ReviewTrends in genetics : TIG2021
Gaining insight into metabolic diseases from human genetic discoveries.
Review in Trends in genetics : TIG, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers.
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.
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.
Who cites it
19 citing papers in PubMed, 29 citations in OpenAlex.
- Spatial metabolomics and multiomics integration for breakthroughs in precision medicine for kidney disease.Nature reviews. Nephrology · 2026Review
- Bridging the variant-to-function gap in type 2 diabetes: advances and challenges.Diabetologia · 2026Review
- Rare Variants in HTRA1, SGTB, and RBM12 Confer Risk of Atherosclerotic Cardiovascular Disease Independent of Traditional Cardiovascular Risk Factors.Circulation. Genomic and precision medicine · 2025Article
- Endosomal Mechanisms in Heart Failure Pathophysiology.Current heart failure reports · 2025Review
- Realizing the promise of genome-wide association studies for effector gene prediction.Nature genetics · 2025Review
- Metabolic reaction fluxes as amplifiers and buffers of risk alleles for coronary artery disease.Molecular systems biology · 2025Article
- Zebrafish navigating the metabolic maze: insights into human disease - assets, challenges and future implications.Journal of diabetes and metabolic disorders · 2025Review
- Variant-to-function approaches for adipose tissue: Insights into cardiometabolic disorders.Cell genomics · 2025Review
- The actin and microtubule network regulator WHAMM is identified as a key kidney disease risk gene.Cell reports · 2025Article
- Understanding genetic variants in context.eLife · 2024Article
- Epigenomic insights into common human disease pathology.Cellular and molecular life sciences : CMLS · 2024Review
- Targeting postsynaptic glutamate receptor scaffolding proteins PSD-95 and PICK1 for obesity treatment.Science advances · 2024Article
- ACSS2 gene variants determine kidney disease risk by controlling de novo lipogenesis in kidney tubules.The Journal of clinical investigation · 2023Article
- Negative correlation between acetyl-CoA acyltransferase 2 and cetuximab resistance in colorectal cancer.Acta biochimica et biophysica Sinica · 2023Article
- Genomic discoveries unveil mechanistic insights in diabetes.Cell genomics · 2022Article
- Genetically personalised organ-specific metabolic models in health and disease.Nature communications · 2022Article
- Pooled image-base screening of mitochondria with microraft isolation distinguishes pathogenic mitofusin 2 mutations.Communications biology · 2022Article
- Kidney omics in hypertension: from statistical associations to biological mechanisms and clinical applications.Kidney international · 2022Review
- From mapping kidney function to mechanism and prediction.Nature reviews. Nephrology · 2022Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors at 2 institutions in 1 country.
Funding
Abstract
Human large-scale genetic association studies have identified sequence variations at thousands of genetic risk loci that are more common in patients with diverse metabolic disease compared with healthy controls. While these genetic associations have been replicated in multiple large cohorts and sometimes can explain up to 50% of heritability, the molecular and cellular mechanisms affected by common genetic variation associated with metabolic disease remains mostly unknown. A variety of new genome-wide data types, in conjunction with novel biostatistical and computational analytical methodologies and foundational experimental technologies, are paving the way for a principled approach to systematic variant-to-function (V2F) studies for metabolic diseases, turning associated regions into causal variants, cell types and states of action, effector genes, and cellular and physiological mechanisms. Identification of new target genes and cellular programs for metabolic risk loci will improve mechanistic understanding of disease biology and identification of novel therapeutic strategies.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
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.