Jordie Croteau

Global gene expression profiling of the polyamine system in suicide completers

In recent years, gene expression, genetic association, and metabolic studies have implicated the polyamine system in psychiatric conditions, including suicide. Given the extensive regulation of genes involved in polyamine metabolism, as well as their interconnections with the metabolism of other amino acids, we were interested in further investigating the expression of polyamine-related genes across the brain in order to obtain a more comprehensive view of the dysregulation of this system in suicide. To this end, we examined the expression of genes related to polyamine metabolism across 22 brain regions in a sample of 29 mood-disordered suicide completers and 16 controls, and identified 14 genes displaying differential expression. Among these, altered expression of spermidine/spermine N1-acetyltransferase, spermine oxidase, and spermine synthase, has previously been observed in brains of suicide completers, while the remainder of the genes represent novel findings. In addition to genes with direct involvement in polyamine metabolism, including S-adenosylmethionine decarboxylase, ornithine decarboxylase antizymes 1 and 2, and arginase II, we identified altered expression of several more distally related genes, including aldehyde dehydrogenase 3 family, member A2, brain creatine kinase, mitochondrial creatine kinase 1, glycine amidinotransferase, glutamic-oxaloacetic transaminase 1, and arginyl-tRNA synthetase-like. Many of these genes displayed altered expression across several brain regions, strongly implying that dysregulated polyamine metabolism is a widespread phenomenon in the brains of suicide completers. This study provides a broader view of the nature and extent of the dysregulation of the polyamine system in suicide, and highlights the importance of this system in the neurobiology of suicide.

Association of Polyaminergic Loci With Anxiety, Mood Disorders, and Attempted Suicide

Background The polyamine system has been implicated in a number of psychiatric conditions, which display both alterations in polyamine levels and altered expression of genes related to polyamine metabolism. Studies have identified associations between genetic variants in spermidine/spermine N1-acetyltransferase (SAT1) and both anxiety and suicide, and several polymorphisms appear to play important roles in determining gene expression. Methodology/Principal Findings We genotyped 63 polymorphisms, spread across four polyaminergic genes (SAT1, spermine synthase (SMS), spermine oxidase (SMOX), and ornithine aminotransferase like-1 (OATL1)), in 1255 French-Canadian individuals who have been followed longitudinally for 22 years. We assessed univariate associations with anxiety, mood disorders, and attempted suicide, as assessed during early adulthood. We also investigated the involvement of gene-environment interactions in terms of childhood abuse, and assessed internalizing and externalizing symptoms as endophenotypes mediating these interactions. Overall, each gene was associated with at least one main outcome: anxiety (SAT1, SMS), mood disorders (SAT1, SMOX), and suicide attempts (SAT1, OATL1). Several SAT1 polymorphisms displayed disease-specific risk alleles, and polymorphisms in this gene were involved in gene-gene interactions with SMS to confer risk for anxiety disorders, as well as gene-environment interactions between childhood physical abuse and mood disorders. Externalizing behaviors demonstrated significant mediation with regards to the association between OATL1 and attempted suicide, however there was no evidence that externalizing or internalizing behaviors were appropriate endophenotypes to explain the associations with mood or anxiety disorders. Finally, childhood sexual abuse did not demonstrate mediating influences on any of our outcomes. Conclusions/Significance These results demonstrate that genetic variants in polyaminergic genes are associated with psychiatric conditions, each of which involves a set of separate and distinct risk alleles. As several of these polymorphisms are associated with gene expression, these findings may provide mechanisms to explain the alterations in polyamine metabolism which have been observed in psychiatric disorders.

An assessment of gene-by-environment interactions in developmental dyslexia-related phenotypes

While the genetic and environmental contributions to developmental dyslexia (DD) have been studied extensively, the effects of identified genetic risk susceptibility and of specified environmental hazardous factors have usually been investigated separately. We assessed potential gene-by-environment (GxE) interactions on DD-related reading, spelling and memory phenotypes. The presence of GxE effects were investigated for the DYX1C1, DCDC2, KIAA0319 and ROBO1 genes, and for seven specified environmental moderators in 165 nuclear families in which at least one member had DD, by implementing a general test for GxE interaction in sib-pair-based association analysis of quantitative traits. Our results support a diathesis-stress model for both reading and memory composites: GxE effects were found between some specified environmental moderators (i.e. maternal smoke during pregnancy, birth weight and socio-economic status) and the DYX1C1-1259C/G marker. We have provided initial evidence that the joint analysis of identified genetic risk susceptibility and measured putative risk factors can be exploited in the study of the etiology of DD and reading-related neuropsychological phenotypes, and may assist in identifying/preventing the occurrence of DD.

Breastfeeding initiation: impact of obesity in a large Canadian perinatal cohort study.

Objective To evaluate incidence of breastfeeding initiation according to maternal pre-pregnancy body mass index (BMI) in “Grossesse en Santé”, a large prospective birth cohort in Quebec City. Methods Breastfeeding initiation in the post-partum period, pre-pregnancy BMI, sociodemographic determinants and obstetrical and neonatal factors were collected from years 2005 to 2010 in 6592 women with single pregnancies. Prenatal non-intention to breastfeed was documented in a subgroup of the cohort (years 2009–2010). Log-binomial regression analyses were performed to assess relative risk (RR) of non-initiation of breastfeeding between maternal BMI categories in models including pre- and post-natal determinants, after exclusion of variables with a mediating effect. Results Twenty percent (20%) of obese women did not initiate breastfeeding in the post-natal period at hospital compared to 12% for normal weight women. Compared with those having a normal pre-pregnancy BMI, obese women had a higher risk of non-initiation of breastfeeding (RRunadj 1.69, 95% CI 1.44–1.98), even after adjustment for prenatal and sociodemographic factors (RRadj 1.26, 95% CI 1.08–1.46). Furthermore, the risk of non-initiation of breastfeeding in obese women still remained higher after introduction of per- and post-natal factors (RR 1.22, 95% CI 1.04–1.42). The prenatal non-intention to breastfeed was strongly associated with the non-initiation of breastfeeding for all categories of BMI. Conclusion Maternal obesity is associated with a two-fold rate of non-initiation of breastfeeding. Considering the benefits of breastfeeding and the increasing obesity rate, adapted interventions and specialized support should target both pre- and immediate post-natal periods in this population.

A Genome-Wide Copy Number Variant Study of Suicidal Behavior

Suicide and suicide attempts are complex behaviors that result from the interaction of different factors, including genetic variants that increase the predisposition to suicidal behaviors. Copy number variations (CNVs) are deletions or duplications of a segment of DNA usually larger than one kilobase. These structural genetic changes, although quite rare, have been associated with genetic liability to mental disorders, such as autism, schizophrenia, and bipolar disorder. No genome-wide level studies have been published investigating the potential role of CNVs in suicidal behaviors. Based on single-nucleotide polymorphism array data, we followed the Penn-CNV standards to detect CNVs in 1,608 subjects, comprising 475 suicide and suicide attempt cases and 1,133 controls. Although the initial algorithms determined the presence of CNVs on chromosomes 6 and 12 in seven and eight cases, respectively, compared with none of the controls, visual inspection of the raw data did not support this finding. Furthermore we were unable to validate these findings by CNV-specific real-time polymerase chain reaction. Additionally, rare CNV burden analysis did not find an association between the frequency or length of rare CNVs and suicidal behavior in our sample population. Although our findings suggest CNVs do not play an important role in the etiology of suicidal behaviors, they are not inconsistent with the strong evidence from the literature suggesting that other genetic variants account for a portion of the total phenotypic variability in suicidal behavior.

Using disease symptoms to improve detection of linkage under genetic heterogeneity

A major reason for the slow progress in identifying susceptibility genes for complex diseases may be that the clinical diagnoses used as phenotypes are genetically heterogeneous. This has led researchers to collect various phenotypes related to the diagnosis, such as detailed symptoms, in the hope that these measurements define more homogeneous disease sub‐types, influenced by a smaller number of genes that will thus be more easily detectable. Latent class analysis can be used to define disease sub‐types from multivariate symptoms under the assumption that the subjects are independent, an assumption that does not hold between members of the same family. We have recently developed a latent class model allowing dependence between the latent disease class status of relatives within nuclear families. In this paper, we propose approaches to use the resulting latent class probabilities in linkage analysis. We present results from a simulation study showing that the latent class approach can provide a substantial gain in power to detect disease genes over the standard heterogeneity approach of Smith and identity‐by‐descent sharing methods applied to the disease diagnosis. Taking into account familial dependence in the latent class model generally provides greater power than assuming independence. In an analysis of autism symptoms in families from the Autism Genetics Research Exchange, linkage signals obtained with latent class‐derived phenotypes were stronger than those obtained using the original autism spectrum disorder diagnosis. Genet. Epidemiol. 2008.

Neuropsychological Measures that Predict Progression from Mild Cognitive Impairment to Alzheimer's type dementia in Older Adults: a Systematic Review and Meta-Analysis

This study aimed to determine the extent to which cognitive measures can predict progression from mild cognitive impairment (MCI) to Alzheimer’s type dementia (AD), assess the predictive accuracy of different cognitive domain categories, and determine whether accuracy varies as a function of age and length of follow-up. We systematically reviewed and meta-analyzed data from longitudinal studies reporting sensitivity and specificity values for neuropsychological tests to identify individuals with MCI who will develop AD. We searched articles in Medline, Cochrane, EMBASE, PsycINFO, and the Web of Science. Methodological quality was assessed using the STARDem and QUADAS standards. Twenty-eight studies met the eligibility criteria (2365 participants) and reported predictive values from 61 neuropsychological tests with a 31-month mean follow-up. Values were pooled to provide combined accuracy for 14 cognitive domains. Many domains showed very good predictive accuracy with high sensitivity and specificity values (≥ 0.7). Verbal memory measures and many language tests yielded very high predictive accuracy. Other domains (e.g., executive functions, visual memory) showed better specificity than sensitivity. Predictive accuracy was highest when combining memory measures with a small set of other domains or when relying on broad cognitive batteries. Cognitive tests are excellent at predicting MCI individuals who will progress to dementia and should be a critical component of any toolkit intended to identify AD at the pre-dementia stage. Some tasks are remarkable as early indicators, whereas others might be used to suggest imminent progression.

Follow-up of a Major Psychosis Linkage Site in 13q13-q14 Reveals Significant Association in Both Case-Control and Family Samples

BACKGROUND We previously reported a genome-wide significant linkage for major psychosis in chromosome 13q13-q14. METHODS An association analysis was conducted in 247 unrelated DSM-IV schizophrenia (SZ) patients and 250 unrelated control subjects from the Eastern Quebec population genotyped with 2150 single nucleotide polymorphisms in 13q13-q14. We also used the kindred sample where linkage was detected (125 SZ, 120 bipolar disorder [BD] and 36 schizoaffective disorder patients vs. 467 unaffected adult relatives) for replication. RESULTS An association of the T allele of rs1156026 found in the case-control sample (odds ratio [OR] = 1.81, p = 4 × 10(-6), false discovery rate = .01) was replicated in the kindred sample (OR = 1.54, p = .01), strengthening the overall association evidence (p = 8 × 10(-7)). The effect size increased in the subset of unrelated patients with a family history (OR = 2.28) and in the 15 families where SZ was predominant (OR = 2.03). In the kindred sample, onset of either SZ or BD was, on average, 5 years earlier for T/T compared with C/C homozygotes, leading to stronger association in patients with onset before 26 years of age (SZ: OR = 2.40, p = 1.3 × 10(-4); SZ, BD, and schizoaffective disorder combined: OR = 1.87, p = 8 × 10(-5)). CONCLUSIONS Case-control and family-based association provided evidence of a locus at 13q13-q14 related to SZ. The proximity of the associated single nucleotide polymorphism with the linkage signal and the extension of the associated phenotype to major psychosis with younger age of onset indicate congruence between the linkage and association signals. The rs1156026 association is novel and factors explaining its nondetection in previous studies are discussed.

Latent class model with familial dependence to address heterogeneity in complex diseases: adapting the approach to family-based association studies

Clinical diagnoses of complex diseases may often encompass multiple genetically heterogeneous disorders. One way of dissecting this heterogeneity is to apply latent class (LC) analysis to measurements related to the diagnosis, such as detailed symptoms, to define more homogeneous disease sub‐types, influenced by a smaller number of genes that will thus be more easily detectable. We have previously developed a LC model allowing dependence between the latent disease class status of relatives within families. We have also proposed a strategy to incorporate the posterior probability of class membership of each subject in parametric linkage analysis, which is not directly transferable to genetic association methods. Under the framework of family‐based association tests (FBAT), we now propose to make the contribution of an affected subject to the FBAT statistic proportional to his or her posterior class membership probability. Simulations showed a modest but robust power advantage compared to simply assigning each subject to his or her most probable class, and important power gains over the analysis of the disease diagnosis without LC modeling under certain scenarios. The use of LC analysis with FBAT is illustrated using autism spectrum disorder (ASD) symptoms on families from the Autism Genetics Research Exchange, where we examined eight regions previously associated to autism in this sample. The analysis using the posterior probability of membership to an LC detected an association in the JARID2 gene as significant as that for ASD (P = 3 × 10−5) but with a larger effect size (odds ratio = 2.17 vs. 1.55). Genet. Epidemiol. 35:182‐189, 2011.   © 2011 Wiley‐Liss, Inc.

Physical activity during pregnancy and infant’s birth weight: results from the 3D Birth Cohort

Aim To evaluate the association between maternal physical activity and infant’s birth weight or risk of inappropriate weight for gestational age (GA), and whether this association differs by infant’s sex, maternal body mass index (BMI) or pregnancy complications in a prospective cohort study. Methods 1913 pregnant women from the 3D Birth Cohort (Québec, Canada) completed the Pregnancy Physical Activity Questionnaire at each trimester. Energy expenditure (metabolic equivalent of task (MET)*hours/week) for total activity, sports and exercise and vigorous intensity activities was calculated. The associations with birth weight and risk of inappropriate weight for GA were evaluated by regression modelling. Interactions were tested with infant’s sex, maternal prepregnancy BMI, gestational diabetes, hypertensive disorders and prematurity. Results Each 1 MET/hours/week increase in sports and exercise in the first trimester was associated with a 2.5 g reduction in infant’s birth weight (95% CI −4.8 to −0.3) but was not associated with the risk of small weight for GA. In contrast, although not significant, a 17% reduction in the risk of large weight for GA was observed with increasing sports and exercise. Furthermore, in women with subsequent pre-eclampsia (but not normotensive or hypertensive women), each 1 MET/hours/week increment spent in any vigorous exercise in the first trimester reduced the infant’s birth weight by 19.8 g (95% CI −35.2 to −4.3). Conclusions Pregnant women with higher sports and exercise levels in the first trimester delivered infants with a lower birth weight. The risk of reducing infant’s birth weight with vigorous exercise in women who develop pre-eclampsia later in pregnancy requires evaluation.