Ketoacidosis is a potentially lethal condition caused by the imbalance between hepatic production and extrahepatic utilization of ketone bodies. We performed exome sequencing in a patient with recurrent, severe ketoacidosis and identified a homozygous frameshift mutation in the gene encoding monocarboxylate transporter 1 (SLC16A1, also called MCT1). Genetic analysis in 96 patients suspected of having ketolytic defects yielded seven additional inactivating mutations in MCT1, both homozygous and heterozygous. Mutational status was found to be correlated with ketoacidosis severity, MCT1 protein levels, and transport capacity. Thus, MCT1 deficiency is a novel cause of profound ketoacidosis; the present work suggests that MCT1-mediated ketone-body transport is needed to maintain acid–base balance.

Phenotypic and biochemical categorization of humans with detrimental variants can provide valuable information on gene function. We illustrate this with the identification of two different homozygous variants resulting in enzymatic loss-of-function in LDHD, encoding lactate dehydrogenase D, in two unrelated patients with elevated D-lactate urinary excretion and plasma concentrations. We establish the role of LDHD by demonstrating that LDHD loss-of-function in zebrafish results in increased concentrations of D-lactate. D-lactate levels are rescued by wildtype LDHD but not by patients’ variant LDHD, confirming these variants’ loss-of-function effect. This work provides the first in vivo evidence that LDHD is responsible for human D-lactate metabolism. This broadens the differential diagnosis of D-lactic acidosis, an increasingly recognized complication of short bowel syndrome with unpredictable onset and severity. With the expanding incidence of intestinal resection for disease or obesity, the elucidation of this metabolic pathway may have relevance for those patients with D-lactic acidosis.

Fusion genes are hallmarks of various cancer types and important determinants for diagnosis, prognosis and treatment. Fusion gene partner choice and breakpoint-position promiscuity restricts diagnostic detection, even for known and recurrent configurations. Here, we develop FUDGE (FUsion Detection from Gene Enrichment) to accurately and impartially identify fusions. FUDGE couples target-selected and strand-specific CRISPR-Cas9 activity for fusion gene driver enrichment — without prior knowledge of fusion partner or breakpoint-location — to long read nanopore sequencing with the bioinformatics pipeline NanoFG. FUDGE has flexible target-loci choices and enables multiplexed enrichment for simultaneous analysis of several genes in multiple samples in one sequencing run. We observe on-average 665 fold breakpoint-site enrichment and identify nucleotide resolution fusion breakpoints within 2 days. The assay identifies cancer cell line and tumor sample fusions irrespective of partner gene or breakpoint-position. FUDGE is a rapid and versatile fusion detection assay for diagnostic pan-cancer fusion detection.

Clinical application of whole-exome and whole-genome sequencing (WES and WGS) has led to an increasing interest in how it could drive healthcare decisions. As with any healthcare innovation, implementation of next-generation sequencing in the clinic raises questions on affordability and costing impact for society as a whole. We retrospectively analyzed medical records of 370 patients with ID who had undergone WES at various stages of their diagnostic trajectory. We collected all medical interventions performed on these patients at the University Medical Center Utrecht (UMCU), Utrecht, the Netherlands. We categorized the patients according to their WES-based preliminary diagnosis (“yes”, “no”, and “uncertain”), and assessed the per-patient healthcare activities and corresponding costs before (pre) and after (post) genetic diagnosis. The WES-specific diagnostic yield among the 370 patients was 35% (128 patients). Pre-WES costs were €7.225 on average. Highest average costs were observed for laboratory-based tests, including genetics, followed by consults. Compared to pre-WES costs, the post-WES costs were on average 80% lower per patient, irrespective of the WES-based diagnostic outcome. Application of WES results in a considerable reduction of healthcare costs, not just in current settings, but even more so when applied earlier in the diagnostic trajectory (genetics-first). In such context, WES may replace less cost-effective traditional technologies without compromising the diagnostic yield. Moreover, WES appears to harbor an intrinsic “end-of-trajectory” effect; regardless of the diagnosis, downstream medical interventions decrease substantially in both number and costs.