Biology subjects

Bucan, M.

Publications and source records attributed to Bucan, M..

10 recordsLinked to original sources

bioRxiv2024

Impact of intragenic NRXN1 deletions on early cortical development

BackgroundDeletions in NRXN1 are strongly associated with neurodevelopmental and psychiatric conditions. While exonic deletions are well-studied, intragenic deletions, particularly in intron 5, are less understood and generally consider benign. Recent studies show exonic deletions impact isoform diversity during neurodevelopment, affecting neurogenesis and neuronal function. However, whether intragenic deletions impact isoform expression and neurodevelopment remains underexplored. MethodsWe used hiPSCs from typically developing individuals (control) and those with NRXN1 intron 5 deletions to study neurodevelopment. HiPSCs were differentiated towards a cortical fate, with NRXN1 isoform expression, molecular differences, and neuronal morphology examined. ResultsWe observed distinct NRXN1 isoform expression dynamics during early neurodevelopment, with two expression peaks post-neuronal induction and NRXN1{beta} being most highly expressed. Both NRXN1 deletion and control lines showed similar acquisition of regional and cell fate identity, but significant differences in NRXN1 isoform expression were observed between deletion and control lines, and between deletion lines. RNA sequencing revealed genotype-dependent alterations, particularly in pathways related to synaptic function and neuronal morphology. Consistent with these findings, NRXN1 deletion lines exhibited altered dendrite outgrowth, with variations between deletion lines. ConclusionsOur results indicate a potential role for intron 5 in controlling NRXN1 isoform expression during neurodevelopment. Alterations in gene expression profiles, correlated with morphological changes, suggest a role for NRXN1 isoforms in shaping dendritic morphology. Molecular and cellular differences observed between lines with identical intronic deletions suggest that additional factors, such as genetic background or biological sex, may also play an important role in these phenotypes. Collectively, these findings indicate that NRXN1 intronic deletions are not benign, influencing isoform expression, cellular phenotypes, and neurodevelopment.

neuroscience↗

bioRxiv2024

Identity-by-descent (IBD) segment outlier detection in endogamous populations using pedigree cohorts

Genomic segments that are inherited from a common ancestor are referred to as identical-by-descent (IBD). Because these segments are inherited, they not only allow us to study diseases, population characteristics, and the sharing of rare variants, but also understand hidden familial relationships within populations. Over the past two decades, various IBD finding algorithms have been developed using hidden Markov models (HMMs), hashing and extension, and Burrows-Wheeler Transform (BWT) approaches. In this study, we investigate the utility of pedigree information in IBD outlier detection methods for endogamous populations. With the increasing prevalence of computationally efficient sequencing technology and proper documentation of pedigree structures, we expect complete pedigree information to become readily available for more populations. While IBD segments have been used to reconstruct pedigrees, because we now have access to the pedigree, it is a natural question to ask if including pedigree information would substantially improve IBD segment finding for the purpose of studying inheritance. We propose an IBD pruning algorithm for reducing the number of false positives in IBD segments detected by existing software. While existing software already identify IBD segments with high success rates, our algorithm analyzes the familial relationships between cohorts of individuals who are initially hypothesized to share IBD segments to remove outliers. Our algorithm is inspired by a k-Nearest Neighbors (kNN) approach with a novel distance metric for pedigrees with loops. We apply our method to simulated genomic data under an Amish pedigree, but it could be applied to pedigrees from other human populations as well as domesticated animals such as dogs and cattle.

genomics↗

bioRxiv2024

Sleep and Activity Patterns in Autism Spectrum Disorder

BackgroundAutism spectrum disorder (ASD) is a highly heritable and heterogeneous neurodevelopmental disorder characterized by impaired social interactions, repetitive behaviors, and a wide range of comorbidities. Between 44-83% of autistic individuals report sleep disturbances, which may share an underlying neurodevelopmental basis with ASD. MethodsWe recruited 382 ASD individuals and 223 of their family members to obtain quantitative ASD-related traits and wearable device-based accelerometer data spanning three consecutive weeks. An unbiased approach identifying traits associated with ASD was achieved by applying the elastic net machine learning algorithm with five-fold cross-validation on 6,878 days of data. The relationship between sleep and physical activity traits was examined through linear mixed-effects regressions using each night of data. ResultsThis analysis yielded 59 out of 242 actimetry measures associated with ASD status in the training set, which were validated in a test set (AUC: 0.777). For several of these traits (e.g. total light physical activity), the day-to-day variability, in addition to the mean, was associated with ASD. Individuals with ASD were found to have a stronger correlation between physical activity and sleep, where less physical activity decreased their sleep more significantly than that of their non-ASD relatives. ConclusionsThe average duration of sleep/physical activity and the variation in the average duration of sleep/physical activity strongly predict ASD status. Physical activity measures were correlated with sleep quality, traits, and regularity, with ASD individuals having stronger correlations. Interventional studies are warranted to investigate whether improvements in both sleep and increased physical activity may improve the core symptoms of ASD.

neuroscience↗

bioRxiv2020

Ancestral Haplotype Reconstruction in Endogamous Populations using Identity-By-Descent

In this work we develop a novel algorithm for reconstructing the genomes of ancestral individuals, given genotype or sequence data from contemporary individuals and an extended pedigree of family relationships. A pedigree with complete genomes for every individual enables the study of allele frequency dynamics and haplotype diversity across generations, including deviations from neutrality such as transmission distortion. When studying heritable diseases, ancestral haplotypes can be used to augment genome-wide association studies and track disease inheritance patterns. The building blocks of our reconstruction algorithm are segments of Identity-By-Descent (IBD) shared between two or more genotyped individuals. The method alternates between identifying a source for each IBD segment and assembling IBD segments placed within each ancestral individual. Unlike previous approaches, our method is able to accommodate complex pedigree structures with hundreds of individuals genotyped at millions of SNPs. We apply our method to an Old Order Amish pedigree from Lancaster, Pennsylvania, whose founders came to the United States from Europe during the early 18th century. The pedigree includes 1338 individuals from the past 10 generations, 394 with genotype data. The motivation for reconstruction is to understand the genetic basis of diseases segregating in the family through tracking haplotype transmission over time. Using our algorithm thread, we are able to reconstruct an average of 224 ancestral individuals per chromosome. For these ancestral individuals, on average we reconstruct 79% of their haplotypes. We also identify a region on chromosome 16 that is difficult to reconstruct - we find that this region harbors a short Amish-specific copy number variation and the gene HYDIN. thread was developed for endogamous populations, but can be applied to any extensive pedigree with the recent generations genotyped. We anticipate that this type of practical ancestral reconstruction will become more common and necessary to understand rare and complex heritable diseases in extended families. Author summaryWhen analyzing complex heritable traits, it is often useful to have genomic data from many generations of an extended family, to increase the amount of information available for statistical inference. However, we typically only have genomic data from the recent generations of a pedigree, as ancestral individuals are deceased. In this work we present an algorithm, called thread, for reconstructing the genomes of ancestral individuals, given a complex pedigree and genomic data from the recent generations. Previous approaches have not been able to accommodate large datasets (both in terms of sites and individuals), made simplifying assumptions about pedigree structure, or did not tie reconstructed sequences back to specific individuals. We apply thread to a complex Old Order Amish pedigree of 1338 individuals, 394 with genotype data.

bioinformatics↗

bioRxiv2019

Polygenic risk of psychiatric disorders exhibits cross-trait associations in electronic health record data

ObjectivePrediction of disease risk is a key component of precision medicine. Common, complex traits such as psychiatric disorders have a complex polygenic architecture making the identification of a single risk predictor difficult. Polygenic risk scores (PRS) denoting the sum of an individuals genetic liability for a disorder are a promising biomarker for psychiatric disorders, but require evaluation in a clinical setting. MethodsWe develop PRS for six psychiatric disorders (schizophrenia, bipolar disorder, major depressive disorder, cross disorder, attention-deficit/hyperactivity disorder, anorexia nervosa) and 17 non-psychiatric traits in over 10,000 individuals from the Penn Medicine Biobank with accompanying electronic health records. We perform phenome-wide association analyses to test their association across disease categories. ResultsFour of the six psychiatric PRS were associated with their primary phenotypes (odds ratios between 1.2-1.6). Individuals in the highest quintile of risk had between 1.4-2.9 times higher odds of the disorder than the remaining 80% of individuals. Cross-trait associations were identified both within the psychiatric domain and across trait domains. PRS for coronary artery disease and years of education were significantly associated with psychiatric disorders, largely driven by an association with tobacco use disorder. ConclusionsWe demonstrate that the genetic architecture of common psychiatric disorders identified in a clinical setting confirms that which has been derived from large consortia. Even though the risk associated is low in this context, these results suggest that as identification of genetic markers proceeds, PRS is a promising approach for prediction of psychiatric disorders and associated conditions in clinical registries.

genetics↗

bioRxiv2019

Human and mouse essentiality screens as a resource for disease gene discovery

Although genomic sequencing has been transformative in the study of rare genetic diseases, identifying causal variants remains a considerable challenge that can be addressed in part by new gene-specific knowledge. Here, we integrate measures of how essential a gene is to supporting life, as inferred from the comprehensive viability and phenotyping screens performed on knockout mice by the International Mouse Phenotyping Consortium and from human cell line essentiality screens. We propose a novel, cross-species gene classification across the Full Spectrum of Intolerance to Loss-of-function (FUSIL) and demonstrate that genes in five mutually exclusive FUSIL categories have differing characteristics in the biological processes they regulate, tissue expression levels and human mutation rates. Most notably, Mendelian disease genes, particularly those associated with developmental disorders, are highly overrepresented in the developmental lethal category, representing genes not essential for cell survival but required for organism development. Exploiting this finding, we have screened developmental disorder cases from three independent disease sequencing consortia and identified potentially pathogenic, de novo variants shared in different patients for several developmental lethal genes that have not previously been associated with rare disease. We therefore propose FUSIL as an efficient resource for disease gene discovery.

genomics↗

bioRxiv2018

PennZzz - an algorithm for estimating behavioral states from wrist-worn accelerometery

Sleep is a heterogeneous behavioral state comprised of different stages and interspersed with episodes of wakefulness. Sleep/wake states can be monitored in the sleep laboratory by polysomnography (PSG). However, sleep studies are intrusive, laborious and expensive, and are usually performed over a single night. In contrast, wrist-worn activity-tracking devices (actimeters) are inexpensive, unobtrusive, and can be used to estimate sleep and wake patterns over multiple nights. We designed the PennZzz algorithm to estimate sleep and wake from actimetry data. Results obtained by actimetry-based monitoring in 26 subjects were compared to stages of sleep and wakefulness detected by simultaneous polysomnography. We found that our algorithm identifies PSG-defined wake episodes with a high accuracy (336/431 - 76% of algorithm wake events correspond to true wakefulness). Furthermore, we find that the algorithm is sensitive enough to detect the majority (258/431 - 59%) of true wake episodes occurring after the first NREM1 to NREM2 transition. With correction, algorithm outputs can be used to estimate the total amount of time awake after sleep onset. We further refined this program for application in a high-throughput manner to assess the total amount of sleep, wake, and non-wear during longer recording periods.

physiology↗

bioRxiv2018

Rare variants in the genetic background modulate the expressivity of neurodevelopmental disorders

PurposeTo assess the contribution of rare variants in the genetic background towards variability of neurodevelopmental phenotypes in individuals with rare copy-number variants (CNVs) and gene-disruptive mutations.\n\nMethodsWe analyzed quantitative clinical information, exome-sequencing, and microarray data from 757 probands and 233 parents and siblings who carry disease-associated mutations.\n\nResultsThe number of rare secondary mutations in functionally intolerant genes (second-hits) correlated with the expressivity of neurodevelopmental phenotypes in probands with 16p12.1 deletion (n=23, p=0.004) and in probands with autism carrying gene-disruptive mutations (n=184, p=0.03) compared to their carrier family members. Probands with 16p12.1 deletion and a strong family history presented more severe clinical features (p=0.04) and higher burden of second-hits compared to those with mild/no family history (p=0.001). The number of secondary variants also correlated with the severity of cognitive impairment in probands carrying pathogenic rare CNVs (n=53) or de novo mutations in disease genes (n=290), and negatively correlated with head size among 80 probands with 16p11.2 deletion. These second-hits involved known disease-associated genes such as SETD5, AUTS2, and NRXN1, and were enriched for genes affecting cellular and developmental processes.\n\nConclusionAccurate genetic diagnosis of complex disorders will require complete evaluation of the genetic background even after a candidate gene mutation is identified.

genomics↗

bioRxiv2018

Estimating sleep parameters using an accelerometer without sleep diary

Wrist worn raw-data accelerometers are used increasingly in large scale population research. We examined whether sleep parameters can be estimated from these data in the absence of sleep diaries. Our heuristic algorithm uses the variance in estimated z-axis angle and makes basic assumptions about sleep interruptions. Detected sleep period time window (SPT-window), was compared against sleep diary in 3752 participants (range=60-82years) and polysomnography in sleep clinic patients (N=28) and in healthy good sleepers (N=22). The SPT-window derived from the algorithm was 10.9 and 2.9 minutes longer compared with sleep diary in men and women, respectively. Mean C-statistic to detect the SPT-window compared to polysomnography was 0.86 and 0.83 in clinic-based and healthy sleepers, respectively. We demonstrated the accuracy of our algorithm to detect the SPT-window. The value of this algorithm lies in studies such as UK Biobank where a sleep diary was not used.

epidemiology↗

bioRxiv2017

Genetic pleiotropy between mood disorders, metabolic, and endocrine traits in a multigenerational pedigree

Bipolar disorder (BD) is a mental disorder characterized by alternating periods of depression and mania. Individuals with BD have higher levels of early mortality than the general population, and a substantial proportion of this may be due to increased risk for comorbid diseases. Recent evidence suggests that pleiotropy, either in the form of a single risk-allele or the combination of multiple loci genome-wide, may underlie medical comorbidity between traits and diseases. To identify the molecular events that underlie BD and related medical comorbidities, we generated imputed whole genome sequence (WGS) data using a population specific reference panel, for an extended multigenerational Old Order Amish pedigree (400 family members) segregating BD and related disorders. First, we investigated all putative disease-causing variants at known Mendelian disease loci present in this pedigree. Second, we performed genomic profiling using polygenic risk scores to establish each individual's risk for several complex diseases. To explore the contribution of disease genes to BD we performed gene-based and variant-based association tests for BD, and found that Mendelian disease genes are enriched in the top results from both tests (OR=20.3, p=1x10-3; OR=2.2, p=1x10-2). We next identified a set of Mendelian variants that co-occur in individuals with BD more frequently than their unaffected family members, including the R3527Q mutation in APOB associated with hypercholesterolemia. Using polygenic risk scores, we demonstrated that BD individuals from this pedigree were enriched for the same common risk-alleles for BD as in the general population ({beta}=0.416, p=6x10-4). Furthermore, in the extended Amish family we find evidence for a common genetic etiology between BD and clinical autoimmune thyroid disease (p=1x10-4), diabetes (p=1x10-3), and lipid traits such as triglyceride levels (p=3x10-4). We identify genomic regions that contribute to the differences between BD individuals and unaffected family members by calculating local genetic risk for independent LD blocks. Our findings provide evidence for the extensive genetic pleiotropy that can drive epidemiological findings of comorbidities between diseases and other complex traits. Identifying such patterns may enable the subtyping of complex diseases and facilitate our understanding of the genetic mechanisms underlying phenotypic heterogeneity.

genetics↗