Evidence map›Paper›PMID 39249108›Full record

ArticleJournal of neurology2024

Improving prediction models of amyotrophic lateral sclerosis (ALS) using polygenic, pre-existing conditions, and survey-based risk scores in the UK Biobank.

Weijia Jin, Jonathan Boss, Kelly M Bakulski, Stephen A Goutman, Eva L Feldman, Lars G Fritsche, Bhramar Mukherjee

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Article in Journal of neurology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
–field-weighted citation impact
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

4 citing papers in PubMed.

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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

7 authors.

Weijia JinDepartment of Biostatistics, University of Florida, Gainesville, FL, 32603, USA.ORCID http://orcid.org/0000-0002-0644-5153
Jonathan BossDepartment of Biostatistics, University of Michigan, University of Michigan, Ann Arbor, MI, 48109, USA.ORCID http://orcid.org/0000-0001-5285-3038
Kelly M BakulskiDepartment of Epidemiology, University of Michigan, Ann Arbor, MI, 48109, USA.ORCID http://orcid.org/0000-0002-9605-6337
Stephen A GoutmanDepartment of Neurology, University of Michigan, Ann Arbor, MI, 48109, USA.ORCID http://orcid.org/0000-0001-8780-6637
Eva L FeldmanDepartment of Neurology, University of Michigan, Ann Arbor, MI, 48109, USA.ORCID http://orcid.org/0000-0002-9162-2694
Lars G Fritsche *Department of Biostatistics, University of Michigan, University of Michigan, Ann Arbor, MI, 48109, USA. larsf@umich.edu.ORCID http://orcid.org/0000-0002-2110-1690
Bhramar Mukherjee *Department of Biostatistics, University of Michigan, University of Michigan, Ann Arbor, MI, 48109, USA. bhramar@umich.edu.ORCID http://orcid.org/0000-0003-0118-4561

Funding

Mapping the ALS Exposome to Gain New Insights into Disease Risk and PathogenesisR01ES030049 · NIEHS · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI BATTERMAN, STUART A, FELDMAN, EVA LUCILLE · 2020 to 2024
$3.5M
Developing novel strategies for personalized treatment and prevention of ALS: Leveraging the global exposome, genome, epigenome, metabolome, and inflammasome with data science in a case/control cohortR01NS127188 · NINDS · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI BATTERMAN, STUART A, FELDMAN, EVA LUCILLE · 2021 to 2024
$3.4M
Impact of Geospatial Factors and Environmental Pollutants on Amyotrophic Lateral Sclerosis in the State of MichiganK23ES027221 · NIEHS · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI GOUTMAN, STEPHEN · 2017 to 2021
$1.0M
ALS Association 20-IIA-532ATSDR CDC HHS R01 TS000344CDC HHS R01TS000344NIEHS NIH HHS K23 ES027221NIH HHS K23ES027221NIH HHS R01ES030049NIH HHS R01NS127188NINDS NIH HHS R01 NS127188
6 · The paper itself

Abstract

BACKGROUND AND

objectivesAmyotrophic lateral sclerosis (ALS) causes profound impairments in neurological function, and a cure for this devastating disease remains elusive. This study aimed to identify pre-disposing genetic, phenotypic, and exposure-related factors for amyotrophic lateral sclerosis using multi-modal data and assess their joint predictive potential.

methodsUtilizing data from the UK (United Kingdom) Biobank, we analyzed an unrelated set of 292 ALS cases and 408,831 controls of European descent. Two polygenic risk scores (PRS) are constructed: "GWAS Hits PRS" and "PRS-CS," reflecting oligogenic and polygenic ALS risk profiles, respectively. Time-restricted phenome-wide association studies (PheWAS) were performed to identify pre-existing conditions increasing ALS risk, integrated into phenotypic risk scores (PheRS). A poly-exposure score ("PXS") captures the influence of environmental exposures measured through survey questionnaires. We evaluate the performance of these scores for predicting ALS incidence and stratifying risk, adjusting for baseline demographic covariates.

resultsBoth PRSs modestly predicted ALS diagnosis but with increased predictive power when combined (covariate-adjusted receiver operating characteristic [AAUC] = 0.584 [0.525, 0.639]). PheRS incorporated diagnoses 1 year before ALS onset (PheRS1) modestly discriminated cases from controls (AAUC = 0.515 [0.472, 0.564]). The "PXS" did not significantly predict ALS. However, a model incorporating PRSs and PheRS1 improved the prediction of ALS (AAUC = 0.604 [0.547, 0.667]), outperforming a model combining all risk scores. This combined risk score identified the top 10% of risk score distribution with a fourfold higher ALS risk (95% CI [2.04, 7.73]) versus those in the 40%-60% range. DISCUSSION: By leveraging UK Biobank data, our study uncovers pre-disposing ALS factors, highlighting the improved effectiveness of multi-factorial prediction models to identify individuals at highest risk for ALS.

Indexed as

Amyotrophic Lateral SclerosisBiological Specimen BanksMultifactorial InheritanceAdultAgedFemaleGenetic Predisposition to DiseaseGenome-Wide Association StudyHumansMaleMiddle AgedPhenotypeUK BiobankUnited KingdomAmyotrophic lateral sclerosis (ALS)Phenotypic risk scoresPolygenic risk scoresUK biobank

Identifiers

PMID39249108

What OpenQuestion holds

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Registered trials

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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.