ArticleNature communications2019
Estimating heritability and genetic correlations from large health datasets in the absence of genetic data.
Article in Nature communications, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers, 2 of them syntheses that pooled it.
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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.
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Who cites it
20 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- Discerning asthma endotypes through comorbidity mapping.Nature communications · 2022Pooled it
- Deep representation learning of patient data from Electronic Health Records (EHR): A systematic review.Journal of biomedical informatics · 2021Pooled it
- Long-range interdependencies aware signal analysis for rapid and accurate obstructive sleep apnea prediction.Nature communications · 2026Article
- Genetic trade-offs in fertility and longevity explain the maintenance of disease-associated alleles in humans.Nature ecology & evolution · 2026Article
- Multi-Level Latent Variable Models for Coheritability Analysis in Electronic Health Records.Statistics in medicine · 2026Article
- Unsupervised characterization of 100,272 EHR patients identifies high-risk groups and comorbidities linked to premature aging.NPJ digital medicine · 2026Article
- Longitudinal analysis of electronic health records reveals medical conditions associated with subsequent Alzheimer's disease development.Alzheimer's research & therapy · 2025Article
- An effective encoding of human medical conditions in disease space provides a versatile framework for deciphering disease associations.Quantitative biology (Beijing, China) · 2025Article
- DualGCN-GE: integration of spatiotemporal representations from whole-blood expression data with dual-view graph convolution network to identify Parkinson's disease subtypes.BMC bioinformatics · 2025Article
- Longitudinal Analysis of Electronic Health Records Reveals Medical Conditions Associated with Subsequent Alzheimer's Disease Development.medRxiv : the preprint server for health sciences · 2025Article
- Linking dietary fiber to human malady through cumulative profiling of microbiota disturbance.iMeta · 2025Article
- Progress and opportunities of foundation models in bioinformatics.Briefings in bioinformatics · 2024Review
- Age-dependent topic modeling of comorbidities in UK Biobank identifies disease subtypes with differential genetic risk.Nature genetics · 2023Article
- The high-dimensional space of human diseases built from diagnosis records and mapped to genetic loci.Nature computational science · 2023Article
- Network expansion of genetic associations defines a pleiotropy map of human cell biology.Nature genetics · 2023Article
- Global patterns of prognostic biomarkers across disease space.Scientific reports · 2022Article
- Mapping phenotypic and aetiological associations between ADHD and physical conditions in adulthood in Sweden: a genetically informed register study.The lancet. Psychiatry · 2021Article
- Do psychiatric diseases follow annual cyclic seasonality?PLoS biology · 2021Article
- Disease trajectory browser for exploring temporal, population-wide disease progression patterns in 7.2 million Danish patients.Nature communications · 2020Article
- An Evolutionary Arms Race BetweenFrontiers in microbiology · 2020Review
Corrections and comments
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Authors and funding
15 authors.
Funding
Abstract
Typically, estimating genetic parameters, such as disease heritability and between-disease genetic correlations, demands large datasets containing all relevant phenotypic measures and detailed knowledge of family relationships or, alternatively, genotypic and phenotypic data for numerous unrelated individuals. Here, we suggest an alternative, efficient estimation approach through the construction of two disease metrics from large health datasets: temporal disease prevalence curves and low-dimensional disease embeddings. We present eleven thousand heritability estimates corresponding to five study types: twins, traditional family studies, health records-based family studies, single nucleotide polymorphisms, and polygenic risk scores. We also compute over six hundred thousand estimates of genetic, environmental and phenotypic correlations. Furthermore, we find that: (1) disease curve shapes cluster into five general patterns; (2) early-onset diseases tend to have lower prevalence than late-onset diseases (Spearman's ρ = 0.32, p < 10
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