Biology subjects

Lal, D.

Publications and source records attributed to Lal, D..

At least 19 recordsLinked to original sources

bioRxiv2024

Optimizing clinical interpretability of functional evidence in epilepsy-related ion channel variants

Variants in genes encoding the voltage-gated ion channels are among the most common monogenic causes of epilepsy and neurodevelopmental disorders. Functional effects of a variant are increasingly important for diagnosis and therapeutic decisions. To incorporate knowledge regarding functional consequences in formal clinical variant interpretation, we developed an approach for evaluating multiple functional measurements within the Bayesian framework of the modified ACMG/AMP guidelines. We analyzed 216 functional assessments of 191 variants in SCN1A (n=74), SCN2A (n=66), SCN3A (n=18), and SCN8A (n=33). Of 20 commonly measured biophysical parameters, the most frequent drivers of overall functional consequence were persistent current (f=0.54), voltage dependence of activation (f=0.51), and voltage dependence of fast inactivation (f=0.40) for gain-of-function and peak current (f=0.87) for loss-of-function. By comparing measurements of 23 benign variants, we determined thresholds by which published data on these four parameters confer Strong evidence of variant pathogenicity (likelihood ratio > 18.7) under the ACMG/AMP rubric. Similarly, we delineated evidence weights for the most common epilepsy-related potassium channel gene, KCNQ2, through reports of 80 pathogenic and 24 benign variants, accounting for heterozygous and homozygous experimental conditions. We collected the resulting categorization of functional data into FENICS, a biomedical ontology of 152 standardized terms for coherent annotation of electrophysiological results. Across 271 variants in SCN1A/2A/3A/8A and KCNQ2, 1,731 annotations are available in ClinVar, facilitating use of this evidence in variant classification. In summary, we introduce and apply an ACMG/AMP-calibrated framework for electrophysiological studies in epilepsy-related channelopathies to delineate the impact of functional evidence on clinical variant interpretation.

genetics↗

bioRxiv2024

Molecular dynamics simulations reveal molecular mechanisms for the gain and loss of function effects of four SCN2A variants

SCN2A gene disorders cover a wide range of medical conditions, from epileptic encephalopathies to neurodevelopmental disorders. The variants of these disorders, studied through electrophysiology, show complex behaviors that go beyond simple classification as either gain or loss of function. In our study, we simulated the biophysical effects of variants (R937C, V208E, S1336Y, and R853Q) to understand their impact. Our findings reveal that all these variants negatively affect the structural stability of the gene, with R937C being the most unstable. Specifically, R937C disrupts important charged interactions affecting sodium ion flow, while S1336Y introduces a new interaction that impacts the channels inactivation gate. Conversely, the variants V208E and R853Q, which are located in the voltage-sensing domains, have opposite effects: R853Q increases compactness and interaction, whereas V208E shows a decrease. Our computer-based method offers a scalable way to gain crucial insights into how genetic variants influence channel dysfunction and contribute to neurodevelopmental disorders. AUTHOR SUMMARYDespite numerous advancements in computational methods for predicting variant pathogenicity in the SCN2A gene, understanding the precise biophysical molecular mechanisms associated with each variant at the atomic level remains a challenge. Presently, variants are predominantly categorized as either gain or loss of function, often overlooking critical structural details associated with these variants. This study focuses on elucidating the molecular mechanisms linked to the four most common SCN2A variants using all-atom molecular dynamics simulations, employing three replicas for each system. Our findings offer insights into the potential mechanisms underlying these four variants, thereby providing explanations for the observed electrophysiological outcomes. This investigation significantly contributes to enhancing our comprehension of how SCN2A variants manifest in various diseases. It underscores the importance of unraveling the biophysical properties underlying potential disease mechanisms, which could potentially enhance diagnostic and therapeutic strategies for patients afflicted with SCN2A-related disorders.

biophysics↗

bioRxiv2023

Variant annotation across homologous proteins (Paralogue Annotation) identifies disease-causing missense variants with high precision, and is widely applicable across protein families

BackgroundDistinguishing pathogenic variants from those that are rare but benign remains a key challenge in clinical genetics, especially for variants not previously observed and characterised in humans. In vitro and in vivo functional characterisation are typically resource intensive, and model systems may not accurately predict influence on human disease. Many in silico tools have been developed to predict which variants are disease-causing, but typically lack precision. Here we demonstrate the applicability of a framework, called Paralogue Annotation, that draws on information from previously-characterised variants in homologous proteins to predict whether variants in a gene of interest are likely disease causing. MethodsWe assessed the performance of Paralogue Annotation through three orthogonal approaches: (1) comparison to established in silico variant prediction tools using 47,016 missense variants from ClinVar across 3,524 genes representing a broad range of diverse protein classes, by calculating precision and sensitivity; (2) evaluation against large-scale functional assays of variant effect; and (3) comparing odd ratios calculated from case-control association tests for inherited cardiac arrhythmia syndromes, and neurodevelopmental disorders with epilepsy, stratifying variants by Paralogue Annotation. ResultsParalogue Annotation correctly annotates 4,328 ClinVar pathogenic variants, with 245 false positives, yielding a precision of 0.95. This increases to 0.99 with more stringent annotation parameters (requiring greater conservation of amino acids between annotated orthologues) at the expense of sensitivity. Compared to established tools, Paralogue Annotation has higher precision for the identification of pathogenic variants, albeit with lower sensitivity across diverse test sets. Extending the technique by transferring annotations between homologous protein domains, rather than full-length protein paralogues, increases sensitivity. Rare variants predicted pathogenic by Paralogue Annotation were more strongly disease-associated (increased odds ratio) than unstratified rare variants for six out of eight genes tested with case-control cohort approaches. ConclusionsWe demonstrate that Paralogue Annotation has high precision for predicting pathogenic missense variants, providing a useful line of evidence for clinical variant interpretation that is complementary to other approaches in use. As the number of characterised variants increases in reference datasets such as ClinVar, Paralogue Annotation will further increase in sensitivity and applicability.

bioinformatics↗

bioRxiv2022

Conserved patterns across ion channels correlate with variant pathogenicity and clinical phenotypes

Clinically identified genetic variants in ion channels can be benign or cause disease by increasing or decreasing the protein function. Consequently, therapeutic decision-making is challenging without molecular testing of each variant. Our biophysical knowledge of ion channel structures and function is just emerging, and it is currently not well understood which amino acid residues cause disease when mutated. We sought to systematically identify biological properties associated with variant pathogenicity across all major voltage and ligand-gated ion channel families. We collected and curated 3,049 pathogenic variants from hundreds of neurodevelopmental and other disorders and 12,546 population variants for 30 ion channel or channel subunits for which a high-quality protein structure was available. Using a wide range of bioinformatics approaches, we computed 163 structural features and tested them for pathogenic variant enrichment. We developed a novel 3D spatial distance scoring approach that enables comparisons of pathogenic and population variant distribution across protein structures. We discovered and independently replicated that several pore residue properties and proximity to the pore axis were most significantly enriched for pathogenic variants compared to population variants. Using our novel 3D scoring approach, we showed that the strongest pathogenic variant enrichment was observed for pore-lining residues and alpha-helix residues within 5[A] distance from the pore axis center and not involved in gating. Within the subset of residues located at the pore, the hydrophobicity of the pore was the feature most strongly associated with variant pathogenicity. We also found an association between the identified properties and both clinical phenotypes and fucntional in vitro assays for voltage-gated sodium channels (SCN1A, SCN2A, SCN8A) and N-methyl-D-aspartate (NMDA) receptor (GRIN1, GRIN2A, GRIN2B) encoding genes. In an independent expert-curated dataset of 1,422 neurodevelopmental disorder pathogenic patient variants, and 679 electrophysiological experiments that pore axis distance is associated with seizure age of onset and cognitive performance as well as differential gain vs. loss-of-channel function. In summary, we identified biological properties associated with ion-channel malfunction and show that these are correlated with in vitro functional read-outs and clinical phenotypes in patients with neurodevelopmental disorders. Our results suggest that clinical decision support algorithms that predict variant pathogenicity and function are feasible in the future.

genetics↗

bioRxiv2020

Visualizing subcellular structures in neurons with expansion microscopy

Protein expansion microscopy (proExM) is a powerful technique that crosslinks proteins to a swellable hydrogel to physically expand and optically clear biological samples. The resulting increased resolution (~70 nm) and physical separation of labeled proteins make it an attractive tool for studying the localization of subcellular organelles in densely packed tissues, such as the brain. However, the digestion and expansion process greatly reduces fluorescence signals making it necessary to optimize ExM conditions per sample for specific end goals. Here we describe a proExM workflow optimized for resolving subcellular organelles (mitochondria and the Golgi apparatus) and reporter-labeled spines in fixed mouse brain tissue. By directly comparing proExM staining and digestion protocols, we found that immunostaining before proExM and using a proteinase K based digestion for 8 hours consistently resulted in the best fluorescence signal to resolve subcellular organelles while maintaining sufficient reporter labeling to visualize spines and trace individual neurons. With these methods, we more accurately quantified mitochondria size and number and better visualized Golgi ultrastructure in reconstructed CA2 neurons of the hippocampus.

neuroscience↗

bioRxiv2020

SimText: A text mining framework for interactive analysis and visualization of similarities among biomedical entities

Literature exploration in PubMed on a large number of biomedical entities (e.g., genes, diseases, experiments) can be time consuming and challenging comparing many entities to one other. Here, we describe SimText, a user-friendly toolset that provides customizable and systematic workflows for the analysis of similarities among a set of entities based on words from abstracts and/or other text. SimText can be used for (i) data generation: text collection from PubMed and extraction of words with different text mining approaches, and (ii) interactive analysis of data using unsupervised learning techniques and visualization in a Shiny web application.Availability and Implementation We developed SimText as an open-source R software and integrated it into Galaxy, an online data analysis platform. A command line version of the toolset is available for download from GitHub at https://github.com/mgramm1/simtext.Competing Interest StatementThe authors have declared no competing interest.View Full Text

bioinformatics↗

bioRxiv2019

Altered Relationship between Soluble TREM2 and Inflammatory Markers in Young Adults with Down Syndrome

Individuals with Down syndrome (DS) develop Alzheimers disease (AD) - related neuropathology, characterized by amyloid plaques with amyloid {beta} (A{beta}) and neurofibrillary tangles with tau accumulation more frequently and at an earlier age than their neurotypical counterparts. Peripheral inflammation and the innate immune response are elevated in DS. Triggering receptor expressed in myeloid cells 2 (TREM2) genetic variants are risk factors for AD and other neurodegenerative diseases. A soluble cleavage product of TREM2 (sTREM2) has been described as elevated in AD cerebrospinal fluid and positively correlates with A{beta} and cognitive decline. There is relatively little information about TREM2 in DS. The objective of this study was to examine the relationship between sTREM2 and inflammatory markers in DS, prior to the development of dementia symptoms. Since TREM2 plays a role in the innate immune response and has been associated with dementia, the hypothesis of this exploratory study was that young adults with DS pre-dementia (n=15, mean age 29.5 years) would exhibit a different relationship between sTREM2 and inflammatory markers in plasma, compared to neurotypical, age-matched controls (n=16, mean age 29.6 years). Indeed, young adults with DS had significantly elevated plasma sTREM2 and inflammatory markers. In addition, in young adults with DS, sTREM2 correlated positively with 24 of the measured cytokines, while there were no significant correlations in the control group. Hierarchical clustering of sTREM2 and cytokine concentrations also differed between the group with DS and controls, supporting the hypothesis that its function is altered in people with DS pre-dementia. This exploratory study provides a basis for future studies investigating the relationship between TREM2 and the broader immune response pre-dementia.

neuroscience↗

bioRxiv2019

Genetic correlation between background EEG oscillations and genetic generalized epilepsy

ObjectiveParoxysmal epileptiform abnormalities on electroencephalography (EEG) are the hallmark of epilepsies, but it is uncertain to what extent epilepsy and background EEG oscillations share neurobiological underpinnings. Here, we aimed to assess the genetic correlation between epilepsy and background EEG oscillations. MethodsConfounding factors, including the heterogeneous etiology of epilepsies and medication effects hamper studies on background brain activity in people with epilepsy. To overcome this limitation, we compared genetic data from a GWAS on epilepsy (n=12,803 people with epilepsy and 24,218 controls) with that from a GWAS on background EEG (n=8,425 subjects without epilepsy), in which background EEG oscillation power was quantified in four different frequency bands: alpha, beta, delta and theta. We replicated our findings in an independent epilepsy replication dataset (n=4851 people with epilepsy and 20,428 controls). To assess the genetic overlap between these phenotypes, we performed genetic correlation analyses using linkage disequilibrium score regression, polygenic risk scores and Mendelian randomization analyses. ResultsOur analyses show strong genetic correlations between genetic generalized epilepsy (GGE) with background EEG oscillations, primarily with the beta frequency band. Furthermore, we show that subjects with higher beta and theta polygenic risk scores have a significantly higher risk of having generalized epilepsy. Mendelian randomization analyses suggest a causal effect of GGE genetic liability on beta oscillations. SignificanceOur results point to shared biological mechanisms underlying background EEG oscillations and the susceptibility for GGE, opening avenues to investigate the clinical utility of background EEG oscillations in the diagnostic work-up of epilepsy.

genetics↗

bioRxiv2019

Insights into protein structural, physicochemical, and functional consequences of missense variants in 1,330 disease-associated human genes

Interpretation of the colossal number of genetic variants identified from sequencing applications is one of the major bottlenecks in clinical genetics, with the inference of the effect of amino acid-substituting missense variants on protein structure and function being especially challenging. Here we evaluated the burden of amino acids affected in pathogenic variants (n=32,923) compared to the variants (n=164,915) from the general population in 1,330 disease-associated genes on forty protein features using over 14,000 experimentally-solved 3D structures. By analyzing the whole gene/variant set jointly, we identified 18 features associated with 3D mutational hotspots that are generally important for protein fitness and stability. Individual analyses performed for twenty-four protein functional classes further revealed 240 characteristics of mutational hotspots in total, including new associations recapitulating the sheer diversity across proteins essential structural regions. We demonstrated that the function-specific features of variants correspond to the readouts of mutagenesis experiments and positively correlate with clinically-interpreted pathogenic and benign missense variants. Finally, we made our results available through a web server to foster accessibility and downstream research. Our findings represent a crucial step towards translational genetics, from highlighting the impact of mutations on protein structure to rationalizing the pathogenicity of variants in terms of the perturbed molecular mechanisms.

genetics↗

bioRxiv2019

Predicting Functional Effects of Missense Variants in Voltage-Gated Sodium and Calcium Channels

Malfunctions of voltage-gated sodium and calcium channels (SCN and CACNA1 genes) have been associated with severe neurologic, psychiatric, cardiac and other diseases. Altered channel activity is frequently grouped into gain or loss of ion channel function (GOF or LOF, respectively) which is not only corresponding to clinical disease manifestations, but also to differences in drug response. Experimental studies of channel function are therefore important, but laborious and usually focus only on a few variants at a time. Based on known gene-disease-mechanisms, we here infer LOF (518 variants) and GOF (309 variants) of likely pathogenic variants from disease phenotypes of variant carriers. We show regional clustering of inferred GOF and LOF variants, respectively, across the alignment of the entire gene family, suggesting shared pathomechanisms in the SCN/CACNA1 genes. By training a machine learning model on sequence- and structure-based features we predict LOF- or GOF- associated disease phenotypes (ROC = 0.85) of likely pathogenic missense variants. We then successfully validate the GOF versus LOF prediction on 87 functionally tested variants in SCN1/2/8A and CACNA1I (ROC = 0.73) and in exome-wide data from > 100.000 cases and controls. Ultimately, functional prediction of missense variants in clinically relevant genes will facilitate precision medicine in clinical practice.

genetics↗

bioRxiv2019

Evaluation of copy number burden in specific epilepsy types from a genome-wide study of 18,564 subjects

Rare and large copy number variants (CNVs) around known genomic hotspots are strongly implicated in epilepsy etiology. But it remains unclear whether the observed associations are specific to an epilepsy phenotype, and if additional risk signal can be found outside hotspots. Here, we present the largest CNV burden and first CNV breakpoint level association analysis in epilepsy to date with 11,246 European epilepsy cases and 7,318 ancestry-matched controls. We studied five epilepsy phenotypes: genetic generalized epilepsy, lesional focal epilepsy, non-acquired focal epilepsy, epileptic encephalopathy, and unclassified epilepsy. We discovered novel epilepsy-associated CNV loci and further characterized the CNV burden enrichment among phenotype-specific epilepsies. Finally, we provide evidence for deletion burden outside of known hotspot regions and show that CNVs play a significant role in the genetic architecture of lesional focal epilepsies.

genetics↗

bioRxiv2019

Identification of pathogenic variant enriched regions across genes and gene families

Missense variant interpretation is challenging. Essential regions for protein function are conserved among gene family members, and genetic variants within these regions are potentially more likely to confer risk to disease. Here, we generated 2,871 gene family protein sequence alignments involving 9,990 genes and performed missense variant burden analyses to identify novel essential protein regions. We mapped 2,219,811 variants from the general population into these alignments and compared their distribution with 65,034 missense variants from patients. With this gene family approach, we identified 398 regions enriched for patient variants spanning 33,887 amino acids in 1,058 genes. As a comparison, testing the same genes individually we identified less patient variant enriched regions involving only 2,167 amino acids and 180 genes. Next, we selected de novo variants from 6,753 patients with neurodevelopmental disorders and 1,911 unaffected siblings, and observed a 5.56-fold enrichment of patient variants in our identified regions (95% C.I. =2.76-Inf, p-value = 6.66x10-8). Using an independent ClinVar variant set, we found missense variants inside the identified regions are 111-fold more likely to be classified as pathogenic in comparison to benign classification (OR = 111.48, 95% C.I = 68.09-195.58, p-value < 2.2e-16). All patient variant enriched regions identified (PERs) are available online through a user-friendly platform for interactive data mining, visualization and download at http://per.broadinstitute.org. In summary, our gene family burden analysis approach identified novel patient variant enriched regions in protein sequences. This annotation can empower variant interpretation.

genetics↗

bioRxiv2019

Targeted gene sequencing in 6994 individuals with neurodevelopmental disorder with epilepsy

PurposeWe aimed to gain insight into frequencies of genetic variants in genes implicated in neurodevelopmental disorder with epilepsy (NDD+E) by investigating large cohorts of patients in a diagnostic setting.\n\nMethodsWe analyzed variants in NDD+E using epilepsy gene panel sequencing performed between 2013 and 2017 by two large diagnostic companies. We compared variant frequencies in 6,994 panels to other 8,588 recently published panels as well as exome-wide de novo variants in 1,942 individuals with NDD+E and 10,937 controls.\n\nResultsGenes with highest frequencies of ultra-rare variants in NDD+E comprised SCN1A, KCNQ2, SCN2A, CDKL5, SCN8A and STXBP1, concordant with the two other epilepsy cohorts we investigated. Only 46% of the analysed 262 dominant and X-linked panel genes contained ultra-rare variants in patients. Among genes with contradictory evidence of association with epilepsy CACNB4, CLCN2, EFHC1, GABRD, MAGI2 and SRPX2 showed equal frequencies in cases and controls.\n\nConclusionWe show that improvement of panel design increased diagnostic yield over time, but panels still display genes with low or no diagnostic yield. With our data, we hope to improve current diagnostic NDD+E panel design and provide a resource of ultra-rare variants in individuals with NDD+E to the community.

genetics↗

bioRxiv2019

Ultra-rare genetic variation in the epilepsies: a whole-exome sequencing study of 17,606 individuals

Sequencing-based studies have identified novel risk genes for rare, severe epilepsies and revealed a role of rare deleterious variation in common epilepsies. To identify the shared and distinct ultra-rare genetic risk factors for rare and common epilepsies, we performed a whole-exome sequencing (WES) analysis of 9,170 epilepsy-affected individuals and 8,364 controls of European ancestry. We focused on three phenotypic groups; the rare but severe developmental and epileptic encephalopathies (DEE), and the commoner phenotypes of genetic generalized epilepsy (GGE) and non-acquired focal epilepsy (NAFE). We observed that compared to controls, individuals with any type of epilepsy carried an excess of ultra-rare, deleterious variants in constrained genes and in genes previously associated with epilepsy, with the strongest enrichment seen in DEE and the least in NAFE. Moreover, we found that inhibitory GABAA receptor genes were enriched for missense variants across all three classes of epilepsy, while no enrichment was seen in excitatory receptor genes. The larger gene groups for the GABAergic pathway or cation channels also showed a significant mutational burden in DEE and GGE. Although no single gene surpassed exome-wide significance among individuals with GGE or NAFE, highly constrained genes and genes encoding ion channels were among the top associations, including CACNA1G, EEF1A2, and GABRG2 for GGE and LGI1, TRIM3, and GABRG2 for NAFE. Our study confirms a convergence in the genetics of common and rare epilepsies associated with ultra-rare coding variation and highlights a ubiquitous role for GABAergic inhibition in epilepsy etiology in the largest epilepsy WES study to date.

genetics↗

bioRxiv2018

The role of sodium channels in sudden unexpected death in pediatrics

Sudden Unexpected Death in Pediatrics (SUDP) is a tragic condition with hypothesized multifactorial etiology. While there is recent evidence implicating genes related to cardiac arrhythmia and epilepsy as genetic risk factors contributing to some cases of SUDP, the underlying mechanisms of SUDP remain under active investigation. SUDP encompasses Sudden Infant Death Syndrome (SIDS) and Sudden Unexplained Death in Childhood (SUDC), affecting children under and over 1 year of age, respectively. The presence of developmental hippocampal malformations in many children with SIDS and SUDC suggests that a subset of patients may share epilepsy-related mechanisms with Sudden Unexplained Death in Epilepsy Patients (SUDEP). Pathogenic variants in both epilepsy- and arrhythmia-related sodium channel genes have recently been identified in patients with SIDS, SUDC, and SUDEP.\n\nWe performed a candidate gene analysis for genes encoding sodium channel subunits in whole exome sequencing (WES) data from 73 SUDP patients. After a thorough literature review, we mapped all reported SUDP-associated sodium channel variants alongside variants from the population on a structural protein model to evaluate whether patient variants clustered in important protein domains compared to controls.\n\nIn our cohort, 13 variants met criteria for pathogenicity or potential pathogenicity. While SCN1A, SCN1B, and SCN5A have established disease associations, we also considered variants in the paralogs SCN3A, SCN4A and SCN9A. Overall, the patient-associated variants clustered at conserved amino acid sites across the sodium channel gene family that do not tolerate variation in these genes.\n\nThis study provides a molecular overview of sodium channel variants present in cases with SUDP and reveals key amino acid sites that do not tolerate variation across the SCN paralog family. Further research will lead to an improved understanding of the contribution of sodium channels to SUDP, with a goal of one day implementing prevention strategies to avoid untimely deaths in at-risk children.\n\nAuthor SummaryThe sudden unexplained death of an infant or a child is a tragic event, which is likely caused by the complex interaction of multiple factors. Besides environmental factors, genes related to epilepsy and cardiac arrhythmia have been identified as risk factors. The sodium channel family encompasses genes, related to both cardiac arrhythmia as well as epilepsy, whose proteins share structural homology. We evaluated sodium channel gene variants in our cohort, examined all known variants in sodium genes in SUDP patients from the literature, and mapped patient variants alongside variants from the population on a 3D protein model. The patient variants clustered at conserved amino acid sites with low rates of variation in the general population, not only in the particular gene involved but also in the gene family. This study illustrates that sodium channel variants contribute to the complex phenotype of sudden death in pediatrics, suggesting complex mechanisms of neurologic and/or cardiac dysfunction contributing to death.

genetics↗

bioRxiv2018

Contribution of rare and common variants to intellectual disability in a high-risk population sub-isolate of Northern Finland

The contribution of de novo and ultra-rare genetic variants in severe and moderate intellectual disability (ID) has been extensively studied whereas the genetic architecture of mild ID has been less well characterized. To elucidate the genetic background of milder ID we studied a regional cohort of 442 ID patients enriched for mild ID (>50%) from a population isolate of Finland. We analyzed rare variants using exome sequencing and CNV genotyping and common variants using common variant polygenic risk scores. As controls we used a Finnish collection of exome sequenced (n=11311) and GWAS chip genotyped (n=11699) individuals.\n\nWe show that rare damaging variants in genes known to be associated with cognitive defects are observed more often in severe (27%) than in mild ID (13%) patients (p-value: 7.0e-4). We further observed a significant enrichment of protein truncating variants in loss-of-function intolerant genes, as well as damaging missense variants in genes not yet associated with cognitive defects (OR: 2.1, p-value: 3e-8). For the first time to our knowledge, we show that a common variant polygenic load significantly contributes to all severity forms of ID. The heritability explained was the highest for educational attainment (EDU) in mild ID explaining 2.2% of the heritability on liability scale. For more severe ID it was lower at 0.6%. Finally, we identified a homozygote variant in the CRADD gene to be a cause of a specific syndrome with ID and pachygyria. The frequency of this variant is 50x higher in the Finnish population than in non-Finnish Europeans, demonstrating the benefits of utilizing population isolates in rare variant analysis of diseases under negative selection.

genetics↗

bioRxiv2017

Common variant burden contributes significantly to the familial aggregation of migraine in 1,589 families

It has long been observed that complex traits, including migraine, often aggregate in families, but the underlying genetic architecture behind this is not well understood. Two competing hypotheses exist, emphasizing either rare or common genetic variation. More specifically, familial aggregation could be predominantly explained by rare, penetrant variants that segregate according to Mendelian inheritance or rather by the sufficient polygenic accumulation of many common variants, each with an individually small effect. Some combination of both common and rare variation could also contribute towards a spectrum of disease risk.\n\nWe investigated this in a collection of 8,319 individuals across 1,589 migraine families from Finland. Family members were individually diagnosed by a migraine-specific questionnaire with either migraine without aura (MO, ICHD-3 code 1.1, n=2,357), migraine with typical aura (ICHD- 3 code 1.2.1, n=2,420), hemiplegic migraine (HM, ICHD-3 code 1.2.3, n=540), or no migraine (n=3,002). For comparison, we used population-based migraine cases (n=1,101) and controls (n=13,369) from the FINRISK study. The disease status of FINRISK individuals was assigned based on health registry data from outpatient clinics and/or prescription medication. All individuals were genotyped on the Illumina(R) CoreExome or PsychArray chip platforms and imputed to a Finnish reference panel of 6,962 haplotypes. Polygenic risk scores (PRS), representing the common variant burden in each individual, were calculated using weights from the most recent large-scale genome-wide association study of migraine. To account for family structure in our analyses, we used a mixed-model approach, adjusting for the genetic relationship matrix as a random effect.\n\nWe found a significantly higher common variant burden in familial cases of migraine (for all subtypes, measured by the odds ratio [OR] per standard deviation [SD] increase in PRS; OR = 1.76, 95% CI = 1.71-1.81, P = 1.7x10-109) compared to cases from a population cohort (OR = 1.32, 95% CI = 1.25-1.38, P = 7.2x10-17) when using the population controls as a reference group. The highest enrichment was observed for HM (OR = 1.96, 95% CI = 1.86-2.07, P = 8.7x10-36) and migraine with typical aura (OR = 1.85, 95% CI = 1.79-1.91, P = 1.4x10-86) but enrichment was also present for MO (OR = 1.57, 95% CI = 1.51-1.63, P = 1.1x10-48). Comparing within cases, there was no significant difference in common variant burden between the migraine with aura subtypes, HM and migraine with typical aura (OR = 1.09, 95% CI = 0.99-1.19, P = 0.09), but both showed significantly higher enrichment compared to MO (OR = 1.28, 95% CI = 1.17-1.38, P = 7.3x10-7, and OR = 1.17, 95% CI = 1.11-1.23, P = 4.62x10-5, respectively). Additionally, we found that higher common variant burden corresponded to earlier age of headache onset (OR per SD increase in PRS for 3,631 cases with onset before 20 years old compared to 1,686 cases with onset later than 20 years old; OR = 1.11, 95% CI = 1.05-1.18, P = 8.3x10-4). FINRISK population cases identified from national health registry data were found to have lower common variant burden in comparison to the familial migraine cases (OR = 1.32, 95% CI = 1.25-1.38, P = 6.8x10-17), unless the individuals had attended both a specialist clinic and also received prophylactic migraine treatment (OR = 1.70, 95% CI = 1.53-1.88, P = 3.9x10-9). Finally, although rare variants have been suggested as the primary cause for familial hemiplegic migraine (FHM), we found only four out of 45 sequenced FHM families (8.9%) with a pathogenic mutation in one of the known risk genes.\n\nIn summary, our results demonstrate a substantial contribution of common polygenic variation to familial aggregation in migraine, comparable to both controls and that observed in migraine cases from a population cohort. The findings also suggest that individuals with migraine aura symptoms (either typical aura, which is mostly visual, or rare motor aura) tend to have higher common variant burden on average supporting the polygenic model also in these migraine subtypes.

genetics↗

bioRxiv2017

Paternal-age-related de novo mutations and risk for five disorders

BackgroundThere are well-established epidemiologic associations between advanced paternal age and increased offspring risk for several psychiatric and developmental disorders. These associations are commonly attributed to age-related de novo mutations. However, the actual magnitude of risk conferred by age-related de novo mutations in the male germline is unknown. Quantifying this risk would clarify the clinical and public health significance of delayed paternity.\n\nMethodsUsing results from large, parent-child trio whole-exome-sequencing studies, we estimated the relationship between paternal-age-related de novo single nucleotide variants (dnSNVs) and offspring risk for five disorders: autism spectrum disorders (ASD), congenital heart disease (CHD), neurodevelopmental disorders with epilepsy (EPI), intellectual disability (ID), and schizophrenia (SCZ). Using Danish national registry data, we then investigated the degree to which the epidemiologic association between each disorder and advanced paternal age was consistent with the estimated role of de novo mutations.\n\nResultsIncidence rate ratios comparing dnSNV-based risk to offspring of 45 versus 25-year-old fathers ranged from 1.05 (95% confidence interval 1.01-1.13) for SCZ to 1.29 (95% CI 1.13-1.68) for ID. Epidemiologic estimates of paternal age risk for CHD, ID and EPI were consistent with the dnSNV effect. However, epidemiologic effects for ASDs and SCZ significantly exceeded the risk that could be explained by dnSNVs alone (p<2e-4 for both comparisons).\n\nConclusionIncreasing dnSNVs due to advanced paternal age confer a small amount of offspring risk for psychiatric and developmental disorders. For ASD and SCZ, epidemiologic associations with delayed paternity largely reflect factors that cannot be assumed to increase with age.

genetics↗