Low disease risk and penetrance in Leber hereditary optic neuropathy.

The risk of Leber hereditary optic neuropathy (LHON) has largely been extrapolated from disease cohorts, which underestimate the population prevalence of pathogenic primary LHON variants as a result of incomplete disease penetrance. Understanding the true population prevalence of primary LHON variants, alongside the rate of clinical disease, provides a better understanding of disease risk and variant penetrance. We identified pathogenic primary LHON variants in whole-genome sequencing data of a well-characterized population-based control cohort and found that the prevalence is far greater than previously estimated, as it occurs in approximately 1 in 800 individuals. Accordingly, we were able to more accurately estimate population risk and disease penetrance in LHON variant carriers, validating our findings by using other large control datasets. These findings will inform accurate counseling in relation to the risk of vision loss in LHON variant carriers and disease manifestation in their family. This Matters Arising paper is in response to Lopez Sanchez et al. (2021), published in The American Journal of Human Genetics. See also the response by Mackey et al. (2022), published in this issue.

Next-Generation Sequencing and Emerging Technologies.

Genetic sequencing technologies are evolving at a rapid pace with major implications for research and clinical practice. In this review, the authors provide an updated overview of next-generation sequencing (NGS) and emerging methodologies. NGS has tremendously improved sequencing output while being more time and cost-efficient in comparison to Sanger sequencing. The authors describe short-read sequencing approaches, such as sequencing by synthesis, ion semiconductor sequencing, and nanoball sequencing. Third-generation long-read sequencing now promises to overcome many of the limitations of short-read sequencing, such as the ability to reliably resolve repeat sequences and large genomic rearrangements. By combining complementary methods with massively parallel DNA sequencing, a greater insight into the biological context of disease mechanisms is now possible. Emerging methodologies, such as advances in nanopore technology, in situ nucleic acid sequencing, and microscopy-based sequencing, will continue the rapid evolution of this area. These new technologies hold many potential applications for hematological disorders, with the promise of precision and personalized medical care in the future.

Decompensation of cardiorespiratory function and emergence of anemia during pregnancy in a case of mitochondrial myopathy, lactic acidosis, and sideroblastic anemia 2 with compound heterozygous YARS2 pathogenic variants.

Myopathy, lactic acidosis, and sideroblastic anemia 2 (MLASA2) is an autosomal recessive mitochondrial disorder caused by pathogenic variants in YARS2. YARS2 variants confer heterogeneous phenotypes ranging from the full MLASA syndrome to a clinically unaffected state. Symptom onset is most common in the first decade of life but can occur in adulthood and has been reported following intercurrent illness. Early death can result from respiratory muscle weakness and cardiomyopathy. We report a case of MLASA2 with compound heterozygous YARS2 pathogenic variants; a known pathogenic nonsense variant [NM_001040436.3:c.98C>A (p.Ser33Ter)] and a likely pathogenic missense variant not previously associated with disease [NM_001040436.3:c.948G>T (p.Arg316Ser)]. The proband initially presented with a relatively mild phenotype of myopathy and lactic acidosis. During pregnancy, anemia emerged as an additional feature and in the postpartum period she experienced severe decompensation of cardiorespiratory function. This is the first reported case of pregnancy-related complications in a patient with YARS2-related mitochondrial disease. This case highlights the need for caution and careful counseling when considering pregnancy in mitochondrial disease, due to the risk of disease exacerbation and pregnancy complications.

Diagnosis of 'possible' mitochondrial disease: an existential crisis.

Primary genetic mitochondrial diseases are often difficult to diagnose, and the term 'possible' mitochondrial disease is used frequently by clinicians when such a diagnosis is suspected. There are now many known phenocopies of mitochondrial disease. Advances in genomic testing have shown that some patients with a clinical phenotype and biochemical abnormalities suggesting mitochondrial disease may have other genetic disorders. In instances when a genetic diagnosis cannot be confirmed, a diagnosis of 'possible' mitochondrial disease may result in harm to patients and their families, creating anxiety, delaying appropriate diagnosis and leading to inappropriate management or care. A categorisation of 'diagnosis uncertain', together with a specific description of the metabolic or genetic abnormalities identified, is preferred when a mitochondrial disease cannot be genetically confirmed.

Next-Generation Sequencing and Emerging Technologies.

Genetic sequencing technologies are evolving at a rapid pace with major implications for research and clinical practice. In this review, the authors provide an updated overview of next-generation sequencing (NGS) and emerging methodologies. NGS has tremendously improved sequencing output while being more time and cost-efficient in comparison to Sanger sequencing. The authors describe short-read sequencing approaches, such as sequencing by synthesis, ion semiconductor sequencing, and nanoball sequencing. Third-generation long-read sequencing now promises to overcome many of the limitations of short-read sequencing, such as the ability to reliably resolve repeat sequences and large genomic rearrangements. By combining complementary methods with massively parallel DNA sequencing, a greater insight into the biological context of disease mechanisms is now possible. Emerging methodologies, such as advances in nanopore technology, in situ nucleic acid sequencing, and microscopy-based sequencing, will continue the rapid evolution of this area. These new technologies hold many potential applications for hematological disorders, with the promise of precision and personalized medical care in the future.

High Degree of Genetic Heterogeneity for Hereditary Cerebellar Ataxias in Australia.

Genetic testing strategies such as next-generation sequencing (NGS) panels and whole genome sequencing (WGS) can be applied to the hereditary cerebellar ataxias (HCAs), but their exact role in the diagnostic pathway is unclear. We aim to determine the yield from genetic testing strategies and the genetic and phenotypic spectrum of HCA in Australia by analysing real-world data. We performed a retrospective review on 87 HCA cases referred to the Neurogenetics Clinic at the Royal North Shore Hospital, Sydney, Australia. Probands underwent triplet repeat expansion testing; those that tested negative had NGS-targeted panels and WGS testing when available. In our sample, 58.6% were male (51/87), with an average age at onset of 37.1 years. Individuals with sequencing variants had a prolonged duration of illness compared to those with a triplet repeat expansion. The detection rate in probands for routine repeat expansion panels was 13.8% (11/80). NGS-targeted panels yielded a further 11 individuals (11/32, 34.4%), with WGS yielding 1 more diagnosis (1/3, 33.3%). NGS panels and WGS improved the overall diagnostic rate to 28.8% (23/80) in 14 known HCA loci. The genetic findings included novel variants in ANO10, CACNA1A, PRKCG and SPG7. Our findings highlight the genetic heterogeneity of HCAs and support the use of NGS approaches for individuals who were negative on repeat expansion testing. In comparison to repeat disorders, individuals with sequencing variants may have a prolonged duration of illness, consistent with slower progression of disease.

Increased Diagnostic Yield of Spastic Paraplegia with or Without Cerebellar Ataxia Through Whole-Genome Sequencing.

Inherited disorders of spasticity or ataxia exist on a spectrum with overlapping causative genes and phenotypes. We investigated the use of whole-genome sequencing (WGS) to detect a genetic cause when considering this spectrum of disorders as a single group. We recruited 18 Korean individuals with spastic paraplegia with or without cerebellar ataxia in whom common causes of hereditary cerebellar ataxia and hereditary spastic paraplegia had been excluded. We performed WGS with analysis for single nucleotide variants, small insertions and deletions, copy number variants (CNVs), structural variants (SVs) and intronic variants. Disease-relevant variants were identified in ABCD1 (n = 3), CAPN1 (n = 2), NIPA1 (n = 1) and PLA2G6 (n = 1) for 7/18 patients (38.9%). A 'reverse phenotyping' approach was used to clarify the diagnosis in individuals with PLA2G6 and ABCD1 variants. One of the ABCD1 disease-relevant variants was detected on analysis for intronic variants. No CNV or SV causes were found. The two males with ABCD1 variants were initiated on monitoring for adrenal dysfunction. This is one of only a few studies to analyse spastic-ataxias as a continuous spectrum using a single approach. The outcome was improved diagnosis of unresolved cases for which common genetic causes had been excluded. This includes the detection of ABCD1 variants which had management implications. Therefore, WGS may be particularly relevant to diagnosing spastic ataxias given the large number of genes associated with this condition and the relatively high diagnostic yield.

Mitochondrial Dysfunction in Parkinson's Disease: New Mechanistic Insights and Therapeutic Perspectives.

PURPOSE OF REVIEW: Parkinson's disease (PD) is a complex neurodegenerative disorder, the aetiology of which is still largely unknown. Overwhelming evidence indicates that mitochondrial dysfunction is a central factor in PD pathophysiology. Here we review recent developments around mitochondrial dysfunction in familial and sporadic PD, with a brief overview of emerging therapies targeting mitochondrial dysfunction. RECENT FINDINGS: Increasing evidence supports the critical role for mitochondrial dysfunction in the development of sporadic PD, while the involvement of familial PD-related genes in the regulation of mitochondrial biology has been expanded by the discovery of new mitochondria-associated disease loci and the identification of their novel functions. Recent research has expanded knowledge on the mechanistic details underlying mitochondrial dysfunction in PD, with the discovery of new therapeutic targets providing invaluable insights into the essential role of mitochondria in PD pathogenesis and unique opportunities for drug development.

Mutation in mitochondrial ribosomal protein S7 (MRPS7) causes congenital sensorineural deafness, progressive hepatic and renal failure and lactic acidemia.

Functional defects of the mitochondrial translation machinery, as a result of mutations in nuclear-encoded genes, have been associated with combined oxidative phosphorylation (OXPHOS) deficiencies. We report siblings with congenital sensorineural deafness and lactic acidemia in association with combined respiratory chain (RC) deficiencies of complexes I, III and IV observed in fibroblasts and liver. One of the siblings had a more severe phenotype showing progressive hepatic and renal failure. Whole-exome sequencing revealed a homozygous mutation in the gene encoding mitochondrial ribosomal protein S7 (MRPS7), a c.550A>G transition that encodes a substitution of valine for a highly conserved methionine (p.Met184Val) in both affected siblings. MRPS7 is a 12S ribosomal RNA-binding subunit of the small mitochondrial ribosomal subunit, and is required for the assembly of the small ribosomal subunit. Pulse labeling of mitochondrial protein synthesis products revealed impaired mitochondrial protein synthesis in patient fibroblasts. Exogenous expression of wild-type MRPS7 in patient fibroblasts rescued complexes I and IV activities, demonstrating the deleterious effect of the mutation on RC function. Moreover, reduced 12S rRNA transcript levels observed in the patient's fibroblasts were also restored to normal levels by exogenous expression of wild-type MRPS7. Our data demonstrate the pathogenicity of the identified MRPS7 mutation as a novel cause of mitochondrial RC dysfunction, congenital sensorineural deafness and progressive hepatic and renal failure.

Genetic Testing of Movements Disorders: A Review of Clinical Utility.

Currently, pathogenic variants in more than 500 different genes are known to cause various movement disorders. The increasing accessibility and reducing cost of genetic testing has resulted in increasing clinical use of genetic testing for the diagnosis of movement disorders. However, the optimal use case(s) for genetic testing at a patient level remain ill-defined. Here, we review the utility of genetic testing in patients with movement disorders and also highlight current challenges and limitations that need to be considered when making decisions about genetic testing in clinical practice. Highlights: The utility of genetic testing extends across multiple clinical and non-clinical domains. Here we review different aspects of the utility of genetic testing for movement disorders and the numerous associated challenges and limitations. These factors should be weighed on a case-by-case basis when requesting genetic tests in clinical practice.

Genome sequencing reanalysis increases the diagnostic yield in dystonia.

PURPOSE: We investigated the contribution of genomic data reanalysis to the diagnostic yield of dystonia patients who remained undiagnosed after prior genome sequencing. METHODS: Probands with heterogeneous dystonia phenotypes who underwent initial genome sequencing (GS) analysis in 2019 were included in the reanalysis, which was performed through gene-specific discovery collaborations and systematic genomic data reanalysis. RESULTS: Initial GS analysis in 2019 (n = 111) identified a molecular diagnosis in 11.7 % (13/111) of cases. Reanalysis between 2020 and 2023 increased the diagnostic yield by 7.2 % (8/111); 3.6 % (4/111) through focused gene-specific clinical correlation collaborative efforts [VPS16 (two probands), AOPEP and POLG], and 3.6 % (4/111) by systematic reanalysis completed in 2023 [NUS1 (two probands) and DDX3X variants, and a microdeletion encompassing VPS16]. Seven of these patients had a high phenotype-based dystonia score ≥3. Notable unverified findings in four additional cases included suspicious variants of uncertain significance in FBXL4 and EIF2AK2, and potential phenotypic expansion associated with SLC2A1 and TREX1 variants. CONCLUSION: GS data reanalysis increased the diagnostic yield from 11.7 % to 18.9 %, with potential extension up to 22.5 %. While optimal timing for diagnostic reanalysis remains to be determined, this study demonstrates that periodic re-interrogation of dystonia GS datasets can provide additional genetic diagnoses, which may have significant implications for patients and their families.

NEMoE: a nutrition aware regularized mixture of experts model to identify heterogeneous diet-microbiome-host health interactions.

BACKGROUND: Unrevealing the interplay between diet, the microbiome, and the health state could enable the design of personalized intervention strategies and improve the health and well-being of individuals. A common approach to this is to divide the study population into smaller cohorts based on dietary preferences in the hope of identifying specific microbial signatures. However, classification of patients based solely on diet is unlikely to reflect the microbiome-host health relationship or the taxonomic microbiome makeup. RESULTS: We present a novel approach, the Nutrition-Ecotype Mixture of Experts (NEMoE) model, for establishing associations between gut microbiota and health state that accounts for diet-specific cohort variability using a regularized mixture of experts model framework with an integrated parameter sharing strategy to ensure data-driven diet-cohort identification consistency across taxonomic levels. The success of our approach was demonstrated through a series of simulation studies, in which NEMoE showed robustness with regard to parameter selection and varying degrees of data heterogeneity. Further application to real-world microbiome data from a Parkinson's disease cohort revealed that NEMoE is capable of not only improving predictive performance for Parkinson's Disease but also for identifying diet-specific microbial signatures of disease. CONCLUSION: In summary, NEMoE can be used to uncover diet-specific relationships between nutritional-ecotype and patient health and to contextualize precision nutrition for different diseases. Video Abstract.

Introme accurately predicts the impact of coding and noncoding variants on gene splicing, with clinical applications.

Predicting the impact of coding and noncoding variants on splicing is challenging, particularly in non-canonical splice sites, leading to missed diagnoses in patients. Existing splice prediction tools are complementary but knowing which to use for each splicing context remains difficult. Here, we describe Introme, which uses machine learning to integrate predictions from several splice detection tools, additional splicing rules, and gene architecture features to comprehensively evaluate the likelihood of a variant impacting splicing. Through extensive benchmarking across 21,000 splice-altering variants, Introme outperformed all tools (auPRC: 0.98) for the detection of clinically significant splice variants. Introme is available at https://github.com/CCICB/introme .

Nutritional Intake and Gut Microbiome Composition Predict Parkinson's Disease.

Background: Models to predict Parkinson's disease (PD) incorporating alterations of gut microbiome (GM) composition have been reported with varying success. Objective: To assess the utility of GM compositional changes combined with macronutrient intake to develop a predictive model of PD. Methods: We performed a cross-sectional analysis of the GM and nutritional intake in 103 PD patients and 81 household controls (HCs). GM composition was determined by 16S amplicon sequencing of the V3-V4 region of bacterial ribosomal DNA isolated from stool. To determine multivariate disease-discriminant associations, we developed two models using Random Forest and support-vector machine (SVM) methodologies. Results: Using updated taxonomic reference, we identified significant compositional differences in the GM profiles of PD patients in association with a variety of clinical PD characteristics. Six genera were overrepresented and eight underrepresented in PD patients relative to HCs, with the largest difference being overrepresentation of Lactobacillaceae at family taxonomic level. Correlation analyses highlighted multiple associations between clinical characteristics and select taxa, whilst constipation severity, physical activity and pharmacological therapies associated with changes in beta diversity. The random forest model of PD, incorporating taxonomic data at the genus level and carbohydrate contribution to total energy demonstrated the best predictive capacity [Area under the ROC Curve (AUC) of 0.74]. Conclusion: The notable differences in GM diversity and composition when combined with clinical measures and nutritional data enabled the development of a predictive model to identify PD. These findings support the combination of GM and nutritional data as a potentially useful biomarker of PD to improve diagnosis and guide clinical management.

The Gut Microbiome in Parkinson's Disease: A Longitudinal Study of the Impacts on Disease Progression and the Use of Device-Assisted Therapies.

Background: Altered gut microbiome (GM) composition has been established in Parkinson's disease (PD). However, few studies have longitudinally investigated the GM in PD, or the impact of device-assisted therapies. Objectives: To investigate the temporal stability of GM profiles from PD patients on standard therapies and those initiating device-assisted therapies (DAT) and define multivariate models of disease and progression. Methods: We evaluated validated clinical questionnaires and stool samples from 74 PD patients and 74 household controls (HCs) at 0, 6, and 12 months. Faster or slower disease progression was defined from levodopa equivalence dose and motor severity measures. 19 PD patients initiating Deep Brain Stimulation or Levodopa-Carbidopa Intestinal Gel were separately evaluated at 0, 6, and 12 months post-therapy initiation. Results: Persistent underrepresentation of short-chain fatty-acid-producing bacteria, Butyricicoccus, Fusicatenibacter, Lachnospiraceae ND3007 group, and Erysipelotrichaceae UCG-003, were apparent in PD patients relative to controls. A sustained effect of DAT initiation on GM associations with PD was not observed. PD progression analysis indicated that the genus Barnesiella was underrepresented in faster progressing PD patients at t = 0 and t = 12 months. Two-stage predictive modeling, integrating microbiota abundances and nutritional profiles, improved predictive capacity (change in Area Under the Curve from 0.58 to 0.64) when assessed at Amplicon Sequence Variant taxonomic resolution. Conclusion: We present longitudinal GM studies in PD patients, showing persistently altered GM profiles suggestive of a reduced butyrogenic production potential. DATs exerted variable GM influences across the short and longer-term. We found that specific GM profiles combined with dietary factors improved prediction of disease progression in PD patients.

The impact of device-assisted therapies on the gut microbiome in Parkinson's disease.

BACKGROUND: Microbiome feedbacks are proposed to influence Parkinson's disease (PD) pathophysiology. A number of studies have evaluated the impact of oral medication on the gut microbiome (GM) in PD. However, the influence of PD device-assisted therapies (DATs) on the GM remains to be investigated. OBJECTIVES: To profile acute gut microbial community alterations in response to PD DAT initiation. METHODS: Clinical data and stool samples were collected from 21 PD patients initiating either deep brain stimulation (DBS) or levodopa-carbidopa intestinal gel (LCIG) and ten spousal healthy control (HC) subjects. 16S amplicon sequencing of stool DNA enabled comparison of temporal GM stability between groups and with clinical measures, including disease alterations relative to therapy initiation. RESULTS: We assessed GM response to therapy in the PD group by comparing pre-therapy (- 2 and 0 weeks) with post-therapy initiation timepoints (+ 2 and + 4 weeks) and HCs at baseline (0 weeks). Altered GM compositions were noted between the PD and HC groups at various taxonomic levels, including specific differences for DBS (overrepresentation of Clostridium_XlVa, Bilophila, Parabacteroides, Pseudoflavonifractor and underrepresentation of Dorea) and LCIG therapy (overrepresentation of Pseudoflavonifractor, Escherichia/Shigella, and underrepresentation of Gemmiger). Beta diversity changes were also found over the 4 week post-treatment initiation period. CONCLUSIONS: We report on initial short-term GM changes in response to the initiation of PD DATs. Prior to the introduction of the DAT, a PD-associated GM was observed. Following initiation of DAT, several DAT-specific changes in GM composition were identified, suggesting DATs can influence the GM in PD.

Strong Predictive Algorithm of Pathogenesis-Based Biomarkers Improves Parkinson's Disease Diagnosis.

Easily accessible and accurate biomarkers can aid Parkinson's disease diagnosis. We investigated whether combining plasma levels of α-synuclein, anti-α-synuclein, and/or their ratios to amyloid beta-40 correlated with clinical diagnosis. The inclusion of amyloid beta-40 (Aß40) is novel. Plasma levels of biomarkers were quantified with ELISA. Using receiver operating characteristic (ROC) curve analysis, levels of α-synuclein, anti-α-synuclein, and their ratios with Aß40 were analyzed in an initial training set of cases and controls. Promising biomarkers were then used to build a diagnostic algorithm. Verification of the results of biomarkers and the algorithm was performed in an independent set. The training set consisted of 50 cases (age 65.2±9.3, range 44-83, female:male=21:29) with 50 age- and gender-matched controls (67.1±10.0, range 45-96 years; female:male=21:29). ROC curve analysis yielded the following area under the curve results: anti-α-synuclein=0.835, α-synuclein=0.738, anti-α-synuclein/Aß40=0.737, and α-synuclein/Aß40=0.663. A 2-step diagnostic algorithm was built: either α-synuclein or anti-α-synuclein was ≥2 times the means of controls (step-1), resulting in 74% sensitivity; and adding α-synuclein/Aß40 or anti-α-synuclein/Aß40 (step-2) yielded better sensitivity (82%) while using step-2 alone yielded good specificity in controls (98%). The results were verified in an independent sample of 46 cases and 126 controls, with sensitivity reaching 91.3% and specificity 90.5%. The algorithm was equally sensitive in Parkinson's disease of ≤5-year duration with 92.6% correctly identified in the training set and 90% in the verification set. With two independent samples totaling 272 subjects, our study showed that combination of biomarkers of α-synuclein, anti-α-synuclein, and their ratios to Aß40 showed promising sensitivity and specificity.

Use of Whole-Genome Sequencing for Mitochondrial Disease Diagnosis.

BACKGROUND AND OBJECTIVES: Mitochondrial diseases (MDs) are the commonest group of heritable metabolic disorders. Phenotypic diversity can make molecular diagnosis challenging, and causative genetic variants may reside in either mitochondrial or nuclear DNA. A single comprehensive genetic diagnostic test would be highly useful and transform the field. We applied whole-genome sequencing (WGS) to evaluate the variant detection rate and diagnostic capacity of this technology with a view to simplifying and improving the MD diagnostic pathway. METHODS: Adult patients presenting to a specialist MD clinic in Sydney, Australia, were recruited to the study if they satisfied clinical MD (Nijmegen) criteria. WGS was performed on blood DNA, followed by clinical genetic analysis for known pathogenic MD-associated variants and MD mimics. RESULTS: Of the 242 consecutive patients recruited, 62 participants had "definite," 108 had "probable," and 72 had "possible" MD classification by the Nijmegen criteria. Disease-causing variants were identified for 130 participants, regardless of the location of the causative genetic variants, giving an overall diagnostic rate of 53.7% (130 of 242). Identification of causative genetic variants informed precise treatment, restored reproductive confidence, and optimized clinical management of MD. DISCUSSION: Comprehensive bigenomic sequencing accurately detects causative genetic variants in affected MD patients, simplifying diagnosis, enabling early treatment, and informing the risk of genetic transmission.

The genetics of mitochondrial disease.

The discovery that defects in mitochondria and mitochondrial DNA could cause human disease has led to the development of a rapidly expanding group of disorders known as mitochondrial disease. Mitochondrial disease is so named because of the common feature of impaired mitochondrial function. The main function of the mitochondrion is to produce energy for the cell in the form of ATP. ATP is generated by the respiratory chain, a series of complex proteins that are located in the mitochondrial membrane, and are encoded for by both the mitochondrial and nuclear genomes. Consequently, mitochondrial disease can be caused by mutations in either mitochondrial or nuclear DNA. Given the distribution of mitochondria throughout the body, the specific properties of mitochondrial DNA, and the mitochondrion's dependence on nuclear genes for its normal function, the clinical presentation of mitochondrial disease can be highly variable. Thus, familiarity with typical clinical presentations and knowledge of the genes that contribute to mitochondrial function will aid the clinician in the recognition, diagnosis, and management of patients with this group of diverse disorders.