targets across both platforms. We create a genetically anchored cross-platform proteome-phenome network comprising 547 protein-phenotype connections, 36.3% of which were only seen with one of the two platforms suggesting that both techniques capture distinct aspects of protein biology. We further highlight discordance of genetically predicted effect directions between assays, such as for PILRA and Alzheimer's disease. Our results showcase the synergistic nature of these technologies to better understand and identify disease mechanisms and provide a benchmark for future cross-platform discoveries.

Mapping the proteo-genomic convergence of human diseases.

Characterization of the genetic regulation of proteins is essential for understanding disease etiology and developing therapies. We identified 10,674 genetic associations for 3892 plasma proteins to create a cis-anchored gene-protein-disease map of 1859 connections that highlights strong cross-disease biological convergence. This proteo-genomic map provides a framework to connect etiologically related diseases, to provide biological context for new or emerging disorders, and to integrate different biological domains to establish mechanisms for known gene-disease links. Our results identify proteo-genomic connections within and between diseases and establish the value of cis-protein variants for annotation of likely causal disease genes at loci identified in genome-wide association studies, thereby addressing a major barrier to experimental validation and clinical translation of genetic discoveries.

Identification of new therapeutic targets for osteoarthritis through genome-wide analyses of UK Biobank data.

Osteoarthritis is the most common musculoskeletal disease and the leading cause of disability globally. Here, we performed a genome-wide association study for osteoarthritis (77,052 cases and 378,169 controls), analyzing four phenotypes: knee osteoarthritis, hip osteoarthritis, knee and/or hip osteoarthritis, and any osteoarthritis. We discovered 64 signals, 52 of them novel, more than doubling the number of established disease loci. Six signals fine-mapped to a single variant. We identified putative effector genes by integrating expression quantitative trait loci (eQTL) colocalization, fine-mapping, and human rare-disease, animal-model, and osteoarthritis tissue expression data. We found enrichment for genes underlying monogenic forms of bone development diseases, and for the collagen formation and extracellular matrix organization biological pathways. Ten of the likely effector genes, including TGFB1 (transforming growth factor beta 1), FGF18 (fibroblast growth factor 18), CTSK (cathepsin K), and IL11 (interleukin 11), have therapeutics approved or in clinical trials, with mechanisms of action supportive of evaluation for efficacy in osteoarthritis.