PSMD11 loss-of-function variants correlate with a neurobehavioral phenotype, obesity, and increased interferon response.

Primary proteasomopathies have recently emerged as a new class of rare early-onset neurodevelopmental disorders (NDDs) caused by pathogenic variants in the PSMB1, PSMC1, PSMC3, or PSMD12 proteasome genes. Proteasomes are large multi-subunit protein complexes that maintain cellular protein homeostasis by clearing ubiquitin-tagged damaged, misfolded, or unnecessary proteins. In this study, we have identified PSMD11 as an additional proteasome gene in which pathogenic variation is associated with an NDD-causing proteasomopathy. PSMD11 loss-of-function variants caused early-onset syndromic intellectual disability and neurodevelopmental delay with recurrent obesity in 10 unrelated children. Our findings demonstrate that the cognitive impairment observed in these individuals could be recapitulated in Drosophila melanogaster with depletion of the PMSD11 ortholog Rpn6, which compromised reversal learning. Our investigations in subject samples further revealed that PSMD11 loss of function resulted in impaired 26S proteasome assembly and the acquisition of a persistent type I interferon (IFN) gene signature, mediated by the integrated stress response (ISR) protein kinase R (PKR). In summary, these data identify PSMD11 as an additional member of the growing family of genes associated with neurodevelopmental proteasomopathies and provide insights into proteasomal biology in human health.

LDLR variant classification for improved cardiovascular risk prediction in familial hypercholesterolemia.

BACKGROUND AND AIMS: Familial hypercholesterolemia (FH) is a genetic disorder marked by high LDL cholesterol and an increased premature coronary artery disease (CAD) risk. Current dichotomous classification of LDL receptor gene (LDLR) variants may inadequately capture patient variability in LDL cholesterol levels and CAD risk. This study assessed a novel approach for determining LDLR variant severity using variant-specific LDL cholesterol percentiles. METHODS: Participants of the Dutch FH cascade screening program were screened for 456 LDLR variants. For each LDLR variant carrier, a sex- and age-specific LDL cholesterol percentile was derived from the LDL cholesterol level measured at study entry, i.e. generally from the blood drawn for DNA analysis. These percentiles were used to calculate the mean LDL cholesterol percentile for each variant. Based on the variant-specific LDL cholesterol percentiles, carriers were grouped into the following LDL cholesterol strata: <75th, 75th-88th, 88th-92nd, 92nd-96.5th, 96.5th-98th, and ≥98th percentile. Additionally, variants were categorized into class 1 (LDLR deficient) and non-class 1 (often LDLR defective) variants. CAD risk between carriers in the different LDL cholesterol strata and non-carriers was compared using a Cox proportional hazard model. RESULTS: Out of 35,067 participants, 12,485 (36 %) LDLR variant carriers (mean age 38.0 ± 20.0 years, 47.7 % male) were identified. Carriers had a 5-fold higher CAD risk compared with non-carriers. Hazard ratios for CAD increased gradually from 2.2 (95%CI 0.97-5.0) to 12.0 (95%CI 5.5-24.8) across the LDL cholesterol strata. A 7.3-fold and 3.9-fold increased CAD risk was observed in carriers of class 1 and non-class 1 LDLR variants, respectively. CONCLUSIONS: This study presents a refined approach for classifying LDLR variants based on their impact on LDL cholesterol levels, allowing for more precise, genotype-specific CAD risk estimation in FH patients compared with traditional methods.

Enhanced identification of familial hypercholesterolemia using central laboratory algorithms.

BACKGROUND AND AIMS: Familial hypercholesterolemia (FH) is a highly prevalent genetic disorder resulting in markedly elevated LDL cholesterol levels and premature coronary artery disease. FH underdiagnosis and undertreatment require novel detection methods. This study evaluated the effectiveness of using an LDL cholesterol cut-off ≥99.5th percentile (sex- and age-adjusted) to identify clinical and genetic FH, and investigated underutilization of genetic testing and undertreatment in FH patients. METHODS: Individuals with at least one prior LDL cholesterol level ≥99.5th percentile were selected from a laboratory database containing lipid profiles of 590,067 individuals. The study comprised three phases: biochemical validation of hypercholesterolemia, clinical identification of FH, and genetic determination of FH. RESULTS: Of 5614 selected subjects, 2088 underwent lipid profile reassessment, of whom 1103 completed the questionnaire (mean age 64.2 ± 12.7 years, 48% male). In these 1103 subjects, mean LDL cholesterol was 4.0 ± 1.4 mmol/l and 722 (65%) received lipid-lowering therapy. FH clinical diagnostic criteria were met by 282 (26%) individuals, of whom 85% had not received guideline-recommended genetic testing and 97% failed to attain LDL cholesterol targets. Of 459 individuals consenting to genetic validation, 13% carried an FH-causing variant, which increased to 19% in clinically diagnosed FH patients. CONCLUSIONS: The identification of a substantial number of previously undiagnosed and un(der)treated clinical and genetic FH patients within a central laboratory database highlights the feasibility and clinical potential of this targeted screening strategy; both in identifying new FH patients and in improving treatment in this high-risk population.