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Abstract Background Breast cancer (BC) is the most commonly diagnosed cancer and the leading cause of cancer death among women globally. Despite advances, there is considerable variation in clinical outcomes for patients with non-luminal A tumors, classified as difficult-to-treat breast cancers (DTBC). This study aims to delineate the proteogenomic landscape of DTBC tumors compared to luminal A (LumA) tumors. Methods We retrospectively collected a total of 117 untreated primary breast tumor specimens, focusing on DTBC subtypes. Breast tumors were processed by laser microdissection (LMD) to enrich tumor cells. DNA, RNA, and protein were simultaneously extracted from each tumor preparation, followed by whole genome sequencing, paired-end RNA sequencing, global proteomics and phosphoproteomics. Differential feature analysis, pathway analysis and survival analysis were performed to better understand DTBC and investigate biomarkers. Results We observed distinct variations in gene mutations, structural variations, and chromosomal alterations between DTBC and LumA breast tumors. DTBC tumors predominantly had more mutations in TP53, PLXNB3, Zinc finger genes, and fewer mutations in SDC2, CDH1, PIK3CA, SVIL, and PTEN. Notably, Cytoband 1q21, which contains numerous cell proliferation-related genes, was significantly amplified in the DTBC tumors. LMD successfully minimized stromal components and increased RNA–protein concordance, as evidenced by stromal score comparisons and proteomic analysis. Distinct DTBC and LumA-enriched clusters were observed by proteomic and phosphoproteomic clustering analysis, some with survival differences. Phosphoproteomics identified two distinct phosphoproteomic profiles for high relapse-risk and low relapse-risk basal-like tumors, involving several genes known to be associated with breast cancer oncogenesis and progression, including KIAA1522, DCK, FOXO3, MYO9B, ARID1A, EPRS, ZC3HAV1, and RBM14. Lastly, an integrated pathway analysis of multi-omics data highlighted a robust enrichment of proliferation pathways in DTBC tumors. Conclusions This study provides an integrated proteogenomic characterization of DTBC vs LumA with tumor cells enriched through laser microdissection. We identified many common features of DTBC tumors and the phosphopeptides that could serve as potential biomarkers for high/low relapse-risk basal-like BC and possibly guide treatment selections.

Preventing the onset of autoimmune type 1 diabetes (T1D) is feasible through pharmacological interventions that target molecular stress-responsive mechanisms. Cellular stresses, such as nutrient deficiency, viral infection, or unfolded proteins, trigger the integrated stress response (ISR), which curtails protein synthesis by phosphorylating eukaryotic translation initiation factor-2[alpha] (eIF2[alpha]). In T1D, maladaptive unfolded protein response (UPR) in insulin-producing [beta] cells renders these cells susceptible to autoimmunity. We found that inhibition of the eIF2a kinase PKR-like ER kinase (PERK), a common component of the UPR and ISR, reversed the mRNA translation block in stressed human islets and delayed the onset of diabetes, reduced islet inflammation, and preserved [beta] cell mass in T1D-susceptible mice. Single-cell RNA-Seq of islets from PERK-inhibited mice showed reductions in the UPR and PERK signaling pathways and alterations in antigen-processing and presentation pathways in p cells. Spatial proteomics of islets from these mice showed an increase in the immune checkpoint protein programmed death-ligand 1 (PD-L1) in [beta] cells. Golgi membrane protein 1, whose levels increased following PERK inhibition in human islets and EndoC-[beta]H1 human [beta] cells, interacted with and stabilized PD-L1. Collectively, our studies show that PERK activity enhances [beta] cell immunogenicity and that inhibition of PERK may offer a strategy for preventing or delaying the development of T1D., Introduction Type 1 diabetes (T1D) is a disorder of glucose homeostasis that results from the autoimmune destruction of insulin-producing islet [beta] cells. The importance of the immune system in initiating [...]

Abstract Human infections caused by viral pathogens trigger a complex gamut of host responses that limit disease, resolve infection, generate immunity, and contribute to severe disease or death. Here, we present experimental methods and multi-omics data capture approaches representing the global host response to infection generated from 45 individual experiments involving human viruses from the Orthomyxoviridae, Filoviridae, Flaviviridae, and Coronaviridae families. Analogous experimental designs were implemented across human or mouse host model systems, longitudinal samples were collected over defined time courses, and global multi-omics data (transcriptomics, proteomics, metabolomics, and lipidomics) were acquired by microarray, RNA sequencing, or mass spectrometry analyses. For comparison, we have included transcriptomics datasets from cells treated with type I and type II human interferon. Raw multi-omics data and metadata were deposited in public repositories, and we provide a central location linking the raw data with experimental metadata and ready-to-use, quality-controlled, statistically processed multi-omics datasets not previously available in any public repository. This compendium of infection-induced host response data for reuse will be useful for those endeavouring to understand viral disease pathophysiology and network biology.

Abstract Background Lipids are regulators of insulitis and β-cell death in type 1 diabetes development, but the underlying mechanisms are poorly understood. Here, we investigated how the islet lipid composition and downstream signaling regulate β-cell death. Methods We performed lipidomics using three models of insulitis: human islets and EndoC-βH1 β cells treated with the pro-inflammatory cytokines interlukine-1β and interferon-γ, and islets from pre-diabetic non-obese mice. We also performed mass spectrometry and fluorescence imaging to determine the localization of lipids and enzyme in islets. RNAi, apoptotic assay, and qPCR were performed to determine the role of a specific factor in lipid-mediated cytokine signaling. Results Across all three models, lipidomic analyses showed a consistent increase of lysophosphatidylcholine species and phosphatidylcholines with polyunsaturated fatty acids and a reduction of triacylglycerol species. Imaging assays showed that phosphatidylcholines with polyunsaturated fatty acids and their hydrolyzing enzyme phospholipase PLA2G6 are enriched in islets. In downstream signaling, omega-3 fatty acids reduce cytokine-induced β-cell death by improving the expression of ADP-ribosylhydrolase ARH3. The mechanism involves omega-3 fatty acid-mediated reduction of the histone methylation polycomb complex PRC2 component Suz12, upregulating the expression of Arh3, which in turn decreases cell apoptosis. Conclusions Our data provide insights into the change of lipidomics landscape in β cells during insulitis and identify a protective mechanism by omega-3 fatty acids. Video Abstract

The global regulator LaeA controls secondary metabolism in diverse Aspergillus species. Here we explored its role in regulation of itaconic acid production in Aspergillus pseudoterreus. To understand its role in regulating metabolism, we deleted and overexpressed laeA, and assessed the transcriptome, proteome, and secreted metabolome prior to and during initiation of phosphate limitation induced itaconic acid production. We found that secondary metabolite clusters, including the itaconic acid biosynthetic gene cluster, are regulated by laeA and that laeA is required for high yield production of itaconic acid. Overexpression of LaeA improves itaconic acid yield at the expense of biomass by increasing the expression of key biosynthetic pathway enzymes and attenuating the expression of genes involved in phosphate acquisition and scavenging. Increased yield was observed in optimized conditions as well as conditions containing excess nutrients that may be present in inexpensive sugar containing feedstocks such as excess phosphate or complex nutrient sources. This suggests that global regulators of metabolism may be useful targets for engineering metabolic flux that is robust to environmental heterogeneity.

Introduction: This research is a continuation of the authors past contributions on this important subject, that has included the first comprehensive analysis of the composition and characteristics of health service managers in Australia, in terms of their service, qualifications and other important attributes. Objectives: This article contains an analysis of the number and characteristics of health service managers in relation to health services provided in Australia in 2006 compared with that of 2021. Design: Design of the analyses follows specifications set by the authors for tabulations prepared by the Australian Bureau of Statistics (ABS) from the censuses of population conducted by ABS in 2006 and 2021. The analysis of health service managers in terms of growth in numbers and change in their characteristics will be reviewed. Findings: A substantial increase was found in the number of health service managers in relation to the population and people employed. Also, there have been considerable changes in the characteristics and qualifications of health service managers during the 15-year period. The study also reported on the nature of the changes in hospitals and medical and other health services, and the surge in the number of managers in medical and other services, that in 2021 outnumbered those in hospitals. Implications: The findings are relevant to policy development aimed at improving the health status of the population. There were implications as well to the planning of health services, training of their labour force and related educational resources. An agenda is also put forward for additional research in view of its findings.

Abstract Background Paediatric electroencephalography (EEG) training is inadequate amongst healthcare practitioners and technicians managing children with epilepsy in sub-Saharan Africa. An entry level handbook was developed for healthcare practitioners in sub-Saharan Africa and subsequently made globally accessible via the International Child Neurology Teaching Network. Aim To investigate the usefulness of a paediatric online EEG handbook. Method A survey of the ICNApedia online EEG handbook was circulated (December 2021–June 2022), to all 108 handbook registered participants (39 countries) via the research electronic data capture (REDCap) from the University of Cape Town (UCT). Results Fifty participants from 25 countries responded: 8 from high income, 16 upper-middle income, 21 lower-middle income and 5 from low-income. 32 (64%) fully and 18 (36%) partially completed the survey. 35/50 (70%) had completed the handbook and seven respondents had partially completed the handbook. Responses supported the handbook as a good entry point to learn EEGs, especially for paediatrics. Likert scale ratings supported the handbook as relevant for gaining/enhancing knowledge and improving diagnosis and management of patients with confidence. The handbook was considered user friendly, comprehensible, and provided a practical experience. For improving EEG reading skills the handbook helped skills development via reinforcement and good illustrations. 29/32 (90%) of respondents confirmed that they are using learnt skills from the handbook in their current work. Conclusion In resource limited settings non-specialist clinicians often provide extended services including EEG interpretation. The survey supports that the handbook is supporting this niche skills area, especially for the accessibility of knowledge gained. The handbook will continue to be adapted in-line with survey feedback.

Abstract We performed a systematic literature review and narrative synthesis according to a pre‐registered protocol (Prospero: CRD42022376561) to identify the evidence associated with the burden of illness in Dravet syndrome (DS), a developmental and epileptic encephalopathy characterized by drug‐resistant epilepsy with neurocognitive and neurobehavioral impairment. We searched MEDLINE, Embase, and APA PsychInfo, Cochrane's database of systematic reviews, and Epistemonikos from inception to June 2022. Non‐interventional studies reporting on epidemiology (incidence, prevalence, and mortality), patient and caregiver health‐related quality of life (HRQoL), direct and indirect costs and healthcare resource utilization were eligible. Two reviewers independently carried out the screening. Pre‐specified data were extracted and a narrative synthesis was conducted. Overall, 49 studies met the inclusion criteria. The incidence varied from 1:15 400–1:40 900, and the prevalence varied from 1.5 per 100 000 to 6.5 per 100 000. Mortality was reported in 3.7%–20.8% of DS patients, most commonly due to sudden unexpected death in epilepsy and status epilepticus. Patient HRQoL, assessed by caregivers, was lower than in non‐DS epilepsy patients; mean scores (0 [worst] to 100/1 [best]) were 62.1 for the Kiddy KINDL/Kid‐KINDL, 46.5–54.7 for the PedsQL and 0.42 for the EQ‐5D‐5L. Caregivers, especially mothers, were severely affected, with impacts on their time, energy, sleep, career, and finances, while siblings were also affected. Symptoms of depression were reported in 47%–70% of caregivers. Mean total direct costs were high across all studies, ranging from $11 048 to $77 914 per patient per year (PPPY), with inpatient admissions being a key cost driver across most studies. Mean costs related to lost productivity were only reported in three publications, ranging from approximately $19 000 to $20 000 PPPY ($17 596 for mothers vs $1564 for fathers). High seizure burden was associated with higher resource utilization, costs and poorer HRQoL. The burden of DS on patients, caregivers, the healthcare system, and society is profound, reflecting the severe nature of the syndrome. Future studies will be able to assess the impact that newly approved therapies have on reducing the burden of DS.

Within the US there are over 300 postsecondary education (PSE) programs for students with intellectual and developmental disabilities (IDD). College students enrolled in PSE programs for students with IDD often require support in using assistive technology (AT) to complete living, learning, and working tasks. To date, there is no systematic review or meta-analysis that examines interventions within these programs that integrate AT to teach these skills. We systematically reviewed 43 intervention studies that targeted 235 students' use of AT to complete living, learning, and working tasks. The average age of students was 21.5 yrs (R = 18.7 to 27.5). Most studies used mobile devices and applications to target living (44.2%), learning (37.2%), and working (18.6%) skills. Forty-two of 43 studies used visual cues and systematic prompting and/or systematic instruction. On average, interventions were 10 sessions. Eighty-seven percent of studies reported treatment fidelity, 94% reported interobserver agreement, and 67% reported social validity. Most studies used correct number of responses or task analysis steps completed as the dependent variable. The meta-analytic results indicated interventions were overall effective at improving student outcomes. An analysis of moderators revealed a significant difference for study quality but no significant difference for disability type, study duration, and area targeted.

Summary: Type 1 diabetes (T1D) is a chronic condition caused by autoimmune destruction of the insulin-producing pancreatic β cells. While it is known that gene-environment interactions play a key role in triggering the autoimmune process leading to T1D, the pathogenic mechanism leading to the appearance of islet autoantibodies—biomarkers of autoimmunity—is poorly understood. Here we show that disruption of the complement system precedes the detection of islet autoantibodies and persists through disease onset. Our results suggest that children who exhibit islet autoimmunity and progress to clinical T1D have lower complement protein levels relative to those who do not progress within a similar time frame. Thus, the complement pathway, an understudied mechanistic and therapeutic target in T1D, merits increased attention for use as protein biomarkers of prediction and potentially prevention of T1D.

Abstract Efficient conversion of pentose sugars remains a significant barrier to the replacement of petroleum-derived chemicals with plant biomass-derived bioproducts. While the oleaginous yeast Rhodosporidium toruloides (also known as Rhodotorula toruloides) has a relatively robust native metabolism of pentose sugars compared to other wild yeasts, faster assimilation of those sugars will be required for industrial utilization of pentoses. To increase the rate of pentose assimilation in R. toruloides, we leveraged previously reported high-throughput fitness data to identify potential regulators of pentose catabolism. Two genes were selected for further investigation, a putative transcription factor (RTO4_12978, Pnt1) and a homolog of a glucose transceptor involved in carbon catabolite repression (RTO4_11990). Overexpression of Pnt1 increased the specific growth rate approximately twofold early in cultures on xylose and increased the maximum specific growth by 18% while decreasing accumulation of arabitol and xylitol in fast-growing cultures. Improved growth dynamics on xylose translated to a 120% increase in the overall rate of xylose conversion to fatty alcohols in batch culture. Proteomic analysis confirmed that Pnt1 is a major regulator of pentose catabolism in R. toruloides. Deletion of RTO4_11990 increased the growth rate on xylose, but did not relieve carbon catabolite repression in the presence of glucose. Carbon catabolite repression signaling networks remain poorly characterized in R. toruloides and likely comprise a different set of proteins than those mainly characterized in ascomycete fungi.

BackgroundMitigation of climate change requires that new routes for the production of fuels and chemicals be as oil-independent as possible. The microbial conversion of lignocellulosic feedstocks into terpene-based biofuels and bioproducts represents one such route. This work builds upon previous demonstrations that the single-celled carotenogenic basidiomycete, Rhodosporidium toruloides, is a promising host for the production of terpenes from lignocellulosic hydrolysates.ResultsThis study focuses on the optimization of production of the monoterpene 1,8-cineole and the sesquiterpene α-bisabolene in R. toruloides. The α-bisabolene titer attained in R. toruloides was found to be proportional to the copy number of the bisabolene synthase (BIS) expression cassette, which in turn influenced the expression level of several native mevalonate pathway genes. The addition of more copies of BIS under a stronger promoter resulted in production of α-bisabolene at 2.2 g/L from lignocellulosic hydrolysate in a 2-L fermenter. Production of 1,8-cineole was found to be limited by availability of the precursor geranylgeranyl pyrophosphate (GPP) and expression of an appropriate GPP synthase increased the monoterpene titer fourfold to 143 mg/L at bench scale. Targeted mevalonate pathway metabolite analysis suggested that 3-hydroxy-3-methyl-glutaryl-coenzyme A reductase (HMGR), mevalonate kinase (MK) and phosphomevalonate kinase (PMK) may be pathway bottlenecks are were therefore selected as targets for overexpression. Expression of HMGR, MK, and PMK orthologs and growth in an optimized lignocellulosic hydrolysate medium increased the 1,8-cineole titer an additional tenfold to 1.4 g/L. Expression of the same mevalonate pathway genes did not have as large an impact on α-bisabolene production, although the final titer was higher at 2.6 g/L. Furthermore, mevalonate pathway intermediates accumulated in the mevalonate-engineered strains, suggesting room for further improvement.ConclusionsThis work brings R. toruloides closer to being able to make industrially relevant quantities of terpene from lignocellulosic biomass.

Intermittent energy restricted (IER) diets have become popular as a body weight management approach. In this pilot study, we investigated if an IER diet would reduce systemic inflammation and if maintaining an elevated protein level while on an IER diet would enhance satiety. Six healthy women, aged 33–55 years with a BMI of 27–33 kg/m2, were randomized to first adhere to either a low- or high-protein IER diet using whole foods for three weeks. They then returned to their regular diets for a week, after which they adhered to the second diet for three weeks. Each test diet consisted of three low-energy intake days followed by four isocaloric energy intake days. The diets differed only in protein content. High-sensitivity C-reactive protein (hs-CRP), glucose, satiety, body weight, and waist circumference were measured at the beginning and end of each dietary intervention. Most participants showed reductions in hs-CRP levels from baseline on both IER diets but reported greater satiety when adhering to the higher protein IER diet. Overall, the IER diets reduced body weight and appeared to decrease inflammation in these overweight women, and the higher protein version enhanced satiety, which may lead to greater long-term dietary adherence.

Abstract The Network for Pancreatic Organ donors with Diabetes (nPOD) is the largest biorepository of human pancreata and associated immune organs from donors with type 1 diabetes (T1D), maturity-onset diabetes of the young (MODY), cystic fibrosis-related diabetes (CFRD), type 2 diabetes (T2D), gestational diabetes, islet autoantibody positivity (AAb+), and without diabetes. nPOD recovers, processes, analyzes, and distributes high-quality biospecimens, collected using optimized standard operating procedures, and associated de-identified data/metadata to researchers around the world. Herein describes the release of high-parameter genotyping data from this collection. 372 donors were genotyped using a custom precision medicine single nucleotide polymorphism (SNP) microarray. Data were technically validated using published algorithms to evaluate donor relatedness, ancestry, imputed HLA, and T1D genetic risk score. Additionally, 207 donors were assessed for rare known and novel coding region variants via whole exome sequencing (WES). These data are publicly-available to enable genotype-specific sample requests and the study of novel genotype:phenotype associations, aiding in the mission of nPOD to enhance understanding of diabetes pathogenesis to promote the development of novel therapies.

Light-sheet microscopy has made possible the 3D imaging of both fixed and live biological tissue, with samples as large as the entire mouse brain. However, segmentation and quantification of that data remains a time-consuming manual undertaking. Machine learning methods promise the possibility of automating this process. This study seeks to advance the performance of prior models through optimizing transfer learning. We fine-tuned the existing TrailMap model using expert-labeled data from noradrenergic axonal structures in the mouse brain. By changing the cross-entropy weights and using augmentation, we demonstrate a generally improved adjusted F1-score over using the originally trained TrailMap model within our test datasets.

Every year individuals experience symptoms that remain undiagnosed by healthcare providers. In the United States, these rare diseases are defined as a condition that affects fewer than 200,000 individuals. However, there are an estimated 7000 rare diseases, and there are an estimated 25-30 million Americans in total (7.6-9.2% of the population as of 2018) affected by such disorders. The NIH Common Fund Undiagnosed Diseases Network (UDN) seeks to provide diagnoses for individuals with undiagnosed disease. Mass spectrometry-based metabolomics and lipidomics analyses could advance the collective understanding of individual symptoms and advance diagnoses for individuals with heretofore undiagnosed disease. Here, we report the mass spectrometry-based metabolomics and lipidomics analyses of blood plasma, urine, and cerebrospinal fluid from 148 patients within the UDN and their families, as well as from a reference population of over 100 individuals with no known metabolic diseases. The raw and processed data are available to the research community so that they might be useful in the diagnoses of current or future patients suffering from undiagnosed disorders.

Abstract Objective Antiseizure medications (ASMs) remain the mainstay of epilepsy treatment. These ASMs have mainly been tested in trials in adults with epilepsy, which subsequently led to market authorization (MA). For treatment of – especially young – children with epilepsy, several ASMs do not have a MA and guidelines are lacking, subsequently leading to “off‐label” use of ASMs. Even though “off‐label” ASM prescriptions for children could lead to more adverse events, it can be clinically appropriate and rational if the benefits outweigh the risks. This could be the case if “on‐label” ASM, in mono‐ or polytherapy, fails to achieve adequate seizure control. Methods The Medical Therapies Task Force of the International League Against Epilepsy (ILAE) Commission for Pediatrics performed a survey to study the current treatment practices in six classic, early life epilepsy scenarios. Our aim was not only to study first‐ and second‐line treatment preferences but also to illustrate the use of “off‐label” drugs in childhood epilepsies. Results Our results reveal that several ASMs (e.g. topiramate, oxcarbazepine, benzodiazepines) are prescribed “off‐label” in distinct scenarios of young children with epilepsy. In addition, recent scientific guidelines were not always adopted by several survey respondents, suggesting a potential knowledge gap. Significance We report the relatively common use of “off‐label” prescriptions that underlines the need for targeted and appropriately designed clinical trials, including younger patients, which will also result in the ability to generate evidence‐based guidelines.

Biological engineering of microorganisms to produce value-added chemicals is a promising route to sustainable manufacturing. However, overproduction of metabolic intermediates at high titer, rate, and yield from inexpensive substrates is challenging in non-model systems where limited information is available regarding metabolic flux and its control in production conditions. Integrated multi-omic analyses of engineered strains offers an in-depth look at metabolites and proteins directly involved in growth and production of target and non-target bioproducts. Here we applied multi-omic analyses to overproduction of the polymer precursor 3-hydroxypropionic acid (3HP) in the filamentous fungus Aspergillus pseudoterreus. A synthetic pathway consisting of aspartate decarboxylase, beta-alanine pyruvate transaminase, and 3HP dehydrogenase was designed and built for A. pseudoterreus. Strains with single- and multi-copy integration events were isolated and multi-omics analysis consisting of intracellular and extracellular metabolomics and targeted and global proteomics was used to interrogate the strains in shake-flask and bioreactor conditions. Production of a variety of co-products (organic acids and glycerol) and oxidative degradation of 3HP were identified as metabolic pathways competing with 3HP production. Intracellular accumulation of nitrogen as 2,4-diaminobutanoate was identified as an off-target nitrogen sink that may also limit flux through the engineered 3HP pathway. Elimination of the high-expression oxidative 3HP degradation pathway by deletion of a putative malonate semialdehyde dehydrogenase improved the yield of 3HP by 3.4 × after 10 days in shake-flask culture. This is the first report of 3HP production in a filamentous fungus amenable to industrial scale biomanufacturing of organic acids at high titer and low pH.

In this article, it is argued that it makes sense to define and distinguish three levels of human intelligence: intelligence as genotypical potential, intelligence as actualised in environmental interaction, and intelligence as measured by tests (IQ). This raises the questions of what is meant by the term "intelligence as potential", and how and in what sense does a child's cognitive potential express the parents' potential and genetics? The larger the number of genes involved in a certain trait, the more possibilities emerge for the formation of new combinations for that trait. The degree of similarity between a child and their parents depends on the "unique" combination of innate genes in each newborn child. The more genes are connected with a human trait or ability, the more refined or intricate the structure of the distribution for that trait in a population will be. The question of how a parents' genes relate to their children's genes has been studied, among other things, in 'twin studies'. Another relevant, but complicated question concerns the relation between genetics (nature) and environment (nurture). Nature appears to be at work in nurture, while nurture influences processes of nature. In psychological research, some DNA differences can be used to predict psychological differences, called polygenic scores. In this context, it is argued that individual cognitive growth comes about by all kinds of influences; psychologists call such influences 'bidirectional' influences. It is also argued that, ultimately, it is the individual human explorative "activity" that is responsible and a strong catalyst for the development and mastery of human traits and for the cognitive qualifications of all newborn children.

IntroductionLimited diagnostics are available for inherited neuromuscular diseases (NMD) in South Africa and (excluding muscle disease) are mainly aimed at the most frequent genes underlying genetic neuropathy (GN) and spastic ataxias in Europeans. In this study, we used next-generation sequencing to screen 61 probands with GN, hereditary spastic paraplegia (HSP), and spastic ataxias for a genetic diagnosis.MethodsAfter identifying four GN probands with PMP22 duplication and one spastic ataxia proband with SCA1, the remaining probands underwent whole exome (n = 26) or genome sequencing (n = 30). The curation of coding/splice region variants using gene panels was guided by allele frequencies from internal African-ancestry control genomes (n = 537) and the Clinical Genome Resource's Sequence Variant Interpretation guidelines.ResultsOf 32 GN probands, 50% had African-genetic ancestry, and 44% were solved: PMP22 (n = 4); MFN2 (n = 3); one each of MORC2, ATP1A1, ADPRHL2, GJB1, GAN, MPZ, and ATM. Of 29 HSP probands (six with predominant ataxia), 66% had African-genetic ancestry, and 48% were solved: SPG11 (n = 3); KIF1A (n = 2); and one each of SPAST, ATL1, SPG7, PCYT2, PSEN1, ATXN1, ALDH18A1, CYP7B1, and RFT1. Structural variants in SPAST, SPG11, SPG7, MFN2, MPZ, KIF5A, and GJB1 were excluded by computational prediction and manual visualisation.DiscussionIn this preliminary cohort screening panel of disease genes using WES/WGS data, we solved ~50% of cases, which is similar to diagnostic yields reported for global cohorts. However, the mutational profile among South Africans with GN and HSP differs substantially from that in the Global North.