Rare genetic variants contribute to complex disease risk; however, the abundance of rare variants in human populations remains unknown. We explored this spectrum of variation by sequencing 202 genes encoding drug targets in 14,002 individuals. We find rare variants are abundant (one every 17 bases) and geographically localized, such that even with large sample sizes, rare variant catalogs will be largely incomplete. We used the observed patterns of variation to estimate population growth parameters, the proportion of variants in a given frequency class that are putatively deleterious, and mutation rates for each gene. Overall we conclude that, due to rapid population growth and weak purifying selection, human populations harbor an abundance of rare variants, many of which are deleterious and have relevance to understanding disease risk.
The QT interval, an electrocardiographic measure reflecting myocardial repolarization, is a heritable trait. QT prolongation is a risk factor for ventricular arrhythmias and sudden cardiac death (SCD) and could indicate the presence of the potentially lethal Mendelian Long QT Syndrome (LQTS). Using a genome-wide association and replication study in up to 100,000 individuals we identified 35 common variant QT interval loci, that collectively explain ∼8-10% of QT variation and highlight the importance of calcium regulation in myocardial repolarization. Rare variant analysis of 6 novel QT loci in 298 unrelated LQTS probands identified coding variants not found in controls but of uncertain causality and therefore requiring validation. Several newly identified loci encode for proteins that physically interact with other recognized repolarization proteins. Our integration of common variant association, expression and orthogonal protein-protein interaction screens provides new insights into cardiac electrophysiology and identifies novel candidate genes for ventricular arrhythmias, LQTS,and SCD.
genome-wide association study; QT interval; Long QT Syndrome; sudden cardiac death; myocardial repolarization; arrhythmias
Elevated intraocular pressure (IOP) is a major risk factor for glaucoma and is influenced by genetic and environmental factors. Recent genome-wide association studies (GWAS) reported associations with IOP at TMCO1 and GAS7, and with primary open-angle glaucoma (POAG) at CDKN2B-AS1, CAV1/CAV2, and SIX1/SIX6. To identify novel genetic variants and replicate the published findings, we performed GWAS and meta-analysis of IOP in >6,000 subjects of European ancestry collected in three datasets: the NEI Glaucoma Human genetics collaBORation, GLAUcoma Genes and ENvironment study, and a subset of the Age-related Macular Degeneration-Michigan, Mayo, AREDS and Pennsylvania study. While no signal achieved genome-wide significance in individual datasets, a meta-analysis identified significant associations with IOP at TMCO1 (rs7518099-G, p = 8.0 × 10−8). Focused analyses of five loci previously reported for IOP and/or POAG, i.e., TMCO1, CDKN2B-AS1, GAS7, CAV1/CAV2, and SIX1/SIX6, revealed associations with IOP that were largely consistent across our three datasets, and replicated the previously reported associations in both effect size and direction. These results confirm the involvement of common variants in multiple genomic regions in regulating IOP and/or glaucoma risk.
Genetic and genomic studies have enhanced our understanding of complex neurodegenerative diseases that exert a devastating impact on individuals and society. One such disease, age-related macular degeneration (AMD), is a major cause of progressive and debilitating visual impairment. Since the pioneering discovery in 2005 of complement factor H (CFH) as a major AMD susceptibility gene, extensive investigations have confirmed 19 additional genetic risk loci, and more are anticipated. In addition to common variants identified by now-conventional genome-wide association studies, targeted genomic sequencing and exome-chip analyses are uncovering rare variant alleles of high impact. Here, we provide a critical review of the ongoing genetic studies and of common and rare risk variants at a total of 20 susceptibility loci, which together explain 40–60% of the disease heritability but provide limited power for diagnostic testing of disease risk. Identification of these susceptibility loci has begun to untangle the complex biological pathways underlying AMD pathophysiology, pointing to new testable paradigms for treatment.
complex disease; genetic susceptibility; neurodegeneration; retina; blindness
Summary: Although the 1000 Genomes haplotypes are the most commonly used reference panel for imputation, medical sequencing projects are generating large alternate sets of sequenced samples. Imputation in African Americans using 3384 haplotypes from the Exome Sequencing Project, compared with 2184 haplotypes from 1000 Genomes Project, increased effective sample size by 8.3–11.4% for coding variants with minor allele frequency <1%. No loss of imputation quality was observed using a panel built from phenotypic extremes. We recommend using haplotypes from Exome Sequencing Project alone or concatenation of the two panels over quality score-based post-imputation selection or IMPUTE2’s two-panel combination.
Supplementary data are available at Bioinformatics online.
Blood lipid levels are heritable, treatable risk factors for cardiovascular disease. We systematically assessed genome-wide coding variation to identify novel lipid genes, fine-map known lipid loci, and evaluate whether low frequency variants with large effect exist. Using an exome array, we genotyped 80,137 coding variants in 5,643 Norwegians. We followed up 18 variants in 4,666 Norwegians to identify 10 loci with coding variants associated with a lipid trait (P < 5×10−8). One coding variant in TM6SF2 (p.Glu167Lys), residing in a GWAS locus for lipid levels, modifies total cholesterol levels and is associated with myocardial infarction. Transient overexpression and knockdown of TM6SF2 in mouse produces alteration in serum lipid profiles consistent with the association observed in humans, identifying TM6SF2 as the functional gene at a large GWAS locus previously known as NCAN/CILP2/PBX4 or 19p13. This study demonstrates that systematic assessment of coding variation can quickly point to a candidate causal gene.
The vast majority of connections between complex disease and common genetic variants were identified through meta-analysis, a powerful approach that enables large sample sizes while protecting against common artifacts due to population structure, repeated small sample analyses, and/or limitations with sharing individual level data. As the focus of genetic association studies shifts to rare variants, genes and other functional units are becoming the unit of analysis. Here, we propose and evaluate new approaches for performing meta-analysis of rare variant association tests, including burden tests, weighted burden tests, variable threshold tests and tests that allow variants with opposite effects to be grouped together. We show that our approach retains useful features of single variant meta-analytic approaches and demonstrate its utility in a study of blood lipid levels in ∼18,500 individuals genotyped with exome arrays.
Knowledge of individual ancestry is important for genetic association studies where population structure leads to false positive signals. Estimating individual ancestry with targeted sequence data, which constitutes the bulk of current sequence datasets, is challenging. Here, we propose a new method for accurate estimation of genetic ancestry. Our method skips genotype calling and directly analyzes sequence reads. We validate the method using simulated and empirical data and show that the method can accurately infer worldwide continental ancestry with whole genome shotgun coverage as low as 0.001X. For estimates of fine-scale ancestry within Europe, the method performs well with coverage of 0.1X. At an even finer-scale, the method improves discrimination between exome-sequenced participants originating from different provinces within Finland. Finally, we show that our method can be used to improve case-control matching in genetic association studies and reduce the risk of spurious findings due to population structure.
Summary: RAREMETAL is a computationally efficient tool for meta-analysis of rare variants genotyped using sequencing or arrays. RAREMETAL facilitates analyses of individual studies, accommodates a variety of input file formats, handles related and unrelated individuals, executes both single variant and burden tests and performs conditional association analyses.
Availability and implementation:
http://genome.sph.umich.edu/wiki/RAREMETAL for executables, source code, documentation and tutorial.
firstname.lastname@example.org or email@example.com
Low-density lipoprotein (LDL) cholesterol, high-density lipoprotein (HDL) cholesterol, triglycerides, and total cholesterol are heritable, modifiable, risk factors for coronary artery disease. To identify new loci and refine known loci influencing these lipids, we examined 188,578 individuals using genome-wide and custom genotyping arrays. We identify and annotate 157 loci associated with lipid levels at P < 5×10−8, including 62 loci not previously associated with lipid levels in humans. Using dense genotyping in individuals of European, East Asian, South Asian, and African ancestry, we narrow association signals in 12 loci. We find that loci associated with blood lipids are often associated with cardiovascular and metabolic traits including coronary artery disease, type 2 diabetes, blood pressure, waist-hip ratio, and body mass index. Our results illustrate the value of genetic data from individuals of diverse ancestries and provide insights into biological mechanisms regulating blood lipids to guide future genetic, biological, and therapeutic research.
Summary: Recent advances in sequencing technologies have revolutionized genetic studies. Although high-coverage sequencing can uncover most variants present in the sequenced sample, low-coverage sequencing is appealing for its cost effectiveness. Here, we present AbCD (arbitrary coverage design) to aid the design of sequencing-based studies. AbCD is a user-friendly interface providing pre-estimated effective sample sizes, specific to each minor allele frequency category, for designs with arbitrary coverage (0.5–30×) and sample size (20–10 000), and for four major ethnic groups (Europeans, Africans, Asians and African Americans). In addition, we also present two software tools: ShotGun and DesignPlanner, which were used to generate the estimates behind AbCD. ShotGun is a flexible short-read simulator for arbitrary user-specified read length and average depth, allowing cycle-specific sequencing error rates and realistic read depth distributions. DesignPlanner is a full pipeline that uses ShotGun to generate sequence data and performs initial SNP discovery, uses our previously presented linkage disequilibrium-aware method to call genotypes, and, finally, provides minor allele frequency-specific effective sample sizes. ShotGun plus DesignPlanner can accommodate effective sample size estimate for any combination of high-depth and low-depth data (for example, whole-genome low-depth plus exonic high-depth) or combination of sequence and genotype data [for example, whole-exome sequencing plus genotyping from existing Genomewide Association Study (GWAS)].
Availability and implementation: AbCD, including its downloadable terminal interface and web-based interface, and the associated tools ShotGun and DesignPlanner, including documentation, examples and executables, are available at http://www.unc.edu/∼yunmli/AbCD.html.
Genetic studies might provide new insights into the biological
mechanisms underlying lipid metabolism and risk of CAD. We therefore
conducted a genome-wide association study to identify novel genetic
determinants of LDL-c, HDL-c and triglycerides.
Methods and results
We combined genome-wide association data from eight studies,
comprising up to 17,723 participants with information on circulating lipid
concentrations. We did independent replication studies in up to 37,774
participants from eight populations and also in a population of Indian Asian
descent. We also assessed the association between SNPs at lipid loci and
risk of CAD in up to 9,633 cases and 38,684 controls.
We identified four novel genetic loci that showed reproducible
associations with lipids (P values 1.6 × 10−8 to
3.1 × 10−10). These include a potentially
functional SNP in the SLC39A8 gene for HDL-c, a SNP near
the MYLIP/GMPR and PPP1R3B genes for LDL-c
and at the AFF1 gene for triglycerides. SNPs showing strong
statistical association with one or more lipid traits at the
APOE-C1-C4-C2 cluster, LPL,
ZNF259-APOA5-A4-C3-A1 cluster and
TRIB1 loci were also associated with CAD risk (P values
1.1 × 10−3 to 1.2 ×
We have identified four novel loci associated with circulating
lipids. We also show that in addition to those that are largely associated
with LDL-c, genetic loci mainly associated with circulating triglycerides
and HDL-c are also associated with risk of CAD. These findings potentially
provide new insights into the biological mechanisms underlying lipid
metabolism and CAD risk.
lipids; lipoproteins; genetics; epidemiology
The Centre for Applied Genomics of the Hospital for Sick Children and the University of Toronto hosted the 10th Human Genome Variation (HGV) Meeting in Toronto, Canada, in October 2008, welcoming about 240 registrants from 34 countries. During the 3 days of plenary workshops, keynote address, and poster sessions, a strong cross-disciplinary trend was evident, integrating expertise from technology and computation, through biology and medicine, to ethics and law. Single nucleotide polymorphisms (SNPs) as well as the larger copy number variants (CNVs) are recognized by ever-improving array and next-generation sequencing technologies, and the data are being incorporated into studies that are increasingly genome-wide as well as global in scope. A greater challenge is to convert data to information, through databases, and to use the information for greater understanding of human variation. In the wake of publications of the first individual genome sequences, an inaugural public forum provided the opportunity to debate whether we are ready for personalized medicine through direct-to-consumer testing. The HGV meetings foster collaboration, and fruits of the interactions from 2008 are anticipated for the 11th annual meeting in September 2009.
SNP; CNV; GWAS; personalized medicine
A genome wide association scan of ~6.6 million genotyped or imputed variants in 882 Sardinian Multiple Sclerosis (MS) cases and 872 controls suggested association of CBLB gene variants with disease, which was confirmed in 1,775 cases and 2,005 controls (overall P =1.60 × 10-10). CBLB encodes a negative regulator of adaptive immune responses and mice lacking the orthologue are prone to experimental autoimmune encephalomyelitis, the animal model of MS.
Personality can be thought of as a set of characteristics that influence people’s thoughts, feelings, and behaviour across a variety of settings. Variation in personality is predictive of many outcomes in life, including mental health. Here we report on a meta-analysis of genome-wide association (GWA) data for personality in ten discovery samples (17 375 adults) and five in-silico replication samples (3 294 adults). All participants were of European ancestry. Personality scores for Neuroticism, Extraversion, Openness to Experience, Agreeableness, and Conscientiousness were based on the NEO Five-Factor Inventory. Genotype data were available of ~2.4M Single Nucleotide Polymorphisms (SNPs; directly typed and imputed using HAPMAP data). In the discovery samples, classical association analyses were performed under an additive model followed by meta-analysis using the weighted inverse variance method. Results showed genome-wide significance for Openness to Experience near the RASA1 gene on 5q14.3 (rs1477268 and rs2032794, P = 2.8 × 10−8 and 3.1 × 10−8) and for Conscientiousness in the brain-expressed KATNAL2 gene on 18q21.1 (rs2576037, P = 4.9 × 10−8). We further conducted a gene-based test that confirmed the association of KATNAL2 to Conscientiousness. In-silico replication did not, however, show significant associations of the top SNPs with Openness and Conscientiousness, although the direction of effect of the KATNAL2 SNP on Conscientiousness was consistent in all replication samples. Larger scale GWA studies and alternative approaches are required for confirmation of KATNAL2 as a novel gene affecting Conscientiousness.
Personality; Five-Factor Model; Genome-wide association; Meta-analysis; Genetic variants
Sequencing efforts, including the 1000 Genomes Project and disease-specific efforts, are producing large collections of haplotypes that can be used for genotype imputation in genome-wide association studies (GWAS). Imputing from these reference panels can help identify new risk alleles, but the use of large panels with existing methods imposes a high computational burden. To keep imputation broadly accessible, we introduce a strategy called “pre-phasing” that maintains the accuracy of leading methods while cutting computational costs by orders of magnitude. In brief, we first statistically estimate the haplotypes for each GWAS individual (“pre-phasing”) and then impute missing genotypes into these estimated haplotypes. This reduces the computational cost because: (i) the GWAS samples must be phased only once, whereas standard methods would implicitly re-phase with each reference panel update; (ii) it is much faster to match a phased GWAS haplotype to one reference haplotype than to match unphased GWAS genotypes to a pair of reference haplotypes. This strategy will be particularly valuable for repeated imputation as reference panels evolve.
Insulin secretion plays a critical role in glucose homeostasis, and failure to secrete sufficient insulin is a hallmark of type 2 diabetes. Genome-wide association studies (GWAS) have identified loci contributing to insulin processing and secretion1,2; however, a substantial fraction of the genetic contribution remains undefined. To examine low-frequency (minor allele frequency (MAF) 0.5% to 5%) and rare (MAF<0.5%) nonsynonymous variants, we analyzed exome array data in 8,229 non-diabetic Finnish males. We identified low-frequency coding variants associated with fasting proinsulin levels at the SGSM2 and MADD GWAS loci and three novel genes with low-frequency variants associated with fasting proinsulin or insulinogenic index: TBC1D30, KANK1, and PAM. We also demonstrate that the interpretation of single-variant and gene-based tests needs to consider the effects of noncoding SNPs nearby and megabases (Mb) away. This study demonstrates that exome array genotyping is a valuable approach to identify low-frequency variants that contribute to complex traits.
Given the anthropometric differences between men and women and previous evidence of sex-difference in genetic effects, we conducted a genome-wide search for sexually dimorphic associations with height, weight, body mass index, waist circumference, hip circumference, and waist-to-hip-ratio (133,723 individuals) and took forward 348 SNPs into follow-up (additional 137,052 individuals) in a total of 94 studies. Seven loci displayed significant sex-difference (FDR<5%), including four previously established (near GRB14/COBLL1, LYPLAL1/SLC30A10, VEGFA, ADAMTS9) and three novel anthropometric trait loci (near MAP3K1, HSD17B4, PPARG), all of which were genome-wide significant in women (P<5×10−8), but not in men. Sex-differences were apparent only for waist phenotypes, not for height, weight, BMI, or hip circumference. Moreover, we found no evidence for genetic effects with opposite directions in men versus women. The PPARG locus is of specific interest due to its role in diabetes genetics and therapy. Our results demonstrate the value of sex-specific GWAS to unravel the sexually dimorphic genetic underpinning of complex traits.
Men and women differ substantially regarding height, weight, and body fat. Interestingly, previous work detecting genetic effects for waist-to-hip ratio, to assess body fat distribution, has found that many of these showed sex-differences. However, systematic searches for sex-differences in genetic effects have not yet been conducted. Therefore, we undertook a genome-wide search for sexually dimorphic genetic effects for anthropometric traits including 133,723 individuals in a large meta-analysis and followed promising variants in further 137,052 individuals, including a total of 94 studies. We identified seven loci with significant sex-difference including four previously established (near GRB14/COBLL1, LYPLAL1/SLC30A10, VEGFA, ADAMTS9) and three novel anthropometric trait loci (near MAP3K1, HSD17B4, PPARG), all of which were significant in women, but not in men. Of interest is that sex-difference was only observed for waist phenotypes, but not for height or body-mass-index. We found no evidence for sex-differences with opposite effect direction for men and women. The PPARG locus is of specific interest due to its link to diabetes genetics and therapy. Our findings demonstrate the importance of investigating sex differences, which may lead to a better understanding of disease mechanisms with a potential relevance to treatment options.
Economic variables such as income, education, and occupation are known to affect mortality and morbidity, such as cardiovascular disease, and have also been shown to be partly heritable. However, very little is known about which genes influence economic variables, although these genes may have both a direct and an indirect effect on health. We report results from the first large-scale collaboration that studies the molecular genetic architecture of an economic variable–entrepreneurship–that was operationalized using self-employment, a widely-available proxy. Our results suggest that common SNPs when considered jointly explain about half of the narrow-sense heritability of self-employment estimated in twin data (σg2/σP2 = 25%, h2 = 55%). However, a meta-analysis of genome-wide association studies across sixteen studies comprising 50,627 participants did not identify genome-wide significant SNPs. 58 SNPs with p<10−5 were tested in a replication sample (n = 3,271), but none replicated. Furthermore, a gene-based test shows that none of the genes that were previously suggested in the literature to influence entrepreneurship reveal significant associations. Finally, SNP-based genetic scores that use results from the meta-analysis capture less than 0.2% of the variance in self-employment in an independent sample (p≥0.039). Our results are consistent with a highly polygenic molecular genetic architecture of self-employment, with many genetic variants of small effect. Although self-employment is a multi-faceted, heavily environmentally influenced, and biologically distal trait, our results are similar to those for other genetically complex and biologically more proximate outcomes, such as height, intelligence, personality, and several diseases.
Smoking is a leading global cause of disease and mortality1. We performed a genomewide meta-analytic association study of smoking-related behavioral traits in a total sample of 41,150 individuals drawn from 20 disease, population, and control cohorts. Our analysis confirmed an effect on smoking quantity (SQ) at a locus on 15q25 (P=9.45e-19) that includes three genes encoding neuronal nicotinic acetylcholine receptor subunits (CHRNA5, CHRNA3, CHRNB4). We used data from the 1000 Genomes project to investigate the region using imputation, which allowed analysis of virtually all common variants in the region and offered a five-fold increase in coverage over the HapMap. This increased the spectrum of potentially causal single nucleotide polymorphisms (SNPs), which included a novel SNP that showed the highest significance, rs55853698, located within the promoter region of CHRNA5. Conditional analysis also identified a secondary locus (rs6495308) in CHRNA3.
Asthma is a complex disease characterized by striking ethnic disparities not explained entirely by environmental, social, cultural, or economic factors. Of the limited genetic studies performed on populations of African descent, notable differences in susceptibility allele frequencies have been observed.
To test the hypothesis that some genes may contribute to the profound disparities in asthma.
We performed a genome-wide association study in two independent populations of African ancestry (935 African American asthma cases and controls from the Baltimore-Washington, D.C. area, and 929 African Caribbean asthmatics and their family members from Barbados) to identify single-nucleotide polymorphisms (SNPs) associated with asthma.
Meta-analysis combining these two African-ancestry populations yielded three SNPs with a combined P-value <10-5 in genes of potential biological relevance to asthma and allergic disease: rs10515807, mapping to alpha-1B-adrenergic receptor (ADRA1B) gene on chromosome 5q33 (3.57×10-6); rs6052761, mapping to prion-related protein (PRNP) on chromosome 20pter-p12 (2.27×10-6); and rs1435879, mapping to dipeptidyl peptidase 10 (DPP10) on chromosome 2q12.3-q14.2. The generalizability of these findings was tested in family and case-control panels of UK and German origin, respectively, but none of the associations observed in the African groups were replicated in these European studies.
Evidence for association was also examined in four additional case-control studies of African Americans; however, none of the SNPs implicated in the discovery population were replicated. This study illustrates the complexity of identifying true associations for a complex and heterogeneous disease such as asthma in admixed populations, especially populations of African descent.
Asthma; GWAS; ADRA1B; PRNP; DPP10; African ancestry; ethnicity; polymorphism; genetic association
Carotid-femoral pulse wave velocity (CFPWV) is a heritable measure of aortic stiffness that is strongly associated with increased risk for major cardiovascular disease events.
Methods and Results
We conducted a meta-analysis of genome-wide association data in 9 community-based European ancestry cohorts consisting of 20,634 participants. Results were replicated in 2 additional European ancestry cohorts involving 5,306 participants. Based on a preliminary analysis of 6 cohorts, we identified a locus on chromosome 14 in the 3′-BCL11B gene desert that is associated with CFPWV (rs7152623, minor allele frequency = 0.42, beta=−0.075±0.012 SD/allele, P = 2.8 x 10−10; replication beta=−0.086±0.020 SD/allele, P = 1.4 x 10−6). Combined results for rs7152623 from 11 cohorts gave beta=−0.076±0.010 SD/allele, P=3.1x10−15. The association persisted when adjusted for mean arterial pressure (beta=−0.060±0.009 SD/allele, P = 1.0 x 10−11). Results were consistent in younger (<55 years, 6 cohorts, N=13,914, beta=−0.081±0.014 SD/allele, P = 2.3 x 10−9) and older (9 cohorts, N=12,026, beta=−0.061±0.014 SD/allele, P=9.4x10−6) participants. In separate meta-analyses, the locus was associated with increased risk for coronary artery disease (hazard ratio [HR]=1.05, confidence interval [CI]=1.02 to 1.08, P=0.0013) and heart failure (HR=1.10, CI=1.03 to 1.16, P=0.004).
Common genetic variation in a locus in the BCL11B gene desert that is thought to harbor one or more gene enhancers is associated with higher CFPWV and increased risk for cardiovascular disease. Elucidation of the role this novel locus plays in aortic stiffness may facilitate development of therapeutic interventions that limit aortic stiffening and related cardiovascular disease events.
aorta; arterial stiffness; pulse wave velocity; genetics; cardiovascular disease
Background Variation in the complement factor H gene (CFH) is associated with risk of late age-related macular degeneration (AMD). Previous studies have been case–control studies in populations of European ancestry with little differentiation in AMD subtype, and insufficient power to confirm or refute effect modification by smoking.
Methods To precisely quantify the association of the single nucleotide polymorphism (SNP rs1061170, ‘Y402H’) with risk of AMD among studies with differing study designs, participant ancestry and AMD grade and to investigate effect modification by smoking, we report two unpublished genetic association studies (n = 2759) combined with data from 24 published studies (26 studies, 26 494 individuals, including 14 174 cases of AMD) of European ancestry, 10 of which provided individual-level data used to test gene–smoking interaction; and 16 published studies from non-European ancestry.
Results In individuals of European ancestry, there was a significant association between Y402H and late-AMD with a per-allele odds ratio (OR) of 2.27 [95% confidence interval (CI) 2.10–2.45; P = 1.1 x 10−161]. There was no evidence of effect modification by smoking (P = 0.75). The frequency of Y402H varied by ancestral origin and the association with AMD in non-Europeans was less clear, limited by paucity of studies.
Conclusion The Y402H variant confers a 2-fold higher risk of late-AMD per copy in individuals of European descent. This was stable to stratification by study design and AMD classification and not modified by smoking. The lack of association in non-Europeans requires further verification. These findings are of direct relevance for disease prediction. New research is needed to ascertain if differences in circulating levels, expression or activity of factor H protein explain the genetic association.
Age-related macular degeneration (AMD); Complement factor H gene; meta-ananlysis
To identify previously unknown genetic loci associated with fasting glucose concentrations, we examined the leading association signals in ten genome-wide association scans involving a total of 36,610 individuals of European descent. Variants in the gene encoding melatonin receptor 1B (MTNR1B) were consistently associated with fasting glucose across all ten studies. The strongest signal was observed at rs10830963, where each G allele (frequency 0.30 in HapMap CEU) was associated with an increase of 0.07 (95% CI = 0.06-0.08) mmol/l in fasting glucose levels (P = 3.2 = × 10−50) and reduced beta-cell function as measured by homeostasis model assessment (HOMA-B, P = 1.1 × 10−15). The same allele was associated with an increased risk of type 2 diabetes (odds ratio = 1.09 (1.05-1.12), per G allele P = 3.3 × 10−7) in a meta-analysis of 13 case-control studies totaling 18,236 cases and 64,453 controls. Our analyses also confirm previous associations of fasting glucose with variants at the G6PC2 (rs560887, P = 1.1 × 10−57) and GCK (rs4607517, P = 1.0 × 10−25) loci.
Aging-associated neurodegenerative diseases significantly influence the quality of life of affected individuals. Genetic approaches, combined with genomic technology, have provided powerful insights into common late-onset diseases, such as age-related macular degeneration (AMD). Here, we discuss current findings on the genetics of AMD to highlight areas of rapid progress and new challenges. We also attempt to integrate available genetic and biochemical data with cellular pathways involved in aging to formulate an integrated model of AMD pathogenesis.
protein homeostasis; gene-environment interaction; genetic variation; neurodegeneration; neovascularization; animal models