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Ali Torkamani

Publications and source records attributed to Ali Torkamani.

2 recordsLinked to original sources
PubMed2026

Comparative whole-exome sequencing of ambulatory patients and transplant recipients with idiopathic dilated cardiomyopathy.

BACKGROUND: Idiopathic dilated cardiomyopathy (DCM) is a major cause of advanced heart failure and heart transplantation (HTx), yet the genetic correlates of progression to HTx and transplant-relevant arrhythmic phenotypes remain incompletely defined. We examined the genetics of idiopathic DCM in a Korean population, focusing on HTx/death and arrhythmic outcomes, to identify adverse outcome-linked genotype-phenotype associations. METHODS: Whole-exome sequencing was performed in 202 Korean patients with idiopathic DCM, including 56 HTx recipients and 146 ambulatory patients, and compared the findings with 1093 population-based controls. Genotype-phenotype correlations were analyzed for major clinical outcomes, including HTx, death, arrhythmias, and left ventricular functional recovery. RESULTS: Pathogenic/likely pathogenic variants were identified in 32% of patients (38% in HTx vs 30% in ambulatory patients). TTN was the most frequently affected gene overall (12%), but LMNA variants predominated in HTx recipients (20% vs 4%, p = 0.001). LMNA carriers showed substantially higher odds of HTx/death (OR 14.65, 95% CI 3.32-139.31; FDR p<0.001), and strong association with arrhythmias, including ventricular tachyarrhythmias and atrial fibrillation. Both missense and loss-of-function LMNA variants were associated with adverse outcomes. In contrast, TNNT2 variants were observed exclusively in ambulatory patients and identified a favorable functional-recovery phenotype, with a greater likelihood of LVEF recovery &#x2265;10 percentage points (OR 6.03, 95% CI 1.52-28.71; FDR p = 0.016). CONCLUSIONS: LMNA variants mark a high-risk transplant-trajectory phenotype in Korean idiopathic DCM. Genetic testing may aid early identification and management of candidates for advanced HF therapies, including HTx and durable MCS.

dilated cardiomyopathy↗
PubMed2026

Selphi, a tool for improving genotype imputation accuracy.

Genotype imputation is a powerful tool for inferring missing genotype data in large-scale genetic studies. Over the last two decades, multiple imputation algorithms have been developed, steadily improving in speed and overall accuracy. However, accurate imputation of rare and infrequent variants remains a challenge, largely because existing methods rely on local haplotype matching within genomic windows and do not fully exploit the extended patterns of haplotype sharing that span entire chromosomes. Here we present Selphi, a new genotype imputation algorithm that combines the Positional Burrows-Wheeler Transform (PBWT) with a multi-stage haplotype selection heuristic operating across entire chromosomes. When compared to state-of-the-art methods Beagle 5.4, IMPUTE5, and Minimac4, Selphi showed higher accuracy on the 1000 Genomes Project and TOPMed datasets, across all super-populations and allele frequencies. Similarly, Selphi achieved higher accuracy than Beagle 5.4 on the UK Biobank dataset, which translated into improved concordance with hc-WGS GWAS summary statistics at known trait-associated loci and more accurate polygenic risk scores (PRS). Selphi outputs standard VCF files with genotype dosages (DS), haplotype-specific allele probabilities (AP1, AP2), and a per-variant dosage R-squared quality score (DR2), enabling direct integration with downstream analytical pipelines including standard post-imputation quality filtering.

Genome-Wide Association Study↗