Gene by smoking interaction in blood pressure

Hypertension (HT) is mediated by the interaction of many genetic and environmental factors. Previous genome-wide linkage analysis studies have found many loci that show linkage to HT or blood pressure (BP) regulation, but the results were generally inconsistent. Gene by environment interaction is among the reasons that potentially explain these inconsistencies between studies. Here we investigate influences of gene by smoking (GxS) interaction on HT and BP in European American (EA), African American (AA) and Mexican American (MA) families from the GENOA study. A variance component-based method was utilized to perform genome-wide linkage analysis of systolic blood pressure (SBP), diastolic blood pressure (DBP), and HT status, as well as bivariate analysis for SBP and DBP for smokers, non-smokers, and combined groups. The most significant results were found for SBP in MA. The strongest signal was for chromosome 17q24 (LOD = 4.2), increased to (LOD = 4.7) in bivariate analysis but there was no evidence of GxS interaction at this locus (p = 0.48). Two signals were identified only in one group: on chromosome 15q26.2 (LOD = 3.37) in non-smokers and chromosome 7q21.11 (LOD = 1.4) in smokers, both of which had strong evidence for GxS interaction (p = 0.00039 and 0.009 respectively). There were also two other signals, one on chromosome 20q12 (LOD = 2.45) in smokers, which became much higher in the combined sample (LOD = 3.53), and one on chromosome 6p22.2 (LOD = 2.06) in non-smokers. Neither peak had very strong evidence for GxS interaction (p = 0.08 and 0.06 respectively). A fine mapping association study was performed using 200 SNPs in 30 genes located under the linkage signals on chromosomes 15 and 17. Under the chromosome 15 peak, the association analysis identified 6 SNPs accounting for a 7 mmHg increase in SBP in MA non-smokers. For the chromosome 17 linkage peak, the association analysis identified 3 SNPs accounting for a 6 mmHg increase in SBP in MA. However, none of these SNPs was significant after correcting for multiple testing, and accounting for them in the linkage analysis produced very small reductions in the linkage signal. ^ The linkage analysis of BP traits considering the smoking status produced very interesting signals for SBP in the MA population. The fine mapping association analysis gave some insight into the contribution of some SNPs to two of the identified signals, but since these SNPs did not remain significant after multiple testing correction and did not explain the linkage peaks, more work is needed to confirm these exploratory results and identify the culprit variations under these linkage peaks. ^

The information bottleneck method for genome-wide association studies

In population studies, most current methods focus on identifying one outcome-related SNP at a time by testing for differences of genotype frequencies between disease and healthy groups or among different population groups. However, testing a great number of SNPs simultaneously has a problem of multiple testing and will give false-positive results. Although, this problem can be effectively dealt with through several approaches such as Bonferroni correction, permutation testing and false discovery rates, patterns of the joint effects by several genes, each with weak effect, might not be able to be determined. With the availability of high-throughput genotyping technology, searching for multiple scattered SNPs over the whole genome and modeling their joint effect on the target variable has become possible. Exhaustive search of all SNP subsets is computationally infeasible for millions of SNPs in a genome-wide study. Several effective feature selection methods combined with classification functions have been proposed to search for an optimal SNP subset among big data sets where the number of feature SNPs far exceeds the number of observations. ^ In this study, we take two steps to achieve the goal. First we selected 1000 SNPs through an effective filter method and then we performed a feature selection wrapped around a classifier to identify an optimal SNP subset for predicting disease. And also we developed a novel classification method-sequential information bottleneck method wrapped inside different search algorithms to identify an optimal subset of SNPs for classifying the outcome variable. This new method was compared with the classical linear discriminant analysis in terms of classification performance. Finally, we performed chi-square test to look at the relationship between each SNP and disease from another point of view. ^ In general, our results show that filtering features using harmononic mean of sensitivity and specificity(HMSS) through linear discriminant analysis (LDA) is better than using LDA training accuracy or mutual information in our study. Our results also demonstrate that exhaustive search of a small subset with one SNP, two SNPs or 3 SNP subset based on best 100 composite 2-SNPs can find an optimal subset and further inclusion of more SNPs through heuristic algorithm doesn't always increase the performance of SNP subsets. Although sequential forward floating selection can be applied to prevent from the nesting effect of forward selection, it does not always out-perform the latter due to overfitting from observing more complex subset states. ^ Our results also indicate that HMSS as a criterion to evaluate the classification ability of a function can be used in imbalanced data without modifying the original dataset as against classification accuracy. Our four studies suggest that Sequential Information Bottleneck(sIB), a new unsupervised technique, can be adopted to predict the outcome and its ability to detect the target status is superior to the traditional LDA in the study. ^ From our results we can see that the best test probability-HMSS for predicting CVD, stroke,CAD and psoriasis through sIB is 0.59406, 0.641815, 0.645315 and 0.678658, respectively. In terms of group prediction accuracy, the highest test accuracy of sIB for diagnosing a normal status among controls can reach 0.708999, 0.863216, 0.639918 and 0.850275 respectively in the four studies if the test accuracy among cases is required to be not less than 0.4. On the other hand, the highest test accuracy of sIB for diagnosing a disease among cases can reach 0.748644, 0.789916, 0.705701 and 0.749436 respectively in the four studies if the test accuracy among controls is required to be at least 0.4. ^ A further genome-wide association study through Chi square test shows that there are no significant SNPs detected at the cut-off level 9.09451E-08 in the Framingham heart study of CVD. Study results in WTCCC can only detect two significant SNPs that are associated with CAD. In the genome-wide study of psoriasis most of top 20 SNP markers with impressive classification accuracy are also significantly associated with the disease through chi-square test at the cut-off value 1.11E-07. ^ Although our classification methods can achieve high accuracy in the study, complete descriptions of those classification results(95% confidence interval or statistical test of differences) require more cost-effective methods or efficient computing system, both of which can't be accomplished currently in our genome-wide study. We should also note that the purpose of this study is to identify subsets of SNPs with high prediction ability and those SNPs with good discriminant power are not necessary to be causal markers for the disease.^

Familial component of epilepsy in cleft lip and palate

It is well recognized that offspring of women with epilepsy who are taking anticonvulsant medications have an increased incidence of clefting abnormalities. This increase has been attributed to the teratogenic effects of anticonvulsant medications but an alternative explanation involving a genetic association of epilepsy and clefting has also been proposed. Five family studies attempting to resolve this controversy have been inconclusive either because of study design or analytic limitations. This family study was designed to determine whether epilepsy aggregates in families ascertained by an individual with a clefting disorder. The Mayo Clinic medical linkage registry was used to identify individuals with cleft lip with or without cleft palate and cleft palate in southeast Minnesota from 1935-1986. Only those cases who were 15 years or younger during this period were included in the study. The proband's parents and descendants of their parents, including the proband's sibs, children, grandchildren, niece/nephews, grandnieces/nephews, halfsibs and spouses were also identified and all of their medical records were reviewed for seizure disorders. The standardized morbidity ratios for epilepsy of 0.9 (95% CI 0.2-2.6) observed for first degree relatives (excluding parents) and 0.0 for second degree relatives were not increased. The SMRs ranged from 0.7-2.2 for the individual relative types (parents 1.5, sibs 0.7, children 2.2, probands 1.1, spouses 2.0) and were also not increased. These results do not support the suggestions of some that clefting and epilepsy aggregate together in families. ^

FZD6, MATN2 AND SLC25A32, POSSIBLE CANDIDATE GENES IN NONSYNDROMIC CLEFT LIP AND PALATE

Nonsyndromic cleft lip with or without cleft palate (NSCLP) is a common birth defect with a multifactorial etiology. Despite decades of research, the genetic underpinnings of NSCLP still remain largely unexplained. A genome wide association study (GWAS) of a large NSCLP African American family with seven affected individuals across three generations found evidence for linkage at 8q21.3-24.12 (LOD = 2.98). This region contained three biologically relevant candidate genes: Frizzled-6 (FZD6) (LOD = 2.8), Matrilin-2 (MATN2) (LOD = 2.3), and Solute Carrier Family 25, Member 32 (SLC26A32) (LOD = 1.6). Sequencing of the coding regions and the 5’ and 3’ UTRs of these genes in two affected family members identified a rare intronic variant, rs138557689 (c.-153+432A>C), in FZD6. The rs138557689/C allele segregated with the NSCLP phenotype; in silico analysis predicted and EMSA analysis showed that the 138557689/C allele creates new DNA binding sites. FZD6 is part of the WNT pathway, which is involved in craniofacial development, including midface development and upper lip fusion. Our novel findings suggest that an alteration in FZD6 gene regulation may perturb this tightly controlled biological pathway and in turn contribute to the development of NSCLP in this family. Studies are underway to further define how the rs138557689/C variant affects expression of FZD6.

THE NATURAL AND ORTHOGONAL INTERACTION (NOIA) MODELS FOR QUANTITATIVE TRAITS (QTs) AND COMPLEX DISEASES

My dissertation focuses on developing methods for gene-gene/environment interactions and imprinting effect detections for human complex diseases and quantitative traits. It includes three sections: (1) generalizing the Natural and Orthogonal interaction (NOIA) model for the coding technique originally developed for gene-gene (GxG) interaction and also to reduced models; (2) developing a novel statistical approach that allows for modeling gene-environment (GxE) interactions influencing disease risk, and (3) developing a statistical approach for modeling genetic variants displaying parent-of-origin effects (POEs), such as imprinting. In the past decade, genetic researchers have identified a large number of causal variants for human genetic diseases and traits by single-locus analysis, and interaction has now become a hot topic in the effort to search for the complex network between multiple genes or environmental exposures contributing to the outcome. Epistasis, also known as gene-gene interaction is the departure from additive genetic effects from several genes to a trait, which means that the same alleles of one gene could display different genetic effects under different genetic backgrounds. In this study, we propose to implement the NOIA model for association studies along with interaction for human complex traits and diseases. We compare the performance of the new statistical models we developed and the usual functional model by both simulation study and real data analysis. Both simulation and real data analysis revealed higher power of the NOIA GxG interaction model for detecting both main genetic effects and interaction effects. Through application on a melanoma dataset, we confirmed the previously identified significant regions for melanoma risk at 15q13.1, 16q24.3 and 9p21.3. We also identified potential interactions with these significant regions that contribute to melanoma risk. Based on the NOIA model, we developed a novel statistical approach that allows us to model effects from a genetic factor and binary environmental exposure that are jointly influencing disease risk. Both simulation and real data analyses revealed higher power of the NOIA model for detecting both main genetic effects and interaction effects for both quantitative and binary traits. We also found that estimates of the parameters from logistic regression for binary traits are no longer statistically uncorrelated under the alternative model when there is an association. Applying our novel approach to a lung cancer dataset, we confirmed four SNPs in 5p15 and 15q25 region to be significantly associated with lung cancer risk in Caucasians population: rs2736100, rs402710, rs16969968 and rs8034191. We also validated that rs16969968 and rs8034191 in 15q25 region are significantly interacting with smoking in Caucasian population. Our approach identified the potential interactions of SNP rs2256543 in 6p21 with smoking on contributing to lung cancer risk. Genetic imprinting is the most well-known cause for parent-of-origin effect (POE) whereby a gene is differentially expressed depending on the parental origin of the same alleles. Genetic imprinting affects several human disorders, including diabetes, breast cancer, alcoholism, and obesity. This phenomenon has been shown to be important for normal embryonic development in mammals. Traditional association approaches ignore this important genetic phenomenon. In this study, we propose a NOIA framework for a single locus association study that estimates both main allelic effects and POEs. We develop statistical (Stat-POE) and functional (Func-POE) models, and demonstrate conditions for orthogonality of the Stat-POE model. We conducted simulations for both quantitative and qualitative traits to evaluate the performance of the statistical and functional models with different levels of POEs. Our results showed that the newly proposed Stat-POE model, which ensures orthogonality of variance components if Hardy-Weinberg Equilibrium (HWE) or equal minor and major allele frequencies is satisfied, had greater power for detecting the main allelic additive effect than a Func-POE model, which codes according to allelic substitutions, for both quantitative and qualitative traits. The power for detecting the POE was the same for the Stat-POE and Func-POE models under HWE for quantitative traits.

Nonlinear dimension reduction in pathway-based genome-wide association analysis

Pathway based genome wide association study evolves from pathway analysis for microarray gene expression and is under rapid development as a complementary for single-SNP based genome wide association study. However, it faces new challenges, such as the summarization of SNP statistics to pathway statistics. The current study applies the ridge regularized Kernel Sliced Inverse Regression (KSIR) to achieve dimension reduction and compared this method to the other two widely used methods, the minimal-p-value (minP) approach of assigning the best test statistics of all SNPs in each pathway as the statistics of the pathway and the principal component analysis (PCA) method of utilizing PCA to calculate the principal components of each pathway. Comparison of the three methods using simulated datasets consisting of 500 cases, 500 controls and100 SNPs demonstrated that KSIR method outperformed the other two methods in terms of causal pathway ranking and the statistical power. PCA method showed similar performance as the minP method. KSIR method also showed a better performance over the other two methods in analyzing a real dataset, the WTCCC Ulcerative Colitis dataset consisting of 1762 cases, 3773 controls as the discovery cohort and 591 cases, 1639 controls as the replication cohort. Several immune and non-immune pathways relevant to ulcerative colitis were identified by these methods. Results from the current study provided a reference for further methodology development and identified novel pathways that may be of importance to the development of ulcerative colitis.^

Análise genética da produção in vitro de embriões em bovinos Guzerá

O objetivo dessa pesquisa foi avaliar aspectos genéticos que relacionados à produção in vitro de embriões na raça Guzerá. O primeiro estudo focou na estimação de (co) variâncias genéticas e fenotípicas em características relacionadas a produção de embriões e na detecção de possível associação com a idade ao primeiro parto (AFC). Foi detectada baixa e média herdabilidade para características relacionadas à produção de oócitos e embriões. Houve fraca associação genética entre características ligadas a reprodução artificial e a idade ao primeiro parto. O segundo estudo avaliou tendências genéticas e de endogamia em uma população Guzerá no Brasil. Doadoras e embriões produzidos in vitro foram considerados como duas subpopulações de forma a realizar comparações acerca das diferenças de variação anual genética e do coeficiente de endogamia. A tendência anual do coeficiente de endogamia (F) foi superior para a população geral, sendo detectado efeito quadrático. No entanto, a média de F para a sub- população de embriões foi maior do que na população geral e das doadoras. Foi observado ganho genético anual superior para a idade ao primeiro parto e para a produção de leite (305 dias) entre embriões produzidos in vitro do que entre doadoras ou entre a população geral. O terceiro estudo examinou os efeitos do coeficiente de endogamia da doadora, do reprodutor (usado na fertilização in vitro) e dos embriões sobre resultados de produção in vitro de embriões na raça Guzerá. Foi detectado efeito da endogamia da doadora e dos embriões sobre as características estudadas. O quarto (e último) estudo foi elaborado para comparar a adequação de modelos mistos lineares e generalizados sob método de Máxima Verossimilhança Restrita (REML) e sua adequação a variáveis discretas. Quatro modelos hierárquicos assumindo diferentes distribuições para dados de contagem encontrados no banco. Inferência foi realizada com base em diagnósticos de resíduo e comparação de razões entre componentes de variância para os modelos em cada variável. Modelos Poisson superaram tanto o modelo linear (com e sem transformação da variável) quanto binomial negativo à qualidade do ajuste e capacidade preditiva, apesar de claras diferenças observadas na distribuição das variáveis. Entre os modelos testados, a pior qualidade de ajuste foi obtida para o modelo linear mediante transformação logarítmica (Log10 X +1) da variável resposta.

Obesidade e genes candidatos: estudo de associação em populações quilombolas do Vale do Ribeira-SP

A obesidade comum é atualmente um dos problemas de saúde pública mais importante no mundo, frequentemente associada a outros distúrbios tais como hipertensão, diabetes, doenças cardiovasculares e câncer. Apesar da alta prevalência de obesidade em diversas populações, muitos dos estudos relacionados aos seus fatores de risco genéticos foram realizados com indivíduos de ascendência europeia ou asiática, mas foram poucos os realizados com populações de origem africana ou nativas americanas. Nosso trabalho tem por objetivo geral investigar potenciais fatores de risco genéticos associados ao sobrepeso e à obesidade em populações afrodescendentes remanescentes de quilombos do Vale do Ribeira - SP, comunidades rurais semi-isoladas, previamente bem caracterizadas do ponto de vista clínico, genealógico e genético-populacional. Nossa amostra constituiu-se de 759 indivíduos, pertencentes a doze populações de remanescentes de quilombos (Abobral, São Pedro, Galvão, Ivaporunduva, Pedro Cubas, André Lopes, Nhunguara, Sapatu, Pilões, Maria Rosa, Poça e Reginaldo), dos quais foram obtidos amostras de DNA, dados clínicos, informações genealógicas e medidas antropométricas. A investigação dos fatores de risco genéticos associados ao sobrepeso/obesidade foi realizada por duas abordagens: (1) estudo de associação baseado em famílias (N = 584, 59 famílias) e (2) estudo de associação populacional com indivíduos não aparentados (N=305). Foram selecionados para estudo nove polimorfismos em oito genes candidatos: LEP rs2167270, LEPR rs1137101, ADRB2 rs1042713, PPARG rs1801282, PLIN1 rs2289487, RETN rs1862513, INSIG2 rs7566605, FTO rs1121980 e FTO rs1421085. As análises de associação baseadas em família indicaram que, nessas populações, apenas o polimorfismo PLIN1 rs2289487 está associado significativamente com o grupo de risco em relação à razão cintura-quadril (RCQ >=0,85 para mulheres e >=0,90 para homens; P=0,013). Aparentemente não existem trabalhos anteriores que verificaram a associação deste polimorfismo com a obesidade por essa metodologia. As análises do estudo populacional com indivíduos não aparentados mostraram associação significativa entre: (i) o alelo G no polimorfismo LEPR rs1137101 e a variação do índice de massa corporal (IMC; P=0,027); (ii) o alelo G do polimorfismo LEPR rs1137101 e o fenótipo de sobrepeso/obesidade (IMC>=25 Kg/m²; P=0,027); (iii) o alelo G no polimorfismo ADRB2 rs1042713 e o fenótipo de risco (IMC>=25 Kg/m²; P=0,029); (iv) o polimorfismo PLIN1 rs2289487 (genótipo GG) e os menores valores do IMC (P=0,025); (v) o polimorfismo FTO rs1121980 (alelo G) e o fenótipo de risco (IMC>=25 Kg/m²), assim como a variação do IMC (P=0,037 e P=0,022 respectivamente); e (vi) o alelo A no polimorfismo FTO rs1421085 e maiores valores da circunferência da cintura (Cc; P=0,016) e da razão cintura-quadril (RCQ; P=0,030). Tomados em conjunto, nossos resultados sugerem a participação dos genes LEP, LEPR, ADRB2, PLIN1 e FTO no aumento da predisposição ao sobrepeso e à obesidade nas populações remanescentes de quilombos. Por fim, as elevadas estimativas de herdabilidade dos três fenótipos investigados (IMC=33%, Cc=33% e RCQ=70%) reforçam a relevância do papel dos fatores genéticos no acúmulo de gordura corporal. O trabalho apresentado é resultado de uma investigação cuidadosa sobre os componentes genéticos associados à regulação do peso corporal em uma população brasileira afrodescendente (com características históricas, ambientais e genéticas peculiares), corroborando a hipótese de que a obesidade comum nas populações quilombolas do Vale do Ribeira é condicionada por um mecanismo poligênico modulado por fatores ambientais importantes como o sedentarismo e a transição nutricional

Association of secondary glioblastoma and pituitary adenoma : case report

Trabalho Final do Curso de Mestrado Integrado em Medicina, Faculdade de Medicina, Universidade de Lisboa, 2014

Recommendations for Genetic Testing to Reduce the Incidence of Anthracycline-induced Cardiotoxicity

AIM Anthracycline-induced cardiotoxicity (ACT) occurs in 57% of treated patients and remains an important limitation of anthracycline-based chemotherapy. In various genetic association studies, potential genetic risk markers for ACT have been identified. Therefore, we developed evidence-based clinical practice recommendations for pharmacogenomic testing to further individualize therapy based on ACT risk. METHODS We followed a standard guideline development process; including a systematic literature search, evidence synthesis and critical appraisal, and the development of clinical practice recommendations with an international expert group. RESULTS RARG rs2229774, SLC28A3 rs7853758 and UGT1A6 rs17863783 variants currently have the strongest and the most consistent evidence for association with ACT. Genetic variants in ABCC1, ABCC2, ABCC5, ABCB1, ABCB4, CBR3, RAC2, NCF4, CYBA, GSTP1, CAT, SULT2B1, POR, HAS3, SLC22A7, SCL22A17, HFE and NOS3 have also been associated with ACT, but require additional validation. We recommend pharmacogenomic testing for the RARG rs2229774 (S427L), SLC28A3 rs7853758 (L461L) and UGT1A6*4 rs17863783 (V209V) variants in childhood cancer patients with an indication for doxorubicin or daunorubicin therapy (Level B - moderate). Based on an overall risk stratification, taking into account genetic and clinical risk factors, we recommend a number of management options including increased frequency of echocardiogram monitoring, follow-up, as well as therapeutic options within the current standard of clinical practice. CONCLUSIONS Existing evidence demonstrates that genetic factors have the potential to improve the discrimination between individuals at higher and lower risk of ACT. Genetic testing may therefore support both patient care decisions and evidence development for an improved prevention of ACT.

Novel multiple sclerosis susceptibility loci implicated in epigenetic regulation.

We conducted a genome-wide association study (GWAS) on multiple sclerosis (MS) susceptibility in German cohorts with 4888 cases and 10,395 controls. In addition to associations within the major histocompatibility complex (MHC) region, 15 non-MHC loci reached genome-wide significance. Four of these loci are novel MS susceptibility loci. They map to the genes L3MBTL3, MAZ, ERG, and SHMT1. The lead variant at SHMT1 was replicated in an independent Sardinian cohort. Products of the genes L3MBTL3, MAZ, and ERG play important roles in immune cell regulation. SHMT1 encodes a serine hydroxymethyltransferase catalyzing the transfer of a carbon unit to the folate cycle. This reaction is required for regulation of methylation homeostasis, which is important for establishment and maintenance of epigenetic signatures. Our GWAS approach in a defined population with limited genetic substructure detected associations not found in larger, more heterogeneous cohorts, thus providing new clues regarding MS pathogenesis.

Australian data and meta-analysis lend support for alpha-synuclein (NACP-Rep1) as a risk factor for Parkinson's disease

It remains unclear whether genetic variants in SNCA (the alpha-synuclein gene) alter risk for sporadic Parkinson's disease (PD). The polymorphic mixed sequence repeat (NACP-Rep I) in the promoter region of SNCA has been previously examined as a potential susceptibility factor for PD with conflicting results. We report genotype and allele distributions at this locus from 369 PD cases and 370 control subjects of European Australian ancestry, with alleles designated as -1, 0, +1, +2, and +3 as previously described. Allele frequencies designated (0) were less common in Australian cases compared to controls (OR = 0.80, 95% CI 0.62-1.03). Combined analysis including all previously published ancestral European Rep1 data yielded a highly significant association between the 0 allele and a reduced risk for PD (OR = 0.79, 95% CI 0.70-0.89, p = 0.0001). Further study must now proceed to examine in detail this interesting and biologically plausible genetic association. (C) 2004 Elsevier Ireland Ltd. All rights reserved.

New concepts for distinguishing the hidden patterns of linkage disequilibrium which underlie association between genotypes and complex phenotypes

A disappointing feature of conventional methods for detecting association between DNA variation and a phenotype of interest is that they tell us little about the hidden pattern of linkage disequilibrium (LD) with the functional variant that is actually responsible for the association. This limitation applies to case-control studies and also to the transmission/disequilibrium test (TDT) and other family-based association methods. Here we present a fresh perspective on genetic association based on two novel concepts called 'LD squares' and 'equi-risk alleles'. These describe and characterize the different patterns of gametic LD which underlie genetic association. These concepts lead to a general principle - the Equi-Risk Allele Segregation Principle - which captures the way in which underlying LD patterns affect the transmission patterns of genetic variants associated with a phenotype. This provides a basis for distinguishing the hidden LD patterns and might help to locate the functional variants responsible for the association.

Maternal alcohol use disorder and offspring ADHD: disentangling genetic and environmental effects using a children-of-twins design

Background. Children of alcoholics are significantly more likely to experience high-risk environmental exposures, including prenatal substance exposure, and are more likely to exhibit externalizing problems [e.g. attention deficit hyperactivity disorder (ADHD)]. While there is evidence that genetic influences and prenatal nicotine and/or alcohol exposure play separate roles in determining risk of ADHD, little has been done on determining the joint roles that genetic risk associated with maternal alcohol use disorder (AUD) and prenatal risk factors play in determining risk of ADHD. Method. Using a children-of-twins design, diagnostic telephone interview data from high-risk families (female monozygotic and dizygotic twins concordant or discordant for AUD as parents) and control families targeted from a large Australian twin cohort were analyzed using logistic regression models. Results. Offspring of twins with a history of AUD, as well as offspring of non-AUD monozygotic twins whose co-twin had AUD, were significantly more likely to exhibit ADHD than offspring of controls. This pattern is consistent with a genetic explanation for the association between maternal AUD and increased offspring risk of ADHD. Adjustment for prenatal smoking, which remained significantly predictive, did not remove the significant genetic association between maternal AUD and offspring ADHD. Conclusions. While maternal smoking during pregnancy probably contributes to the association between maternal AUD and offspring ADHD risk, the evidence for a significant genetic correlation suggests: (i) pleiotropic genetic effects, with some genes that influence risk of AUD also influencing vulnerability to ADHD; or (ii) ADHD is a direct risk-factor for AUD.

Identification of the semaphorin receptor PLXNA2 as a candidate for susceptibility to schizophrenia

The discovery of genetic factors that contribute to schizophrenia susceptibility is a key challenge in understanding the etiology of this disease. Here, we report the identification of a novel schizophrenia candidate gene on chromosome 1q32, plexin A2 (PLXNA2), in a genome-wide association study using 320 patients with schizophrenia of European descent and 325 matched controls. Over 25 000 single-nucleotide polymorphisms (SNPs) located within approximately 14 000 genes were tested. Out of 62 markers found to be associated with disease status, the most consistent finding was observed for a candidate locus on chromosome 1q32. The marker SNP rs752016 showed suggestive association with schizophrenia (odds ratio (OR) = 1.49, P = 0.006). This result was confirmed in an independent case control sample of European Americans (combined OR = 1.38, P = 0.035) and similar genetic effects were observed in smaller subsets of Latin Americans (OR = 1.26) and Asian Americans (OR = 1.37). Supporting evidence was also obtained from two family-based collections, one of which reached statistical significance (OR = 2.2, P = 0.02). High-density SNP mapping showed that the region of association spans approximately 60 kb of the PLXNA2 gene. Eight out of 14 SNPs genotyped showed statistically significant differences between cases and controls. These results are in accordance with previous genetic findings that identified chromosome 1q32 as a candidate region for schizophrenia. PLXNA2 is a member of the transmembrane semaphorin receptor family that is involved in axonal guidance during development and may modulate neuronal plasticity and regeneration. The PLXNA2 ligand semaphorin 3A has been shown to be upregulated in the cerebellum of individuals with schizophrenia. These observations, together with the genetic results, make PLXNA2 a likely candidate for the 1q32 schizophrenia susceptibility locus.