Critical assessment of missense variant effect predictors on disease-relevant variant data - Ruchir Rastogi; Ryan Chung; Sindy Li; Chang Li; Kyoungyeul Lee; Junwoo Woo; Dong-Wook Kim; Changwon Keum; Giulia Babbi; Pier Luigi Martelli; Castrense Savojardo; Rita Casadio; et al. (Human Genetics, 2025)
Regular, systematic, and independent assessments of computational tools that are used to predict the pathogenicity of missense variants are necessary to evaluate their clinical and research utility and guide future improvements. The Critical Assessment of Genome Interpretation (CAGI) conducts the ongoing Annotate-All-Missense (Missense Marathon) challenge, in which missense variant effect predictors (also called variant impact predictors) are evaluated on missense variants added to disease-relevant databases following the prediction submission deadline. Here we assess predictors submitted to the CAGI 6 Annotate-All-Missense challenge, predictors commonly used in clinical genetics, and recently developed deep learning methods. We examine performance across a range of settings relevant for clinical and research applications, focusing on different subsets of the evaluation data as well as high-specificity and high-sensitivity regimes. Our evaluations reveal notable advances in current methods relative to older, well-cited tools in the field. While meta-predictors tend to outperform their constituent individual predictors, several newer individual predictors perform comparably to commonly used meta-predictors. Predictor performance varies between high-specificity and high-sensitivity regimes, highlighting that different methods may be optimal for different use cases. We also characterize two potential sources of bias. Predictors that incorporate allele frequency as a predictive feature tend to have reduced performance when distinguishing pathogenic variants from very rare benign variants, and predictors trained on pathogenicity labels from curated variant databases often inherit gene-level label imbalances. Our findings help illuminate the clinical and research utility of modern missense variant effect predictors and identify potential areas for future development.

Migraine, chronic kidney disease and kidney function: observational and genetic analyses - Wenqiang Zhang; Li Zhang; Luo Yang; Chenghan Xiao; Xueyao Wu; Peijing Yan; Huijie Cui; Chao Yang; Jingwei Zhu; Xuan Wu; Mingshuang Tang; Yutong Wang; et al. (Human Genetics, 2023)
Epidemiological studies demonstrate an association between migraine and chronic kidney disease (CKD), while the genetic basis underlying the phenotypic association has not been investigated. We aimed to help avoid unnecessary interventions in individuals with migraine through the investigation of phenotypic and genetic relationships underlying migraine, CKD, and kidney function. We first evaluated phenotypic associations using observational data from UK Biobank ( N = 255,896). We then investigated genetic relationships leveraging genomic data in European ancestry for migraine ( N case / N control = 48,975/540,381), CKD ( N case / N control = 41,395/439,303), and two traits of kidney function (estimated glomerular filtration rate [eGFR, N = 567,460] and urinary albumin-to-creatinine ratio [UACR, N = 547,361]). Observational analyses suggested no significant association of migraine with the risk of CKD (HR = 1.13, 95% CI = 0.85–1.50). While we did not find any global genetic correlation in general, we identified four specific genomic regions showing significant for migraine with eGFR. Cross-trait meta-analysis identified one candidate causal variant (rs1047891) underlying migraine, CKD, and kidney function. Transcriptome-wide association study detected 28 shared expression–trait associations between migraine and kidney function. Mendelian randomization analysis suggested no causal effect of migraine on CKD (OR = 1.03, 95% CI = 0.98–1.09; P = 0.28). Despite a putative causal effect of migraine on an increased level of UACR (log-scale-beta = 0.02, 95% CI = 0.01–0.04; P = 1.92 × 10 −3 ), it attenuated to null when accounting for both correlated and uncorrelated pleiotropy. Our work does not find evidence supporting a causal association between migraine and CKD. However, our study highlights significant biological pleiotropy between migraine and kidney function. The value of a migraine prophylactic treatment for reducing future CKD in people with migraine is likely limited.

Leveraging linkage evidence to identify low-frequency and rare variants on 16p13 associated with blood pressure using TOPMed whole genome sequencing data - Karen Y. He; Xiaoyin Li; Tanika N. Kelly; Jingjing Liang; Brian E. Cade; Themistocles L. Assimes; Lewis C. Becker; Amber L. Beitelshees; Adam P. Bress; Yen-Pei Christy Chang; Yii-Der Ida Chen; Paul S. de Vries; et al. (Human Genetics, 2019)

Trans-ethnic fine-mapping of genetic loci for body mass index in the diverse ancestral populations of the Population Architecture using Genomics and Epidemiology (PAGE) Study reveals evidence for multiple signals at established loci - Lindsay Fernández-Rhodes; Jian Gong; Jeffrey Haessler; Nora Franceschini; Mariaelisa Graff; Katherine K. Nishimura; Yujie Wang; Heather M. Highland; Sachiko Yoneyama; William S. Bush; Robert Goodloe; Marylyn D. Ritchie; et al. (Human Genetics, 2017)

Candidate locus analysis of the TERT–CLPTM1L cancer risk region on chromosome 5p15 identifies multiple independent variants associated with endometrial cancer risk - Luis G. Carvajal-Carmona; Tracy A. O’Mara; Jodie N. Painter; Felicity A. Lose; Joe Dennis; Kyriaki Michailidou; Jonathan P. Tyrer; Shahana Ahmed; Kaltin Ferguson; Catherine S. Healey; Karen Pooley; Jonathan Beesley; et al. (Human Genetics, 2015)

Genome-wide association study and meta-analysis of intraocular pressure - A. Bilge Ozel; Sayoko E. Moroi; David M. Reed; Melisa Nika; Caroline M. Schmidt; Sara Akbari; Kathleen Scott; Frank Rozsa; Hemant Pawar; David C. Musch; Paul R. Lichter; Doug Gaasterland; et al. (Human Genetics, 2014)

Meta-analysis of new genome-wide association studies of colorectal cancer risk - Ulrike Peters; Carolyn M. Hutter; Li Hsu; Fredrick R. Schumacher; David V. Conti; Christopher S. Carlson; Christopher K. Edlund; Robert W. Haile; Steven Gallinger; Brent W. Zanke; Mathieu Lemire; Jagadish Rangrej; et al. (Human Genetics, 2012)

Characterization of Usher syndrome type I gene mutations in an Usher syndrome patient population - Xiao Mei Ouyang; Denise Yan; Li Lin Du; J. Fielding. Hejtmancik; Samuel G. Jacobson; Walter E. Nance; An Ren Li; Simon Angeli; Muriel Kaiser; Valerie Newton; Steve D. M. Brown; Thomas Balkany; et al. (Human Genetics, 2005)

Evidence of a founder effect for the 235delC mutation of GJB2 (connexin26) in east Asians - Denise Yan; Hong-Joon Park; Xiao Mei Ouyang; Arti Pandya; Katsumi Doi; Raadnabazar Erdenetungalag; Li Lin Du; Naoki Matsushiro; Walter E. Nance; Andrew J. Griffith; Xue Zhong Liu (Human Genetics, 2003)

Mutations in the alternatively spliced exons of USH1C cause non-syndromic recessive deafness - Xiao Ouyang; Xia Xia; Elisabeth Verpy; Li Du; Arti Pandya; Christine Petit; Thomas Balkany; Walter E. Nance; Xue Liu (Human Genetics, 2002)