The genetic architecture of schizophrenia and bipolar disorder: identity by descent and exome sequencing in a family-based population sample

Schizophrenia (SCZ) and bipolar disorder (BPD) are complex genetic disorders, each with a prevalence of 1% in the population worldwide, and a consistent genetic overlap. Several genome-wide association studies (GWASs) have demonstrated that common polymorphisms can account only for half of the observed genetic variance in liability. Therefore, attention has turned towards the discovery of rare, high-penetrant risk variants. In this study a unique population sample is investigated, as all the patients have a common ancestry from a closed population with a high prevalence of SCZ and BPD. More than 150 familial cases are available for study. Considering these features, an enrichment of rare alleles can be hypothesized, facilitating their discovery in this sample. In a preliminary investigation, copy number variants (CNVs) were found to have a minor role for the disorders. Consequently, a novel approach has been developed to track loci shared by patients because inherited from common ancestors (IBD, identical by descent). A genome-wide map of the shared haplotype was obtained and then used to prioritize rare (MAF<1%) or novel variants from whole-exome sequencing of 17 patients. The results suggest that genes affected by these variants are selectively involved in axon guidance and synaptic transmission processes, both fundamental for neurosystem development and function. Moreover, the presence of identified variants was inferred in non-sequenced subjects on the basis of IBD map. Variants were shared across different families and some of them are segregating within multiple pedigrees, overall revealing a puzzle of loci coherent with the complex and polygenic architecture of the disorders. Among the candidate genes are GRM7 and GRM8, two metabotrobic glutamate receptors, and NCAM1 and NCAN, playing a role in neurite formation. Finally ,specific combinations of variants were detected in multiple patients from different pedigrees, possibly indicating interplays of alleles substantially increasing risk for the disorders. Concluding, a novel approach has been developed in this study, combining IBD mapping and whole-exome sequencing to investigate rare sequence variants in a closed population. Results provide some insights on the genetic architecture of SCZ and BPD, additionally proposing the involvement of axon guidance and synaptic transmission pathways in etiology. The identification of some candidate genes, then, could ultimately inform the search of new therapeutic targets for this common disorders with such a high burden for the society

In search of complex disease risk through genome wide association studies

The identification and characterisation of genomic changes (variants) that can lead to human diseases is one of the central aims of biomedical research. The generation of catalogues of genetic variants that have an impact on specific diseases is the basis of Personalised Medicine, where diagnoses and treatment protocols are selected according to each patient&rsquo;s profile. In this context, the study of complex diseases, such as Type 2 diabetes or cardiovascular alterations, is fundamental. However, these diseases result from the combination of multiple genetic and environmental factors, which makes the discovery of causal variants particularly challenging at a statistical and computational level. Genome-Wide Association Studies (GWAS), which are based on the statistical analysis of genetic variant frequencies across non-diseased and diseased individuals, have been successful in finding genetic variants that are associated to specific diseases or phenotypic traits. But GWAS methodology is limited when considering important genetic aspects of the disease and has not yet resulted in meaningful translation to clinical practice. This review presents an outlook on the study of the link between genetics and complex phenotypes. We first present an overview of the past and current statistical methods used in the field. Next, we discuss current practices and their main limitations. Finally, we describe the open challenges that remain and that might benefit greatly from further mathematical developments.L.A. was supported by grant BES-2017-081635. This publication is part of R&D and Innovation grant BES-2017-081635 funded by MCIN and by “FSE Investing in your future”I.M. was supported by grant FJCI-2017-31878. This publication is part of R&D and Innovation grant FJCI-2017-31878 funded by MCIN. C.S. received funding from the European Union’s Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie grant agreement H2020-MSCA-COFUND-2016-754433.Peer ReviewedPostprint (published version

GCAT|Panel, a comprehensive structural variant haplotype map of the Iberian population from high-coverage whole-genome sequencing

The combined analysis of haplotype panels with phenotype clinical cohorts is a common approach to explore the genetic architecture of human diseases. However, genetic studies are mainly based on single nucleotide variants (SNVs) and small insertions and deletions (indels). Here, we contribute to fill this gap by generating a dense haplotype map focused on the identification, characterization, and phasing of structural variants (SVs). By integrating multiple variant identification methods and Logistic Regression Models (LRMs), we present a catalogue of 35 431 441 variants, including 89 178 SVs (≥50 bp), 30 325 064 SNVs and 5 017 199 indels, across 785 Illumina high coverage (30x) whole-genomes from the Iberian GCAT Cohort, containing a median of 3.52M SNVs, 606 336 indels and 6393 SVs per individual. The haplotype panel is able to impute up to 14 360 728 SNVs/indels and 23 179 SVs, showing a 2.7-fold increase for SVs compared with available genetic variation panels. The value of this panel for SVs analysis is shown through an imputed rare Alu element located in a new locus associated with Mononeuritis of lower limb, a rare neuromuscular disease. This study represents the first deep characterization of genetic variation within the Iberian population and the first operational haplotype panel to systematically include the SVs into genome-wide genetic studies.GCAT|Genomes for Life, a cohort study of the Genomes of Catalonia, Fundació Institut Germans Trias i Pujol (IGTP); IGTP is part of the CERCA Program/Generalitat de Catalunya; GCAT is supported by Acción de Dinamización del ISCIII-MINECO; Ministry of Health of the Generalitat of Catalunya [ADE 10/00026]; Agència de Gestió d’Ajuts Universitaris i de Recerca (AGAUR) [2017-SGR 529]; B.C. is supported by national grants [PI18/01512]; X.F. is supported by VEIS project [001-P-001647] (co-funded by European Regional Development Fund (ERDF), ‘A way to build Europe’); a full list of the investigators who contributed to the generation of the GCAT data is available from www.genomesforlife.com/; Severo Ochoa Program, awarded by the Spanish Government [SEV-2011-00067 and SEV2015-0493]; Spanish Ministry of Science [TIN2015-65316-P]; Innovation and by the Generalitat de Catalunya [2014-SGR-1051 to D.T.]; Agencia Estatal de Investigación (AEI, Spain) [BFU2016-77244-R and PID2019-107836RB-I00]; European Regional Development Fund (FEDER, EU) (to M.C.); Spanish Ministry of Science and Innovation [FPI BES-2016-0077344 to J.V.M.]; C.S. received funding from the European Union's Horizon 2020 research and innovation program under the Marie Skłodowska-Curie grant agreement [H2020-MSCA-COFUND-2016-754433]; this study made use of data generated by the UK10K Consortium from UK10K COHORT IMPUTATION [EGAS00001000713]; formal agreement with the Barcelona Supercomputing Center (BSC); this study made use of data generated by the Genome of the Netherlands’ project, which is funded by the Netherlands Organization for Scientific Research [184021007], allowing us to use the GoNL reference panel containing SVs, upon request (GoNL Data Access request 2019203); this study also used data generated by the Haplotype Reference Consortium (HRC) accessed through the European Genome-phenome Archive with the accession numbers EGAD00001002729; formal agreement of the Barcelona Supercomputing Center (BSC) with WTSI; this study made use of data generated by the 1000 Genomes (1000G), accessed through the FTP portal (http://ftp.1000genomes.ebi.ac.uk/vol1/ftp/release/20130502/); this study used the GeneHancer-for-AnnotSV dump for GeneCards Suite Version 4.14, through a formal agreement between the BSC and the Weizmann Institute of Science. Funding for open access charge: GCAT|Genomes for Life, a cohort study of the Genomes of Catalonia, Fundació Institut Germans Trias i Pujol (IGTP); IGTP is part of the CERCA Program/Generalitat de Catalunya; GCAT is supported by Acción de Dinamización del ISCIII-MINECO; Ministry of Health of the Generalitat of Catalunya [ADE 10/00026]; Agència de Gestió d’Ajuts Universitaris i de Recerca (AGAUR) [2017-SGR 529]; B.C. is supported by national grants [PI18/01512]; X.F. is supported by VEIS project [001-P-001647] (co-funded by European Regional Development Fund (ERDF), ‘A way to build Europe’); a full list of the investigators who contributed to the generation of the GCAT data is available from www.genomesforlife.com/; Severo Ochoa Program, awarded by the Spanish Government [SEV-2011-00067 and SEV2015-0493]; Spanish Ministry of Science [TIN2015-65316-P]; Innovation and by the Generalitat de Catalunya [2014-SGR-1051 to D.T.]; [Agencia Estatal de Investigación (AEI, Spain) [BFU2016-77244-R and PID2019-107836RB-I00]; European Regional Development Fund (FEDER, EU) (to M.C.); Spanish Ministry of Science and Innovation [FPI BES-2016-0077344 to J.V.M.]; C.S. received funding from the European Union's Horizon 2020 research and innovation program under the Marie Skłodowska-Curie grant agreement [H2020-MSCA-COFUND-2016-754433]; this study made use of data generated by the UK10K Consortium from UK10K COHORT IMPUTATION [EGAS00001000713]; formal agreement with the Barcelona Supercomputing Center (BSC); this study made use of data generated by the Genome of the Netherlands’ project, which is funded by the Netherlands Organization for Scientific Research [184021007], allowing us to use the GoNL reference panel containing SVs, upon request (GoNL Data Access request 2019203); this study also used data generated by the Haplotype Reference Consortium (HRC) accessed through the European Genome-phenome Archive with the accession numbers EGAD00001002729; formal agreement of the Barcelona Supercomputing Center (BSC) with WTSI; this study made use of data generated by the 1000 Genomes (1000G), accessed through the FTP portal (http://ftp.1000genomes.ebi.ac.uk/vol1/ftp/release/20130502/); this study used the GeneHancer-for-AnnotSV dump for GeneCards Suite Version 4.14, through a formal agreement between the BSC and The Weizmann Institute of Science."Article signat per 21 autors/es: Jordi Valls-Margarit, Iván Galván-Femenía, Daniel Matías-Sánchez, Natalia Blay, Montserrat Puiggròs, Anna Carreras, Cecilia Salvoro, Beatriz Cortés, Ramon Amela, Xavier Farre, Jon Lerga-Jaso, Marta Puig, Jose Francisco Sánchez-Herrero, Victor Moreno, Manuel Perucho, Lauro Sumoy, Lluís Armengol, Olivier Delaneau, Mario Cáceres, Rafael de Cid, David Torrents"Postprint (published version

The impact of non-additive genetic associations on age-related complex diseases

Genome-wide association studies (GWAS) are not fully comprehensive, as current strategies typically test only the additive model, exclude the X chromosome, and use only one reference panel for genotype imputation. We implement an extensive GWAS strategy, GUIDANCE, which improves genotype imputation by using multiple reference panels and includes the analysis of the X chromosome and non-additive models to test for association. We apply this methodology to 62,281 subjects across 22 age-related diseases and identify 94 genome-wide associated loci, including 26 previously unreported. Moreover, we observe that 27.7% of the 94 loci are missed if we use standard imputation strategies with a single reference panel, such as HRC, and only test the additive model. Among the new findings, we identify three novel low-frequency recessive variants with odds ratios larger than 4, which need at least a three-fold larger sample size to be detected under the additive model. This study highlights the benefits of applying innovative strategies to better uncover the genetic architecture of complex diseases. Most genome-wide association studies assume an additive model, exclude the X chromosome, and use one reference panel. Here, the authors implement a strategy including non-additive models and find that the number of loci for age-related traits increases as compared to the additive model alone.Peer reviewe

GCAT|Panel, a comprehensive structural variant haplotype map of the Iberian population from high-coverage whole-genome sequencing

The combined analysis of haplotype panels with phenotype clinical cohorts is a common approach to explore the genetic architecture of human diseases. However, genetic studies are mainly based on single nucleotide variants (SNVs) and small insertions and deletions (indels). Here, we contribute to fill this gap by generating a dense haplotype map focused on the identification, characterization, and phasing of structural variants (SVs). By integrating multiple variant identification methods and Logistic Regression Models (LRMs), we present a catalogue of 35 431 441 variants, including 89 178 SVs (≥50 bp), 30 325 064 SNVs and 5 017 199 indels, across 785 Illumina high coverage (30x) whole-genomes from the Iberian GCAT Cohort, containing a median of 3.52M SNVs, 606 336 indels and 6393 SVs per individual. The haplotype panel is able to impute up to 14 360 728 SNVs/indels and 23 179 SVs, showing a 2.7-fold increase for SVs compared with available genetic variation panels. The value of this panel for SVs analysis is shown through an imputed rare Alu element located in a new locus associated with Mononeuritis of lower limb, a rare neuromuscular disease. This study represents the first deep characterization of genetic variation within the Iberian population and the first operational haplotype panel to systematically include the SVs into genome-wide genetic studies

Diagnosis of Primary Ciliary Dyskinesia by a Targeted Next-Generation Sequencing Panel: Molecular and Clinical Findings in Italian Patients

none12noPrimary ciliary dyskinesia (PCD) is a rare genetic disorder that alters mucociliary clearance, with consequent chronic disease of upper and lower airways. Diagnosis of PCD is challenging, and genetic testing is hampered by the high heterogeneity of the disease, because autosomal recessive causative mutations were found in 34 different genes. In this study, we clinically and molecularly characterized a cohort of 51 Italian patients with clinical signs of PCD. A custom next-generation sequencing panel that enables the affordable and simultaneous screening of 24 PCD genes was developed for genetic analysis. After variant filtering and prioritization, the molecular diagnosis of PCD was achieved in 43% of the patients. Overall, 5 homozygous and 27 compound heterozygous mutations, 21 of which were never reported before, were identified in 11 PCD genes. The DNAH5 and DNAH11 genes were the most common cause of PCD in Italy, but some population specificities were identified. In addition, the number of unsolved cases and the identification of only a single mutation in six patients suggest further genetic heterogeneity and invoke the need of novel strategies to detect unconventional pathogenic DNA variants. Finally, despite the availability of mutation databases and in silico prediction tools helping the interpretation of variants in next-generation sequencing screenings, a comprehensive segregation analysis is required to establish the in trans inheritance and support the pathogenic role of mutations.mixedBoaretto, Francesca; Snijders, Deborah; Salvoro, Cecilia; Spalletta, Ambra; Mostacciuolo, Maria Luisa; Collura, Mirella; Cazzato, Salvatore; Girosi, Donatella; Silvestri, Michela; Rossi, Giovanni Arturo; Barbato, Angelo; Vazza, GiovanniBoaretto, Francesca; Snijders, Deborah; Salvoro, Cecilia; Spalletta, Ambra; Mostacciuolo, MARIA LUISA; Collura, Mirella; Cazzato, Salvatore; Girosi, Donatella; Silvestri, Michela; Rossi, Giovanni Arturo; Barbato, Angelo; Vazza, Giovann

Diurnal preference, mood and the response to morning light in relation to polymorphisms in the human clock gene PER3

PER3 gene polymorphisms have been associated with differences in human sleep-wake phenotypes, and sensitivity to light. The aims of this study were to assess: i) the frequency of allelic variants at two PER3 polymorphic sites (rs57875989 length polymorphism: PER3 (4), PER3 (5); rs228697 SNP: PER3 (C), PER3 (G)) in relation to sleep-wake timing; ii) the effect of morning light on behavioural/circadian variables in PER3 (4) /PER3 (4) and PER3 (5) /PER3 (5) homozygotes. 786 Caucasian subjects living in Northern Italy donated buccal DNA and completed diurnal preference, sleep quality/timing and sleepiness/mood questionnaires. 19 PER3 (4) /PER3 (4) and 11 PER3 (5) /PER3 (5) homozygotes underwent morning light administration, whilst monitoring sleep-wake patterns and the urinary 6-sulphatoxymelatonin (aMT6s) rhythm. No significant relationship was observed between the length polymorphism and diurnal preference. By contrast, a significant association was observed between the PER3 (G) variant and morningness (OR\u2009=\u20092.10), and between the PER3 (G)-PER3 (4) haplotype and morningness (OR\u2009=\u20092.19), for which a mechanistic hypothesis is suggested. No significant differences were observed in sleep timing/aMT6s rhythms between PER3 (5) /PER3 (5) and PER3 (4) /PER3 (4) subjects at baseline. After light administration, PER3 (4) /PER3 (4) subjects advanced their aMT6s acrophase (p\u2009&lt;\u20090.05), and showed a trend of advanced sleep-wake timing. In conclusion, significant associations were observed between PER3 polymorphic variants/their combinations and both diurnal preference and the response to light