Hundreds of variants clustered in genomic loci and biological pathways affect human height

Most common human traits and diseases have a polygenic pattern of inheritance: DNA sequence variants at many genetic loci influence the phenotype. Genome-wide association (GWA) studies have identified more than 600 variants associated with human traits, but these typically explain small fractions of phenotypic variation, raising questions about the use of further studies. Here, using 183,727 individuals, we show that hundreds of genetic variants, in at least 180 loci, influence adult height, a highly heritable and classic polygenic trait. The large number of loci reveals patterns with important implications for genetic studies of common human diseases and traits. First, the 180 loci are not random, but instead are enriched for genes that are connected in biological pathways (P = 0.016) and that underlie skeletal growth defects (P < 0.001). Second, the likely causal gene is often located near the most strongly associated variant: in 13 of 21 loci containing a known skeletal growth gene, that gene was closest to the associated variant. Third, at least 19 loci have multiple independently associated variants, suggesting that allelic heterogeneity is a frequent feature of polygenic traits, that comprehensive explorations of already-discovered loci should discover additional variants and that an appreciable fraction of associated loci may have been identified. Fourth, associated variants are enriched for likely functional effects on genes, being over-represented among variants that alter amino-acid structure of proteins and expression levels of nearby genes. Our data explain approximately 10% of the phenotypic variation in height, and we estimate that unidentified common variants of similar effect sizes would increase this figure to approximately 16% of phenotypic variation (approximately 20% of heritable variation). Although additional approaches are needed to dissect the genetic architecture of polygenic human traits fully, our findings indicate that GWA studies can identify large numbers of loci that implicate biologically relevant genes and pathways.

The Consequences of Phenotypic Plasticity in Cyclically Varying Environments: A Genetic Algorithm Study

By “phenotypic plasticity” we refer to the capacity of a genotype to exhibit different phenotypes, whether in the same or in different environments. We have previously demonstrated that phenotypic plasticity can improve the degree of adaptation achieved via natural selection (Behera & Nanjundiah, 1995). That result was obtained from a genetic algorithm model of haploid genotypes (idealized as one-dimensional strings of genes) evolving in a fixed environment. Here, the dynamics of evolution is examined under conditions of a cyclically varying environment. We find that the rate of evolution, as well as the extent of adaptation (as measured by mean population fitness) is lowered because of environmental cycling. The decrease is adaptation caused by a varying environment can, however, be partly or wholly compensated by an increase in the degree of plasticity that a genotype is capable of. Also, the reduction of population fitness caused by a variable environment can be partially offset by decreasing the total number of genetic loci. We conjecture that an increase in genome size may have been among the factors responsible for the evolution of phenotypic plasticity.

Timing of puberty : Genetic regulation

In the general population, the timing of puberty is normally distributed. This variation is determined by genetic and environmental factors, but the exact mechanisms underlying these influences remain elusive. The purpose of this study was to gain insight into genetic regulation of pubertal timing. Contributions of genetic versus environmental factors to the normal variation of pubertal timing were explored in twins. Familial occurrence and inheritance patterns of constitutional delay of growth and puberty, CDGP (a variant of normal pubertal timing), were studied in pedigrees of patients with this condition. To ultimately detect genes involved in the regulation of pubertal timing, genetic loci conferring susceptibility to CDGP were mapped by linkage analysis in the same family cohort. To subdivide the overall phenotypic variance of pubertal timing into genetic and environmental components, genetic modeling based on monozygous twins sharing 100% and dizygous twins sharing 50% of their genes was used in 2309 girls and 1828 boys from the FinnTwin 12-17 study. The timing of puberty was estimated from height growth, i.e. change in the relative height between the age when pubertal growth velocity peaks in the general population and adulthood. This reflects the percentage of adult height achieved at the average peak height velocity age, and thus, pubertal timing. Boys and girls diagnosed with CDGP were gathered through medical records from six pediatric clinics in Finland. First-degree relatives of the probands were invited to participate by letter; altogether, 286 families were recruited. When possible, families were extended to include also second-, third-, or fourth-degree relatives. The timing of puberty in all family members was primarily assessed from longitudinal growth data. Delayed puberty was defined by onset of pubertal growth spurt or peak height velocity taking place 1.5 (relaxed criterion) or 2 SD (strict criterion) beyond the mean. If growth data were unavailable, pubertal timing was based on interviews. In this case, CDGP criteria were set as having undergone pubertal development more than 2 (strict criterion) or 1.5 years (relaxed criterion) later than their peers, or menarche after 15 (strict criterion) or 14 years (relaxed criterion). Familial occurrence of strict CDGP was explored in families of 124 patients (95 males and 29 females) from two clinics in Southern Finland. In linkage analysis, we used relaxed CDGP criteria; 52 families with solely growth data-based CDGP diagnoses were selected from all clinics. Based on twin data, genetic factors explain 86% and 82% of the variance of pubertal timing in girls and boys, respectively. In families, 80% of male and 76% of female probands had affected first-degree relatives, in whom CDGP was 15 times more common than the expected (2.5%). In 74% (17 of 23) of the extended families with only one affected parent, familial patterns were consistent with autosomal dominant inheritance. By using 383 multiallelic markers and subsequently fine-mapping with 25 additional markers, significant linkage for CDGP was detected to the pericentromeric region of chromosome 2, to 2p13-2q13 (multipoint HLOD 4.44, α 0.41). The findings of the large twin study imply that the vast majority of the normal variation of pubertal timing is attributed to genetic effects. Moreover, the high frequency of dominant inheritance patterns and the large number of affected relatives of CDGP patients suggest that genetic factors also markedly contribute to constitutional delay of puberty. Detection of the locus 2p13-2q13 in the pericentromeric region of chromosome 2 associating with CDGP is one step towards unraveling the genes that determine pubertal timing.

GENETIC DIVERSITY IN THE CHINESE PANGOLIN (MANIS-PENTADACTYLA) INFERRED FROM PROTEIN ELECTROPHORESIS

We examined protein polymorphism of Chinese pangolins (Manis pentadactyla) from Yunnan Province of China, including two forms of three brown and nine dusky Chinese pangolins. Sixty-two genetic loci were screened; 12 loci were found to be polymorphic. The percentage of polymorphic loci (P) is 0.194, the mean individual heterozygosity (H) is 0.078, and the mean number of alleles (A) is 1.258. Furthermore, we calculated the genetic distance (D) between the two forms and found a low level of genetic divergence (D = 0.0206) between them, which indicates an almost-indistinguishable divergence at the level of proteins.

Protein polymorphism and genetic divergence in slow loris (Genus nycticebus)

In this study, protein electrophoresis was assayed to detect genetic variation in Genus Nycticebus. A total of 29 samples (2 N. coucang and 27 N. pygmaeus) were analyzed for 42 genetic loci. In the 27 samples of N. pygmaeus, 4 loci were observed to be polymorphic. Therefore, the estimated P value (proportion of polymorphic loci) is 0.095, the A value (average number of alleles each locus) is 1.045, and the H value (mean individual heterozygosity) is 0.040. After comparing the H of N. pygmaeus with those of other primates reported, we found that the protein variation in N. pygmaeus is slightly lower than the average level. Additionally, we also observed obvious allele difference between N. pygmaeus and N. coucang. There are no shared alleles between these two species in eight loci. The NEI's genetic distance between them was calculated as 0.2541, which falls in the spectrum of genetic difference between species in primates.

Genetic diversity of Yunnan local pig breeds inferred from blood protein electrophoresis

Protein electrophoresis was used to examine the blood protein polymorphism in Yunnan local pig breeds, i.e., the Saba pig, Dahe pig, and Diannan small-ear pig breeds, Of 38 genetic loci surveyed 9 were found to be polymorphic. The percentage of polymorphic loci (P) varies from 0.1875 to 0.2121, and the mean individual heterozygosity (H) varies front 0.0712 to 0.1027 in three pig breeds. The results indicate that blood protein polymorphism in Yunnan pig breeds is high. Yunnan local pig breeds have a wealth of genetic diversity at the level of blood proteins.

Functional annotation signatures of disease susceptibility loci improve SNP association analysis.

BACKGROUND: Genetic association studies are conducted to discover genetic loci that contribute to an inherited trait, identify the variants behind these associations and ascertain their functional role in determining the phenotype. To date, functional annotations of the genetic variants have rarely played more than an indirect role in assessing evidence for association. Here, we demonstrate how these data can be systematically integrated into an association study's analysis plan. RESULTS: We developed a Bayesian statistical model for the prior probability of phenotype-genotype association that incorporates data from past association studies and publicly available functional annotation data regarding the susceptibility variants under study. The model takes the form of a binary regression of association status on a set of annotation variables whose coefficients were estimated through an analysis of associated SNPs in the GWAS Catalog (GC). The functional predictors examined included measures that have been demonstrated to correlate with the association status of SNPs in the GC and some whose utility in this regard is speculative: summaries of the UCSC Human Genome Browser ENCODE super-track data, dbSNP function class, sequence conservation summaries, proximity to genomic variants in the Database of Genomic Variants and known regulatory elements in the Open Regulatory Annotation database, PolyPhen-2 probabilities and RegulomeDB categories. Because we expected that only a fraction of the annotations would contribute to predicting association, we employed a penalized likelihood method to reduce the impact of non-informative predictors and evaluated the model's ability to predict GC SNPs not used to construct the model. We show that the functional data alone are predictive of a SNP's presence in the GC. Further, using data from a genome-wide study of ovarian cancer, we demonstrate that their use as prior data when testing for association is practical at the genome-wide scale and improves power to detect associations. CONCLUSIONS: We show how diverse functional annotations can be efficiently combined to create 'functional signatures' that predict the a priori odds of a variant's association to a trait and how these signatures can be integrated into a standard genome-wide-scale association analysis, resulting in improved power to detect truly associated variants.

Genetic and Epigenetic Risk Factors for Diabetic Kidney Disease

Diabetes is increasing at daunting rates worldwide, and approximately 40% of affected individuals will develop kidney complications. Diabetic kidney disease (DKD) is the leading cause of end-stage kidney disease, and there are significant healthcare costs providing appropriate renal replacement therapies to affected individuals. For several decades, investigators have sought to discover inherited risk factors and biomarkers for DKD. In recent years, advances in high-throughput laboratory techniques and computational analyses, coupled with the establishment of multicenter consortia, have helped to identify genetic loci that are replicated across multiple populations. Several genome-wide association studies (GWAS) have been conducted for DKD with further meta-analysis of GWAS and comprehensive ”single gene” meta-analyses now published. Despite these efforts, much of the inherited predisposition to DKD remains unexplained. Meta-analyses and integrated–omics pathway studies are being used to help elucidate underlying genetic risks. Epigenetic phenomena are increasingly recognized as important drivers of disease risk, and several epigenome-wide association studies have now been completed. This review describes key findings and ongoing genetic and epigenetic initiatives for DKD.

Invited review - genetic and epigenetic factors influencing CKD

Chronic kidney disease (CKD) has become a serious public health problem because of its associated morbidity, premature mortality and attendant healthcare costs. The rising number of persons with CKD is linked with ageing population structure and an increased prevalence of diabetes, hypertension and obesity. There is an inherited risk associated with developing CKD as evidenced by familial clustering and differing prevalence rates across ethnic groups. Earlier studies to determine the inherited risk factors for CKD rarely identified genetic variants that were robustly replicated. However, improvements in genotyping technologies and analytical methods are now helping to identify promising genetic loci aided by international collaboration and multi-consortia efforts. More recently, epigenetic modifications have been proposed to play a role in both the inherited susceptibility to CKD and, importantly, to explain how the environment dynamically interacts with the genome to alter an individual's disease risk. Genome-wide, epigenome-wide and whole transcriptome studies have been performed and optimal approaches for integrative analysis are being developed. This review summarises recent research and the current status of genetic and epigenetic risk factors influencing CKD using population-based information.

Outlier SNP markers reveal fine-scale genetic structuring across European hake populations (Merluccius merluccius)

Shallow population structure is generally reported for most marine fish and explained as a consequence of high dispersal, connectivity and large population size. Targeted gene analyses and more recently genome-wide studies have challenged such view, suggesting that adaptive divergence might occur even when neutral markers provide genetic homogeneity across populations. Here, 381 SNPs located in transcribed regions were used to assess large- and fine-scale population structure in the European hake (Merluccius merluccius), a widely distributed demersal species of high priority for the European fishery. Analysis of 850 individuals from 19 locations across the entire distribution range showed evidence for several outlier loci, with significantly higher resolving power. While 299 putatively neutral SNPs confirmed the genetic break between basins (F(CT) = 0.016) and weak differentiation within basins, outlier loci revealed a dramatic divergence between Atlantic and Mediterranean populations (F(CT) range 0.275-0.705) and fine-scale significant population structure. Outlier loci separated North Sea and Northern Portugal populations from all other Atlantic samples and revealed a strong differentiation among Western, Central and Eastern Mediterranean geographical samples. Significant correlation of allele frequencies at outlier loci with seawater surface temperature and salinity supported the hypothesis that populations might be adapted to local conditions. Such evidence highlights the importance of integrating information from neutral and adaptive evolutionary patterns towards a better assessment of genetic diversity. Accordingly, the generated outlier SNP data could be used for tackling illegal practices in hake fishing and commercialization as well as to develop explicit spatial models for defining management units and stock boundaries.

Blood pressure loci identified with a gene-centric array.

Raised blood pressure (BP) is a major risk factor for cardiovascular disease. Previous studies have identified 47 distinct genetic variants robustly associated with BP, but collectively these explain only a few percent of the heritability for BP phenotypes. To find additional BP loci, we used a bespoke gene-centric array to genotype an independent discovery sample of 25,118 individuals that combined hypertensive case-control and general population samples. We followed up four SNPs associated with BP at our p < 8.56 × 10(-7) study-specific significance threshold and six suggestively associated SNPs in a further 59,349 individuals. We identified and replicated a SNP at LSP1/TNNT3, a SNP at MTHFR-NPPB independent (r(2) = 0.33) of previous reports, and replicated SNPs at AGT and ATP2B1 reported previously. An analysis of combined discovery and follow-up data identified SNPs significantly associated with BP at p < 8.56 × 10(-7) at four further loci (NPR3, HFE, NOS3, and SOX6). The high number of discoveries made with modest genotyping effort can be attributed to using a large-scale yet targeted genotyping array and to the development of a weighting scheme that maximized power when meta-analyzing results from samples ascertained with extreme phenotypes, in combination with results from nonascertained or population samples. Chromatin immunoprecipitation and transcript expression data highlight potential gene regulatory mechanisms at the MTHFR and NOS3 loci. These results provide candidates for further study to help dissect mechanisms affecting BP and highlight the utility of studying SNPs and samples that are independent of those studied previously even when the sample size is smaller than that in previous studies.

Genetic variants influencing circulating lipid levels and risk of coronary artery disease.

OBJECTIVE: 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 low-density lipoprotein cholesterol (LDL-C), high-density lipoprotein cholesterol (HDL-C), and triglycerides. METHODS AND RESULTS: We combined genome-wide association data from 8 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 8 populations and also in a population of Indian Asian descent. We also assessed the association between single-nucleotide polymorphisms (SNPs) at lipid loci and risk of CAD in up to 9 633 cases and 38 684 controls. We identified 4 novel genetic loci that showed reproducible associations with lipids (probability values, 1.6×10(-8) to 3.1×10(-10)). These include a potentially functional SNP in the SLC39A8 gene for HDL-C, an SNP near the MYLIP/GMPR and PPP1R3B genes for LDL-C, and at the AFF1 gene for triglycerides. SNPs showing strong statistical association with 1 or more lipid traits at the CELSR2, APOB, APOE-C1-C4-C2 cluster, LPL, ZNF259-APOA5-A4-C3-A1 cluster and TRIB1 loci were also associated with CAD risk (probability values, 1.1×10(-3) to 1.2×10(-9)). CONCLUSIONS: We have identified 4 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.

COMT Val158Met and 5HTTLPR functional loci interact to predict anxiety across adolescence : results from the Victorian Adolescent Health Cohort Study (1992-2006)

We investigated whether a composite genetic factor, based on the combined actions of catechol-O-methyltransferase (COMT) (Val158Met) and serotonin transporter (5HTTLPR) (Long-Short) functional loci, has a greater capacity to predict persistence of anxiety across adolescence than either locus in isolation. Analyses were performed on DNA collected from 962 young Australians participating in an eight-wave longitudinal study of mental health and well-being (Victorian Adolescent Health Cohort Study). When the effects of each locus were examined separately, small dose–response reductions in the odds of reporting persisting generalized (free-floating) anxiety across adolescence were observed for the COMT Met158 [odds ratio (OR) = 0.85, 95% confidence interval (CI) = 0.76–0.95, P = 0.004] and 5HTTLPR Short alleles (OR = 0.88, CI = 0.79–0.99, P = 0.033). There was no evidence for a dose–response interaction effect between loci. However, there was a double-recessive interaction effect in which the odds of reporting persisting generalized anxiety were more than twofold reduced (OR = 0.45, CI = 0.29–0.70, P < 0.001) among carriers homozygous for both the COMT Met158 and the 5HTTLPR Short alleles (Met158Met + Short-Short) compared with the remaining cohort. The double-recessive effect remained after multivariate adjustment for a range of psychosocial predictors of anxiety. Exploratory stratified analyses suggested that genetic protection may be more pronounced under conditions of high stress (insecure attachments and sexual abuse), although strata differences did not reach statistical significance. By describing the interaction between genetic loci, it may be possible to describe composite genetic factors that have a more substantial impact on psychosocial development than individual loci alone, and in doing so, enhance understanding of the contribution of constitutional processes in mental health outcomes.

Variation of genetic expression during development, revealed by esterase patterns in Aedes aegypti (Diptera, Culicidae)

Polyacrylamide gel electrophoresis was used to analyze esterase patterns during development of Aedes aegypti from the cities of Marília and São José do Rio Preto (SJRP), Brazil. The zymograms showed a total of 23 esterase bands, 22 of which were in the specimens from Marília and 19 in those from SJRP. These esterase bands were considered to be the product of 23 alleles distributed tentatively in eight genetic loci. Most of the alleles were developmentally regulated. The larval stage expressed the greatest number of them (19 alleles, from the eight loci, in Marília; and 17 alleles, from seven loci, in SJRP). The pupal stage expressed 10 alleles from seven loci, in both populations, and the adult stage expressed 8 alleles from five and six loci in SJRP and Marília, respectively. Some alleles that were active in every stage were developmentally controlled at the level of expression (amount of product). A single allele was constitutively and highly expressed, in larvae, pupae, and adults, in both populations. Differences in esterase synthesis among stages are probably due to regulatory mechanisms acting in agreement with the requirements of a variable number of processes in which esterases are involved. The larval stage is the most active in developmental processes and shows very intense intake of food and very high mobility. These features may demand increased esterase production at that stage. Comparison of the two populations examined showed (besides the existence of alleles that they do not share) that they exhibit differences in the control of expression of other alleles. Such findings may reflect genetic differences between founders in each population, but the possibility of involvement of the intensive use of insecticides in SJRP is also discussed.

Genetic analyses of smoking initiation, persistence, quantity, and age-at-onset of regular cigarette use in Brazilian families: the Baependi Heart Study

Background: The purpose of this study was to estimate the genetic influences on the initiation of cigarette smoking, the persistence, quantity and age-at-onset of regular cigarette use in Brazilian families. Methods: The data set consisted of 1,694 individuals enrolled in the Baependi Heart Study. The heritability and the heterogeneity in genetic and environmental variance components by gender were estimated from variance components approaches, using the SOLAR (Sequential Oligogenic Linkage Analysis Routines) computer package. The mixed-effects Cox model was used for the genetic analysis of the age-at onset of regular cigarette use. Results: The heritability estimates were high (> 50%) for smoking initiation and were intermediate, ranging from 23.4 to 31.9%, for smoking persistence and quantity. Significant evidence for heterogeneity in variance components by gender was observed for smoking initiation and age-at-onset of regular cigarette use. Genetic factors play an important role in the interindividual variation of these phenotypes in females, while in males there is a predominant environmental component, which could be explained by greater social influences in the initiation of tobacco use. Conclusions: Significant heritabilities were observed in smoking phenotypes for both males and females from the Brazilian population. These data add to the literature and are concordant with the notion of significant biological determination in smoking behavior. Samples from the Baependi Heart Study may be valuable for the mapping of genetic loci that modulate this complex biological trait.