Human longevity is influenced by many genetic variants: evidence from 75,000 UK Biobank participants

Variation in human lifespan is 20 to 30% heritable in twins but few genetic variants have been identified. We undertook a Genome Wide Association Study (GWAS) using age at death of parents of middle-aged UK Biobank participants of European decent (n=75,244 with father's and/or mother's data, excluding early deaths). Genetic risk scores for 19 phenotypes (n=777 proven variants) were also tested. In GWAS, a nicotine receptor locus(CHRNA3, previously associated with increased smoking and lung cancer) was associated with fathers' survival. Less common variants requiring further confirmation were also identified. Offspring of longer lived parents had more protective alleles for coronary artery disease, systolic blood pressure, body mass index, cholesterol and triglyceride levels, type-1 diabetes, inflammatory bowel disease and Alzheimer's disease. In candidate analyses, variants in the TOMM40/APOE locus were associated with longevity, but FOXO variants were not. Associations between extreme longevity (mother >=98 years, fathers >=95 years, n=1,339) and disease alleles were similar, with an additional association with HDL cholesterol (p=5.7x10-3). These results support a multiple protective factors model influencing lifespan and longevity (top 1% survival) in humans, with prominent roles for cardiovascular-related pathways. Several of these genetically influenced risks, including blood pressure and tobacco exposure, are potentially modifiable.

Adherence to Oral Glucose-Lowering Therapies and Associations With 1-Year HbA1c: A Retrospective Cohort Analysis in a Large Primary Care Database

OBJECTIVE

The impact of taking oral glucose-lowering medicines intermittently, rather than as recommended, is unclear. We conducted a retrospective cohort study using community-acquired U.K. clinical data (Clinical Practice Research Database [CPRD] and GoDARTS database) to examine the prevalence of nonadherence to treatment for type 2 diabetes and investigate its potential impact on HbA1c reduction stratified by type of glucose-lowering medication.

RESEARCH DESIGN AND METHODS

Data were extracted for patients treated between 2004 and 2014 who were newly prescribed metformin, sulfonylurea, thiazolidinedione, or dipeptidyl peptidase 4 inhibitors and who continued to obtain prescriptions over 1 year. Cohorts were defined by prescribed medication type, and good adherence was defined as a medication possession ratio ≥0.8. Linear regression was used to determine potential associations between adherence and 1-year baseline-adjusted HbA1c reduction.

RESULTS

In CPRD and GoDARTS, 13% and 15% of patients, respectively, were nonadherent. Proportions of nonadherent patients varied by the oral glucose-lowering treatment prescribed (range 8.6% [thiazolidinedione] to 18.8% [metformin]). Nonadherent, compared with adherent, patients had a smaller HbA1c reduction (0.4% [4.4 mmol/mol] and 0.46% [5.0 mmol/mol] for CPRD and GoDARTs, respectively). Difference in HbA1c response for adherent compared with nonadherent patients varied by drug (range 0.38% [4.1 mmol/mol] to 0.75% [8.2 mmol/mol] lower in adherent group). Decreasing levels of adherence were consistently associated with a smaller reduction in HbA1c.

CONCLUSIONS

Reduced medication adherence for commonly used glucose-lowering therapies among patients persisting with treatment is associated with smaller HbA1c reductions compared with those taking treatment as recommended. Differences observed in HbA1c responses to glucose-lowering treatments may be explained in part by their intermittent use.

Genetic evidence that lower circulating FSH levels lengthen menstrual cycle, increase age at menopause and impact female reproductive health

STUDY QUESTION

How does a genetic variant in the FSHB promoter, known to alter FSH levels, impact female reproductive health?

SUMMARY ANSWER

The T allele of the FSHB promoter polymorphism (rs10835638; c.-211G>T) results in longer menstrual cycles and later menopause and, while having detrimental effects on fertility, is protective against endometriosis.

WHAT IS KNOWN ALREADY

The FSHB promoter polymorphism (rs10835638; c.-211G>T) affects levels of FSHB transcription and, as a result, circulating levels of FSH. FSH is required for normal fertility and genetic variants at the FSHB locus are associated with age at menopause and polycystic ovary syndrome (PCOS).

STUDY DESIGN, SIZE, DURATION

We used cross-sectional data from the UK Biobank to look at associations between the FSHB promoter polymorphism and reproductive traits, and performed a genome-wide association study (GWAS) for length of menstrual cycle.

PARTICIPANTS/MATERIALS, SETTING, METHODS

We included white British individuals aged 40-69 years in 2006-2010, in the May 2015 release of genetic data from UK Biobank. We tested the FSH-lowering T allele of the FSHB promoter polymorphism (rs10835638; c.-211G>T) for associations with 29, mainly female, reproductive phenotypes in up to 63 350 women and 56 608 men. We conducted a GWAS in 9534 individuals to identify genetic variants associated with length of menstrual cycle.

MAIN RESULTS AND THE ROLE OF CHANCE

The FSH-lowering T allele of the FSHB promoter polymorphism (rs10835638; MAF 0.16) was associated with longer menstrual cycles [0.16 SD (c. 1 day) per minor allele; 95% confidence interval (CI) 0.12-0.20; P = 6 × 10(-16)], later age at menopause (0.13 years per minor allele; 95% CI 0.04-0.22; P = 5.7 × 10(-3)), greater female nulliparity [odds ratio (OR) = 1.06; 95% CI 1.02-1.11; P = 4.8 × 10(-3)] and lower risk of endometriosis (OR = 0.79; 95% CI 0.69-0.90; P = 4.1 × 10(-4)). The FSH-lowering T allele was not associated with other female reproductive illnesses or conditions in our study and we did not replicate associations with male infertility or PCOS. In the GWAS for menstrual cycle length, only variants near the FSHB gene reached genome-wide significance (P < 5 × 10(-9)).

LIMITATIONS, REASONS FOR CAUTION

The data included might be affected by recall bias. Cycle length was not available for 25% of women still cycling (1% did not answer, 6% did not know and for 18% cycle length was recorded as 'irregular'). Women with a cycle length recorded were aged over 40 and were approaching menopause; however, we did not find evidence that this affected the results. Many of the groups with illnesses had relatively small sample sizes and so the study may have been under-powered to detect an effect.

WIDER IMPLICATIONS OF THE FINDINGS

We found a strong novel association between a genetic variant that lowers FSH levels and longer menstrual cycles, at a locus previously robustly associated with age at menopause. The variant was also associated with nulliparity and endometriosis risk. These findings should now be verified in a second independent group of patients. We conclude that lifetime differences in circulating levels of FSH between individuals can influence menstrual cycle length and a range of reproductive outcomes, including menopause timing, infertility, endometriosis and PCOS.

STUDY FUNDING/COMPETING INTERESTS

None.

TRIAL REGISTRATION NUMBER

Not applicable.

Association analysis of 29,956 individuals confirms that a low-frequency variant at CCND2 halves the risk of type 2 diabetes by enhancing insulin secretion

A recent study identified a low-frequency variant at CCND2 associated with lower risk of type 2 diabetes, enhanced insulin response to a glucose challenge, higher height, and, paradoxically, higher BMI. We aimed to replicate the strength and effect size of these associations in independent samples and to assess the underlying mechanism. We genotyped the variant in 29,956 individuals and tested its association with type 2 diabetes and related traits. The low-frequency allele was associated with a lower risk of type 2 diabetes (OR 0.53; P = 2 × 10(-13); 6,647 case vs. 12,645 control subjects), higher disposition index (β = 0.07 log10; P = 2 × 10(-11); n = 13,028), and higher Matsuda index of insulin sensitivity (β = 0.02 log10; P = 5 × 10(-3); n = 13,118) but not fasting proinsulin (β = 0.01 log10; P = 0.5; n = 6,985). The low frequency allele was associated with higher adult height (β = 1.38 cm; P = 6 × 10(-9); n = 13,927), but the association of the variant with BMI (β = 0.36 kg/m(2); P = 0.02; n = 24,807), estimated in four population-based samples, was less than in the original publication where the effect estimate was biased by analyzing case subjects with type 2 diabetes and control subjects without diabetes separately. Our study establishes that a low-frequency allele in CCND2 halves the risk of type 2 diabetes primarily through enhanced insulin secretion.

A partially inactivating mutation in the sodium-dependent lysophosphatidylcholine transporter MFSD2A causes a non-lethal microcephaly syndrome

The major pathway by which the brain obtains essential omega-3 fatty acids from the circulation is through a sodium-dependent lysophosphatidylcholine (LPC) transporter (MFSD2A), expressed in the endothelium of the blood-brain barrier. Here we show that a homozygous mutation affecting a highly conserved MFSD2A residue (p.Ser339Leu) is associated with a progressive microcephaly syndrome characterized by intellectual disability, spasticity and absent speech. We show that the p.Ser339Leu alteration does not affect protein or cell surface expression but rather significantly reduces, although not completely abolishes, transporter activity. Notably, affected individuals displayed significantly increased plasma concentrations of LPCs containing mono- and polyunsaturated fatty acyl chains, indicative of reduced brain uptake, confirming the specificity of MFSD2A for LPCs having mono- and polyunsaturated fatty acyl chains. Together, these findings indicate an essential role for LPCs in human brain development and function and provide the first description of disease associated with aberrant brain LPC transport in humans.

A cautionary tale: the non-causal association between type 2 diabetes risk SNP, rs7756992, and levels of non-coding RNA, CDKAL1-v1

AIMS/HYPOTHESIS

Intronic single nucleotide polymorphisms (SNPs) in the CDKAL1 gene are associated with risk of developing type 2 diabetes. A strong correlation between risk alleles and lower levels of the non-coding RNA, CDKAL1-v1, has recently been reported in whole blood extracted from Japanese individuals. We sought to replicate this association in two independent cohorts: one using whole blood from white UK-resident individuals, and one using a collection of human pancreatic islets, a more relevant tissue type to study with respect to the aetiology of diabetes.

METHODS

Levels of CDKAL1-v1 were measured by real-time PCR using RNA extracted from human whole blood (n = 70) and human pancreatic islets (n = 48). Expression with respect to genotype was then determined.

RESULTS

In a simple linear regression model, expression of CDKAL1-v1 was associated with the lead type 2 diabetes-associated SNP, rs7756992, in whole blood and islets. However, these associations were abolished or substantially reduced in multiple regression models taking into account rs9366357 genotype: a moderately linked SNP explaining a much larger amount of the variation in CDKAL1-v1 levels, but not strongly associated with risk of type 2 diabetes.

CONCLUSIONS/INTERPRETATION

Contrary to previous findings, we provide evidence against a role for dysregulated expression of CDKAL1-v1 in mediating the association between intronic SNPs in CDKAL1 and susceptibility to type 2 diabetes. The results of this study illustrate how caution should be exercised when inferring causality from an association between disease-risk genotype and non-coding RNA expression.

Targeted allelic expression profiling in human islets identifies cis-regulatory effects for multiple variants identified by type 2 diabetes genome-wide association studies

Genome-wide association studies (GWAS) have identified variation at >65 genomic loci associated with susceptibility to type 2 diabetes, but little progress has been made in elucidating the molecular mechanisms behind most of these associations. Using samples heterozygous for transcribed single nucleotide polymorphisms (SNPs), allelic expression profiling is a powerful technique for identifying cis-regulatory variants controlling gene expression. In this study, exonic SNPs, suitable for measuring mature mRNA levels and in high linkage disequilibrium with 65 lead type 2 diabetes GWAS SNPs, were identified and allelic expression determined by real-time PCR using RNA and DNA isolated from islets of 36 white nondiabetic donors. A significant allelic expression imbalance (AEI) was identified for 7/14 (50%) genes tested (ANPEP, CAMK2B, HMG20A, KCNJ11, NOTCH2, SLC30A8, and WFS1), with significant AEI confirmed for five of these genes using other linked exonic SNPs. Lastly, results of a targeted islet expression quantitative trait loci experiment support the AEI findings for ANPEP, further implicating ANPEP as the causative gene at its locus. The results of this study support the hypothesis that changes to cis-regulation of gene expression are involved in a large proportion of SNP associations with type 2 diabetes susceptibility.

Identification and validation of N-acetyltransferase 2 as an insulin sensitivity gene

Decreased insulin sensitivity, also referred to as insulin resistance (IR), is a fundamental abnormality in patients with type 2 diabetes and a risk factor for cardiovascular disease. While IR predisposition is heritable, the genetic basis remains largely unknown. The GENEticS of Insulin Sensitivity consortium conducted a genome-wide association study (GWAS) for direct measures of insulin sensitivity, such as euglycemic clamp or insulin suppression test, in 2,764 European individuals, with replication in an additional 2,860 individuals. The presence of a nonsynonymous variant of N-acetyltransferase 2 (NAT2) [rs1208 (803A>G, K268R)] was strongly associated with decreased insulin sensitivity that was independent of BMI. The rs1208 "A" allele was nominally associated with IR-related traits, including increased fasting glucose, hemoglobin A1C, total and LDL cholesterol, triglycerides, and coronary artery disease. NAT2 acetylates arylamine and hydrazine drugs and carcinogens, but predicted acetylator NAT2 phenotypes were not associated with insulin sensitivity. In a murine adipocyte cell line, silencing of NAT2 ortholog Nat1 decreased insulin-mediated glucose uptake, increased basal and isoproterenol-stimulated lipolysis, and decreased adipocyte differentiation, while Nat1 overexpression produced opposite effects. Nat1-deficient mice had elevations in fasting blood glucose, insulin, and triglycerides and decreased insulin sensitivity, as measured by glucose and insulin tolerance tests, with intermediate effects in Nat1 heterozygote mice. Our results support a role for NAT2 in insulin sensitivity.

Whole-genome sequencing to understand the genetic architecture of common gene expression and biomarker phenotypes

Initial results from sequencing studies suggest that there are relatively few low-frequency (<5%) variants associated with large effects on common phenotypes. We performed low-pass whole-genome sequencing in 680 individuals from the InCHIANTI study to test two primary hypotheses: (i) that sequencing would detect single low-frequency–large effect variants that explained similar amounts of phenotypic variance as single common variants, and (ii) that some common variant associations could be explained by low-frequency variants. We tested two sets of disease-related common phenotypes for which we had statistical power to detect large numbers of common variant–common phenotype associations—11 132 cis-gene expression traits in 450 individuals and 93 circulating biomarkers in all 680 individuals. From a total of 11 657 229 high-quality variants of which 6 129 221 and 5 528 008 were common and low frequency (<5%), respectively, low frequency–large effect associations comprised 7% of detectable cis-gene expression traits [89 of 1314 cis-eQTLs at P < 1 × 10⁻⁰⁶ (false discovery rate ∼5%)] and one of eight biomarker associations at P < 8 × 10⁻¹⁰. Very few (30 of 1232; 2%) common variant associations were fully explained by low-frequency variants. Our data show that whole-genome sequencing can identify low-frequency variants undetected by genotyping based approaches when sample sizes are sufficiently large to detect substantial numbers of common variant associations, and that common variant associations are rarely explained by single low-frequency variants of large effect.

Defining the role of common variation in the genomic and biological architecture of adult human height

Using genome-wide data from 253,288 individuals, we identified 697 variants at genome-wide significance that together explained one-fifth of the heritability for adult height. By testing different numbers of variants in independent studies, we show that the most strongly associated ∼2,000, ∼3,700 and ∼9,500 SNPs explained ∼21%, ∼24% and ∼29% of phenotypic variance. Furthermore, all common variants together captured 60% of heritability. The 697 variants clustered in 423 loci were enriched for genes, pathways and tissue types known to be involved in growth and together implicated genes and pathways not highlighted in earlier efforts, such as signaling by fibroblast growth factors, WNT/β-catenin and chondroitin sulfate-related genes. We identified several genes and pathways not previously connected with human skeletal growth, including mTOR, osteoglycin and binding of hyaluronic acid. Our results indicate a genetic architecture for human height that is characterized by a very large but finite number (thousands) of causal variants.

HLA-DQA1-HLA-DRB1 variants confer susceptibility to pancreatitis induced by thiopurine immunosuppressants

Pancreatitis occurs in approximately 4% of patients treated with the thiopurines azathioprine or mercaptopurine. Its development is unpredictable and almost always leads to drug withdrawal. We identified patients with inflammatory bowel disease (IBD) who had developed pancreatitis within 3 months of starting these drugs from 168 sites around the world. After detailed case adjudication, we performed a genome-wide association study on 172 cases and 2,035 controls with IBD. We identified strong evidence of association within the class II HLA region, with the most significant association identified at rs2647087 (odds ratio 2.59, 95% confidence interval 2.07-3.26, P = 2 × 10(-16)). We replicated these findings in an independent set of 78 cases and 472 controls with IBD matched for drug exposure. Fine mapping of the HLA region identified association with the HLA-DQA1*02:01-HLA-DRB1*07:01 haplotype. Patients heterozygous at rs2647087 have a 9% risk of developing pancreatitis after administration of a thiopurine, whereas homozygotes have a 17% risk.

A central role for GRB10 in regulation of islet function in man

Variants in the growth factor receptor-bound protein 10 (GRB10) gene were in a GWAS meta-analysis associated with reduced glucose-stimulated insulin secretion and increased risk of type 2 diabetes (T2D) if inherited from the father, but inexplicably reduced fasting glucose when inherited from the mother. GRB10 is a negative regulator of insulin signaling and imprinted in a parent-of-origin fashion in different tissues. GRB10 knock-down in human pancreatic islets showed reduced insulin and glucagon secretion, which together with changes in insulin sensitivity may explain the paradoxical reduction of glucose despite a decrease in insulin secretion. Together, these findings suggest that tissue-specific methylation and possibly imprinting of GRB10 can influence glucose metabolism and contribute to T2D pathogenesis. The data also emphasize the need in genetic studies to consider whether risk alleles are inherited from the mother or the father.

In this paper, we report the first large genome-wide association study in man for glucose-stimulated insulin secretion (GSIS) indices during an oral glucose tolerance test. We identify seven genetic loci and provide effects on GSIS for all previously reported glycemic traits and obesity genetic loci in a large-scale sample. We observe paradoxical effects of genetic variants in the growth factor receptor-bound protein 10 (GRB10) gene yielding both reduced GSIS and reduced fasting plasma glucose concentrations, specifically showing a parent-of-origin effect of GRB10 on lower fasting plasma glucose and enhanced insulin sensitivity for maternal and elevated glucose and decreased insulin sensitivity for paternal transmissions of the risk allele. We also observe tissue-specific differences in DNA methylation and allelic imbalance in expression of GRB10 in human pancreatic islets. We further disrupt GRB10 by shRNA in human islets, showing reduction of both insulin and glucagon expression and secretion. In conclusion, we provide evidence for complex regulation of GRB10 in human islets. Our data suggest that tissue-specific methylation and imprinting of GRB10 can influence glucose metabolism and contribute to T2D pathogenesis. The data also emphasize the need in genetic studies to consider whether risk alleles are inherited from the mother or the father.

The HNF4A R76W mutation causes atypical dominant Fanconi syndrome in addition to a β cell phenotype

BACKGROUND

Mutation specific effects in monogenic disorders are rare. We describe atypical Fanconi syndrome caused by a specific heterozygous mutation in HNF4A. Heterozygous HNF4A mutations cause a beta cell phenotype of neonatal hyperinsulinism with macrosomia and young onset diabetes. Autosomal dominant idiopathic Fanconi syndrome (a renal proximal tubulopathy) is described but no genetic cause has been defined.

METHODS AND RESULTS

We report six patients heterozygous for the p.R76W HNF4A mutation who have Fanconi syndrome and nephrocalcinosis in addition to neonatal hyperinsulinism and macrosomia. All six displayed a novel phenotype of proximal tubulopathy, characterised by generalised aminoaciduria, low molecular weight proteinuria, glycosuria, hyperphosphaturia and hypouricaemia, and additional features not seen in Fanconi syndrome: nephrocalcinosis, renal impairment, hypercalciuria with relative hypocalcaemia, and hypermagnesaemia. This was mutation specific, with the renal phenotype not being seen in patients with other HNF4A mutations. In silico modelling shows the R76 residue is directly involved in DNA binding and the R76W mutation reduces DNA binding affinity. The target(s) selectively affected by altered DNA binding of R76W that results in Fanconi syndrome is not known.

CONCLUSIONS

The HNF4A R76W mutation is an unusual example of a mutation specific phenotype, with autosomal dominant atypical Fanconi syndrome in addition to the established beta cell phenotype.

Next generation sequencing of chromosomal rearrangements in patients with split-hand/split-foot malformation provides evidence for DYNC1I1 exonic enhancers of DLX5/6 expression in humans

Objective

Split-hand/foot malformation type 1 is an autosomal dominant condition with reduced penetrance and variable expression. We report three individuals from two families with split-hand/split-foot malformation (SHFM) in whom next generation sequencing was performed to investigate the cause of their phenotype.

Methods and results

The first proband has a de novo balanced translocation t(2;7)(p25.1;q22) identified by karyotyping. Whole genome sequencing showed that the chromosome 7 breakpoint is situated within the SHFM1 locus on chromosome 7q21.3. This separates the DYNC1I1 exons recently identified as limb enhancers in mouse studies from their target genes, DLX5 and DLX6. In the second family, X-linked recessive inheritance was suspected and exome sequencing was performed to search for a mutation in the affected proband and his uncle. No coding mutation was found within the SHFM2 locus at Xq26 or elsewhere in the exome, but a 106 kb deletion within the SHFM1 locus was detected through copy number analysis. Genome sequencing of the deletion breakpoints showed that the DLX5 and DLX6 genes are disomic but the putative DYNC1I1 exon 15 and 17 enhancers are deleted.

Conclusions

Exome sequencing identified a 106 kb deletion that narrows the SHFM1 critical region from 0.9 to 0.1 Mb and confirms a key role of DYNC1I1 exonic enhancers in normal limb formation in humans.

Improved genetic testing for monogenic diabetes using targeted next-generation sequencing

AIMS/HYPOTHESIS

Current genetic tests for diagnosing monogenic diabetes rely on selection of the appropriate gene for analysis according to the patient's phenotype. Next-generation sequencing enables the simultaneous analysis of multiple genes in a single test. Our aim was to develop a targeted next-generation sequencing assay to detect mutations in all known MODY and neonatal diabetes genes.

METHODS

We selected 29 genes in which mutations have been reported to cause neonatal diabetes, MODY, maternally inherited diabetes and deafness (MIDD) or familial partial lipodystrophy (FPLD). An exon-capture assay was designed to include coding regions and splice sites. A total of 114 patient samples were tested--32 with known mutations and 82 previously tested for MODY (n = 33) or neonatal diabetes (n = 49) but in whom a mutation had not been found. Sequence data were analysed for the presence of base substitutions, small insertions or deletions (indels) and exonic deletions or duplications.

RESULTS

In the 32 positive controls we detected all previously identified variants (34 mutations and 36 polymorphisms), including 55 base substitutions, ten small insertions or deletions and five partial/whole gene deletions/duplications. Previously unidentified mutations were found in five patients with MODY (15%) and nine with neonatal diabetes (18%). Most of these patients (12/14) had mutations in genes that had not previously been tested.

CONCLUSIONS/INTERPRETATION

Our novel targeted next-generation sequencing assay provides a highly sensitive method for simultaneous analysis of all monogenic diabetes genes. This single test can detect mutations previously identified by Sanger sequencing or multiplex ligation-dependent probe amplification dosage analysis. The increased number of genes tested led to a higher mutation detection rate.

An in-frame deletion at the polymerase active site of POLD1 causes a multisystem disorder with lipodystrophy

DNA polymerase δ, whose catalytic subunit is encoded by POLD1, is responsible for lagging-strand DNA synthesis during DNA replication. It carries out this synthesis with high fidelity owing to its intrinsic 3'- to 5'-exonuclease activity, which confers proofreading ability. Missense mutations affecting the exonuclease domain of POLD1 have recently been shown to predispose to colorectal and endometrial cancers. Here we report a recurring heterozygous single-codon deletion in POLD1 affecting the polymerase active site that abolishes DNA polymerase activity but only mildly impairs 3'- to 5'-exonuclease activity. This mutation causes a distinct multisystem disorder that includes subcutaneous lipodystrophy, deafness, mandibular hypoplasia and hypogonadism in males. This discovery suggests that perturbing the function of the ubiquitously expressed POLD1 polymerase has unexpectedly tissue-specific effects in humans and argues for an important role for POLD1 function in adipose tissue homeostasis.

Genetic variants associated with glycine metabolism and their role in insulin sensitivity and type 2 diabetes

Circulating metabolites associated with insulin sensitivity may represent useful biomarkers, but their causal role in insulin sensitivity and diabetes is less certain. We previously identified novel metabolites correlated with insulin sensitivity measured by the hyperinsulinemic-euglycemic clamp. The top-ranking metabolites were in the glutathione and glycine biosynthesis pathways. We aimed to identify common genetic variants associated with metabolites in these pathways and test their role in insulin sensitivity and type 2 diabetes. With 1,004 nondiabetic individuals from the RISC study, we performed a genome-wide association study (GWAS) of 14 insulin sensitivity-related metabolites and one metabolite ratio. We replicated our results in the Botnia study (n = 342). We assessed the association of these variants with diabetes-related traits in GWAS meta-analyses (GENESIS [including RISC, EUGENE2, and Stanford], MAGIC, and DIAGRAM). We identified four associations with three metabolites-glycine (rs715 at CPS1), serine (rs478093 at PHGDH), and betaine (rs499368 at SLC6A12; rs17823642 at BHMT)-and one association signal with glycine-to-serine ratio (rs1107366 at ALDH1L1). There was no robust evidence for association between these variants and insulin resistance or diabetes. Genetic variants associated with genes in the glycine biosynthesis pathways do not provide consistent evidence for a role of glycine in diabetes-related traits.

Imputation of variants from the 1000 Genomes Project modestly improves known associations and can identify low-frequency variant-phenotype associations undetected by HapMap based imputation

Genome-wide association (GWA) studies have been limited by the reliance on common variants present on microarrays or imputable from the HapMap Project data. More recently, the completion of the 1000 Genomes Project has provided variant and haplotype information for several million variants derived from sequencing over 1,000 individuals. To help understand the extent to which more variants (including low frequency (1% ≤ MAF <5%) and rare variants (<1%)) can enhance previously identified associations and identify novel loci, we selected 93 quantitative circulating factors where data was available from the InCHIANTI population study. These phenotypes included cytokines, binding proteins, hormones, vitamins and ions. We selected these phenotypes because many have known strong genetic associations and are potentially important to help understand disease processes. We performed a genome-wide scan for these 93 phenotypes in InCHIANTI. We identified 21 signals and 33 signals that reached P<5×10(-8) based on HapMap and 1000 Genomes imputation, respectively, and 9 and 11 that reached a stricter, likely conservative, threshold of P<5×10(-11) respectively. Imputation of 1000 Genomes genotype data modestly improved the strength of known associations. Of 20 associations detected at P<5×10(-8) in both analyses (17 of which represent well replicated signals in the NHGRI catalogue), six were captured by the same index SNP, five were nominally more strongly associated in 1000 Genomes imputed data and one was nominally more strongly associated in HapMap imputed data. We also detected an association between a low frequency variant and phenotype that was previously missed by HapMap based imputation approaches. An association between rs112635299 and alpha-1 globulin near the SERPINA gene represented the known association between rs28929474 (MAF = 0.007) and alpha1-antitrypsin that predisposes to emphysema (P = 2.5×10(-12)). Our data provide important proof of principle that 1000 Genomes imputation will detect novel, low frequency-large effect associations.

Identification of heart rate-associated loci and their effects on cardiac conduction and rhythm disorders

Elevated resting heart rate is associated with greater risk of cardiovascular disease and mortality. In a 2-stage meta-analysis of genome-wide association studies in up to 181,171 individuals, we identified 14 new loci associated with heart rate and confirmed associations with all 7 previously established loci. Experimental downregulation of gene expression in Drosophila melanogaster and Danio rerio identified 20 genes at 11 loci that are relevant for heart rate regulation and highlight a role for genes involved in signal transmission, embryonic cardiac development and the pathophysiology of dilated cardiomyopathy, congenital heart failure and/or sudden cardiac death. In addition, genetic susceptibility to increased heart rate is associated with altered cardiac conduction and reduced risk of sick sinus syndrome, and both heart rate-increasing and heart rate-decreasing variants associate with risk of atrial fibrillation. Our findings provide fresh insights into the mechanisms regulating heart rate and identify new therapeutic targets.

Genome-wide association studies of human growth traits

Despite the high heritability of human growth traits, until recently little was known about the underlying genes and genetic variants which explain normal variation of growth. In the past few years, genome-wide association studies have successfully identified hundreds of genetic variants that are associated with human growth traits. These variants have implicated many novel genes in the regulation of birthweight and pubertal timing through to final adult height, and are providing new insights into the biology of growth. For example, 180 genetic loci have been robustly shown to influence variation in final adult height. Despite this success, the effect sizes of these variants are small and, even in combination, have left the majority of heritable genetic variation of growth traits unexplained. In this review, I discuss the successes of the genome-wide association approach and some of the novel insights into the biology of growth that have come from these studies. I will also discuss what these studies have not told us and what the future holds for genetic studies of human growth.

A genome-wide association study of early menopause and the combined impact of identified variants

Early menopause (EM) affects up to 10% of the female population, reducing reproductive lifespan considerably. Currently, it constitutes the leading cause of infertility in the western world, affecting mainly those women who postpone their first pregnancy beyond the age of 30 years. The genetic aetiology of EM is largely unknown in the majority of cases. We have undertaken a meta-analysis of genome-wide association studies (GWASs) in 3493 EM cases and 13 598 controls from 10 independent studies. No novel genetic variants were discovered, but the 17 variants previously associated with normal age at natural menopause as a quantitative trait (QT) were also associated with EM and primary ovarian insufficiency (POI). Thus, EM has a genetic aetiology which overlaps variation in normal age at menopause and is at least partly explained by the additive effects of the same polygenic variants. The combined effect of the common variants captured by the single nucleotide polymorphism arrays was estimated to account for ∼30% of the variance in EM. The association between the combined 17 variants and the risk of EM was greater than the best validated non-genetic risk factor, smoking.

Stratifying type 2 diabetes cases by BMI identifies genetic risk variants in LAMA1 and enrichment for risk variants in lean compared to obese cases

Common diseases such as type 2 diabetes are phenotypically heterogeneous. Obesity is a major risk factor for type 2 diabetes, but patients vary appreciably in body mass index. We hypothesized that the genetic predisposition to the disease may be different in lean (BMI<25 Kg/m²) compared to obese cases (BMI≥30 Kg/m²). We performed two case-control genome-wide studies using two accepted cut-offs for defining individuals as overweight or obese. We used 2,112 lean type 2 diabetes cases (BMI<25 kg/m²) or 4,123 obese cases (BMI≥30 kg/m²), and 54,412 un-stratified controls. Replication was performed in 2,881 lean cases or 8,702 obese cases, and 18,957 un-stratified controls. To assess the effects of known signals, we tested the individual and combined effects of SNPs representing 36 type 2 diabetes loci. After combining data from discovery and replication datasets, we identified two signals not previously reported in Europeans. A variant (rs8090011) in the LAMA1 gene was associated with type 2 diabetes in lean cases (P = 8.4×10⁻⁹, OR = 1.13 [95% CI 1.09-1.18]), and this association was stronger than that in obese cases (P = 0.04, OR = 1.03 [95% CI 1.00-1.06]). A variant in HMG20A--previously identified in South Asians but not Europeans--was associated with type 2 diabetes in obese cases (P = 1.3×10⁻⁸, OR = 1.11 [95% CI 1.07-1.15]), although this association was not significantly stronger than that in lean cases (P = 0.02, OR = 1.09 [95% CI 1.02-1.17]). For 36 known type 2 diabetes loci, 29 had a larger odds ratio in the lean compared to obese (binomial P = 0.0002). In the lean analysis, we observed a weighted per-risk allele OR = 1.13 [95% CI 1.10-1.17], P = 3.2×10⁻¹⁴. This was larger than the same model fitted in the obese analysis where the OR = 1.06 [95% CI 1.05-1.08], P = 2.2×10⁻¹⁶. This study provides evidence that stratification of type 2 diabetes cases by BMI may help identify additional risk variants and that lean cases may have a stronger genetic predisposition to type 2 diabetes.

Conditional and joint multiple-SNP analysis of GWAS summary statistics identifies additional variants influencing complex traits

We present an approximate conditional and joint association analysis that can use summary-level statistics from a meta-analysis of genome-wide association studies (GWAS) and estimated linkage disequilibrium (LD) from a reference sample with individual-level genotype data. Using this method, we analyzed meta-analysis summary data from the GIANT Consortium for height and body mass index (BMI), with the LD structure estimated from genotype data in two independent cohorts. We identified 36 loci with multiple associated variants for height (38 leading and 49 additional SNPs, 87 in total) via a genome-wide SNP selection procedure. The 49 new SNPs explain approximately 1.3% of variance, nearly doubling the heritability explained at the 36 loci. We did not find any locus showing multiple associated SNPs for BMI. The method we present is computationally fast and is also applicable to case-control data, which we demonstrate in an example from meta-analysis of type 2 diabetes by the DIAGRAM Consortium.