An inverse association between birth weight and the risk of developing type 2 diabetes (T2D) in adulthood has been reported. This association may be explained by common genetic variants related to insulin secretion and resistance, since insulin is the most important growth factor in fetal life. The objective of this study was to examine whether T2D gene polymorphism TCF7L2 rs7903146 is associated with growth patterns from fetal life until infancy.

To identify genetic loci influencing central obesity and fat distribution, we performed a meta-analysis of 16 genome-wide association studies (GWAS, N = 38,580) informative for adult waist circumference (WC) and waist-hip ratio (WHR). We selected 26 SNPs for follow-up, for which the evidence of association with measures of central adiposity (WC and/or WHR) was strong and disproportionate to that for overall adiposity or height. Follow-up studies in a maximum of 70,689 individuals identified two loci strongly associated with measures of central adiposity; these map near TFAP2B (WC, P = 1.9x10(-11)) and MSRA (WC, P = 8.9x10(-9)). A third locus, near LYPLAL1, was associated with WHR in women only (P = 2.6x10(-8)). The variants near TFAP2B appear to influence central adiposity through an effect on overall obesity/fat-mass, whereas LYPLAL1 displays a strong female-only association with fat distribution. By focusing on anthropometric measures of central obesity and fat distribution, we have identified three loci implicated in the regulation of human adiposity.

Age-related macular degeneration (AMD) is the leading cause of irreversible visual loss in the developed countries and is caused by both environmental and genetic factors. A recent study (Tuo et al., PNAS) reported an association between AMD and a single nucleotide polymorphism (SNP) (rs3793784) in the ERCC6 (NM_000124) gene. The risk allele also increased ERCC6 expression. ERCC6 is involved in DNA repair and mutations in ERCC6 cause Cockayne syndrome (CS). Amongst others, photosensitivity and pigmentary retinopathy are hallmarks of CS.

Serum lactate dehydrogenase (LDH) is used in diagnosing many diseases and is significantly determined by genetic factors. Three genes coding for LDH isoenzymes were mapped to chromosome 11q15 and 12p12. We used 330 Framingham Heart Study largest families for microsatellite linkage scan and 100K SNPs association scan to determine quantitative trait loci of LDH level. We estimated the heritability at 41%. Our genome-wide linkage analysis yielded several chromosomal regions, other than 11q and 12p, with LOD scores between 1 and 2.5. None of the 100K SNPs with a P-value <10(-4) in our genome-wide association study was close to the chromosomal regions where the LDH genes reside. Our study demonstrated a strong genetic effect on the variation of LDH levels. There may not be a single gene with a large effect, instead may be several genes with small effects in controlling the variation of serum LDH. Those genes may be located on chromosomal regions that differ from where the genes encoding LDH isoenzymes reside.

Migraine is a common episodic neurological disorder, typically presenting with recurrent attacks of severe headache and autonomic dysfunction. Apart from rare monogenic subtypes, no genetic or molecular markers for migraine have been convincingly established. We identified the minor allele of rs1835740 on chromosome 8q22.1 to be associated with migraine (P = 5.38 × 10⁻⁹, odds ratio = 1.23, 95% CI 1.150-1.324) in a genome-wide association study of 2,731 migraine cases ascertained from three European headache clinics and 10,747 population-matched controls. The association was replicated in 3,202 cases and 40,062 controls for an overall meta-analysis P value of 1.69 × 10⁻¹¹ (odds ratio = 1.18, 95% CI 1.127-1.244). rs1835740 is located between MTDH (astrocyte elevated gene 1, also known as AEG-1) and PGCP (encoding plasma glutamate carboxypeptidase). In an expression quantitative trait study in lymphoblastoid cell lines, transcript levels of the MTDH were found to have a significant correlation to rs1835740 (P = 3.96 × 10⁻⁵, permuted threshold for genome-wide significance 7.7 × 10⁻⁵. To our knowledge, our data establish rs1835740 as the first genetic risk factor for migraine.

Iron overload may contribute to the risk of Alzheimer's disease (AD). In the Epistasis Project, with 1757 cases of AD and 6295 controls, we studied 4 variants in 2 genes of iron metabolism: hemochromatosis (HFE) C282Y and H63D, and transferrin (TF) C2 and -2G/A. We replicated the reported interaction between HFE 282Y and TF C2 in the risk of AD: synergy factor, 1.75 (95% confidence interval, 1.1-2.8, p = 0.02) in Northern Europeans. The synergy factor was 3.1 (1.4-6.9; 0.007) in subjects with the APOEε4 allele. We found another interaction, between HFE 63HH and TF -2AA, markedly modified by age. Both interactions were found mainly or only in Northern Europeans. The interaction between HFE 282Y and TF C2 has now been replicated twice, in altogether 2313 cases of AD and 7065 controls, and has also been associated with increased iron load. We therefore suggest that iron overload may be a causative factor in the development of AD. Treatment for iron overload might thus be protective in some cases.

Major depression (MD) is one of the most prevalent psychiatric disorders and a leading cause of loss in work productivity. A combination of genetic and environmental risk factors probably contributes to MD. We present data from a genome-wide association study revealing a neuron-specific neutral amino acid transporter (SLC6A15) as a susceptibility gene for MD. Risk allele carrier status in humans and chronic stress in mice were associated with a downregulation of the expression of this gene in the hippocampus, a brain region implicated in the pathophysiology of MD. The same polymorphisms also showed associations with alterations in hippocampal volume and neuronal integrity. Thus, decreased SLC6A15 expression, due to genetic or environmental factors, might alter neuronal circuits related to the susceptibility for MD. Our convergent data from human genetics, expression studies, brain imaging, and animal models suggest a pathophysiological mechanism for MD that may be accessible to drug targeting.

Migraine is a common neurological disorder with a genetically complex background. This paper describes a meta-analysis of genome-wide association (GWA) studies on migraine, performed by the Dutch-Icelandic migraine genetics (DICE) consortium, which brings together six population-based European migraine cohorts with a total sample size of 10,980 individuals (2446 cases and 8534 controls). A total of 32 SNPs showed marginal evidence for association at a P-value<10(-5). The best result was obtained for SNP rs9908234, which had a P-value of 8.00 × 10(-8). This top SNP is located in the nerve growth factor receptor (NGFR) gene. However, this SNP did not replicate in three cohorts from the Netherlands and Australia. Of the other 31 SNPs, 18 SNPs were tested in two replication cohorts, but none replicated. In addition, we explored previously identified candidate genes in the meta-analysis data set. This revealed a modest gene-based significant association between migraine and the metadherin (MTDH) gene, previously identified in the first clinic-based GWA study (GWAS) for migraine (Bonferroni-corrected gene-based P-value=0.026). This finding is consistent with the involvement of the glutamate pathway in migraine. Additional research is necessary to further confirm the involvement of glutamate.

Genome-wide association studies (GWAS) using high-density array of single-nucleotide polymorphisms (SNPs) offer an unbiased strategy to identify new candidate genes for osteoporosis. We used a subset of autosomal SNPs from the Affymetrix 500K+50K SNP GeneChip marker set to examine genetic linkage with multiple highly heritable osteoporosis-related traits, including BMD of the hip and spine, heel ultrasound (attenuation and speed of sound), and geometric indices of the hip, in two generations from the Framingham Osteoporosis Study. Variance component linkage analysis was performed using normalized residuals (adjusted for age, height, BMI, and estrogen status in women). Multipoint linkage analyses produced LOD scores > or =3.0 for BMD on chromosomes (chr.) 9 and 11 and for ultrasound speed of sound on chr. 5. Hip geometric traits were linked with higher LOD scores, such as with shaft width on chr. 4 (LOD=3.9) and chr. 16 (LOD=3.8) and with shaft section modulus on chr. 22 (LOD=4.0). LOD score > or =5.0 was obtained for femoral neck width on chr. 7. In conclusion, with an SNP-based linkage approach, we identified several novel potential QTLs and confirmed previously identified chromosomal regions linked to bone mass and geometry. Subsequent focus on the spectrum of genetic polymorphisms in these refined regions may contribute to finding variants predisposing to osteoporosis.

SIRT1 has pleiotropic metabolic functions. We investigated whether SIRT1 genetic variation is associated with obesity.

The RETN gene encodes the adipokine resistin. Associations of RETN with plasma resistin levels, type 2 diabetes, and related metabolic traits have been inconsistent. Using comprehensive linkage disequilibrium mapping, we genotyped tag single nucleotide polymorphisms (SNPs) in RETN and tested associations with plasma resistin levels, risk of diabetes, and glycemic traits.

Type 2 diabetes (T2D) is a metabolic disorder characterized by disturbances of carbohydrate, fat and protein metabolism and insulin resistance. The majority of T2D patients are obese and obesity by itself may be a cause of insulin resistance. Our aim was to evaluate whether the recently identified T2D risk alleles are associated with human measures of fatness as characterized with Dual Energy X-ray Absorptiometry (DEXA).

Sudden cardiac death (SCD) continues to be one of the leading causes of mortality worldwide, with an annual incidence estimated at 250,000-300,000 in the United States and with the vast majority occurring in the setting of coronary disease. We performed a genome-wide association meta-analysis in 1,283 SCD cases and >20,000 control individuals of European ancestry from 5 studies, with follow-up genotyping in up to 3,119 SCD cases and 11,146 controls from 11 European ancestry studies, and identify the BAZ2B locus as associated with SCD (P = 1.8×10(-10)). The risk allele, while ancestral, has a frequency of ~1.4%, suggesting strong negative selection and increases risk for SCD by 1.92-fold per allele (95% CI 1.57-2.34). We also tested the role of 49 SNPs previously implicated in modulating electrocardiographic traits (QRS, QT, and RR intervals). Consistent with epidemiological studies showing increased risk of SCD with prolonged QRS/QT intervals, the interval-prolonging alleles are in aggregate associated with increased risk for SCD (P = 0.006).

Runs of homozygosity (ROH) are extended tracts of adjacent homozygous single nucleotide polymorphisms (SNPs) that are more common in unrelated individuals than previously thought. It has been proposed that estimating ROH on a genome-wide level, by making use of the genome-wide single nucleotide polymorphism (SNP) data, will enable to indentify recessive variants underlying complex traits. Here, we examined ROH larger than 1.5 Mb individually and in combination for association with survival in 5974 participants of the Rotterdam Study. In addition, we assessed the role of overall homozygosity, expressed as a percentage of the autosomal genome that is in ROH longer than 1.5 Mb, on survival during a mean follow-up period of 12 years. None of these measures of homozygosity was associated with survival to old age.

Obesity is highly heritable. Genetic variants showing robust associations with obesity traits have been identified through genome-wide association studies. We investigated whether a composite score representing healthy diet modifies associations of these variants with obesity traits. Totally, 32 body mass index (BMI)- and 14 waist-hip ratio (WHR)-associated single nucleotide polymorphisms were genotyped, and genetic risk scores (GRS) were calculated in 18 cohorts of European ancestry (n = 68 317). Diet score was calculated based on self-reported intakes of whole grains, fish, fruits, vegetables, nuts/seeds (favorable) and red/processed meats, sweets, sugar-sweetened beverages and fried potatoes (unfavorable). Multivariable adjusted, linear regression within each cohort followed by inverse variance-weighted, fixed-effects meta-analysis was used to characterize: (a) associations of each GRS with BMI and BMI-adjusted WHR and (b) diet score modification of genetic associations with BMI and BMI-adjusted WHR. Nominally significant interactions (P = 0.006-0.04) were observed between the diet score and WHR-GRS (but not BMI-GRS), two WHR loci (GRB14 rs10195252; LYPLAL1 rs4846567) and two BMI loci (LRRN6C rs10968576; MTIF3 rs4771122), for the respective BMI-adjusted WHR or BMI outcomes. Although the magnitudes of these select interactions were small, our data indicated that associations between genetic predisposition and obesity traits were stronger with a healthier diet. Our findings generate interesting hypotheses; however, experimental and functional studies are needed to determine their clinical relevance.

Mutations create variation in the population, fuel evolution and cause genetic diseases. Current knowledge about de novo mutations is incomplete and mostly indirect. Here we analyze 11,020 de novo mutations from the whole genomes of 250 families. We show that de novo mutations in the offspring of older fathers are not only more numerous but also occur more frequently in early-replicating, genic regions. Functional regions exhibit higher mutation rates due to CpG dinucleotides and show signatures of transcription-coupled repair, whereas mutation clusters with a unique signature point to a new mutational mechanism. Mutation and recombination rates independently associate with nucleotide diversity, and regional variation in human-chimpanzee divergence is only partly explained by heterogeneity in mutation rate. Finally, we provide a genome-wide mutation rate map for medical and population genetics applications. Our results provide new insights and refine long-standing hypotheses about human mutagenesis.

To profile the differential gene expression of the KEGG Adipocytokine Signaling pathway in omental compared to subcutaneous tissue in normal pregnancy.

Variants associated with blood lipid levels may be population-specific. To identify low-frequency variants associated with this phenotype, population-specific reference panels may be used. Here we impute nine large Dutch biobanks (~35,000 samples) with the population-specific reference panel created by the Genome of The Netherlands Project and perform association testing with blood lipid levels. We report the discovery of five novel associations at four loci (P value <6.61 × 10(-4)), including a rare missense variant in ABCA6 (rs77542162, p.Cys1359Arg, frequency 0.034), which is predicted to be deleterious. The frequency of this ABCA6 variant is 3.65-fold increased in the Dutch and its effect (βLDL-C=0.135, βTC=0.140) is estimated to be very similar to those observed for single variants in well-known lipid genes, such as LDLR.

Elucidating the genetic basis of complex traits and diseases in non-European populations is particularly challenging because US minority populations have been under-represented in genetic association studies. We developed an empirical Bayes approach named XPEB (cross-population empirical Bayes), designed to improve the power for mapping complex-trait-associated loci in a minority population by exploiting information from genome-wide association studies (GWASs) from another ethnic population. Taking as input summary statistics from two GWASs-a target GWAS from an ethnic minority population of primary interest and an auxiliary base GWAS (such as a larger GWAS in Europeans)-our XPEB approach reprioritizes SNPs in the target population to compute local false-discovery rates. We demonstrated, through simulations, that whenever the base GWAS harbors relevant information, XPEB gains efficiency. Moreover, XPEB has the ability to discard irrelevant auxiliary information, providing a safeguard against inflated false-discovery rates due to genetic heterogeneity between populations. Applied to a blood-lipids study in African Americans, XPEB more than quadrupled the discoveries from the conventional approach, which used a target GWAS alone, bringing the number of significant loci from 14 to 65. Thus, XPEB offers a flexible framework for mapping complex traits in minority populations.

Metabolite quantitative traits carry great promise for epidemiological studies, and their genetic background has been addressed using Genome-Wide Association Studies (GWAS). Thus far, the role of less common variants has not been exhaustively studied. Here, we set out a GWAS for metabolite quantitative traits in serum, followed by exome sequence analysis to zoom in on putative causal variants in the associated genes. 1H Nuclear Magnetic Resonance (1H-NMR) spectroscopy experiments yielded successful quantification of 42 unique metabolites in 2,482 individuals from The Erasmus Rucphen Family (ERF) study. Heritability of metabolites were estimated by SOLAR. GWAS was performed by linear mixed models, using HapMap imputations. Based on physical vicinity and pathway analyses, candidate genes were screened for coding region variation using exome sequence data. Heritability estimates for metabolites ranged between 10% and 52%. GWAS replicated three known loci in the metabolome wide significance: CPS1 with glycine (P-value  = 1.27×10-32), PRODH with proline (P-value  = 1.11×10-19), SLC16A9 with carnitine level (P-value  = 4.81×10-14) and uncovered a novel association between DMGDH and dimethyl-glycine (P-value  = 1.65×10-19) level. In addition, we found three novel, suggestively significant loci: TNP1 with pyruvate (P-value  = 1.26×10-8), KCNJ16 with 3-hydroxybutyrate (P-value  = 1.65×10-8) and 2p12 locus with valine (P-value  = 3.49×10-8). Exome sequence analysis identified potentially causal coding and regulatory variants located in the genes CPS1, KCNJ2 and PRODH, and revealed allelic heterogeneity for CPS1 and PRODH. Combined GWAS and exome analyses of metabolites detected by high-resolution 1H-NMR is a robust approach to uncover metabolite quantitative trait loci (mQTL), and the likely causative variants in these loci. It is anticipated that insight in the genetics of intermediate phenotypes will provide additional insight into the genetics of complex traits.