Statistics to prioritize rare variants in family-based sequencing studies with disease subtypes.

Family-based sequencing studies are increasingly used to find rare genetic variants of high risk for disease traits with familial clustering. In some studies, families with multiple disease subtypes are collected and the exomes of affected relatives are sequenced for shared rare variants (RVs). Since different families can harbor different causal variants and each family harbors many RVs, tests to detect causal variants can have low power in this study design. Our goal is rather to prioritize shared variants for further investigation by, for example, pathway analyses or functional studies. The transmission-disequilibrium test prioritizes variants based on departures from Mendelian transmission in parent-child trios. Extending this idea to families, we propose methods to prioritize RVs shared in affected relatives with two disease subtypes, with one subtype more heritable than the other. Global approaches condition on a variant being observed in the study and assume a known probability of carrying a causal variant. In contrast, local approaches condition on a variant being observed in specific families to eliminate the carrier probability. Our simulation results indicate that global approaches are robust to misspecification of the carrier probability and prioritize more effectively than local approaches even when the carrier probability is misspecified.

Efficient inference of parent-of-origin effect using case-control mother-child genotype data.

Parent-of-origin effect plays an important role in mammal development and disorder. Case-control mother-child pair genotype data can be used to detect parent-of-origin effect and is often convenient to collect in practice. Most existing methods for assessing parent-of-origin effect do not incorporate any covariates, which may be required to control for confounding factors. We propose to model the parent-of-origin effect through a logistic regression model, with predictors including maternal and child genotypes, parental origins, and covariates. The parental origins may not be fully inferred from genotypes of a target genetic marker, so we propose to use genotypes of markers tightly linked to the target marker to increase inference efficiency. A robust statistical inference procedure is developed based on a modified profile log-likelihood in a retrospective way. A computationally feasible expectation-maximization algorithm is devised to estimate all unknown parameters involved in the modified profile log-likelihood. This algorithm differs from the conventional expectation-maximization algorithm in the sense that it is based on a modified instead of the original profile log-likelihood function. The convergence of the algorithm is established under some mild regularity conditions. This expectation-maximization algorithm also allows convenient handling of missing child genotypes. Large sample properties, including weak consistency, asymptotic normality, and asymptotic efficiency, are established for the proposed estimator under some mild regularity conditions. Finite sample properties are evaluated through extensive simulation studies and the application to a real dataset.

Heterogeneity in the longitudinal courses of global functioning in children at familial risk of major psychiatric disorders: Association with trauma and familial characteristics.

OBJECTIVES: The extent to which heterogeneity in childhood risk trajectories may underlie later heterogeneity in schizophrenia (SZ), bipolar disorder (BP), and major depressive disorder (MDD) remains a chief question. Answers may optimally be found by studying the longitudinal trajectories of children born to an affected parent. We aimed to differentiate trajectories of global functioning and their sensitive periods from the age of 6 to 17 years in children at familial risk (FHRs). METHODS: First, a latent class mixed model analysis (LCMM) was applied to yearly ratings of the Children's Global Assessment Scale (CGAS) from the age of 6 to 17 years in 170 FHRs born to a parent affected by DSM-IV SZ (N = 37), BP (N = 82) or MDD (N = 51). Then, we compared the obtained Classes or trajectories of FHRs in terms of sex, parental diagnosis, IQ, child clinical status, childhood trauma, polygenic risk score (PRS), and outcome in transition to illness. RESULTS: The LCMM on yearly CGAS trajectories identified a 4-class solution showing markedly different childhood and adolescence dynamic courses and temporal vulnerability windows marked by a functioning decline and a degree of specificity in parental diagnosis. Moreover, IQ, trauma exposure, PRS level, and timing of later transition to illness differentiated the trajectories. Almost half (46%) of the FHRs exhibited a good and stable global functioning trajectory. CONCLUSIONS: FHRs of major psychiatric disorders show heterogeneous functional decline during development associated with parental diagnosis, polygenic risk loading, and childhood trauma.

A novel rare variants association test for binary traits in family-based designs via copulas.

With the cost-effectiveness technology in whole-genome sequencing, more sophisticated statistical methods for testing genetic association with both rare and common variants are being investigated to identify the genetic variation between individuals. Several methods which group variants, also called gene-based approaches, are developed. For instance, advanced extensions of the sequence kernel association test, which is a widely used variant-set test, have been proposed for unrelated samples and extended for family data. Family data have been shown to be powerful when analyzing rare variants. However, most of such methods capture familial relatedness using a random effect component within the generalized linear mixed model framework. Therefore, there is a need to develop unified and flexible methods to study the association between a set of genetic variants and a trait, especially for a binary outcome. Copulas are multivariate distribution functions with uniform margins on the [0,1] interval and they provide suitable models to capture familial dependence structure. In this work, we propose a flexible family-based association test for both rare and common variants in the presence of binary traits. The method, termed novel rare variant association test (NRVAT), uses a marginal logistic model and a Gaussian Copula. The latter is employed to model the dependence between relatives. An analytic score-type test is derived. Through simulations, we show that our method can achieve greater power than existing approaches. The proposed model is applied to investigate the association between schizophrenia and bipolar disorder in a family-based cohort consisting of 17 extended families from Eastern Quebec.

Multivariate extension of penalized regression on summary statistics to construct polygenic risk scores for correlated traits.

Genetic correlations between human traits and disorders such as schizophrenia (SZ) and bipolar disorder (BD) diagnoses are well established. Improved prediction of individual traits has been obtained by combining predictors of multiple genetically correlated traits derived from summary statistics produced by genome-wide association studies, compared with single trait predictors. We extend this idea to penalized regression on summary statistics in Multivariate Lassosum, expressing regression coefficients for the multiple traits on single nucleotide polymorphisms (SNPs) as correlated random effects, similarly to multi-trait summary statistic best linear unbiased predictors (MT-SBLUPs). We also allow the SNP contributions to genetic covariance and heritability to depend on genomic annotations. We conducted simulations with two dichotomous traits having polygenic architecture similar to SZ and BD, using genotypes from 29,330 subjects from the CARTaGENE cohort. Multivariate Lassosum produced polygenic risk scores (PRSs) more strongly correlated with the true genetic risk predictor and had better discrimination power between affected and non-affected subjects than previously published sparse multi-trait (PANPRS) and univariate (Lassosum, sparse LDpred2, and the standard clumping and thresholding) methods in most simulation settings. Application of Multivariate Lassosum to predict SZ, BD, and related psychiatric traits in the Eastern Quebec SZ and BD kindred study revealed associations with every trait stronger than those obtained with univariate sparse PRSs, particularly when heritability and genetic covariance depended on genomic annotations. Multivariate Lassosum thus appears promising to improve prediction of genetically correlated traits with summary statistics for a selected subset of SNPs.

Methods and Software to Analyze Gene-Environment Interactions under a Case-Mother-Control-Mother Design with Partially Missing Child Genotype.

INTRODUCTION: The case-mother-control-mother design allows to study fetal and maternal genetic factors together with environmental exposures on early life outcomes. Mendelian constraints and conditional independence between child genotype and environmental factors enabled semiparametric likelihood methods to estimate logistic models with greater efficiency than standard logistic regression. Difficulties in child genotype collection require methods handling missing child genotype. METHODS: We review a stratified retrospective likelihood and two semiparametric likelihood approaches: a prospective one and a modified retrospective one, the latter either modeling the maternal genotype as a function of covariates or leaving their joint distribution unspecified (robust version). We also review software implementing these modeling alternatives, compare their statistical properties in a simulation study, and illustrate their application, focusing on gene-environment interactions and partially missing child genotype. RESULTS: The robust retrospective likelihood provides generally unbiased estimates, with standard errors only slightly larger than when modeling maternal genotype based on exposure. The prospective likelihood encounters maximization problems. In the application to the association of small-for-gestational-age babies with CYP2E1 and drinking water disinfection by-products, the retrospective likelihood allowed a full array of covariates, while the prospective likelihood was limited to few covariates. CONCLUSION: We recommend the robust version of the modified retrospective likelihood.

Molecular test of Paget's disease of bone in families not linked to SQSTM1 gene mutations.

Purpose: Paget's disease of bone (PDB) is a focal metabolic bone disorder characterized by an increased bone remodeling. Fifteen to 40 % of PDB patients have a familial form with an autosomal dominant inheritance. Disease-causing mutations of the SQSTM1 gene have been linked to PDB in about 40 % of families whereas genes linked to the remaining families are unknown. Several single nucleotide polymorphisms (SNPs) have been associated with PDB in unrelated patient non-carriers of a SQSTM1 mutation. The current clinical practice guidelines still recommend the measure of serum total alkaline phosphatase (sALP) for PDB screening. In unrelated individual non-carriers of SQSTM1 mutations, we previously developed a genetic test combining male sex with five genetic markers (rs499345, rs5742915, rs2458413, rs3018362, rs2234968), giving rise to an area under the curve (AUC) for PDB phenotype of 0.73 (0.69; 0.77). A combination of male sex with total calcium corrected for albumin and Procollagen type I N-terminal propeptide (P1NP), had an AUC of 0.82 (0.73; 0.92). Combining both genetic and biochemical tests increased the AUC to 0.89 (0.83; 0.95). Objective: This study aimed at estimating the performance of our previous test of PDB, in families not linked to SQSTM1 mutations with disease-causing genes yet unknown, and at developing a new algorithm if the performance is not satisfactory. Methods: We genotyped the five SNPs cited above, and measured calcium corrected for albumin and P1NP in 181 relatives, with PDB or not, from 19 PDB families not linked to SQSTM1 mutations. Bivariate and multivariate logistic regression models including male sex were fitted to search for a molecular test that could best detect PDB in these families. A receiving operating characteristics analysis was done to establish a cut-off point for continuous variables. Results: Logistic regression estimates of our previous molecular test gave rise to a high sensitivity of 78 %, 97 % and 88 % for the genetic, biochemical, and combined test but the specificity was very low, 35 %, 11 % and 21 %, respectively. This poor specificity persisted even when the cut-off point was changed. We then generated in these families, new logistic regression estimates but on the same parameters as mentioned above, giving rise to an AUC of 0.65 (0.55; 0.75) for the genetic test, of 0.84 (0.74; 0.94) for the biochemical test, and 0.89 (0.82; 0.96) for the combination test, the latter having a sensitivity of 96 % and specificity of 57 %. By comparison serum P1NP alone gave rise to an AUC of 0.84 (0.73; 0.94), with a sensitivity of 71 % and a specificity of 79 %. Conclusion: In PDB families not linked to SQSTM1 mutations, the estimates of our previous molecular test gave rise to a poor specificity. Using new estimates, the biochemical and combined tests have similar predictive abilities than our former test. Serum P1NP is a bone marker of interest for the screening for PDB in families not linked to SQSTM1 mutations.

Time trends in social contacts before and during the COVID-19 pandemic: the CONNECT study.

BACKGROUND: Since the beginning of the COVID-19 pandemic, many countries, including Canada, have adopted unprecedented physical distancing measures such as closure of schools and non-essential businesses, and restrictions on gatherings and household visits. We described time trends in social contacts for the pre-pandemic and pandemic periods in Quebec, Canada. METHODS: CONNECT is a population-based study of social contacts conducted shortly before (2018/2019) and during the COVID-19 pandemic (April 2020 - February 2021), using the same methodology for both periods. We recruited participants by random digit dialing and collected data by self-administered web-based questionnaires. Questionnaires documented socio-demographic characteristics and social contacts for two assigned days. A contact was defined as a two-way conversation at a distance ≤ 2 m or as a physical contact, irrespective of masking. We used weighted generalized linear models with a Poisson distribution and robust variance (taking possible overdispersion into account) to compare the mean number of social contacts over time and by socio-demographic characteristics. RESULTS: A total of 1291 and 5516 Quebecers completed the study before and during the pandemic, respectively. Contacts significantly decreased from a mean of 8 contacts/day prior to the pandemic to 3 contacts/day during the spring 2020 lockdown. Contacts remained lower than the pre-COVID period thereafter (lowest = 3 contacts/day during the Christmas 2020/2021 holidays, highest = 5 in September 2020). Contacts at work, during leisure activities/in other locations, and at home with visitors showed the greatest decreases since the beginning of the pandemic. All sociodemographic subgroups showed significant decreases of contacts since the beginning of the pandemic. The mixing matrices illustrated the impact of public health measures (e.g. school closure, gathering restrictions) with fewer contacts between children/teenagers and fewer contacts outside of the three main diagonals of contacts between same-age partners/siblings and between children and their parents. CONCLUSION: Physical distancing measures in Quebec significantly decreased social contacts, which most likely mitigated the spread of COVID-19.

Understanding Gene-Lifestyle Interaction in Obesity: The Role of Mediation versus Moderation.

BACKGROUND: Obesity results from complex interactions between genetic susceptibility to weight gain and poor eating and lifestyle behaviors. The approach that has been traditionally used in genetics to investigate gene-environment/lifestyle interaction in obesity is based on the concept of moderation or effect modification. Another approach called mediation analysis can be used to investigate gene-environment interaction in obesity. The objective of this review article is to explain the differences between the concepts of moderation and mediation and summarize the studies that have used mediation analysis to support the role of eating or lifestyle behaviors as putative mediators of genetic susceptibility to obesity. SUMMARY: Moderation is used to determine whether the effect of an exposure (genes associated with obesity) on an outcome (obesity phenotype) differs in magnitude and/or direction across the spectrum of environmental exposure. Mediation analysis is used to assess the extent to which the effect of the exposure on the outcome is explained by a given set of hypothesized mediators with the aim of understanding how the exposure could lead to the outcome. In comparison with moderation, relatively few studies used mediation analyses to investigate gene-environment interaction in obesity. Most studies found evidence that traits related to appetite or eating behaviors partly mediated genetic susceptibility to obesity in either children or adults. KEY MESSAGES: Moderation and mediation represent two complementary approaches to investigate gene-environment interaction in obesity and address different research questions pertaining to the cause-effect relationship between genetic susceptibility to obesity and various obesity outcomes. More studies relying on mediation are needed to better understand the role of eating and lifestyle habits in mediating genetic susceptibility to obesity.

Cis-regulatory hubs: a new 3D model of complex disease genetics with an application to schizophrenia.

The 3D conformation of the chromatin creates complex networks of noncoding regulatory regions (distal elements) and promoters impacting gene regulation. Despite the importance of the role of noncoding regions in complex diseases, little is known about their interplay within regulatory hubs and implication in multigenic diseases such as schizophrenia. Here we show that cis-regulatory hubs (CRHs) in neurons highlight functional interactions between distal elements and promoters, providing a model to explain epigenetic mechanisms involved in complex diseases. CRHs represent a new 3D model, where distal elements interact to create a complex network of active genes. In a disease context, CRHs highlighted strong enrichments in schizophrenia-associated genes, schizophrenia-associated SNPs, and schizophrenia heritability compared with equivalent structures. Finally, CRHs exhibit larger proportions of genes differentially expressed in schizophrenia compared with promoter-distal element pairs or TADs. CRHs thus capture causal regulatory processes improving the understanding of complex disease etiology such as schizophrenia. These multiple lines of genetic and statistical evidence support CRHs as 3D models to study dysregulation of gene expression in complex diseases more generally.

Childhood Trauma May Increase Risk of Psychosis and Mood Disorder in Genetically High-risk Children and Adolescents by Enhancing the Accumulation of Risk Indicators.

Background: Genetically high-risk children carry indicators of brain dysfunctions that adult patients with schizophrenia or bipolar disorder display. The accumulation of risk indicators would have a higher predictive value of a later transition to psychosis or mood disorder than each individual risk indicator. Since more than 50% of adult patients report having been exposed to childhood trauma, we investigated whether exposure to trauma during childhood was associated with the early accumulation of risk indicators in youths at genetic risk. Methods: We first inspected the characteristics of childhood trauma in 200 young offspring (51% male) born to a parent affected by DSM-IV schizophrenia, bipolar disorder, or major depressive disorder. A subsample of 109 offspring (51% male) had measurements on four risk indicators: cognitive impairments, psychotic-like experiences, nonpsychotic nonmood childhood DSM diagnoses, poor global functioning. Trauma was assessed from direct interviews and reviews of lifetime medical and school records of offspring. Results: Trauma was present in 86 of the 200 offspring (43%). The relative risk of accumulating risk indicators in offspring exposed to trauma was 3.33 (95% CI 1.50, 7.36), but more pronounced in males (RR = 4.64, 95% CI 1.71, 12.6) than females (RR = 2.01, 95% CI 0.54, 7.58). Conclusion: Childhood trauma would be related to the accumulation of developmental precursors of major psychiatric disorders and more so in young boys at high genetic risk. Our findings may provide leads for interventions targeting the early mechanisms underlying the established relation between childhood trauma and adult psychiatric disorders.

Exploring polypharmacy with artificial intelligence: data analysis protocol.

BACKGROUND: Polypharmacy is common among older adults and it represents a public health concern, due to the negative health impacts potentially associated with the use of several medications. However, the large number of medication combinations and sequences of use makes it complicated for traditional statistical methods to predict which therapy is genuinely associated with health outcomes. The project aims to use artificial intelligence (AI) to determine the quality of polypharmacy among older adults with chronic diseases in the province of Québec, Canada. METHODS: We will use data from the Quebec Integrated Chronic Disease Surveillance System (QICDSS). QICDSS contains information about prescribed medications in older adults in Quebec collected over 20 years. It also includes diagnostic codes and procedures, and sociodemographic data linked through a unique identification number for each individual. Our research will be structured around three interconnected research axes: AI, Health, and Law&Ethics. The AI research axis will develop algorithms for finding frequent patterns of medication use that correlate with health events, considering data locality and temporality (explainable AI or XAI). The Health research axis will translate these patterns into polypharmacy indicators relevant to public health surveillance and clinicians. The Law&Ethics axis will assess the social acceptability of the algorithms developed using AI tools and the indicators developed by the Heath axis and will ensure that the developed indicators neither discriminate against any population group nor increase the disparities already present in the use of medications. DISCUSSION: The multi-disciplinary research team consists of specialists in AI, health data, statistics, pharmacy, public health, law, and ethics, which will allow investigation of polypharmacy from different points of view and will contribute to a deeper understanding of the clinical, social, and ethical issues surrounding polypharmacy and its surveillance, as well as the use of AI for health record data. The project results will be disseminated to the scientific community, healthcare professionals, and public health decision-makers in peer-reviewed publications, scientific meetings, and reports. The diffusion of the results will ensure the confidentiality of individual data.

A multimodal attempt to follow-up linkage regions using RNA expression, SNPs and CpG methylation in schizophrenia and bipolar disorder kindreds.

The complexity of schizophrenia (SZ) and bipolar disorder (BD) has slowed down progress in understanding their genetic roots. Alternative genomic approaches are needed to bypass these difficulties. We attempted a multimodal approach to follow-up on reported linkage findings in SZ and BD from the Eastern Quebec kindreds in chromosomes 3q21, 4p34, 6p22, 8p21, 8p11, 13q11-q14, 15q13, 16p12, and 18q21. First, in 498 subjects, we measured RNA expression (47 K Illumina chips) in SZ and BD patients that we compared with their non-affected relatives (NARs) to identify, for each chromosomal region, genes showing the most significant differences in expression. Second, we performed SNP genotyping (700 K Illumina chips) and cis-eQTN analysis. Third, we measured DNA methylation on genes with RNA expression differences or eQTNs. We found a significant overexpression of the gene ITGB5 at 3q25 in SZ and BD after multiple testing p value adjustment. SPCS3 gene at 4q34, and FZD3 gene at 8p21, contained significant eQTNs after multiple testing corrections, while ITGB5 provided suggestive results. Methylation in associated genes did not explain the expression differences between patients and NARs. Our multimodal approach involving RNA expression, dense SNP genotyping and eQTN analyses, restricted to chromosomal regions having shown linkage, lowered the multiple testing burden and allowed for a deeper examination of candidate genes in SZ or BD.

Exposure to polychlorinated biphenyls and organochlorine pesticides and risk of dementia, Alzheimer's disease and cognitive decline in an older population: a prospective analysis from the Canadian Study of Health and Aging.

BACKGROUND: Little attention has been paid to neurotoxicants on the risk of dementia. Exposure to known neurotoxicants such as polychlorinated biphenyls (PCBs) and organochlorine (OC) pesticides is suspected to have adverse cognitive effects in older populations. OBJECTIVE: To assess whether plasma concentrations of PCBs and OC pesticides are associated with the risk of cognitive decline, Alzheimer's disease (AD) and of all-cause dementia in the Canadian older population. METHODS: Analyses were based on data from the Canadian Study of Health and Aging, a 3-phase, 10-year population-based study of individuals aged 65+ years. Analyses included 669 clinically assessed subjects, of which 156 developed dementia including 108 incident cases of AD. Subjects were screened at each phase with the 100-point Modified Mini-Mental State Examination (3MS), a measurement of global cognitive function. Statistical analyses included Cox proportional hazards model when the outcome was dementia or AD, and a repeated-measure mixed model when the outcome was the 3MS score. RESULTS: No association of PCB and OC pesticides with the risk of dementia and AD was observed. Elevated concentrations of PCB congeners nos 118, 153, 156, 163, and OC pesticides 1,1,1-trichloro-2,2-bis(p-chlorophenyl)ethane (p,p'-DDT) and its metabolite 1,1-dichloro-2,2-bis(p-chlorophenyl)ethylene (p,p'-DDE) were significantly associated with cognitive decline as assessed with the 3MS. A posteriori analyses suggested that only p,p'-DDE was significantly related to a higher cognitive decline in time based on the 3MS among incident cases of dementia compared to subjects remaining nondemented. CONCLUSION: PCB and OC pesticide plasma concentrations were not related to the incident diagnosis of neither dementia, nor AD. Using the 3MS scores as the outcome, higher concentrations of four PCB congeners and two OC pesticides were associated with lower cognitive performances in subjects. The association of p,p'-DDE with cognitive decline in time in incident cases of dementia merits further investigation.

Adverse events following immunisation with four-component meningococcal serogroup B vaccine (4CMenB): interaction with co-administration of routine infant vaccines and risk of recurrence in European randomised controlled trials.

OBJECTIVES: (1) To assess if co-administration of four-component meningococcal serogroup B vaccine (4CMenB) and other routine vaccines caused an interaction increasing the risk and/or severity of adverse events following immunisation (AEFI) compared with administration at separate visits and (2) to estimate the risk of AEFI recurrence. DESIGN: Risk-interval design SETTING: Three randomised controlled trials conducted in Europe. PARTICIPANTS: A total of 5026 healthy 2-month-old to 15-month-old infants. INTERVENTIONS: 4CMenB and routine vaccines (hexavalent combined diphtheria-tetanus-acellular pertussis-inactivated polio-Haemophilus influenzae type b-hepatitis B vaccine+seven-valent pneumococcal conjugate vaccine or measles-mumps-rubella-varicella vaccine) administered concomitantly or separately 1 month apart, in regular (2, 4, 6 and 12 months), accelerated (2, 3, 4 and 12 months) or delayed (two doses of 4CMenB at ≥12 months of age) schedules. OUTCOME MEASURES: Primary: Fever (≥38°C) during the first 48 hours post immunisation. Secondary: crying, change in eating habits, diarrhoea, irritability and tenderness at the 4CMenB injection site. RESULTS: Compared with separate administration, concomitant administration decreased the overall incidence of fever (≥38°C), 86% versus 75%, and other systemic AEFIs but increased the incidence of 4CMenB injection site tenderness, 55% versus 66%, moderate/severe fevers (≥39°C), 13% versus 18%, and long-lasting (>1 day) fevers, 23% versus 33%. Co-administration reduced AEFI risk by 4%-49% with the greatest impact among infants with prior AEFI(s). Fever recurrence risk was proportional to the number of prior fever events: 79% at dose 2 with one prior episode; 44% and 74% at dose 3 with one and two prior episodes, respectively; and 29%, 45% and 60% at dose 4 with one, two and three prior episodes, respectively. Severity was not increased at recurrence and a similar pattern of recurrence risk proportional to the number of prior events was observed for other AEFIs. CONCLUSIONS: The cumulative risk of AEFI is reduced with concomitant versus separate administration of 4CMenB and routine infant vaccines. Infants with a prior AEFI are at higher risk of the same AEFI at subsequent immunisations, but severity with recurrence is usually not increased. TRIALS REGISTRATION NUMBER: NCT00657709, NCT00847145, NCT00721396 and NCT02712177; Pre-results.

Detection of rare disease variants in extended pedigrees using RVS.

SUMMARY: Family-based sequencing studies enable researchers to identify highly penetrant genetic variants too rare to be tested in conventional case-control studies, by studying co-segregation of variant and disease phenotypes. When multiple affected subjects in a family are sequenced, the probability that a variant or a set of variants is shared identical-by-descent by some or all affected relatives provides evidence against the null hypothesis of complete absence of linkage and association. The Rare Variant Sharing software package RVS implements a suite of tools to assess association and linkage between rare genetic variants and a dichotomous disease indicator in family pedigrees. AVAILABILITY AND IMPLEMENTATION: RVS is available as open source software from the Bioconductor webpage at https://bioconductor.org/packages/release/bioc/html/RVS.html. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Inferring disease risk genes from sequencing data in multiplex pedigrees through sharing of rare variants.

We previously demonstrated how sharing of rare variants (RVs) in distant affected relatives can be used to identify variants causing a complex and heterogeneous disease. This approach tested whether single RVs were shared by all sequenced affected family members. However, as with other study designs, joint analysis of several RVs (e.g., within genes) is sometimes required to obtain sufficient statistical power. Further, phenocopies can lead to false negatives for some causal RVs if complete sharing among affected is required. Here, we extend our methodology (Rare Variant Sharing, RVS) to address these issues. Specifically, we introduce gene-based analyses, a partial sharing test based on RV sharing probabilities for subsets of affected relatives and a haplotype-based RV definition. RVS also has the desirable feature of not requiring external estimates of variant frequency or control samples, provides functionality to assess and address violations of key assumptions, and is available as open source software for genome-wide analysis. Simulations including phenocopies, based on the families of an oral cleft study, revealed the partial and complete sharing versions of RVS achieved similar statistical power compared with alternative methods (RareIBD and the Gene-Based Segregation Test), and had superior power compared with the pedigree Variant Annotation, Analysis, and Search Tool (pVAAST) linkage statistic. In studies of multiplex cleft families, analysis of rare single nucleotide variants in the exome of 151 affected relatives from 54 families revealed no significant excess sharing in any one gene, but highlighted different patterns of sharing revealed by the complete and partial sharing tests.

Referential Choices in a Collaborative Storytelling Task: Discourse Stages and Referential Complexity Matter.

During a narrative discourse, accessibility of the referents is rarely fixed once and for all. Rather, each referent varies in accessibility as the discourse unfolds, depending on the presence and prominence of the other referents. This leads the speaker to use various referential expressions to refer to the main protagonists of the story at different moments in the narrative. This study relies on a new, collaborative storytelling in sequence task designed to assess how speakers adjust their referential choices when they refer to different characters at specific discourse stages corresponding to the introduction, maintaining, or shift of the character in focus, in increasingly complex referential contexts. Referential complexity of the stories was manipulated through variations in the number of characters (1 vs. 2) and, for stories in which there were two characters, in their ambiguity in gender (different vs. same gender). Data were coded for the type of reference markers as well as the type of reference content (i.e., the extent of the information provided in the referential expression). Results showed that, beyond the expected effects of discourse stages on reference markers (more indefinite markers at the introduction stage, more pronouns at the maintaining stage, and more definite markers at the shift stage), the number of characters and their ambiguity in gender also modulated speakers' referential choices at specific discourse stages, For the maintaining stage, an effect of the number of characters was observed for the use of pronouns and of definite markers, with more pronouns when there was a single character, sometimes replaced by definite expressions when two characters were present in the story. For the shift stage, an effect of gender ambiguity was specifically noted for the reference content with more specific information provided in the referential expression when there was referential ambiguity. Reference content is an aspect of referential marking that is rarely addressed in a narrative context, yet it revealed a quite flexible referential behavior by the speakers.

Polygenic risk scores distinguish patients from non-affected adult relatives and from normal controls in schizophrenia and bipolar disorder multi-affected kindreds.

Recent studies have used results on SNP association with schizophrenia (SZ) and bipolar disorder (BD) to create polygenic risk scores (PRS) discriminating non-familial unrelated patients from controls. Little is known about the role of PRS in densely affected multigenerational families. We tested PRS differences between affected SZ and BD family members from their non-affected adult relatives (NAARs) in Eastern Quebec Kindreds and from controls. We examined 1227 subjects: from 17 SZ and BD kindreds, we studied 153 patients (57 SZ, 13 schizoaffective, and 83 BD) and 180 NAARs, and 894 unrelated controls from the Eastern Quebec population. PRS were derived from published case-control association studies of SZ and BD. We also constructed a combined SZ and BD PRS by using SNPs from both SZ and BD PRS. SZ patients had higher SZ PRS than controls (p = 0.0039, R2 = 0.027) and BD patients had higher BD PRS than controls (p = 0.013, R2 = 0.027). Differences between affected subjects and NAARs and controls were significant with both SZ and BD PRS. Moreover, a combined SZ-BD PRS was also significantly associated with SZ and BD when compared to NAARs (p = 0.0019, R2 = 0.010) and controls (p = 0.0025, R2 = 0.028), revealing a SZ-BD commonality effect in PRS at the diagnosis level. The SZ and the BD PRS, however, showed a degree of specificity regarding thought disorder symptoms. Overall, our report would confirm the usefulness of PRS in capturing the contribution of common genetic variants to the risk of SZ and BD in densely affected families.

Prenatal exposure to drinking-water chlorination by-products, cytochrome P450 gene polymorphisms and small-for-gestational-age neonates.

Genetic susceptibility may modulate chlorination by-products (CBPs) effects on fetal growth, especially genes coding for the cytochrome P450 involved in the metabolism of CBPs and steroidogenesis. In a case-control study of 1432 mother-child pairs, we assessed the association between maternal and child single nucleotide polymorphisms (SNPs) within CYP1A2, CYP2A6, CYP2D6 and CYP17A1 genes and small-for-gestational-age neonates (SGA<10th percentile) as well as interaction between these SNPs and maternal exposure to trihalomethanes or haloacetic acids (HAAs) during the third trimester of pregnancy. Interactions were found between mother and neonate carrying CYP17A1 rs4919687A and rs743572G alleles and maternal exposure to total trihalomethanes or five regulated HAAs species. However, these interactions became non statistically significant after correction for multiple testing. There is some evidence, albeit weak, of a potential effect modification of the association between CBPs and SGA by SNPs in CYP17A1 gene. Further studies are needed to validate these observations.