Publications by authors named "Chris Cotsapas"

47 Publications

Sex-Dependent Shared and Nonshared Genetic Architecture Across Mood and Psychotic Disorders.

Biol Psychiatry 2021 Mar 23. Epub 2021 Mar 23.

Department of Psychiatry and Behavioral Neuroscience, University of Chicago, Chicago, Illinois; Department of Psychiatry and Behavioral Sciences, North Shore University Health System, Evanston, Illinois.

Background: Sex differences in incidence and/or presentation of schizophrenia (SCZ), major depressive disorder (MDD), and bipolar disorder (BIP) are pervasive. Previous evidence for shared genetic risk and sex differences in brain abnormalities across disorders suggest possible shared sex-dependent genetic risk.

Methods: We conducted the largest to date genome-wide genotype-by-sex (G×S) interaction of risk for these disorders using 85,735 cases (33,403 SCZ, 19,924 BIP, and 32,408 MDD) and 109,946 controls from the PGC (Psychiatric Genomics Consortium) and iPSYCH.

Results: Across disorders, genome-wide significant single nucleotide polymorphism-by-sex interaction was detected for a locus encompassing NKAIN2 (rs117780815, p = 3.2 × 10), which interacts with sodium/potassium-transporting ATPase (adenosine triphosphatase) enzymes, implicating neuronal excitability. Three additional loci showed evidence (p < 1 × 10) for cross-disorder G×S interaction (rs7302529, p = 1.6 × 10; rs73033497, p = 8.8 × 10; rs7914279, p = 6.4 × 10), implicating various functions. Gene-based analyses identified G×S interaction across disorders (p = 8.97 × 10) with transcriptional inhibitor SLTM. Most significant in SCZ was a MOCOS gene locus (rs11665282, p = 1.5 × 10), implicating vascular endothelial cells. Secondary analysis of the PGC-SCZ dataset detected an interaction (rs13265509, p = 1.1 × 10) in a locus containing IDO2, a kynurenine pathway enzyme with immunoregulatory functions implicated in SCZ, BIP, and MDD. Pathway enrichment analysis detected significant G×S interaction of genes regulating vascular endothelial growth factor receptor signaling in MDD (false discovery rate-corrected p < .05).

Conclusions: In the largest genome-wide G×S analysis of mood and psychotic disorders to date, there was substantial genetic overlap between the sexes. However, significant sex-dependent effects were enriched for genes related to neuronal development and immune and vascular functions across and within SCZ, BIP, and MDD at the variant, gene, and pathway levels.
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http://dx.doi.org/10.1016/j.biopsych.2021.02.972DOI Listing
March 2021

Do monogenic inborn errors of immunity cause susceptibility to severe COVID-19?

J Clin Invest 2021 07;131(14)

Department of Pathology and Laboratory Medicine, Nationwide Children's Hospital, Columbus, Ohio, USA.

The SARS-CoV-2 virus, which causes COVID-19, has been associated globally with substantial morbidity and mortality. Numerous reports over the past year have described the clinical and immunological profiles of COVID-19 patients, and while some trends have emerged for risk stratification, they do not provide a complete picture. Therefore, efforts are ongoing to identify genetic susceptibility factors of severe disease. In this issue of the JCI, Povysil et al. performed a large, multiple-country study, sequencing genomes from patients with mild and severe COVID-19, along with population controls. Contrary to previous reports, the authors observed no enrichment of predicted loss-of-function variants in genes in the type I interferon pathway, which might predispose to severe disease. These studies suggest that more evidence is needed to substantiate the hypothesis for a genetic immune predisposition to severe COVID-19, and highlights the importance of considering experimental design when implicating a monogenic basis for severe disease.
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http://dx.doi.org/10.1172/JCI149459DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8279660PMC
July 2021

Birth characteristics and risk of febrile seizures.

Acta Neurol Scand 2021 Jul 6;144(1):51-57. Epub 2021 Apr 6.

Department of Economics and Business Economics, National Centre for Register-Based Research, Aarhus BSS, Aarhus University, Aarhus, Denmark.

Objective: Febrile seizure is a common childhood disorder that affects 2-5% of all children, and is associated with later development of epilepsy and psychiatric disorders. This study determines how the incidence of febrile seizures correlates with birth characteristics, age, sex and brain development.

Methods: This is a cohort study of all children born Denmark between 1977 and 2011 who were alive at 3 months of age (N = 2,103,232). The Danish National Patient Register was used to identify children with febrile seizures up to 5 years of age. Follow-up ended on 31 December 2016 when all cohort members had potentially reached 5 years of age.

Results: In total, 75,593 (3.59%, 95% CI: 3.57-3.62%) were diagnosed with febrile seizures. Incidence peaked at 16.7 months of age (median: 16.7 months, interquartile range: 12.5-24.0). The 5-year cumulative incidence of febrile seizures increased with decreasing birth weight (<1500 g; 5.42% (95% CI: 4.98-5.88% vs. 3,000-4,000 g; 3.53% (95% CI: 3.50-3.56%)) and with decreasing gestational age at birth (31-32 weeks; 5.90% (95% CI: 5.40-6.44%) vs. 39-40 weeks; 3.56% (95% CI: 3.53-3.60)). Lower gestational age at birth was associated with higher age at onset of a first febrile seizure; an association that essentially disappeared when correcting for age from conception.

Conclusions: The risk of febrile seizures increased with decreasing birth weight and gestational age at birth. The association between low gestational age at birth and age at first febrile seizure suggests that onset of febrile seizures is associated with the stage of brain development.
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http://dx.doi.org/10.1111/ane.13420DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8178233PMC
July 2021

Shared associations identify causal relationships between gene expression and immune cell phenotypes.

Commun Biol 2021 03 4;4(1):279. Epub 2021 Mar 4.

Department of Neurology, Yale School of Medicine, New Haven, CT, USA.

Genetic mapping studies have identified thousands of associations between common variants and hundreds of human traits. Translating these associations into mechanisms is complicated by two factors: they fall into gene regulatory regions; and they are rarely mapped to one causal variant. One way around these limitations is to find groups of traits that share associations, using this genetic link to infer a biological connection. Here, we assess how many trait associations in the same locus are due to the same genetic variant, and thus shared; and if these shared associations are due to causal relationships between traits. We find that only a subset of traits share associations, with many due to causal relationships rather than pleiotropy. We therefore suggest that simply observing overlapping associations at a genetic locus is insufficient to infer causality; direct evidence of shared associations is required to support mechanistic hypotheses in genetic studies of complex traits.
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http://dx.doi.org/10.1038/s42003-021-01823-wDOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7933159PMC
March 2021

Epilepsy risk in offspring of affected parents; a cohort study of the "maternal effect" in epilepsy.

Ann Clin Transl Neurol 2021 01 29;8(1):153-162. Epub 2020 Nov 29.

National Centre for Register-Based Research, Department of Economics and Business Economics, Aarhus BSS, Aarhus University, Aarhus, Denmark.

Objective: To assess whether the risk of epilepsy is higher in offspring of mothers with epilepsy than in offspring of fathers with epilepsy.

Methods: In a prospective population-based register study, we considered all singletons born in Denmark between 1981 and 2016 (N = 1,754,742). From the Danish National Patient Register since 1977, we identified epilepsy diagnoses in all study participants and their family members. Cox regression models were used to estimate hazard ratios (HRs) and corresponding 95% confidence intervals (CI), adjusted for relevant confounders.

Results: We included 1,754,742 individuals contributing > 30 million person-years of follow-up. The incidence rate of epilepsy in offspring of unaffected parents was 78.8 (95% CI: 77.8-79.8) per 100,000 person-years, while the corresponding rate in offspring with an affected father was 172 per 100,000 person-years (95% CI: 156-187) and in offspring with an affected mother was 260 per 100,000 person-years (95% CI: 243-277). Having an affected mother was associated with a 1.45-fold (95% CI: 1.30-1.63) higher risk of epilepsy in the offspring, compared to having an affected father. This maternal effect was found both in male (HR = 1.39, 95% CI: 1.19-1.62) and female offspring (HR = 1.53, 95% CI: 1.30-1.80), and across various ages at onset in the offspring. The maternal effect was also found in familial epilepsies (i.e. where the affected parent had an affected sibling; HR = 1.50, 95% CI: 1.04-2.16).

Interpretation: We found a clear maternal effect on offspring risk of epilepsy in this nationwide cohort study.
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http://dx.doi.org/10.1002/acn3.51258DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7818075PMC
January 2021

ImmuneRegulation: a web-based tool for identifying human immune regulatory elements.

Nucleic Acids Res 2019 07;47(W1):W142-W150

Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA.

Humans vary considerably both in their baseline and activated immune phenotypes. We developed a user-friendly open-access web portal, ImmuneRegulation, that enables users to interactively explore immune regulatory elements that drive cell-type or cohort-specific gene expression levels. ImmuneRegulation currently provides the largest centrally integrated resource on human transcriptome regulation across whole blood and blood cell types, including (i) ∼43,000 genotyped individuals with associated gene expression data from ∼51,000 experiments, yielding genetic variant-gene expression associations on ∼220 million eQTLs; (ii) 14 million transcription factor (TF)-binding region hits extracted from 1945 ChIP-seq studies; and (iii) the latest GWAS catalog with 67,230 published variant-trait associations. Users can interactively explore associations between queried gene(s) and their regulators (cis-eQTLs, trans-eQTLs or TFs) across multiple cohorts and studies. These regulators may explain genotype-dependent gene expression variations and be critical in selecting the ideal cohorts or cell types for follow-up studies or in developing predictive models. Overall, ImmuneRegulation significantly lowers the barriers between complex immune regulation data and researchers who want rapid, intuitive and high-quality access to the effects of regulatory elements on gene expression in multiple studies to empower investigators in translating these rich data into biological insights and clinical applications, and is freely available at https://immuneregulation.mssm.edu.
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http://dx.doi.org/10.1093/nar/gkz450DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6602512PMC
July 2019

Childhood seizures and risk of psychiatric disorders in adolescence and early adulthood: a Danish nationwide cohort study.

Lancet Child Adolesc Health 2019 02 7;3(2):99-108. Epub 2018 Dec 7.

National Center for Register-Based Research, Aarhus University, Aarhus, Denmark; Department of Neurology, Aarhus University Hospital, Aarhus, Denmark.

Background: Paediatric seizures have been linked to psychiatric disorders in childhood, but there is a paucity of large-scale population-based studies of psychiatric comorbidity in later life. We aimed to examine the relation between childhood seizures and the risk of psychiatric disorders in adolescence and early adulthood.

Methods: We did a register-based cohort study of all individuals born in Denmark in 1978-2002. Using diagnostic information from the Danish National Patient Register, all cohort members were categorised according to occurrence of febrile seizures and epilepsy, before entering the follow-up period on their 10th birthday. Individuals were followed up until onset of mental illness, death, emigration, or the end of the study period on Dec 31, 2012. Cox regression analyses were used to estimate the risk of five predefined groups of psychiatric disorders (substance abuse disorders, schizophrenia, mood disorder, anxiety, and personality disorder), separately and combined. Models were adjusted for relevant confounders.

Findings: Between Jan 1, 1978, and Dec 31, 2002, 1 291 679 individuals were born in Denmark and followed up in our population cohort (approximately 15 million person-years). 43 148 individuals had a history of febrile seizures, 10 355 had epilepsy, and 1696 had both these disorders. 83 735 (6%) cohort members were identified with at least one of the psychiatric disorders of interest. The risk of any psychiatric disorder was raised in individuals with a history of febrile seizures (hazard ratio [HR] 1·12, 95% CI 1·08-1·17), epilepsy (1·34, 1·25-1·44), or both disorders (1·50, 1·28-1·75). Excess risk of psychiatric illness associated with childhood seizures was present across a range of different disorders, most notably schizophrenia but also anxiety and mood disorders. Associations did not differ between males and females (p=0·30) but increased with a growing number of admissions for febrile seizures (p<0·0001) and with later onset of childhood epilepsy (p<0·0001).

Interpretation: Children with epilepsy and febrile seizures-with and without concomitant epilepsy-are at increased risk of developing a broad range of psychiatric disorders in later life. Clarification of the underlying mechanisms attributable to these associations is needed to identify potential options for prevention.

Funding: Novo Nordisk Foundation, Danish Epilepsy Association, Central Denmark Region, Lundbeck Foundation, and Stanley Medical Research Institute.
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http://dx.doi.org/10.1016/S2352-4642(18)30351-1DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6903917PMC
February 2019

Erratum: Genome-wide association studies of multiple sclerosis.

Clin Transl Immunology 2018 16;7(8):e1038. Epub 2018 Aug 16.

[This corrects the article DOI: 10.1002/cti2.1018.].
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http://dx.doi.org/10.1002/cti2.1038DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6095721PMC
August 2018

Analysis of shared heritability in common disorders of the brain.

Science 2018 06;360(6395)

Department of Neuroscience, Icahn School of Medicine at Mount Sinai, New York, NY, USA.

Disorders of the brain can exhibit considerable epidemiological comorbidity and often share symptoms, provoking debate about their etiologic overlap. We quantified the genetic sharing of 25 brain disorders from genome-wide association studies of 265,218 patients and 784,643 control participants and assessed their relationship to 17 phenotypes from 1,191,588 individuals. Psychiatric disorders share common variant risk, whereas neurological disorders appear more distinct from one another and from the psychiatric disorders. We also identified significant sharing between disorders and a number of brain phenotypes, including cognitive measures. Further, we conducted simulations to explore how statistical power, diagnostic misclassification, and phenotypic heterogeneity affect genetic correlations. These results highlight the importance of common genetic variation as a risk factor for brain disorders and the value of heritability-based methods in understanding their etiology.
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http://dx.doi.org/10.1126/science.aap8757DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6097237PMC
June 2018

Genome-wide association studies of multiple sclerosis.

Clin Transl Immunology 2018 31;7(6):e1018. Epub 2018 May 31.

Departments of Neurology and Genetics Yale School of Medicine New Haven CT USA.

Large-scale genetic studies of multiple sclerosis have identified over 230 risk effects across the human genome, making it a prototypical common disease with complex genetic architecture. Here, after a brief historical background on the discovery and definition of the disease, we summarise the last fifteen years of genetic discoveries and map out the challenges that remain to translate these findings into an aetiological framework and actionable clinical understanding.
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http://dx.doi.org/10.1002/cti2.1018DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5983059PMC
May 2018

Multiple sclerosis.

Handb Clin Neurol 2018 ;148:723-730

Department of Neurology, Yale School of Medicine, New Haven, CT, United States.

Multiple sclerosis is a potentially progressive, autoimmune neurologic disorder of the central nervous system, resulting from an autoimmune attack on central nervous system white matter. It is a leading cause of neurologic symptoms in young adults, with no known cure. Emerging disease-modifying therapies aim to control symptoms, with increasingly sophisticated immune function modulation. Though several environmental exposures increase the risk of developing the disease, a large fraction of overall risk is heritable and can be attributed to hundreds of common genetic variants influencing gene regulation in specific immune subsets. Here, we review the history of the disease, the realization that risk is heritable, and the recent revelation of hundreds of genetic variants driving this risk by international consortia studying tens of thousands of patients. Finally, we discuss how these results are revealing the specific pathobiology of multiple sclerosis and how this knowledge is transforming drug discovery.
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http://dx.doi.org/10.1016/B978-0-444-64076-5.00046-6DOI Listing
August 2018

Microbiota control immune regulation in humanized mice.

JCI Insight 2017 11 2;2(21). Epub 2017 Nov 2.

Department of Immunobiology.

The microbiome affects development and activity of the immune system, and may modulate immune therapies, but there is little direct information about this control in vivo. We studied how the microbiome affects regulation of human immune cells in humanized mice. When humanized mice were treated with a cocktail of 4 antibiotics, there was an increase in the frequency of effector T cells in the gut wall, circulating levels of IFN-γ, and appearance of anti-nuclear antibodies. Teplizumab, a non-FcR-binding anti-CD3ε antibody, no longer delayed xenograft rejection. An increase in CD8+ central memory cells and IL-10, markers of efficacy of teplizumab, were not induced. IL-10 levels were only decreased when the mice were treated with all 4 but not individual antibiotics. Antibiotic treatment affected CD11b+CD11c+ cells, which produced less IL-10 and IL-27, and showed increased expression of CD86 and activation of T cells when cocultured with T cells and teplizumab. Soluble products in the pellets appeared to be responsible for the reduced IL-27 expression in DCs. Similar changes in IL-10 induction were seen when human peripheral blood mononuclear cells were cultured with human stool samples. We conclude that changes in the microbiome may impact the efficacy of immunosuppressive medications by altering immune regulatory pathways.
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http://dx.doi.org/10.1172/jci.insight.91709DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5752290PMC
November 2017

Integrative Genetic and Epigenetic Analysis Uncovers Regulatory Mechanisms of Autoimmune Disease.

Am J Hum Genet 2017 Jul;101(1):75-86

Department of Neurology, Yale School of Medicine, New Haven, CT 06511, USA; Program in Medical and Population Genetics and Stanley Center for Psychiatric Research, Broad Institute of Harvard and MIT, Cambridge, MA 02142, USA; Department of Genetics, Yale School of Medicine, New Haven, CT 06520, USA. Electronic address:

Genome-wide association studies in autoimmune and inflammatory diseases (AID) have uncovered hundreds of loci mediating risk. These associations are preferentially located in non-coding DNA regions and in particular in tissue-specific DNase I hypersensitivity sites (DHSs). While these analyses clearly demonstrate the overall enrichment of disease risk alleles on gene regulatory regions, they are not designed to identify individual regulatory regions mediating risk or the genes under their control, and thus uncover the specific molecular events driving disease risk. To do so we have departed from standard practice by identifying regulatory regions which replicate across samples and connect them to the genes they control through robust re-analysis of public data. We find significant evidence of regulatory potential in 78/301 (26%) risk loci across nine autoimmune and inflammatory diseases, and we find that individual genes are targeted by these effects in 53/78 (68%) of these. Thus, we are able to generate testable mechanistic hypotheses of the molecular changes that drive disease risk.
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http://dx.doi.org/10.1016/j.ajhg.2017.06.001DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5501874PMC
July 2017

Large-Scale trans-eQTLs Affect Hundreds of Transcripts and Mediate Patterns of Transcriptional Co-regulation.

Am J Hum Genet 2017 Apr 9;100(4):581-591. Epub 2017 Mar 9.

Department of Neurology, Yale University School of Medicine, New Haven, CT 06520, USA; Program in Medical and Population Genetics, Broad Institute, Cambridge, MA 02142, USA; Department of Genetics, Yale University School of Medicine, New Haven, CT 06520, USA. Electronic address:

Efforts to decipher the causal relationships between differences in gene regulation and corresponding differences in phenotype have been stymied by several basic technical challenges. Although detecting local, cis-eQTLs is now routine, trans-eQTLs, which are distant from the genes of origin, are far more difficult to find because millions of SNPs must currently be compared to thousands of transcripts. Here, we demonstrate an alternative approach: we looked for SNPs associated with the expression of many genes simultaneously and found that hundreds of trans-eQTLs each affect hundreds of transcripts in lymphoblastoid cell lines across three African populations. These trans-eQTLs target the same genes across the three populations and show the same direction of effect. We discovered that target transcripts of a high-confidence set of trans-eQTLs encode proteins that interact more frequently than expected by chance, are bound by the same transcription factors, and are enriched for pathway annotations indicative of roles in basic cell homeostasis. We thus demonstrate that our approach can uncover trans-acting transcriptional control circuits that affect co-regulated groups of genes: a key to understanding how cellular pathways and processes are orchestrated.
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http://dx.doi.org/10.1016/j.ajhg.2017.02.004DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5384037PMC
April 2017

Limited statistical evidence for shared genetic effects of eQTLs and autoimmune-disease-associated loci in three major immune-cell types.

Nat Genet 2017 Apr 20;49(4):600-605. Epub 2017 Feb 20.

Broad Institute of Harvard and MIT, Cambridge, Massachusetts, USA.

Most autoimmune-disease-risk effects identified by genome-wide association studies (GWAS) localize to open chromatin with gene-regulatory activity. GWAS loci are also enriched in expression quantitative trait loci (eQTLs), thus suggesting that most risk variants alter gene expression. However, because causal variants are difficult to identify, and cis-eQTLs occur frequently, it remains challenging to identify specific instances of disease-relevant changes to gene regulation. Here, we used a novel joint likelihood framework with higher resolution than that of previous methods to identify loci where autoimmune-disease risk and an eQTL are driven by a single shared genetic effect. Using eQTLs from three major immune subpopulations, we found shared effects in only ∼25% of the loci examined. Thus, we show that a fraction of gene-regulatory changes suggest strong mechanistic hypotheses for disease risk, but we conclude that most risk mechanisms are not likely to involve changes in basal gene expression.
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http://dx.doi.org/10.1038/ng.3795DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5374036PMC
April 2017

Novel determinants of mammalian primary microRNA processing revealed by systematic evaluation of hairpin-containing transcripts and human genetic variation.

Genome Res 2017 03 13;27(3):374-384. Epub 2017 Jan 13.

Department of Genetics, Yale University School of Medicine, New Haven, Connecticut 06510, USA.

Mature microRNAs (miRNAs) are processed from hairpin-containing primary miRNAs (pri-miRNAs). However, rules that distinguish pri-miRNAs from other hairpin-containing transcripts in the genome are incompletely understood. By developing a computational pipeline to systematically evaluate 30 structural and sequence features of mammalian RNA hairpins, we report several new rules that are preferentially utilized in miRNA hairpins and govern efficient pri-miRNA processing. We propose that a hairpin stem length of 36 ± 3 nt is optimal for pri-miRNA processing. We identify two bulge-depleted regions on the miRNA stem, located ∼16-21 nt and ∼28-32 nt from the base of the stem, that are less tolerant of unpaired bases. We further show that the CNNC primary sequence motif selectively enhances the processing of optimal-length hairpins. We predict that a small but significant fraction of human single-nucleotide polymorphisms (SNPs) alter pri-miRNA processing, and confirm several predictions experimentally including a disease-causing mutation. Our study enhances the rules governing mammalian pri-miRNA processing and suggests a diverse impact of human genetic variation on miRNA biogenesis.
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http://dx.doi.org/10.1101/gr.208900.116DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5340965PMC
March 2017

Network Analysis of Genome-Wide Selective Constraint Reveals a Gene Network Active in Early Fetal Brain Intolerant of Mutation.

PLoS Genet 2016 06 15;12(6):e1006121. Epub 2016 Jun 15.

Department of Neurology, Yale School of Medicine, New Haven Connecticut, United States of America.

Using robust, integrated analysis of multiple genomic datasets, we show that genes depleted for non-synonymous de novo mutations form a subnetwork of 72 members under strong selective constraint. We further show this subnetwork is preferentially expressed in the early development of the human hippocampus and is enriched for genes mutated in neurological Mendelian disorders. We thus conclude that carefully orchestrated developmental processes are under strong constraint in early brain development, and perturbations caused by mutation have adverse outcomes subject to strong purifying selection. Our findings demonstrate that selective forces can act on groups of genes involved in the same process, supporting the notion that purifying selection can act coordinately on multiple genes. Our approach provides a statistically robust, interpretable way to identify the tissues and developmental times where groups of disease genes are active.
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http://dx.doi.org/10.1371/journal.pgen.1006121DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4909280PMC
June 2016

Progress and challenges for treating Type 1 diabetes.

J Autoimmun 2016 07 17;71:1-9. Epub 2016 May 17.

Department of Immunobiology, Yale University, New Haven, CT, USA; Department of Internal Medicine, Yale University, New Haven, CT, USA.

It has been more than 30 years since the initial trials of Cyclosporin A to treat patients with new onset Type 1 diabetes (T1D). Since that time, there have been insights into genetic predisposition to the disease, the failures of immune tolerance, and mechanisms that cause the immune mediated β cell destruction. The genetic loci associated affect lymphocyte development and tolerance mechanisms. Discoveries related to the roles of specific immune responses gene such as the major histocompatibility complex, PTPN22, CTLA-4, IL-2RA, as well as the mechanisms of antigen presentation in the thymus have suggested ways in which autoreactivity may follow changes in the functions of these genes that are associated with risk. Antigens that are recognized by the immune system in patients with T1D have been identified. With this information, insights into the novel cellular mechanisms leading to the initiation and orchestration of β cell killing have been developed such as the presentation of unique antigens within the islets. Clinical trials have been performed, some of which have shown efficacy in improving β cell function but none have been able to permanently prevent loss of insulin secretion. The reasons for the lack of long term success are not clear but may include the heterogeneity of the immune response and in individual responses to immune therapies, recurrence of autoimmunity after the initial effects of the therapies, or even intrinsic mechanisms of β cell death that proceeds independently of immune attack after initiation of the disease. In this review, we cover developments that have led to new therapeutics and characteristics of patients who may show the most benefits from therapies. We also identify areas of incomplete understanding that might be addressed to develop more effective therapeutic strategies.
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http://dx.doi.org/10.1016/j.jaut.2016.04.004DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4903889PMC
July 2016

Genetic analysis for a shared biological basis between migraine and coronary artery disease.

Neurol Genet 2015 Jun 2;1(1):e10. Epub 2015 Jul 2.

Author affiliations are provided at the end of the article.

Objective: To apply genetic analysis of genome-wide association data to study the extent and nature of a shared biological basis between migraine and coronary artery disease (CAD).

Methods: Four separate methods for cross-phenotype genetic analysis were applied on data from 2 large-scale genome-wide association studies of migraine (19,981 cases, 56,667 controls) and CAD (21,076 cases, 63,014 controls). The first 2 methods quantified the extent of overlapping risk variants and assessed the load of CAD risk loci in migraineurs. Genomic regions of shared risk were then identified by analysis of covariance patterns between the 2 phenotypes and by querying known genome-wide significant loci.

Results: We found a significant overlap of genetic risk loci for migraine and CAD. When stratified by migraine subtype, this was limited to migraine without aura, and the overlap was protective in that patients with migraine had a lower load of CAD risk alleles than controls. Genes indicated by 16 shared risk loci point to mechanisms with potential roles in migraine pathogenesis and CAD, including endothelial dysfunction (PHACTR1) and insulin homeostasis (GIP).

Conclusions: The results suggest that shared biological processes contribute to risk of migraine and CAD, but surprisingly this commonality is restricted to migraine without aura and the impact is in opposite directions. Understanding the mechanisms underlying these processes and their opposite relationship to migraine and CAD may improve our understanding of both disorders.
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http://dx.doi.org/10.1212/NXG.0000000000000010DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4821079PMC
June 2015

Survey of variation in human transcription factors reveals prevalent DNA binding changes.

Science 2016 Mar 24;351(6280):1450-1454. Epub 2016 Mar 24.

Division of Genetics, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA 02115, USA.

Sequencing of exomes and genomes has revealed abundant genetic variation affecting the coding sequences of human transcription factors (TFs), but the consequences of such variation remain largely unexplored. We developed a computational, structure-based approach to evaluate TF variants for their impact on DNA binding activity and used universal protein-binding microarrays to assay sequence-specific DNA binding activity across 41 reference and 117 variant alleles found in individuals of diverse ancestries and families with Mendelian diseases. We found 77 variants in 28 genes that affect DNA binding affinity or specificity and identified thousands of rare alleles likely to alter the DNA binding activity of human sequence-specific TFs. Our results suggest that most individuals have unique repertoires of TF DNA binding activities, which may contribute to phenotypic variation.
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http://dx.doi.org/10.1126/science.aad2257DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4825693PMC
March 2016

Regulatory polymorphisms modulate the expression of HLA class II molecules and promote autoimmunity.

Elife 2016 Feb 15;5. Epub 2016 Feb 15.

Department of Immunology, University of Texas Southwestern Medical Center, Dallas, United States.

Targeted sequencing of sixteen SLE risk loci among 1349 Caucasian cases and controls produced a comprehensive dataset of the variations causing susceptibility to systemic lupus erythematosus (SLE). Two independent disease association signals in the HLA-D region identified two regulatory regions containing 3562 polymorphisms that modified thirty-seven transcription factor binding sites. These extensive functional variations are a new and potent facet of HLA polymorphism. Variations modifying the consensus binding motifs of IRF4 and CTCF in the XL9 regulatory complex modified the transcription of HLA-DRB1, HLA-DQA1 and HLA-DQB1 in a chromosome-specific manner, resulting in a 2.5-fold increase in the surface expression of HLA-DR and DQ molecules on dendritic cells with SLE risk genotypes, which increases to over 4-fold after stimulation. Similar analyses of fifteen other SLE risk loci identified 1206 functional variants tightly linked with disease-associated SNPs and demonstrated that common disease alleles contain multiple causal variants modulating multiple immune system genes.
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http://dx.doi.org/10.7554/eLife.12089DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4811771PMC
February 2016

Changes in T-cell subsets identify responders to FcR-nonbinding anti-CD3 mAb (teplizumab) in patients with type 1 diabetes.

Eur J Immunol 2016 Jan 14;46(1):230-41. Epub 2015 Dec 14.

Department of Immunobiology, Yale School of Medicine, New Haven, CT, USA.

The mechanisms whereby immune therapies affect progression of type 1 diabetes (T1D) are not well understood. Teplizumab, an FcR nonbinding anti-CD3 mAb, has shown efficacy in multiple randomized clinical trials. We previously reported an increase in the frequency of circulating CD8(+) central memory (CD8CM) T cells in clinical responders, but the generalizability of this finding and the molecular effects of teplizumab on these T cells have not been evaluated. We analyzed data from two randomized clinical studies of teplizumab in patients with new- and recent-onset T1D. At the conclusion of therapy, clinical responders showed a significant reduction in circulating CD4(+) effector memory T cells. Afterward, there was an increase in the frequency and absolute number of CD8CM T cells. In vitro, teplizumab expanded CD8CM T cells by proliferation and conversion of non-CM T cells. Nanostring analysis of gene expression of CD8CM T cells from responders and nonresponders versus placebo-treated control subjects identified decreases in expression of genes associated with immune activation and increases in expression of genes associated with T-cell differentiation and regulation. We conclude that CD8CM T cells with decreased activation and regulatory gene expression are associated with clinical responses to teplizumab in patients with T1D.
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http://dx.doi.org/10.1002/eji.201545708DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4882099PMC
January 2016

Class II HLA interactions modulate genetic risk for multiple sclerosis.

Nat Genet 2015 Oct 7;47(10):1107-1113. Epub 2015 Sep 7.

Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden.

Association studies have greatly refined the understanding of how variation within the human leukocyte antigen (HLA) genes influences risk of multiple sclerosis. However, the extent to which major effects are modulated by interactions is poorly characterized. We analyzed high-density SNP data on 17,465 cases and 30,385 controls from 11 cohorts of European ancestry, in combination with imputation of classical HLA alleles, to build a high-resolution map of HLA genetic risk and assess the evidence for interactions involving classical HLA alleles. Among new and previously identified class II risk alleles (HLA-DRB1*15:01, HLA-DRB1*13:03, HLA-DRB1*03:01, HLA-DRB1*08:01 and HLA-DQB1*03:02) and class I protective alleles (HLA-A*02:01, HLA-B*44:02, HLA-B*38:01 and HLA-B*55:01), we find evidence for two interactions involving pairs of class II alleles: HLA-DQA1*01:01-HLA-DRB1*15:01 and HLA-DQB1*03:01-HLA-DQB1*03:02. We find no evidence for interactions between classical HLA alleles and non-HLA risk-associated variants and estimate a minimal effect of polygenic epistasis in modulating major risk alleles.
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http://dx.doi.org/10.1038/ng.3395DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4874245PMC
October 2015

Genetic variants associated with autoimmunity drive NFκB signaling and responses to inflammatory stimuli.

Sci Transl Med 2015 Jun;7(291):291ra93

Department of Neurology and Immunobiology, Yale School of Medicine, New Haven, CT 06511, USA. Broad Institute of Harvard University and Massachusetts Institute of Technology, Cambridge, MA 02142, USA.

The transcription factor nuclear factor κB (NFκB) is a central regulator of inflammation, and genome-wide association studies in subjects with autoimmune disease have identified a number of variants within the NFκB signaling cascade. In addition, causal variant fine-mapping has demonstrated that autoimmune disease susceptibility variants for multiple sclerosis (MS) and ulcerative colitis are strongly enriched within binding sites for NFκB. We report that MS-associated variants proximal to NFκB1 and in an intron of TNFRSF1A (TNFR1) are associated with increased NFκB signaling after tumor necrosis factor-α (TNFα) stimulation. Both variants result in increased degradation of inhibitor of NFκB α (IκBα), a negative regulator of NFκB, and nuclear translocation of p65 NFκB. The variant proximal to NFκB1 controls signaling responses by altering the expression of NFκB itself, with the GG risk genotype expressing 20-fold more p50 NFκB and diminished expression of the negative regulators of the NFκB pathway: TNFα-induced protein 3 (TNFAIP3), B cell leukemia 3 (BCL3), and cellular inhibitor of apoptosis 1 (CIAP1). Finally, naïve CD4 T cells from patients with MS express enhanced activation of p65 NFκB. These results demonstrate that genetic variants associated with risk of developing MS alter NFκB signaling pathways, resulting in enhanced NFκB activation and greater responsiveness to inflammatory stimuli. As such, this suggests that rapid genetic screening for variants associated with NFκB signaling may identify individuals amenable to NFκB or cytokine blockade.
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http://dx.doi.org/10.1126/scitranslmed.aaa9223DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4574294PMC
June 2015

Shared genetic basis for migraine and ischemic stroke: A genome-wide analysis of common variants.

Neurology 2015 May 1;84(21):2132-45. Epub 2015 May 1.

Author affiliations are provided at the end of the article.

Objective: To quantify genetic overlap between migraine and ischemic stroke (IS) with respect to common genetic variation.

Methods: We applied 4 different approaches to large-scale meta-analyses of genome-wide data on migraine (23,285 cases and 95,425 controls) and IS (12,389 cases and 62,004 controls). First, we queried known genome-wide significant loci for both disorders, looking for potential overlap of signals. We then analyzed the overall shared genetic load using polygenic scores and estimated the genetic correlation between disease subtypes using data derived from these models. We further interrogated genomic regions of shared risk using analysis of covariance patterns between the 2 phenotypes using cross-phenotype spatial mapping.

Results: We found substantial genetic overlap between migraine and IS using all 4 approaches. Migraine without aura (MO) showed much stronger overlap with IS and its subtypes than migraine with aura (MA). The strongest overlap existed between MO and large artery stroke (LAS; p = 6.4 × 10(-28) for the LAS polygenic score in MO) and between MO and cardioembolic stroke (CE; p = 2.7 × 10(-20) for the CE score in MO).

Conclusions: Our findings indicate shared genetic susceptibility to migraine and IS, with a particularly strong overlap between MO and both LAS and CE pointing towards shared mechanisms. Our observations on MA are consistent with a limited role of common genetic variants in this subtype.
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http://dx.doi.org/10.1212/WNL.0000000000001606DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4451048PMC
May 2015

Analysis of immune-related loci identifies 48 new susceptibility variants for multiple sclerosis.

Nat Genet 2013 Nov 29;45(11):1353-60. Epub 2013 Sep 29.

1] John P. Hussman Institute for Human Genomics, University of Miami, Miller School of Medicine, Miami, Florida, USA. [2].

Using the ImmunoChip custom genotyping array, we analyzed 14,498 subjects with multiple sclerosis and 24,091 healthy controls for 161,311 autosomal variants and identified 135 potentially associated regions (P < 1.0 × 10(-4)). In a replication phase, we combined these data with previous genome-wide association study (GWAS) data from an independent 14,802 subjects with multiple sclerosis and 26,703 healthy controls. In these 80,094 individuals of European ancestry, we identified 48 new susceptibility variants (P < 5.0 × 10(-8)), 3 of which we found after conditioning on previously identified variants. Thus, there are now 110 established multiple sclerosis risk variants at 103 discrete loci outside of the major histocompatibility complex. With high-resolution Bayesian fine mapping, we identified five regions where one variant accounted for more than 50% of the posterior probability of association. This study enhances the catalog of multiple sclerosis risk variants and illustrates the value of fine mapping in the resolution of GWAS signals.
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http://dx.doi.org/10.1038/ng.2770DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3832895PMC
November 2013

Protein array-based profiling of CSF identifies RBPJ as an autoantigen in multiple sclerosis.

Neurology 2013 Sep 6;81(11):956-63. Epub 2013 Aug 6.

From the Department of Neurology (L.Q., P.L.C., M.A.B., C.C., D.A.H., J.-Y.L., K.C.O.), Human and Translational Immunology Program (D.A.H., K.C.O.), Department of Genetics (C.C.), Department of Pathology (S.H.K., G.Y.), and Department of Immunobiology (D.A.H.), Yale School of Medicine, New Haven, CT; Neuromuscular Diseases Unit (L.Q.), Hospital de la Santa Creu i Sant Pau, Universitat Autónoma de Barcelona, Spain; Medical and Population Genetics (C.C.), Broad Institute of MIT and Harvard, Cambridge, MA; Department of Neurology (A.H.C.), Washington University School of Medicine, St. Louis, MO; Interdepartmental Program in Computational Biology and Bioinformatics (S.H.K.), Yale University, New Haven, CT; and Department of Neurology (S.N.W.), Harvard Medical School and Brigham and Women's Hospital, Boston, MA. Simon N. Willis is currently affiliated with the Walter and Eliza Hall Institute of Medical Research, Parkville, Australia.

Objective: To profile the reactivity of CSF-derived immunoglobulin from patients with multiple sclerosis (MS) against a large panel of antigens, to identify disease-specific reactivities.

Methods: CSF from subjects with MS with elevated immunoglobulin G and CSF from control subjects presenting with other inflammatory neurologic disease were screened against a protein array consisting of 9,393 proteins. Reactivity to a candidate protein identified using these arrays was confirmed with ELISA and immunocytochemistry.

Results: Autoantibodies against one protein on the array, recombination signal binding protein for immunoglobulin kappa J region (RBPJ), discriminated between patients with MS and controls (p = 0.0052). Using a large validation cohort, we found a higher prevalence of autoantibodies against RBPJ in the CSF of patients with MS (12.5%) compared with the CSF of patients with other neurologic diseases (1.6%; p = 0.02) by ELISA. This difference in reactivity was restricted to the CSF as serum reactivity against RBPJ did not differ between patients and controls. The presence of CSF autoantibodies against RBPJ was further confirmed by immunocytochemistry.

Conclusions: These data indicate that RBPJ, a ubiquitous protein of the Notch signaling pathway that plays an important role in Epstein-Barr virus infection, is a novel MS autoantigen candidate that is recognized by CSF-derived immunoglobulin G in a subset of patients with MS.
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http://dx.doi.org/10.1212/WNL.0b013e3182a43b48DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3888197PMC
September 2013

Pleiotropy in complex traits: challenges and strategies.

Nat Rev Genet 2013 Jul 11;14(7):483-95. Epub 2013 Jun 11.

Center for Human Genetics Research, Massachusetts General Hospital, 185 Cambridge Street, Boston, Massachusetts 02114, USA.

Genome-wide association studies have identified many variants that each affects multiple traits, particularly across autoimmune diseases, cancers and neuropsychiatric disorders, suggesting that pleiotropic effects on human complex traits may be widespread. However, systematic detection of such effects is challenging and requires new methodologies and frameworks for interpreting cross-phenotype results. In this Review, we discuss the evidence for pleiotropy in contemporary genetic mapping studies, new and established analytical approaches to identifying pleiotropic effects, sources of spurious cross-phenotype effects and study design considerations. We also outline the molecular and clinical implications of such findings and discuss future directions of research.
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http://dx.doi.org/10.1038/nrg3461DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4104202PMC
July 2013

Weight loss after gastric bypass is associated with a variant at 15q26.1.

Am J Hum Genet 2013 May;92(5):827-34

Obesity, Metabolism, and Nutrition Institute and Gastrointestinal Unit, Massachusetts General Hospital, Boston, MA 02114, USA.

The amount of weight loss attained after Roux-en-Y gastric bypass (RYGB) surgery follows a wide and normal distribution, and recent evidence indicates that this weight loss is due to physiological, rather than mechanical, mechanisms. To identify potential genetic factors associated with weight loss after RYGB, we performed a genome-wide association study (GWAS) of 693 individuals undergoing RYGB and then replicated this analysis in an independent population of 327 individuals undergoing RYGB. We found that a 15q26.1 locus near ST8SIA2 and SLCO3A1 was significantly associated with weight loss after RYGB. Expression of ST8SIA2 in omental fat of these individuals at baseline was significantly associated with weight loss after RYGB. Gene expression analysis in RYGB and weight-matched, sham-operated (WMS) mice revealed that expression of St8sia2 and Slco3a1 was significantly altered in metabolically active tissues in RYGB-treated compared to WMS mice. These findings provide strong evidence for specific genetic influences on weight loss after RYGB and underscore the biological nature of the response to RYGB.
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http://dx.doi.org/10.1016/j.ajhg.2013.04.009DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3644642PMC
May 2013

Unraveling multiple MHC gene associations with systemic lupus erythematosus: model choice indicates a role for HLA alleles and non-HLA genes in Europeans.

Am J Hum Genet 2012 Nov 18;91(5):778-93. Epub 2012 Oct 18.

Divisions of Genetics and Molecular Medicine and Immunology, Infection and Inflammatory Disease, King's College London, London, UK.

We have performed a meta-analysis of the major-histocompatibility-complex (MHC) region in systemic lupus erythematosus (SLE) to determine the association with both SNPs and classical human-leukocyte-antigen (HLA) alleles. More specifically, we combined results from six studies and well-known out-of-study control data sets, providing us with 3,701 independent SLE cases and 12,110 independent controls of European ancestry. This study used genotypes for 7,199 SNPs within the MHC region and for classical HLA alleles (typed and imputed). Our results from conditional analysis and model choice with the use of the Bayesian information criterion show that the best model for SLE association includes both classical loci (HLA-DRB1(∗)03:01, HLA-DRB1(∗)08:01, and HLA-DQA1(∗)01:02) and two SNPs, rs8192591 (in class III and upstream of NOTCH4) and rs2246618 (MICB in class I). Our approach was to perform a stepwise search from multiple baseline models deduced from a priori evidence on HLA-DRB1 lupus-associated alleles, a stepwise regression on SNPs alone, and a stepwise regression on HLA alleles. With this approach, we were able to identify a model that was an overwhelmingly better fit to the data than one identified by simple stepwise regression either on SNPs alone (Bayes factor [BF] > 50) or on classical HLA alleles alone (BF > 1,000).
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http://dx.doi.org/10.1016/j.ajhg.2012.08.026DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3487133PMC
November 2012
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