Evidence map›Paper›PMID 31289819›Full record

SynthesisBrain : a journal of neurology2019

Early complement genes are associated with visual system degeneration in multiple sclerosis.

Kathryn C Fitzgerald, Kicheol Kim, Matthew D Smith, Sean A Aston, Nicholas Fioravante, Alissa M Rothman, Stephen Krieger, Stacey S Cofield, Dorlan J Kimbrough, Pavan Bhargava and 9 more

Open access · bronzeAbstract readMeta-Analysis
In one paragraph

Synthesis in Brain : a journal of neurology, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 31 papers.

0numbers the graph read from it
0cells of the map it votes in
31citing papers in PubMed
2.0field-weighted citation impact, top 13% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

31 citing papers in PubMed, 49 citations in OpenAlex.

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  15. C1q and central nervous system disorders.Frontiers in immunology · 2023
    Review
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

19 authors at 6 institutions in 1 country.

Kathryn C FitzgeraldDepartment of Neurology, Johns Hopkins School of Medicine, Baltimore, MD, USA.
Kicheol KimDepartment of Neurology, University of California San Francisco, San Francisco, CA, USA.
Matthew D SmithDepartment of Neurology, Johns Hopkins School of Medicine, Baltimore, MD, USA.
Sean A AstonDepartment of Neurology, Johns Hopkins School of Medicine, Baltimore, MD, USA.
Nicholas FioravanteDepartment of Neurology, Johns Hopkins School of Medicine, Baltimore, MD, USA.
Alissa M RothmanDepartment of Neurology, Johns Hopkins School of Medicine, Baltimore, MD, USA.
Stephen KriegerDepartment of Neurology, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
Stacey S CofieldDepartment of Biostatistics, University of Alabama at Birmingham, Birmingham, AL, USA.
Dorlan J KimbroughDepartment of Neurology, Harvard Medical School, Boston, MA, USA.
Pavan BhargavaDepartment of Neurology, Johns Hopkins School of Medicine, Baltimore, MD, USA.
Shiv SaidhaDepartment of Neurology, Johns Hopkins School of Medicine, Baltimore, MD, USA.
Katharine A WhartenbyDepartment of Neurology, Johns Hopkins School of Medicine, Baltimore, MD, USA.
Ari J GreenDepartment of Neurology, University of California San Francisco, San Francisco, CA, USA.
Ellen M MowryDepartment of Neurology, Johns Hopkins School of Medicine, Baltimore, MD, USA.
Gary R CutterDepartment of Biostatistics, University of Alabama at Birmingham, Birmingham, AL, USA.
Fred D LublinDepartment of Neurology, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
Sergio E BaranziniDepartment of Neurology, University of California San Francisco, San Francisco, CA, USA.
Philip L De JagerCenter for Translational and Computational Neuroimmunology, Department of Neurology, College of Physicians and Surgeons, Columbia University, New York, NY, USA.
Peter A CalabresiDepartment of Neurology, Johns Hopkins School of Medicine, Baltimore, MD, USA.
Johns Hopkins University · USUniversity of California, San Francisco · USIcahn School of Medicine at Mount Sinai · USUniversity of Alabama at Birmingham · USBroad Institute · USHarvard University · US

Funding

Extension of Combination Therapy for Multiple Sclerosis (eCombiRx)U01NS045719 · NINDS · MOUNT SINAI SCHOOL OF MEDICINE OF NYU · PI LUBLIN, FRED D · 2003 to 2012
$44.7M
Imaging Neurodegeneration in Multiple SclerosisR01NS082347 · NINDS · JOHNS HOPKINS UNIVERSITY · PI PETER A CALABRESI, Shiv Saidha · 2013 to 2026
$7.0M
Post GWAS approach to identify cell-specific genetic pathways underlying MS riskR01NS088155 · NINDS · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI BARANZINI, SERGIO E · 2014 to 2018
$2.2M
Etiologic studies on EMND: An animal model for ALSR21NS041968 · NINDS · CORNELL UNIVERSITY ITHACA · PI MOHAMMED, HUSSNI O · 2003 to 2004
$376k
NINDS NIH HHS R01 NS082347NINDS NIH HHS R01 NS088155NINDS NIH HHS R21 NS041968NINDS NIH HHS U01 NS045719
6 · The paper itself

Abstract

Multiple sclerosis is a heterogeneous disease with an unpredictable course and a wide range of severity; some individuals rapidly progress to a disabled state whereas others experience only mild symptoms. Though genetic studies have identified variants that are associated with an increased risk of developing multiple sclerosis, no variants have been consistently associated with multiple sclerosis severity. In part, the lack of findings is related to inherent limitations of clinical rating scales; these scales are insensitive to early degenerative changes that underlie disease progression. Optical coherence tomography imaging of the retina and low-contrast letter acuity correlate with and predict clinical and imaging-based outcomes in multiple sclerosis. Therefore, they may serve as sensitive phenotypes to discover genetic predictors of disease course. We conducted a set of genome-wide association studies of longitudinal structural and functional visual pathway phenotypes in multiple sclerosis. First, we assessed genetic predictors of ganglion cell/inner plexiform layer atrophy in a discovery cohort of 374 patients with multiple sclerosis using mixed-effects models adjusting for age, sex, disease duration, optic neuritis and genetic ancestry and using a combination of single-variant and network-based analyses. For candidate variants identified in discovery, we conducted a similar set of analyses of ganglion cell/inner plexiform layer thinning in a replication cohort (n = 376). Second, we assessed genetic predictors of sustained loss of 5-letters in low-contrast letter acuity in discovery (n = 582) using multivariable-adjusted Cox proportional hazards models. We then evaluated candidate variants/pathways in a replication cohort. (n = 253). Results of both studies revealed novel subnetworks highly enriched for connected genes in early complement activation linked to measures of disease severity. Within these networks, C3 was the gene most strongly associated with ganglion cell/inner plexiform layer atrophy (P = 0.004) and C1QA and CR1 were top results in analysis of sustained low-contrast letter acuity loss. Namely, variant rs158772, linked to C1QA, and rs61822967, linked to CR1, were associated with 71% and 40% increases in risk of sustained LCLA loss, respectively, in meta-analysis pooling discovery and replication cohorts (rs158772: hazard ratio: 1.71; 95% confidence interval 1.30-2.25; P = 1.3 × 10-4; rs61822967: hazard ratio: 1.40; 95% confidence interval: 1.16-1.68; P = 4.1 × 10-4). In conclusion, early complement pathway gene variants were consistently associated with structural and functional measures of multiple sclerosis severity. These results from unbiased analyses are strongly supported by several prior reports that mechanistically implicated early complement factors in neurodegeneration.

Indexed as

AdultClinical Trials, Phase III as TopicComplement System ProteinsDouble-Blind MethodFemaleFollow-Up StudiesGene Regulatory NetworksGenetic HeterogeneityGenome-Wide Association StudyGenotypeHumansMaleMiddle AgedMultiple SclerosisNerve DegenerationPolymorphism, Single NucleotideComplement System Proteinsearly complement pathway genesgenome-wide association studiesmultiple sclerosisoptical coherence tomography

Identifiers

PMID31289819
PMCPMC6776113
OpenAlexW2957111643

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.