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Genome-wide association studies (GWAS) have identified thousands of genetic variants linked to the risk of human disease. However, GWAS have so far remained largely underpowered in relation to identifying associations in the rare and low-frequency allelic spectrum and have lacked the resolution to trace causal mechanisms to underlying genes 1 . Here we combined whole-exome sequencing in 392,814 UK Biobank participants with imputed genotypes from 260,405 FinnGen participants (653,219 total individuals) to conduct association meta-analyses for 744 disease endpoints across the protein-coding allelic frequency spectrum, bridging the gap between common and rare variant studies. We identified 975 associations, with more than one-third being previously unreported. We demonstrate population-level relevance for mutations previously ascribed to causing single-gene disorders, map GWAS associations to likely causal genes, explain disease mechanisms, and systematically relate disease associations to levels of 117 biomarkers and clinical-stage drug targets. Combining sequencing and genotyping in two population biobanks enabled us to benefit from increased power to detect and explain disease associations, validate findings through replication and propose medical actionability for rare genetic variants. Our study provides a compendium of protein-coding variant associations for future insights into disease biology and drug discovery. A meta-analysis combining whole-exome sequencing data from UK Biobank participants and imputed genotypes from FinnGen participants enables identification of genetic associations with human disease in the rare and low-frequency allelic spectrum

Like most complex phenotypes, exceptional longevity is thought to reflect a combined influence of environmental (e.g., lifestyle choices, where we live) and genetic factors. To explore the genetic contribution, we undertook a genome-wide association study of exceptional longevity in 801 centenarians (median age at death 104 years) and 914 genetically matched healthy controls. Using these data, we built a genetic model that includes 281 single nucleotide polymorphisms (SNPs) and discriminated between cases and controls of the discovery set with 89% sensitivity and specificity, and with 58% specificity and 60% sensitivity in an independent cohort of 341 controls and 253 genetically matched nonagenarians and centenarians (median age 100 years). Consistent with the hypothesis that the genetic contribution is largest with the oldest ages, the sensitivity of the model increased in the independent cohort with older and older ages (71% to classify subjects with an age at death>102 and 85% to classify subjects with an age at death>105). For further validation, we applied the model to an additional, unmatched 60 centenarians (median age 107 years) resulting in 78% sensitivity, and 2863 unmatched controls with 61% specificity. The 281 SNPs include the SNP rs2075650 in TOMM40/APOE that reached irrefutable genome wide significance (posterior probability of association = 1) and replicated in the independent cohort. Removal of this SNP from the model reduced the accuracy by only 1%. Further in-silico analysis suggests that 90% of centenarians can be grouped into clusters characterized by different \"genetic signatures\" of varying predictive values for exceptional longevity. The correlation between 3 signatures and 3 different life spans was replicated in the combined replication sets. The different signatures may help dissect this complex phenotype into sub-phenotypes of exceptional longevity.

The ratio of forced expiratory volume in one second to forced vital capacity (FEV(1)/FVC) is a measure used to diagnose airflow obstruction and is highly heritable. We performed a genome-wide association study in 7,691 Framingham Heart Study participants to identify single-nucleotide polymorphisms (SNPs) associated with the FEV(1)/FVC ratio, analyzed as a percent of the predicted value. Identified SNPs were examined in an independent set of 835 Family Heart Study participants enriched for airflow obstruction. Four SNPs in tight linkage disequilibrium on chromosome 4q31 were associated with the percent predicted FEV(1)/FVC ratio with p-values of genome-wide significance in the Framingham sample (best p-value = 3.6e-09). One of the four chromosome 4q31 SNPs (rs13147758; p-value 2.3e-08 in Framingham) was genotyped in the Family Heart Study and produced evidence of association with the same phenotype, percent predicted FEV(1)/FVC (p-value = 2.0e-04). The effect estimates for association in the Framingham and Family Heart studies were in the same direction, with the minor allele (G) associated with higher FEV(1)/FVC ratio levels. Results from the Family Heart Study demonstrated that the association extended to FEV(1) and dichotomous airflow obstruction phenotypes, particularly among smokers. The SNP rs13147758 was associated with the percent predicted FEV(1)/FVC ratio in independent samples from the Framingham and Family Heart Studies producing a combined p-value of 8.3e-11, and this region of chromosome 4 around 145.68 megabases was associated with COPD in three additional populations reported in the accompanying manuscript. The associated SNPs do not lie within a gene transcript but are near the hedgehog-interacting protein (HHIP) gene and several expressed sequence tags cloned from fetal lung. Though it is unclear what gene or regulatory effect explains the association, the region warrants further investigation.

Five genes have been identified that contribute to Mendelian forms of Parkinson disease (PD); however, mutations have been found in fewer than 5% of patients, suggesting that additional genes contribute to disease risk. Unlike previous studies that focused primarily on sporadic PD, we have performed the first genomewide association study (GWAS) in familial PD. Genotyping was performed with the Illumina HumanCNV370Duo array in 857 familial PD cases and 867 controls. A logistic model was employed to test for association under additive and recessive modes of inheritance after adjusting for gender and age. No result met genomewide significance based on a conservative Bonferroni correction. The strongest association result was with SNPs in the GAK/DGKQ region on chromosome 4 (additive model: p = 3.4 x 10⁻⁶; OR = 1.69). Consistent evidence of association was also observed to the chromosomal regions containing SNCA (additive model: p = 5.5 x 10⁻⁵; OR = 1.35) and MAPT (recessive model: p = 2.0 x 10⁻⁵; OR = 0.56). Both of these genes have been implicated previously in PD susceptibility; however, neither was identified in previous GWAS studies of PD. Meta-analysis was performed using data from a previous case-control GWAS, and yielded improved p values for several regions, including GAK/DGKQ (additive model: p = 2.5 x 10⁻⁷) and the MAPT region (recessive model: p = 9.8 x 10⁻⁶; additive model: p = 4.8 x 10⁻⁵). These data suggest the identification of new susceptibility alleles for PD in the GAK/DGKQ region, and also provide further support for the role of SNCA and MAPT in PD susceptibility.

Copy number variants (CNVs) are known to cause Mendelian forms of Parkinson disease (PD), most notably in SNCA and PARK2. PARK2 has a recessive mode of inheritance; however, recent evidence demonstrates that a single CNV in PARK2 (but not a single missense mutation) may increase risk for PD. We recently performed a genome-wide association study for PD that excluded individuals known to have either a LRRK2 mutation or two PARK2 mutations. Data from the Illumina370Duo arrays were re-clustered using only white individuals with high quality intensity data, and CNV calls were made using two algorithms, PennCNV and QuantiSNP. After quality assessment, the final sample included 816 cases and 856 controls. Results varied between the two CNV calling algorithms for many regions, including the PARK2 locus (genome-wide p = 0.04 for PennCNV and p = 0.13 for QuantiSNP). However, there was consistent evidence with both algorithms for two novel genes, USP32 and DOCK5 (empirical, genome-wide p-values<0.001). PARK2 CNVs tended to be larger, and all instances that were molecularly tested were validated. In contrast, the CNVs in both novel loci were smaller and failed to replicate using real-time PCR, MLPA, and gel electrophoresis. The DOCK5 variation is more akin to a VNTR than a typical CNV and the association is likely caused by artifact due to DNA source. DNA for all the cases was derived from whole blood, while the DNA for all controls was derived from lymphoblast cell lines. The USP32 locus contains many SNPs with low minor allele frequency leading to a loss of heterozygosity that may have been spuriously interpreted by the CNV calling algorithms as support for a deletion. Thus, only the CNVs within the PARK2 locus could be molecularly validated and associated with PD susceptibility.

Background Age at onset in Parkinson disease (PD) is a highly heritable quantitative trait for which a significant genetic influence is supported by multiple segregation analyses. Because genes associated with onset age may represent invaluable therapeutic targets to delay the disease, we sought to identify such genetic modifiers using a genomewide association study in familial PD. There have been previous genomewide association studies (GWAS) to identify genes influencing PD susceptibility, but this is the first to identify genes contributing to the variation in onset age. Methods Initial analyses were performed using genotypes generated with the Illumina HumanCNV370Duo array in a sample of 857 unrelated, familial PD cases. Subsequently, a meta-analysis of imputed SNPs was performed combining the familial PD data with that from a previous GWAS of 440 idiopathic PD cases. The SNPs from the meta-analysis with the lowest p-values and consistency in the direction of effect for onset age were then genotyped in a replication sample of 747 idiopathic PD cases from the Parkinson Institute Biobank of Milan, Italy. Results Meta-analysis across the three studies detected consistent association (p < 1 × 10 -5 ) with five SNPs, none of which reached genomewide significance. On chromosome 11, the SNP with the lowest p-value (rs10767971; p = 5.4 × 10 -7 ) lies between the genes QSER1 and PRRG4 . Near the PARK3 linkage region on chromosome 2p13, association was observed with a SNP (rs7577851; p = 8.7 × 10 -6 ) which lies in an intron of the AAK1 gene. This gene is closely related to GAK , identified as a possible PD susceptibility gene in the GWAS of the familial PD cases. Conclusion Taken together, these results suggest an influence of genes involved in endocytosis and lysosomal sorting in PD pathogenesis.

African Americans have been understudied in genome wide association studies of diabetes and related traits. In the current study, we examined the joint association of single nucleotide polymorphisms (SNPs) and copy number variants (CNVs) with fasting insulin and an index of insulin resistance (HOMA-IR) in the HyperGEN study, a family based study with proband ascertainment for hypertension. This analysis is restricted to 1,040 African Americans without diabetes. We generated allele specific CNV genotypes at 872,243 autosomal loci using Birdsuite, a freely available multi-stage program. Joint tests of association for SNPs and CNVs were performed using linear mixed models adjusting for covariates and familial relationships. Our results highlight SNPs associated with fasting insulin and HOMA-IR (rs6576507 and rs8026527, 3.7*10(-7)≤P≤1.1*10(-5)) near ATPase, class V, type 10A (ATP10A), and the L Type voltage dependent calcium channel (CACNA1D, rs1401492, P≤5.2*10(-6)). ATP10A belongs to a family of aminophospholipid-transporting ATPases and has been associated with type 2 diabetes in mice. CACNA1D has been linked to pancreatic beta cell generation in mice. The two most significant copy variable markers (rs10277702 and rs361367; P<2.0*10(-4)) were in the beta variable region of the T-cell receptor gene (TCRVB). Human and mouse TCR has been shown to mimic insulin and its receptor and could contribute to insulin resistance. Our findings differ from genome wide association studies of fasting insulin and other diabetes related traits in European populations, highlighting the continued need to investigate unique genetic influences for understudied populations such as African Americans.

For genome-wide association studies in family-based designs, we propose a new, universally applicable approach. The new test statistic exploits all available information about the association, while, by virtue of its design, it maintains the same robustness against population admixture as traditional family-based approaches that are based exclusively on the within-family information. The approach is suitable for the analysis of almost any trait type, e.g. binary, continuous, time-to-onset, multivariate, etc., and combinations of those. We use simulation studies to verify all theoretically derived properties of the approach, estimate its power, and compare it with other standard approaches. We illustrate the practical implications of the new analysis method by an application to a lung-function phenotype, forced expiratory volume in one second (FEV1) in 4 genome-wide association studies.

Stephanie London and colleagues from the CHARGE Consortium report genome-wide association studies for pulmonary function. Spirometric measures of lung function are heritable traits that reflect respiratory health and predict morbidity and mortality. We meta-analyzed genome-wide association studies for two clinically important lung-function measures: forced expiratory volume in the first second (FEV 1 ) and its ratio to forced vital capacity (FEV 1 /FVC), an indicator of airflow obstruction. This meta-analysis included 20,890 participants of European ancestry from four CHARGE Consortium studies: Atherosclerosis Risk in Communities, Cardiovascular Health Study, Framingham Heart Study and Rotterdam Study. We identified eight loci associated with FEV 1 /FVC ( HHIP , GPR126 , ADAM19 , AGER - PPT2 , FAM13A , PTCH1 , PID1 and HTR4 ) and one locus associated with FEV 1 ( INTS12-GSTCD-NPNT ) at or near genome-wide significance ( P < 5 × 10 −8 ) in the CHARGE Consortium dataset. Our findings may offer insights into pulmonary function and pathogenesis of chronic lung disease.

We examined common variants in the fatty acid binding protein 4 gene ( FABP4 ) and plasma levels of FABP4 in adults aged 65 and older from the Cardiovascular Health Study. We genotyped rs16909187, rs1054135, rs16909192, rs10808846, rs7018409, rs2290201, and rs6992708 and measured circulating FABP4 levels among 3190 European Americans and 660 African Americans. Among European Americans, the minor alleles of six single nucleotide polymorphisms (SNP) were associated with lower FABP4 levels (all p  ≤ 0.01). Among African Americans, the SNP with the lowest minor allele frequency was associated with lower FABP4 levels ( p  = 0.015). The C-A haplotype of rs16909192 and rs2290201 was associated with lower FABP4 levels in both European Americans (frequency = 16 %; p  = 0.001) and African Americans (frequency = 8 %; p  = 0.04). The haplotype combined a SNP in the first intron with one in the 3′untranslated region. However, the alleles associated with lower FABP4 levels were associated with higher fasting glucose in meta-analyses from the MAGIC consortium. These results demonstrate associations of common SNP and haplotypes in the FABP4 gene with lower plasma FABP4 but higher fasting glucose levels.