Managing Polyploidy in Ex Situ Conservation Genetics: The Case of the Critically Endangered Adriatic Sturgeon (Acipenser naccarii)

While the current expansion of conservation genetics enables to address more efficiently the management of threatened species, alternative methods for genetic relatedness data analysis in polyploid species are necessary. Within this framework, we present a standardized and simple protocol specifically designed for polyploid species that can facilitate management of genetic diversity, as exemplified by the ex situ conservation program for the tetraploid Adriatic sturgeon Acipenser naccarii. A critically endangered endemic species of the Adriatic Sea tributaries, its persistence is strictly linked to the ex situ conservation of a single captive broodstock currently decimated to about 25 individuals, which represents the last remaining population of Adriatic sturgeon of certain wild origin. The genetic variability of three F1 broodstocks available as future breeders was estimated based on mitochondrial and microsatellite information and compared with the variability of the parental generation. Genetic data showed that the F1 stocks have only retained part of the genetic variation present in the original stock due to the few parent pairs used as founders. This prompts for the urgent improvement of the current F1 stocks by incorporating new founders that better represent the genetic diversity available. Following parental allocation based on band sharing values, we set up a user-friendly tool for selection of candidate breeders according to relatedness between all possible parent-pairs that secures the use of non-related individuals. The approach developed here could also be applied to other endangered tetraploid sturgeon species overexploited for caviar production, particularly in regions lacking proper infrastructure and/or expertise

Pre-attentive processing in children with early and continuously-treated PKU. Effects of concurrent Phe level and lifetime dietary control

Sixty-four children, aged 7 to 14 years, with early-treated PKU, were compared with control children on visual evoked potential (VEP) amplitudes and latencies and auditory mismatch negativity (MMN) amplitudes. It was further investigated whether indices of dietary control would be associated with these evoked potentials parameters. There were no significant differences between controls and children with PKU in VEP- and MMN-indices. However, higher lifetime Phe levels were, in varying degree and stronger than concurrent Phe level, related to increased N75 amplitudes, suggesting abnormalities in attention, and longer P110 latencies, indicating a reduction in speed of neural processing, possibly due to deficits in myelination or reduced dopamine levels in brain and retina. Similarly, higher lifetime Phe levels and Index of Dietary Control (IDC) were associated with decreased MMN amplitudes, suggesting a reduced ability to respond to stimulus change and poorer triggering of the frontally mediated attention switch. In summary, the present study in children with PKU investigated bottom-up information processing, i.e., triggered by external events, a fundamental prerequisite for the individual’s responsiveness to the outside world. Results provide evidence that quality of dietary control may affect the optimal development of these pre-attentive processes, and suggest the existence of windows of vulnerability to Phe exposure

Using rare genetic mutations to revisit structural brain asymmetry

Asymmetry between the left and right hemisphere is a key feature of brain organization. Hemispheric functional specialization underlies some of the most advanced human-defining cognitive operations, such as articulated language, perspective taking, or rapid detection of facial cues. Yet, genetic investigations into brain asymmetry have mostly relied on common variants, which typically exert small effects on brain-related phenotypes. Here, we leverage rare genomic deletions and duplications to study how genetic alterations reverberate in human brain and behavior. We designed a pattern-learning approach to dissect the impact of eight high-effect-size copy number variations (CNVs) on brain asymmetry in a multi-site cohort of 552 CNV carriers and 290 non-carriers. Isolated multivariate brain asymmetry patterns spotlighted regions typically thought to subserve lateralized functions, including language, hearing, as well as visual, face and word recognition. Planum temporale asymmetry emerged as especially susceptible to deletions and duplications of specific gene sets. Targeted analysis of common variants through genome-wide association study (GWAS) consolidated partly diverging genetic influences on the right versus left planum temporale structure. In conclusion, our gene-brain-behavior data fusion highlights the consequences of genetically controlled brain lateralization on uniquely human cognitive capacities

Effects of eight neuropsychiatric copy number variants on human brain structure

peer reviewedMany copy number variants (CNVs) confer risk for the same range of neurodevelopmental symptoms and psychiatric conditions including autism and schizophrenia. Yet, to date neuroimaging studies have typically been carried out one mutation at a time, showing that CNVs have large effects on brain anatomy. Here, we aimed to characterize and quantify the distinct brain morphometry effects and latent dimensions across 8 neuropsychiatric CNVs. We analyzed T1-weighted MRI data from clinically and non-clinically ascertained CNV carriers (deletion/duplication) at the 1q21.1 (n = 39/28), 16p11.2 (n = 87/78), 22q11.2 (n = 75/30), and 15q11.2 (n = 72/76) loci as well as 1296 non-carriers (controls). Case-control contrasts of all examined genomic loci demonstrated effects on brain anatomy, with deletions and duplications showing mirror effects at the global and regional levels. Although CNVs mainly showed distinct brain patterns, principal component analysis (PCA) loaded subsets of CNVs on two latent brain dimensions, which explained 32 and 29% of the variance of the 8 Cohen’s d maps. The cingulate gyrus, insula, supplementary motor cortex, and cerebellum were identified by PCA and multi-view pattern learning as top regions contributing to latent dimension shared across subsets of CNVs. The large proportion of distinct CNV effects on brain morphology may explain the small neuroimaging effect sizes reported in polygenic psychiatric conditions. Nevertheless, latent gene brain morphology dimensions will help subgroup the rapidly expanding landscape of neuropsychiatric variants and dissect the heterogeneity of idiopathic conditions. © 2021, The Author(s)

Multi-site normative modeling of diffusion tensor imaging metrics using hierarchical bayesian regression

Multi-site imaging studies can increase statistical power and improve the reproducibility and generalizability of findings, yet data often need to be harmonized. One alternative to data harmonization in the normative modeling setting is Hierarchical Bayesian Regression (HBR), which overcomes some of the weaknesses of data harmonization. Here, we test the utility of three model types, i.e., linear, polynomial and b-spline - within the normative modeling HBR framework - for multi-site normative modeling of diffusion tensor imaging (DTI) metrics of the brain’s white matter microstructure, across the lifespan. These models of age dependencies were fitted to cross-sectional data from over 1,300 healthy subjects (age range: 2–80 years), scanned at eight sites in diverse geographic locations. We found that the polynomial and b-spline fits were better suited for modeling relationships of DTI metrics to age, compared to the linear fit. To illustrate the method, we also apply it to detect microstructural brain differences in carriers of rare genetic copy number variants, noting how model complexity can impact findings

The Montreal Antenatal Well-Being Study (MAWS): a prospective longitudinal study of perinatal mental health.

Objective: This prospective longitudinal cohort aims to identify biological, psychological, and social factors that contribute to maternal perinatal mental health, family well-being, and child development. Method: Pregnant individuals (N=1130) were recruited between 8-20 gestation weeks. Questionnaire data were collected through a web-based platform together with biosamples for genetic analysis. Baseline characteristics of the cohort are described. A Bayesian model explored potential pandemic-associated changes in baseline maternal mental health symptoms throughout recruitment. Results: At baseline, 28.3% and 11.6% of pregnant participants reported clinically significant symptoms of anxiety (Spielberger Trait Anxiety Inventory ≥ 40) or depression (Edinburgh Postnatal Depression Scale ≥ 13). The onset of the COVID-19 pandemic was associated with increased likelihood of elevated scores on brief screening instruments for anxiety and depression. There was insufficient evidence for such effects using other screening tools. Conclusion(s): We further highlight anxiety and depression as common complications of pregnancy but find a modest impact of the pandemic on mental health within this cohort. Leveraging the unique data collected through this study we seek to inform screening practices and health policy to improve the well-being of mothers and families

Brain functional connectivity mirrors genetic pleiotropy in psychiatric conditions

Pleiotropy occurs when a genetic variant influences more than one trait. This is a key property of the genomic architecture of psychiatric disorders and has been observed for rare and common genomic variants. It is reasonable to hypothesize that the microscale genetic overlap (pleiotropy) across psychiatric conditions and cognitive traits may lead to similar overlaps at the macroscale brain level such as large-scale brain functional networks. We took advantage of brain connectivity, measured by resting-state functional MRI to measure the effects of pleiotropy on large-scale brain networks, a putative step from genes to behavior. We processed nine resting-state functional MRI datasets including 32,726 individuals and computed connectome-wide profiles of seven neuropsychiatric copy-number-variants, five polygenic scores, neuroticism, and fluid intelligence as well as four idiopathic psychiatric conditions. Nine out of nineteen pairs of conditions and traits showed significant functional connectivity correlations (rFunctional connectivity), which could be explained by previously published levels of genomic (rGenetic) and transcriptomic (rTranscriptomic) correlations with moderate to high concordance: rGenetic - rFunctional connectivity= 0.71 [0.40-0.87] and rTranscriptomic - rFunctional connectivity= 0.83 [0.52; 0.94]. Extending this analysis to functional connectivity profiles associated with rare and common genetic risk showed that 30 out of 136 pairs of connectivity profiles were correlated above chance. These similarities between genetic risks and psychiatric disorders at the connectivity level were mainly driven by the overconnectivity of the thalamus and the somatomotor networks. Our findings suggest a substantial genetic component for shared connectivity profiles across conditions and traits, opening avenues to delineate general mechanisms - amenable to intervention - across psychiatric conditions and genetic risks

Brain functional connectivity mirrors genetic pleiotropy in psychiatric conditions

Pleiotropy occurs when a genetic variant influences more than one trait. This is a key property of the genomic architecture of psychiatric disorders and has been observed for rare and common genomic variants. It is reasonable to hypothesize that the microscale genetic overlap (pleiotropy) across psychiatric conditions and cognitive traits may lead to similar overlaps at the macroscale brain level such as large-scale brain functional networks. We took advantage of brain connectivity, measured by resting-state functional MRI to measure the effects of pleiotropy on large-scale brain networks, a putative step from genes to behavior. We processed nine resting-state functional MRI datasets including 32,726 individuals and computed connectome-wide profiles of seven neuropsychiatric copy-number-variants, five polygenic scores, neuroticism, and fluid intelligence as well as four idiopathic psychiatric conditions. Nine out of nineteen pairs of conditions and traits showed significant functional connectivity correlations (rFunctional connectivity), which could be explained by previously published levels of genomic (rGenetic) and transcriptomic (rTranscriptomic) correlations with moderate to high concordance: rGenetic - rFunctional connectivity= 0.71 [0.40-0.87] and rTranscriptomic - rFunctional connectivity= 0.83 [0.52; 0.94]. Extending this analysis to functional connectivity profiles associated with rare and common genetic risk showed that 30 out of 136 pairs of connectivity profiles were correlated above chance. These similarities between genetic risks and psychiatric disorders at the connectivity level were mainly driven by the overconnectivity of the thalamus and the somatomotor networks. Our findings suggest a substantial genetic component for shared connectivity profiles across conditions and traits, opening avenues to delineate general mechanisms - amenable to intervention - across psychiatric conditions and genetic risks