ArticlePloS one2011
Genetic background of patients from a university medical center in Manhattan: implications for personalized medicine.
Article in PloS one, 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 51 papers, 5 of them syntheses that pooled 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.
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
51 citing papers in PubMed, 5 syntheses or guidelines pooled it, 73 citations in OpenAlex.
- Large-scale multi-omics analyses in Hispanic/Latino populations identify genes for cardiometabolic traits.Nature communications · 2025Pooled it
- Genome-wide association study of prostate-specific antigen levels in 392,522 men identifies new loci and improves prediction across ancestry groups.Nature genetics · 2025Pooled it
- Evidence of Novel Susceptibility Variants for Prostate Cancer and a Multiancestry Polygenic Risk Score Associated with Aggressive Disease in Men of African Ancestry.European urology · 2023Pooled it
- Identification of genetic effects underlying type 2 diabetes in South Asian and European populations.Communications biology · 2022Pooled it
- The association of the vanin-1 N131S variant with blood pressure is mediated by endoplasmic reticulum-associated degradation and loss of function.PLoS genetics · 2014Pooled it
- Capturing multi-disease states on a spectrum with machine learning and routine clinical data.Med (New York, N.Y.) · 2026Article
- Cancer risk in adults with pathogenic germline variants in RAS/MAPK genes using genomic ascertainment.Genetics in medicine : official journal of the American College of Medical Genetics · 2026Article
- Machine learning-based penetrance of genetic variants.Science (New York, N.Y.) · 2025Article
- Expanding scope of genetic studies in the era of biobanks.Human molecular genetics · 2025Article
- Insights from the largest diverse ancestry sex-specific disease map for genetically predicted height.NPJ genomic medicine · 2025Article
- Re-envisioning genetic predisposition to childhood and adolescent cancers.Nature reviews. Cancer · 2025Review
- Ensemble and consensus approaches to prediction of recessive inheritance for missense variants in human disease.Cell reports methods · 2024Article
- Use of Diagnostic Codes for Primary Open-Angle Glaucoma Polygenic Risk Score Construction in Electronic Health Record-Linked Biobanks.American journal of ophthalmology · 2024Article
- Big data in sarcoidosis.Current opinion in pulmonary medicine · 2024Review
- Polygenic Risk for Type 2 Diabetes in African Americans.Diabetes · 2024Article
- Cholesterol Contributes to Risk, Severity, and Machine Learning-Driven Diagnosis of Lyme Disease.Clinical infectious diseases : an official publication of the Infectious Diseases Society of America · 2023Article
- A machine learning model identifies patients in need of autoimmune disease testing using electronic health records.Nature communications · 2023Article
- Machine learning-based marker for coronary artery disease: derivation and validation in two longitudinal cohorts.Lancet (London, England) · 2023Article
- Type 2 Diabetes Partitioned Polygenic Scores Associate With Disease Outcomes in 454,193 Individuals Across 13 Cohorts.Diabetes care · 2022Article
- Prognostic value of polygenic risk scores for adults with psychosis.Nature medicine · 2021Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
12 authors at 5 institutions in 2 countries.
Funding
Abstract
backgroundThe rapid progress currently being made in genomic science has created interest in potential clinical applications; however, formal translational research has been limited thus far. Studies of population genetics have demonstrated substantial variation in allele frequencies and haplotype structure at loci of medical relevance and the genetic background of patient cohorts may often be complex. METHODS AND
findingsTo describe the heterogeneity in an unselected clinical sample we used the Affymetrix 6.0 gene array chip to genotype self-identified European Americans (N = 326), African Americans (N = 324) and Hispanics (N = 327) from the medical practice of Mount Sinai Medical Center in Manhattan, NY. Additional data from US minority groups and Brazil were used for external comparison. Substantial variation in ancestral origin was observed for both African Americans and Hispanics; data from the latter group overlapped with both Mexican Americans and Brazilians in the external data sets. A pooled analysis of the African Americans and Hispanics from NY demonstrated a broad continuum of ancestral origin making classification by race/ethnicity uninformative. Selected loci harboring variants associated with medical traits and drug response confirmed substantial within- and between-group heterogeneity.
conclusionAs a consequence of these complementary levels of heterogeneity group labels offered no guidance at the individual level. These findings demonstrate the complexity involved in clinical translation of the results from genome-wide association studies and suggest that in the genomic era conventional racial/ethnic labels are of little value.
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.