Abstract
African populations are consistently underrepresented in molecular research on autism spectrum disorders (ASD). Yet, Africa’s genetic diversity could reveal novel mechanisms associated with ASD etiology. We review the molecular ASD research from Africa between 2016–2022, highlighting region-specific limitations, opportunities, and areas of progress. We emphasize a need to advance null-hypothesis based molecular studies in Africa, particularly in critically understudied Sub-Saharan African (SSA) populations. Using South Africa as a case study, we show that this geographical disparity is not solely attributable to sociocultural barriers nor to an absence of molecular research infrastructure. We emphasize the importance of interdisciplinary collaboration within SSA and internationally to harness existing infrastructure for the expansion of molecular ASD research in Africa.
Similar content being viewed by others
Avoid common mistakes on your manuscript.
Introduction
Autism spectrum disorder (ASD), a neurodevelopmental condition characterized by challenges related to behavior, communication, and cognition, is a leading cause of psychological distress in children and adolescents (Divan et al. 2021). The global prevalence of ASD is estimated to range from 0.6–1% but data availability varies widely between continents (Salari et al. 2022; Zeidan et al. 2022). The majority of current research is conducted in high-income countries (HICs) across the Global North while little is known about ASD in low-to-middle-income countries (LMICs) in the Global South, despite 95% of children with developmental disabilities residing in these settings (Vries 2016; Olusanya et al. 2018). Several studies have highlighted a critical shortage of ASD research from Africa during the preceding decades (Bakare and Munir 2011; Abubakar et al. 2016; Franz et al. 2017; Bakare et al. 2022; Salari et al. 2022). The three most recent reviews of ASD research in African regions found that there were no population-based prevalence studies of ASD in Sub-Saharan Africa (SSA), with only 0.5% of the world’s ASD research conducted in this region (Abubakar et al. 2016; Franz et al. 2017; Bakare et al. 2022). Several studies with limited scope in SSA reported prevalence rates of 0.08 to 2.3% (Pillay and Brownlow 2017; Abubakar et al. 2016; Salari et al. 2022), however these studies largely relied on convenience-based sampling and generally do not incorporate validated ASD diagnostic tools. Moreover, studies on the molecular etiology of ASD are the most limited; there are only four such publications from two African countries identified across all three reviews. Notably, none of these reviews go beyond reporting the significant shortage of molecular autism research in Africa, without discussing factors that may contribute to, exacerbate, or mitigate this geographical disparity.
Autism research aims to be inclusive and internationally relevant, but this requires that molecular research includes underrepresented populations. This is particularly pertinent in the context of ASD, given that it is a highly heterogeneous condition that is underpinned by substantial genetic complexity (Lord et al. 2020). Molecular research aims to elucidate the underlying mechanisms that contribute to ASD, which has crucial implications for the development of diagnostic biomarkers, therapeutic interventions, and other strategies to improve quality of life. However, since genetic associations differ significantly among populations, mitigating the geographical disparity in genomic research is recognized as a top priority in the field (Martin et al. 2018; Oni-Orisan et al. 2021; Sirugo et al. 2019). Thus, several recent scoping reviews have summarized the existing data on ASD in understudied populations, including Arabian (Almandil et al. 2019; Hussein and Taha 2013), Indian (Patra and Kar 2021), and Middle Eastern (Rahmani et al. 2021) populations.
However, a comprehensive scoping review of molecular ASD etiology in Africa has not been conducted in the last century. This is likely a result of the documented scarcity of molecular data from African populations. Moreover, research in Africa being driven by African research groups may not be a priority for most international publishers and African countries often lack the resources to fund research on non-communicable and neuropsychiatric conditions. Nevertheless, African genomes are characterized by rich genetic diversity and reduced linkage disequilibrium, which represents a unique resource for the discovery of novel genetic loci and high-powered genetic fine-mapping (Campbell and Tishkoff 2008; Sirugo et al. 2019; Tishkoff and Verrelli 2003). Thus, expanding molecular ASD research to include African populations has the potential to make valuable contributions to both local and global research efforts to characterize ASD etiology.
In this comprehensive scoping review, we collate data from molecular ASD research in Africa published since 2016. We quantitatively examine the geographical disparity in molecular ASD research and we thematically summarize the existing molecular literature on ASD in Africa. We explore molecular trends in current research with respect to molecular methodologies and convergent mechanisms implicated in African ASD cohorts. We consider the strengths and limitations of the current body of work in order to inform future research in this context. Finally, we interrogate the trends in ASD research and molecular research capacity in South Africa (SA) more closely, as a case study to inform the progression of ASD research in SSA.
Methods
Search Strategy
This scoping review was conducted according to the Arksey and O’Malley framework (Arksey and O’Malley 2005; Levac et al. 2010) and the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) framework (Moher et al. 2009). Briefly, we identified the research question, captured the studies for screening, selected the relevant studies for inclusion, charted the data, and finally, we collated, summarized, and reported our results. To identify peer-reviewed original research publications from 1 January 2016 to 31 December 2022, we conducted searches of PubMed and Scopus, and we searched AfricaWide, CINAHL, PsychArticles, and PsychInfo through EBSCOhost. For the PubMed search, both text words and Medical Subject Headings (MeSH) terms were used. The search strategy used a combination of three key concepts to identify molecular ASD research in the respective geographical regions of interest, using the search terms listed in Table 1. Concept one related to ASD and comprised a string of keywords such as "Autism Spectrum Disorder" OR "autism" OR "ASD". Concept two defined molecular study aspects using keywords such as "genetic" OR "molecular". The third concept specified the geographical region of interest with keywords such as "Brazil" OR "Brazilian". Using concepts one, two, and three, separate searches were done for the five regions of interest, i.e., Africa, Brazil, India, the United Kingdom (UK), and the United States of America (USA). Finally, we conducted a search to capture the volume and scope of all ASD publications from SA (2016–2022), using concepts one and three.
Eligibility Criteria
Articles from the molecular ASD searches in each region of interest were screened for eligibility based on the title and abstract using the following inclusion criteria:
-
i.
ASD was the primary focus of the study,
-
ii.
the study was carried out within the region of interest by authors from that region,
-
iii.
the study generated primary data, and
-
iv.
the study used molecular methods or reported molecular data.
For the search of all ASD research outputs from SA, eligibility criteria were as above, with the exception that the methods used in the study were not restricted to molecular techniques.
All searches were filtered for the date of publication (1 January 2016 – 31 December 2022). Studies that did not meet the above criteria were excluded. Dissertations and conference reports/abstracts were also excluded. Where there were numerous authors from multiple regions, studies were excluded if the main author and/or the ethics approval was not from the region of interest.
Screening and Selection
All research articles captured by the search strategy were exported to an EndNote 20 library and then uploaded to Rayyan (Ouzzani et al. 2016) which was used to remove duplicates and carry out screening for article inclusion. All publication titles and abstracts were independently reviewed by two authors, and any conflicts were resolved by a joint review of the full text. When an agreement was not reached, the senior author also reviewed the title and abstract to reach a consensus. The final PRISMA diagram depicting the screening and selection process is presented in Fig. 1.
Results
The articles that passed our eligibility criteria were collated and analyzed to address three main objectives. First, we quantitatively assessed publication output across Africa, two non-African LMICs, and two HICs to examine the geographical disparity in ASD molecular research. Secondly, we thematically summarized all molecular publications from Africa between 2016 and 2022 to provide an overview of the current state of research on ASD in African populations. Finally, we examined the trends in ASD research in SA (a LMIC in SSA) more closely to identify limitations and opportunities for ASD research in SSA.
The Geographical Disparity in Molecular ASD Research
This review set out to quantitatively measure the geographical disparity in molecular ASD research. To do this, we compared the research output from all 54 countries in Africa, two non-African LMICs (India and Brazil) and two HICs (the UK and the USA). We retrieved 2846 articles across all regions of interest, and after removing 569 duplicates and screening the dataset according to predefined eligibility criteria, 259 publications were included in the review (Fig. 1). A total of 84 and 68 publications were identified from the USA and the UK, respectively, with substantially lower outputs observed from Brazil (n = 34) and India (n = 36) (Fig. 2). Strikingly, the output from each of these non-African LMICs was roughly equivalent to the output from the entire African continent and was three times higher than the output from SSA. There were 37 publications from the entire African continent, originating from only seven of 54 African countries (Online Resource 1). Research from two northern African populations accounted for more than 75% of all the research produced from Africa between 2016–2022, of which more than 80% was produced in Egypt (n = 23). On the other hand, the SSA region produced only nine publications over the six-year period included in this review.
ASD Etiology in Africa: A Review of Recent Findings
In order to summarize the research progress and lay the foundation for future studies, we summarized the existing molecular literature on ASD in Africa based on methodological and mechanistic research themes. Of the 37 African molecular studies produced since 2016, 33 studies were conducted in African cohorts, three used the valproic acid animal model for ASD, and one study used previously published datasets in a bioinformatic analysis. The main findings from each of the African cohort studies are summarized in Table 2 and Online Resource 1. We identified 33 studies that examined molecular mechanisms in ASD cohorts from Egypt (n = 20), Tunisia (n = 4), SA (n = 3), Nigeria (n = 3), and Cameroon, Seychelles, and Uganda (n = 1). Of these, a majority of studies examined metabolites or trace elements (36%), proteins (27%), or genetic factors (23%). Conversely, studies on the epigenome, transcriptome, and microbiome were the most underrepresented (< 5%) (Fig. 3a). All 33 studies focused on one or more of four molecular mechanisms – metabolic or redox homeostasis (41%), chromosomal or genetic aberrations (25%), one-carbon metabolism (19%), and immune dysregulation (16%) (Fig. 3b).
This overview highlights the convergent nature of the data from African ASD cohorts, which highlights that intracontinental collaboration has the potential to advance this area of research. However, the prevailing scarcity of molecular ASD research in Africa demonstrates that this research is still in its infancy. Moreover, current data represents a small minority of African populations, whilst most regions – particularly in SSA – remain critically understudied. If research output is to be tangibly improved, it is critical to understand the factors that contribute to this geographical disparity in molecular autism research so that these factors can be mitigated.
ASD Research in South Africa: A Case Study in SSA
Previous reviews reported that over 50% of all ASD research in SSA between 1936 and 2017 originated from SA (Abubakar et al. 2016; Franz et al. 2017). Despite this, we found that SA produced only three molecular ASD publications in the last seven years; this is almost 9 times less than their northern African counterparts. Therefore, we examined the trends in ASD research in SA in order to characterize the capacity for molecular ASD research in the region. After screening ASD research from all thematic focus areas in SA published between 2016–2022, we identified 85 publications spanning eight thematic focus areas (Online Resource 2). Combining this data with three previous reviews (Abubakar et al. 2016; Franz et al. 2017; Bakare et al. 2022), we identified a total of 119 ASD studies ever published in SA up to 2022 (Fig. 4a). Interestingly, 87 of these studies (73%) were published between 2016 and 2022, which indicates a promising exponential increase in ASD research. However, this increase in output was not reflected in molecular research and only five molecular studies from SA were identified since 1935. In fact, molecular studies still represent the smallest focus area, making up only 3% of all ASD research in SA over the past five years (Fig. 4b). On the other hand, the most well-studied thematic focus areas relate to family or social aspects (40%), clinical or behavioral (15%), or educational (13%) aspects of ASD.
The regional scarcity of autism research is often attributed to socio-economic factors that include the pervasive stigmatization of ASD, poor access to healthcare, a lack of trained mental health professionals, an absence of specialized educational facilities, and a lack of culturally relevant diagnostic tools (Samadi 2022). These factors undoubtedly pose significant challenges to ASD research and have wide-reaching implications for the diagnosis and management of ASD in the region that have been comprehensively discussed elsewhere (Vries 2016); Divan et al. 2021; Franz et al. 2017; Pillay et al. 2021). Nevertheless, the much larger publication output in other thematic focus areas suggests that these factors cannot solely account for the paucity of molecular ASD research in SA. Therefore, we sought to investigate whether differences in molecular research capacity could explain the gap in research output. To do this, we examined established indices of molecular research capacity in SA compared to African (Nigeria and Egypt) and non-African (Brazil and India) LMICs to identify potential limiting factors (Fig. 4c). We included previously reported indices of health science research capacity in Africa (Wenham et al. 2021) as well as indices of molecular research infrastructure as reported in the UNESCO 2021 Science Report (UNESCO et al. 2021) which include indicators of research funding, infrastructure, human capital, and research output (Online Resource 3).
This assessment revealed that molecular autism research output across Africa deviated notably from several important indicators of research capacity. Among all the LMICs included in this analysis, SA produced the highest number of scientific publications and ranked among the highest in GDP per capita, Research and Development (R&D) expenditure, and number of researchers per million inhabitants (UNESCO et al 2021; The World Bank 2022). SA’s mental health research output is nearly 6 times that of Egypt (World Health Organisation (WHO) 2021) and SA has the top six universities in Africa with three of these ranking in the global top 500 universities (Round University Ranking 2023). Conversely, SA lags behind both Egypt and Brazil in terms of human capital. Compared to SA, Egypt has 1.3 times more researchers and almost 3 times the number of technicians per million inhabitants (UNESCO et al 2021). This highlights a deficit of skilled labor in the molecular sector that may contribute to the lack of molecular ASD research in SA. Nevertheless, this does not entirely account for the fact that SA produced between 6 and 10 times fewer molecular autism publications than non-African LMICs despite increased infrastructure relating to tertiary education, research, R&D, and mental healthcare.
Discussion
Molecular Mechanisms in African Cohorts
Molecular research in African cohorts has revealed four interdependent mechanisms implicated in ASD etiology; these mechanisms are well-established in the broader literature. Firstly, six studies from Egypt, Cameroon, and Tunisia focused solely on genetic alterations including chromosomal aberrations, copy number variants (CNVs), deletions, and duplications. These studies found that genetic aberrations were uncommon among the ASD cohort studies and are most reliably detected using large sample sizes and microarray-based or comparative genomic hybridization (CGH) techniques (El-Baz et al. 2016); Elserogy et al. 2017); Meguid et al. 2018); Kamga et al., 2020; Meguid et al. 2020; Chehbani et al. 2022). Four studies using traditional cytogenetic techniques revealed structural chromosomal abnormalities in 7.6% of Egyptian children (17/304), while the frequency of chromosomal abnormalities ranged from 0–7.5% across all four studies (El-Baz et al. 2016; Elserogy et al. 2017; Meguid et al. 2018; Meguid et al. 2020). A Tunisian study using higher resolution array-CGH identified CNVs of 207 genes that converged on synaptic signaling and neurogenesis pathways (Chehbani et al. 2022). These studies are consistent with the fact that only 10–20% of ASDs are attributed to known genetic causes, while individual gene mutations each account for less than 1% of all ASD cases globally (Geschwind 2011; Yoo 2015). Thus, the data from North African populations reinforces a well established premise that syndromic autism contributes to a minority of all ASD cases.
The remaining 27 African cohort studies used a range of molecular techniques to explore alterations to metabolic, redox, and immune homeostasis in ASD. Together, studies on metabolism or redox mechanisms accounted for almost half of all molecular ASD publications from Africa. These studies demonstrated metabolic and oxidative stress in cohorts from Egypt, Tunisia, SA, Nigeria, and Uganda at the level of the genome, epigenome, proteome, and metabolome (Khaled et al. 2016; Arony et al. 2018; El-Baz et al. 2018; Grayaa et al. 2018; Fotoh et al. 2019; Hassan et al. 2019; Chehbani et al. 2020; Stathopoulos et al. 2020; Bam et al. 2021; Omotosho et al. 2021). (Hassan et al. 2019) reported increased lactate and pyruvate levels, as well as upregulation of key mitochondrial enzymes, consistent with clinical observations of mitochondrial dysfunction reported in ASD (Griffiths and Levy 2017; Balachandar et al. 2021; Frye 2020). Moreover, independent studies reported serum carnitine deficiency (Arony et al. 2018; Hassan et al. 2019) and significant perturbations to cholesterol metabolism (Grayaa et al. 2018; Hassan et al. 2019) in African ASD cohorts. Carnitine is required for mitochondrial beta fatty acid oxidation and cholesterol is important for the availability of fat-soluble vitamins, the biosynthesis of steroid derivatives, and the development, function, and structure of the nervous system (Hassan et al. 2019). Notably, both carnitine and cholesterol metabolism have been explored as potential biomarkers in non-African populations (Frye et al. 2019; Kępka et al. 2021; Zhang et al. 2023) and therapeutic targets (Esposito et al. 2021; Frye 2020; Lin et al. 2023; Malaguarnera and Cauli 2019) in ASD.
Data from African ASD cohorts also illustrate changes to cofactors and trace elements involved in metabolic and redox homeostasis, with five studies reporting elevated levels of heavy metals (Hg, Pb, and Al) which are known to increase oxidative stress, perturb glutathione-dependent antioxidant responses, and induce secondary mitochondrial dysfunction (Fotoh et al. 2019; Hassan et al. 2019; Khaled et al. 2016; Omotosho et al. 2021; Said et al. 2021). Moreover, there were consistent reports of decreased Zn, Mg, Fe, Ca, and Vitamin D3 (Fotoh et al. 2019; Higazi et al. 2021; Meguid et al. 2017; Omotosho et al. 2021), as well as alterations to Cu (Chehbani et al. 2020; Fotoh et al. 2019; El-Baz et al. 2018; Omotosho et al. 2021) in African ASD cohorts. These essential trace elements not only function as critical cofactors for a variety of enzymes needed for metabolism, immune regulation, and neurogenesis, but are also important modulators of redox homeostasis. In line with this, six studies showed decreased antioxidant capacity and/or an increase in oxidative stress markers in Nigerian, South African, and Egyptian children (Bam et al. 2021; Hassan et al. 2019; Omotosho et al. 2021; Oshodi et al. 2017; Said et al. 2021; (Stathopoulos et al. 2020)). Of these, one study found urinary markers of oxidative stress that were associated with increased mitochondrial DNA copy number (Bam et al. 2021), while two studies identified genetic variants in glutathione S-transferases (GSTs) that are associated with oxidative stress in ASD (Oshodi et al. 2017; Said et al. 2021).
GSTs play an important role in one carbon (1C) metabolism, which was separately implicated in nine of the 33 cohort studies identified in this review. Genetic variants in key enzymes involved in the folate and methionine cycles were reported in children with ASD from Nigeria and Egypt (Esmaiel et al. 2020; Ismail et al. 2019; Khemir et al. 2016). Adjacent pathways responsible for phenylalanine and tryptophan metabolism were also implicated in genetic and mRNA expression data from Tunisian and Egyptian cohorts (Higazi et al. 2021; Khemir et al. 2016). Additionally, metabolomic studies revealed alterations across all three 1C cycles, including disruptions to serum folate, vitamin B12, cysteine, tryptophan, reduced glutathione, glutamine, glutamate, and GABA (El-Ansary et al. 2021; Fagbayi et al. 2018; Meguid et al. 2017). The 1C cycle is broadly implicated in ASD etiology as these metabolites play important roles in the synthesis and turnover of neurotransmitters including serotonin, dopamine, and glutamate (Hoxha et al. 2021; Tisato et al. 2021; Wei et al. 2021). Additionally, recent studies have shown that the folate and transsulfuration pathways show promise in the development of biomarkers for ASD (Qureshi and Hahn 2023).
Finally, eight studies from Egypt, Tunisia, and Seychelles examined immune abnormalities in ASD. These studies report increased inflammatory markers in ASD, as well as perturbations to immune regulators like interleukins-1β and -1RA, TAM receptor kinases and the T-cell modulator CD5 (Desoky et al. 2017; Saad et al. 2017, 2020; Mostafa et al. 2021, 2022) . Two studies showed that increased immune activation correlated significantly with reduced levels of vitamin D (Desoky et al. 2017; Saad et al. 2017), which is essential for the regulation of innate immune responses and also functions as an antioxidant to reduce mitochondrial dysfunction and oxidative stress. In fact, neuroimmune responses are regulated by both the metabolic (Marchi et al. 2023; Missiroli et al. 2020) and redox (Pangrazzi et al. 2020; Picca et al. 2020) mechanisms that have been implicated in other African cohorts. Interestingly, (Mostafa et al. 2021) reported that the levels of brain-specific auto-antibodies correlated significantly with levels of serotonin in ASD, while (Desoky et al. 2017) showed that immune activation was associated with decreased levels of thyroid stimulating hormone (TSH). Both serotonin and TSH are derived from 1C metabolic precursors and, in addition to their role in immune homeostasis, each are implicated in the regulation of neurodevelopment, neurotransmission, and behavior in ASD (Muller et al. 2016; Daly et al. 2019; Ames et al. 2020)). Together, these findings provide evidence for an interplay between mitochondrial metabolism, oxidative stress, and immune dysregulation in African ASD cohorts. This provides a mechanistic framework to inform the future work that will be critical to address the current knowledge gaps in African populations.
Molecular Autism Research in Africa: Current Gaps in the Literature
This review illustrates the relative scarcity of molecular ASD research in Africa, but the existing data is also inherently limited in terms of sample size and scope. Across all 33 cohort studies, the mean sample size per study came to 110 individuals, with a mode of 40. More than 55% of studies had cohorts of fewer than 100 individuals and more than 90% included fewer than 200 individuals. These sample sizes are significantly lower than cohorts from countries in the Global North, and smaller cohorts are particularly limiting in the context of such a genetically heterogeneous disorder. Sample sizes also limit the scope and specificity of the research that can be done. Of 33 studies, only two used a null-hypothesis based approach as opposed to a targeted investigation of single genes, proteins, or metabolites.
This approach has both advantages and limitations in this context. On the one hand, these methods contribute to the identification of proteins or metabolites that could serve as biomarkers for ASD in Africa. Moreover, large-scale "omics" studies are costly and typically require cohorts much larger than any of those in the studies listed above. However, targeted approaches are based on data from cohorts in the Global North, with their different genealogies. Whilst downstream mechanisms may indeed converge on pathways that have previously been implicated in different populations, African populations are likely to have significant differences in their upstream genetic architecture. Therefore, null-hypothesis based approaches are essential to drive meaningful research into the unique aspects of ASD etiology in African populations.
Notably, two research groups used alternative approaches to circumvent these limitations (Chehbani et al. 2022) used array comparative genomic hybridization (aCGH) which maps CNVs to a resolution of 5–100 kb, as opposed to the 3–5 Mb resolution of traditional cytogenetic techniques. While aCGH provides less resolution than whole genome sequencing (WGS), it facilitates mapping of structural changes at specific loci which allows for mechanistic conclusions to be made. It is also far less costly than WGS and, in combination with well-phenotyped probands from both multiplex and simplex families, is able to yield significant results in smaller cohorts. Similarly, (Stathopoulos et al. 2020) conducted a whole-epigenome screen (WES) in a small South African cohort. In contrast to WGS, WES yields insight into mechanisms that directly alter gene expression and consequently require fewer individuals to draw meaningful mechanistic conclusions. This approach highlighted a significant enrichment of mitochondrial pathways among differentially methylated genes, which informed subsequent targeted studies to validate this hypothesis. These studies provide examples of how null-hypothesis based molecular research can be done in the African context.
Similarly, it will be important to address the skewed nature of molecular research in Africa in terms of the molecular approaches that are used. The vast majority of studies in African cohorts have investigated proteins, metabolites, or trace elements, whilst only three studies investigated either transcriptomic or epigenomic changes. Proteomic and metabolomic changes are undoubtedly useful to identify functional changes to certain mechanisms, and to identify potential biomarkers that could be used in a diagnostic context. The development of accurate diagnostic strategies is a priority among stakeholders in autism communities (Dey, et al. 2023). Additionally, both proteomic and metabolomic studies are well-positioned to provide insight into the functional manifestations of genetic diversity in small African cohorts. Moreover, the current research infrastructure and published data from African populations can be used to inform future molecular ASD research efforts in Africa. Given the current African research context, Africa’s clinical diagnostic infrastructure could be harnessed for high-throughput, less expensive metabolomic screens to upscale molecular ASD research in the short term. Building on the existing proteomic and metabolomic data could facilitate a better understanding of the oxidative, metabolic and immune processes implicated in African populations, and how these mechanisms could inform novel diagnostic biomarkers.
However, transcriptomic and epigenomic studies are essential to understand the regulatory mechanisms responsible for changes to gene expression and function and to identify molecular targets that are responsible for a range of pleiotropic systemic alterations. As more advanced molecular techniques become more affordable and molecular infrastructure develops across Africa, such studies will become more possible in understudied African populations. Intracontinental collaborations between healthcare providers and molecular scientists would greatly facilitate the building of cohorts large enough for this type of research. Likewise, international collaborations that facilitate access to high throughput molecular techniques could play an instrumental role in improving our understanding of the genetic and epigenetic architecture that underlies ASD in Africa.
A Focus on Sub-Saharan Africa: Lessons from South Africa
This review demonstrated the paucity of molecular research on SSA populations. Given SA’s recorded contribution to autism research in SSA, a scrutiny of their ASD research capacity may provide insight into the underlying reasons for this gap in the literature. Despite producing more than 50% of all ASD research in SSA and an exponential increase in research output over the last decade, SA produced only five molecular ASD publications since 1935. This is in stark contrast to Egypt, which has contributed more than 80% of all molecular ASD research from Africa since 2016. Yet, SA outranks Egypt with respect to GDP per capita, number of research institutions, and both scientific and mental health research output. Indeed, a previous review of health science research capacity showed that SA ranked first in Africa with respect to the number of universities, first author publications, and clinical trials (Wenham et al. 2021). Where SA falls short is in human research capital, most significantly in terms of the number of technicians per million inhabitants.
Indeed, a noted weakness of SA’s science sector is that R&D expenditure focuses on infrastructure but neglects the operational costs of research (HESTIIL Ministerial Committee 2020). Moreover, the number of total researchers and technicians in SA has declined since 2017 and 2015, respectively (National Advisory Council on Innovation 2022). Consequently, research in SA is heavily dependent on foreign doctoral and postdoctoral students, only 10% of whom remain in SA long-term, whilst 11 800 skilled workers per year are lost to emigration (National Advisory Council on Innovation 2021). These factors culminate in a relative shortage of skilled research workers. This may significantly impact molecular and genetic research, which is dependent on full-time, highly skilled laboratory technicians for data generation.
This deficit of human capital also means that differential resource allocation could profoundly skew research output across different sectors. Much of SA’s biomedical capacity is apportioned to infectious diseases research, which represent a huge health burden in SSA (Bhutta et al. 2014); (Boutayeb 2010). This is reflected in foreign and local funding that has driven research on human immunodeficiency virus and acquired immunodeficiency syndrome (HIV/AIDS), tuberculosis (TB), malaria and more recently SARS-CoV-2 (Arvanitis et al. 2022; N.D. of H. 2022). As a result, SA matched Egypt’s research output in Immunology and Microbiology over the past five years (SJR 2022). However, Egypt’s output in Biochemistry and Genetics was 40% higher than SA’s, despite SA’s H index – a measure of research quality and impact – being higher during the same period. Thus, SA has the infrastructure to produce high quality molecular research, but the majority of its constrained pool of human resources is likely allocated to infectious disease research, at the expense of molecular research into other areas.
Finally, molecular research generally requires larger sample sizes than other areas of autism research. Consequently, molecular studies are likely to be most impacted by the barriers to diagnosis and a lack of a centralized national support system in SSA, which pose significant challenges to establishing large study cohorts. Although SA has more child psychiatrists per 100 000 inhabitants than Egypt, Brazil, or India (World Health Organisation (WHO) 2021), 80% of psychiatrists in SA work in the private sector, while rural sectors average only 0.03 mental health specialists per 100 000 people (Janse van Rensburg et al. 2022). Moreover, there is insufficient training of public healthcare nurses, which limits their capacity to facilitate referrals for a diagnosis (Petersen et al. 2009). The average waiting period for a child to receive a clinical diagnosis in an autism specialist clinic is at least 18 months (Guler et al. 2018), and SA has only nine autism specialist schools with an estimated waiting period of more than three years for enrolment (Franz et al. 2018; Pillay and Brownlow 2017). The significant shortage of appropriate healthcare and educational facilities means that SA has little potential for centralized ASD data collection that would enable building the large cohorts that facilitate ASD research in HICs.
Nevertheless, SA has the infrastructure to produce high quality research in both autism and molecular biology. SA has historically produced half of the total ASD research in SSA, and this output has increased exponentially in recent years. Concurrently, SA is established as a continental leader in genetic research (Shaffer et al. 2019; Wenham et al. 2021). A shortage of skilled researchers and technicians in SA combined with a prioritization of infectious disease research has constrained molecular research on non-communicable diseases. Similarly, research on autism and other neuropsychiatric conditions faces funding shortages, and prioritizes studies on diagnosis and intervention rather than an understanding of molecular etiology. Still, the fact that SA is separately established as a continental leader in both genetic and autism research suggests that harnessing these resources could play a significant role in improving ASD research from and within SSA as awareness and understanding of ASD improves.
Region-Specific Opportunities and Considerations
Historically, molecular autism publications in SSA hailed from SA and Nigeria, but we report recent publications from Cameroon, Uganda, and the Seychelles that indicate an emerging interest in the region. Moreover, the recent acceleration of the African Pathogen Genomics Initiative in the wake of the COVID-19 pandemic has expanded sequencing capacity and transport networks across SSA (Ibe et al. 2023). These trends suggest an increasing capacity for molecular ASD research in SSA; however, the allocation of funding to drive such research will require an increased awareness and understanding of ASD among local stakeholders. Additionally, interdisciplinary and cross-border collaborations could be essential to circumvent socioeconomic barriers.
It is undisputed that molecular research in genetically diverse populations is globally significant, and international collaborations have facilitated some of the first ASD research in neglected SSA populations (Arony et al. 2018); Irwin et al. 2019; Kamga et al., 2020). However, the most effective collaborations will avoid thee "mining" of genetic diversity for the benefit of global research without yielding tangible benefits to the local African communities used in these studies. Thus, it is important to limit parachute research that uses African cohorts without facilitating the development of infrastructure or human resources to drive future research in Africa (Bentley et al. 2019).
It is also critical for international collaborators to work closely with African researchers to navigate cultural and linguistic differences. General awareness and understanding about autism in SSA lags behind the Global North, with a pervasive stigmatization of ASD sometimes rooted in culture-bound beliefs that autism has supernatural causes (Booysen et al. 2021; Vries 2016; Gona et al. 2015). Thus, molecular researchers have to be particularly intentional about taking a neurodiversity-informed approach to avoid perpetuating this deficits-based view of ASD. Here, it is worth highlighting Kamga et al. (2020) as an example of research design that also improves local understanding of ASD and community support networks. While not all studies will have the resources or expertise to integrate these aims so thoroughly, any effort to facilitate a better understanding of ASD could meaningfully improve the lives of study participants long before molecular interventions are likely to be available in these contexts.
In conclusion, this review reports a critically low number of molecular ASD publications from Africa, particularly SSA, compared to Brazil, India, the UK, and the USA. Addressing the shortage of molecular research in Africa is paramount for the advancement of global autism research, given the distinctive genetic diversity of African populations. Funding is crucial for propelling research capacity, and resources will need to be reallocated to redress the shortfall in molecular ASD studies. An increased focus on molecular ASD research in Africa could be instrumental in expanding our understanding of ASD etiology to understudied populations. This may ultimately improve the quality of life for individuals with autism in Africa who are navigating a challenging socio-economic and cultural landscape.
Data Availability
All data included in this review is available in public online databases or included as supplementary material in the online resources.
References
Abdel Ghaffar, H. M. G. E. D., et al. (2022). Study of serum neopterin in children with attention deficit hyperactivity disorder and autistic spectrum disorder: Fayoum Governorate, Egypt. Egypt J Neurol Psychiatry Neurosurg, 58(1), 1–6. https://doi.org/10.1186/s41983-022-00448-y
Abubakar, A., Ssewanyana, D., & Newton, C. R. (2016). A systematic review of research on autism spectrum disorders in Sub-Saharan Africa. Behavioural Neurology, 2016, 3501910. https://doi.org/10.1155/2016/3501910
Almandil, N., et al. (2019). Environmental and genetic factors in autism spectrum disorders: Special emphasis on data from Arabian studies. International Journal of Environmental Research and Public Health, 16(4), 658. https://doi.org/10.3390/ijerph16040658
Ames, J. L., et al. (2020). Neonatal thyroid stimulating hormone and subsequent diagnosis of autism spectrum disorders and intellectual disability. Autism Research, 13(3), 444–455. https://doi.org/10.1002/aur.2247
Arksey, H., & O’Malley, L. (2005). Scoping studies: Towards a methodological framework. International Journal of Social Research Methodology, 8(1), 19–32. https://doi.org/10.1080/1364557032000119616
Arony, D. A., Gazda, S., & Kitara, D. L. (2018). ‘Could nodding syndrome in Northern Uganda be a form of autism spectrum disorder? An observational study design. Pan African Medical Journal, 30, 115. https://doi.org/10.11604/pamj.2018.30.115.13634
Arvanitis, R., Mouton, J., & Néron, A. (2022). Funding research in Africa: Landscapes of re-institutionalisation. Science, Technology and Society, 27(3), 351–367. https://doi.org/10.1177/09717218221078235
Bakare, M., & Munir, K. (2011). Autism spectrum disorders (ASD) in Africa: A perspective. African Journal of Psychiatry, 14(3), 208–210. https://doi.org/10.4314/ajpsy.v14i3.3
Bakare, M. O., et al. (2022). Picture of autism spectrum disorder (ASD) research in West Africa — A scoping review. Research in Autism Spectrum Disorders, 90, 101888. https://doi.org/10.1016/j.rasd.2021.101888
Balachandar, V., et al. (2021). Mitochondrial dysfunction: A hidden trigger of autism? Genes & Diseases, 8(5), 629–639. https://doi.org/10.1016/j.gendis.2020.07.002
Bam, S., et al. (2021). DNA methylation of PGC-1α is associated with elevated mtDNA copy number and altered urinary metabolites in autism spectrum disorder. Frontiers in Cell and Developmental Biology, 9, 696428. https://doi.org/10.3389/fcell.2021.696428
Bentley, A. R., Callier, S., & Rotimi, C. (2019). ‘The emergence of genomic research in Africa and new frameworks for equity in biomedical research. Ethnicity & Disease, 29(Suppl 1), 179–186. https://doi.org/10.18865/ed.29.S1.179
Bhutta, Z. A., et al. (2014). Global burden, distribution, and interventions for infectious diseases of poverty. Infectious Diseases of Poverty, 3, 21. https://doi.org/10.1186/2049-9957-3-21
Booysen, D., Mahe-Poyo, P., & Grant, R. (2021). The experiences and perceptions of mental health service provision at a primary health centre in the Eastern Cape. South African Journal of Psychiatry, 27, a1641. https://doi.org/10.4102/sajpsychiatry.v27i0.1641
Boutayeb, A. (2010) ‘The impact of infectious diseases on the development of Africa’, in Handbook of Disease Burdens and Quality of Life Measures. New York, NY: Springer New York, 1171–1188. https://doi.org/10.1007/978-0-387-78665-0_66.
Campbell, M. C., & Tishkoff, S. A. (2008). African genetic diversity: Implications for human demographic history, modern human origins, and complex disease mapping. Annual Review of Genomics and Human Genetics, 9, 403–433. https://doi.org/10.1146/annurev.genom.9.081307.164258
Chehbani, F., et al. (2020). The status of chemical elements in the blood plasma of children with autism spectrum disorder in Tunisia: A case-control study. Environmental Science and Pollution Research, 27(28), 35738–35749. https://doi.org/10.1007/s11356-020-09819-5
Chehbani, F., et al. (2022). Yield of array-CGH analysis in Tunisian children with autism spectrum disorder. Molecular Genetics & Genomic Medicine, 10(8), e1939. https://doi.org/10.1002/mgg3.1939
Daly, E., Tricklebank, M.D. and Wichers, R. (2019) ‘Neurodevelopmental roles and the serotonin hypothesis of autism spectrum disorder’, in The Serotonin System. Academic Press, pp. 23–44. https://doi.org/10.1016/B978-0-12-813323-1.00002-5.
de Vries, P. J. (2016). Thinking globally to meet local needs: Autism spectrum disorders in Africa and other low-resource environments. Current Opinion in Neurology, 29(2), 130–136. https://doi.org/10.1097/WCO.0000000000000297
Desoky, T., et al. (2017). Biochemical assessments of thyroid profile, serum 25-hydroxycholecalciferol and cluster of differentiation 5 expression levels among children with autism. Neuropsychiatric Disease and Treatment, 13, 2397–2403. https://doi.org/10.2147/NDT.S146152
Dey, I. et al. (2023) ‘Autism community priorities in diverse low-resource settings: A country-wide scoping exercise in India’, Autism, 0(0). https://doi.org/10.1177/13623613231154067
Divan, G., et al. (2021). Annual research review: Achieving universal health coverage for young children with autism spectrum disorder in low- and middle-income countries: A review of reviews. Journal of Child Psychology and Psychiatry, 62(2), 514–535. https://doi.org/10.1111/jcpp.13404
El Fotoh, W. M. M. A., El Naby, S. A. A., & Abd El Hady, N. M. S. (2019). Autism spectrum disorders: The association with inherited metabolic disorders and some trace elements. A retrospective study. CNS & Neurological Disorders - Drug Targets, 18(5), 413–420. https://doi.org/10.2174/1871527318666190430162724
El-Ansary, A., et al. (2021). GABA synaptopathy promotes the elevation of caspases 3 and 9 as pro-apoptotic markers in Egyptian patients with autism spectrum disorder. Acta Neurologica Belgica, 121(2), 489–501. https://doi.org/10.1007/s13760-019-01226-z
El-Baz, F., et al. (2016). Chromosomal abnormalities and autism. Egyptian Journal of Medical Human Genetics, 17(1), 57–62. https://doi.org/10.1016/j.ejmhg.2015.05.002
El-Baz, F., Mowafy, M. E., & Lotfy, A. (2018). Study of serum copper and ceruloplasmin levels in Egyptian autistic children. Egyptian Journal of Medical Human Genetics, 19(2), 113–116. https://doi.org/10.1016/j.ejmhg.2017.08.002
Elserogy, Y., et al. (2017). Chromosomal aberrations in children with autism spectrum disorders in Upper Egypt. Anatolian Journal of Psychiatry, 18(3), 243–249. https://doi.org/10.5455/apd.244540
Esmaiel, N. N., et al. (2020). The potential impact of COMT gene variants on dopamine regulation and phenotypic traits of ASD patients. Behavioural Brain Research, 378, 112272. https://doi.org/10.1016/j.bbr.2019.112272
Esposito, C. M., et al. (2021). The role of cholesterol and fatty acids in the etiology and diagnosis of autism spectrum disorders. International Journal of Molecular Sciences, 22(7), 3550. https://doi.org/10.3390/ijms22073550
Fagbayi, T. A., et al. (2018). Neurotransmitter and amino acid levels in Nigerian children with autism spectrum disorders. Nigerian Journal of Paediatrics, 45(3), 129–134. https://doi.org/10.4314/njp.v45i3.1
Franz, L., et al. (2017). Autism spectrum disorder in sub-saharan africa: A comprehensive scoping review. Autism Research, 10, 723–749. https://doi.org/10.1002/aur.1766
Franz, L., et al. (2018). Providing early detection and early intervention for autism spectrum disorder in South Africa: Stakeholder perspectives from the Western Cape province. Journal of Child & Adolescent Mental Health, 30(3), 149–165. https://doi.org/10.2989/17280583.2018.1525386
Frye, R. E. (2020). Mitochondrial dysfunction in autism spectrum disorder: Unique abnormalities and targeted treatments. Seminars in Pediatric Neurology, 35, 100829. https://doi.org/10.1016/j.spen.2020.100829
Frye, R. E., et al. (2019). ‘Emerging biomarkers in autism spectrum disorder: A systematic review. Annals of Translational Medicine, 7(23), 792. https://doi.org/10.21037/atm.2019.11.53
Geschwind, D. H. (2011). Genetics of autism spectrum disorders. Trends in Cognitive Sciences, 15(9), 409–416. https://doi.org/10.1016/j.tics.2011.07.003
Gona, J. K., et al. (2015). Parents’ and professionals’ perceptions on causes and treatment options for autism spectrum disorders (ASD) in a multicultural context on the Kenyan Coast. PLoS ONE, 10(8), e0132729. https://doi.org/10.1371/journal.pone.0132729
Grayaa, S., et al. (2018). Plasma oxysterol profiling in children reveals 24-hydroxycholesterol as a potential marker for autism spectrum disorders. Biochimie, 153, 80–85. https://doi.org/10.1016/j.biochi.2018.04.026
Griffiths, K. K., & Levy, R. J. (2017). Evidence of mitochondrial dysfunction in autism: biochemical links, genetic-based associations, and non-energy-related mechanisms. Oxidative Medicine and Cellular Longevity, 2017, 4314025. https://doi.org/10.1155/2017/4314025
Guler, J., et al. (2018). The importance of context in early autism intervention: A qualitative South African study. Autism, 22(8), 1005–1017. https://doi.org/10.1177/1362361317716604
Hassan, M. H., et al. (2019). Possible metabolic alterations among autistic male children: Clinical and biochemical approaches. Journal of Molecular Neuroscience, 67(2), 204–216. https://doi.org/10.1007/s12031-018-1225-9
HESTIIL Ministerial Committee (2020) A New Pathway 2030: Catalysing South Africa’s NSI for Urgent Scaled Social and Economic Impact. http://www.dst.gov.za/images/2021/Higher%20Education,%20Science,%20Technology%20and%20Innovation%20Institutional%20Landscape%20Review%20Report.pdf (Accessed: 3 August 2023).
Higazi, A. M., et al. (2021). Expression analysis of selected genes involved in tryptophan metabolic pathways in Egyptian children with Autism Spectrum Disorder and learning disabilities. Scientific Reports, 11(1), 6931. https://doi.org/10.1038/s41598-021-86162-w
Hoxha, B., et al. (2021). Folic acid and autism: A systematic review of the current state of knowledge. Cells, 10(8), 1976. https://doi.org/10.3390/cells10081976
Hussein, H., & Taha, G. R. A. (2013). Autism spectrum disorders: A review of the literature from Arab countries. Middle East Current Psychiatry, 20, 106–116. https://doi.org/10.1097/01.XME.0000430433.49160.a4
Ibe, C., Otu, A. A., & Mnyambwa, N. P. (2023). Advancing disease genomics beyond COVID-19 and reducing health disparities: What does the future hold for Africa? Briefings in Functional Genomics, 22(3), 241–249. https://doi.org/10.1093/bfgp/elac040
Irwin, J. L., et al. (2019). Maternal gestational immune response and autism spectrum disorder phenotypes at 7 years of age in the Seychelles child development study. Molecular Neurobiology, 56(7), 5000–5008. https://doi.org/10.1007/s12035-018-1424-y
Ismail, S., et al. (2019). Study of C677T variant of methylene tetrahydrofolate reductase gene in autistic spectrum disorder Egyptian children. American Journal of Medical Genetics Part b: Neuropsychiatric Genetics, 180(5), 305–309. https://doi.org/10.1002/ajmg.b.32729
Janse van Rensburg, B., et al. (2022). Profile of the current psychiatrist workforce in South Africa: Establishing a baseline for human resource planning and strategy. Health Policy and Planning, 37(4), 492–504. https://doi.org/10.1093/heapol/czab144
Kamga, K. K., et al. (2020). Cascade testing for Fragile X Syndrome in a rural setting in Cameroon (Sub-Saharan Africa). Genes, 11(2), 136. https://doi.org/10.3390/genes11020136
Kępka, A., et al. (2021). Potential role of L-carnitine in autism spectrum disorder. Journal of Clinical Medicine, 10(6), 1202. https://doi.org/10.3390/jcm10061202
Khaled, E. M., et al. (2016). Altered urinary porphyrins and mercury exposure as biomarkers for autism severity in Egyptian children with autism spectrum disorder. Metabolic Brain Disease, 31(6), 1419–1426. https://doi.org/10.1007/s11011-016-9870-6
Kharrat, N., et al. (2020). Non-classical human leukocyte antigen class I in Tunisian children with autism. Cent J Immunol, 45(2), 176–183. https://doi.org/10.5114/ceji.2020.97906
Khemir, S., et al. (2016). Autism in Phenylketonuria patients: From clinical presentation to molecular defects. Journal of Child Neurology, 31(7), 843–849. https://doi.org/10.1177/0883073815623636
Levac, D., Colquhoun, H., & O’Brien, K. K. (2010). Scoping studies: Advancing the methodology. Implementation Science, 5, 69. https://doi.org/10.1186/1748-5908-5-69
Lin, J., et al. (2023). Cholesterol metabolism pathway in autism spectrum disorder: From animal models to clinical observations. Pharmacology Biochemistry and Behavior, 223, 173522. https://doi.org/10.1016/j.pbb.2023.173522
Lord, C., et al. (2020). Autism Spectrum Disorder. Nature Reviews Disease Primers, 6, 5. https://doi.org/10.1038/s41572-019-0138-4
Malaguarnera, M., & Cauli, O. (2019). Effects of l-carnitine in patients with autism spectrum disorders: Review of clinical studies. Molecules, 24(23), 4262. https://doi.org/10.3390/molecules24234262
Marchi, S., et al. (2023). Mitochondrial control of inflammation. Nature Reviews Immunology, 23(3), 159–173. https://doi.org/10.1038/s41577-022-00760-x
Martin, A. R., et al. (2018). The critical needs and challenges for genetic architecture studies in Africa. Current Opinion in Genetics & Development, 53, 113–120. https://doi.org/10.1016/j.gde.2018.08.005
Meguid, N. A., et al. (2017). Dietary adequacy of Egyptian children with autism spectrum disorder compared to healthy developing children. Metabolic Brain Disease, 32(2), 607–615. https://doi.org/10.1007/s11011-016-9948-1
Meguid, N. A., et al. (2018). Contribution of chromosomal abnormalities at 10q and 22q to autism. Research in Autism Spectrum Disorders, 50, 43–50. https://doi.org/10.1016/j.rasd.2018.03.003
Meguid, N. A., et al. (2020). Copy number variations of SHANK3 and related sensory profiles in Egyptian children with autism spectrum disorder. Research in Autism Spectrum Disorders, 75, 101558. https://doi.org/10.1016/j.rasd.2020.101558
Missiroli, S., et al. (2020). The Role of mitochondria in inflammation: From cancer to neurodegenerative disorders. Journal of Clinical Medicine, 9(3), 740. https://doi.org/10.3390/jcm9030740
Moher, D., et al. (2009). Preferred reporting items for systematic reviews and meta-analyses: The PRISMA statement. Annals of Internal Medicine, 151(4), 264–269. https://doi.org/10.7326/0003-4819-151-4-200908180-00135
Mostafa, G. A., et al. (2021). Plasma levels of nerve growth factor in Egyptian autistic children: Relation to hyperserotonemia and autoimmunity. Journal of Neuroimmunology, 358, 577638. https://doi.org/10.1016/j.jneuroim.2021.577638
Mostafa, G. A., et al. (2022). Up-regulated serum levels of TAM receptor tyrosine kinases in a group of Egyptian autistic children. Journal of Neuroimmunology, 15, 364. https://doi.org/10.1016/j.jneuroim.2022.577811
Muller, C. L., Anacker, A. M. J., & Veenstra-VanderWeele, J. (2016). The serotonin system in autism spectrum disorder: From biomarker to animal models. Neuroscience, 321, 24–41. https://doi.org/10.1016/j.neuroscience.2015.11.010
National Advisory Council on Innovation (2022) South African science, technology and innovation indicators report. http://www.naci.org.za/wp-content/uploads/2022/07/141483-DST-Report-25-July-12h20.pdf (Accessed: 3 August 2023).
National Advisory Council on Innovation (2021) South African science, technology and innovation indicators report. http://www.dst.gov.za/images/NACI_2021-STI-Indicators-Report-_Final.pdf (Accessed: 3 August 2023).
National Health Research Committee, N.D. of H. (2022) Health research priorities (revised) for South Africa 2021–2024. http://www.health.gov.za/wp-content/uploads/2022/05/National-Health-Research-Priorities-2021-2024.pdf (Accessed: 3 August 2023).
Olusanya, B. O., et al. (2018). Developmental disabilities among children younger than 5 years in 195 countries and territories, 1990–2016: A systematic analysis for the Global Burden of Disease Study 2016. The Lancet Global Health, 6(10), e1100–e1121. https://doi.org/10.1016/S2214-109X(18)30309-7
Omotosho, I. O., et al. (2021). Oxidative stress indices in ASD children in Sub-Sahara Africa. Journal of Neurodevelopmental Disorders, 13(1), 50. https://doi.org/10.1186/s11689-021-09379-w
Oni-Orisan, A., et al. (2021). Embracing genetic diversity to improve black health. New England Journal of Medicine, 384, 1163–1167. https://doi.org/10.1056/NEJMms2031080
Oshodi, Y., et al. (2017). Oxidative stress markers and genetic polymorphisms of glutathione S-transferase T1, M1, and P1 in a subset of children with autism spectrum disorder in Lagos, Nigeria. Nigerian Journal of Clinical Practice, 20(9), 1161–1167. https://doi.org/10.4103/njcp.njcp_282_16
Ouzzani, M., et al. (2016). Rayyan — a web and mobile app for systematic reviews. Systematic Reviews, 5, 210. https://doi.org/10.1186/s13643-016-0384-4
Pangrazzi, L., Balasco, L., & Bozzi, Y. (2020). Oxidative stress and immune system dysfunction in autism spectrum disorders. International Journal of Molecular Sciences, 21(9), 3293. https://doi.org/10.3390/ijms21093293
Patra, S., & Kar, S. K. (2021). Autism spectrum disorder in India: A scoping review. International Review of Psychiatry, 33(1–2), 81–112. https://doi.org/10.1080/09540261.2020.1761136
Petersen, I., et al. (2009). Planning for district mental health services in South Africa: A situational analysis of a rural district site. Health Policy and Planning, 24(2), 140–150. https://doi.org/10.1093/heapol/czn049
Picca, A., et al. (2020). Mitochondrial dysfunction, oxidative stress, and neuroinflammation: Intertwined roads to neurodegeneration. Antioxidants, 9(8), 647. https://doi.org/10.3390/antiox9080647
Pillay, Y., & Brownlow, C. (2017). Predictors of successful employment outcomes for adolescents with autism spectrum disorders: A systematic literature review. Review Journal of Autism and Developmental Disorders, 4, 1–11. https://doi.org/10.1007/s40489-016-0092-y
Pillay, S., Duncan, M., & de Vries, P. J. (2021). Autism in the Western Cape province of South Africa: Rates, socio-demographics, disability and educational characteristics in one million school children. Autism, 25(4), 1076–1089. https://doi.org/10.1177/1362361320978042
Qureshi, F., & Hahn, J. (2023). Towards the development of a diagnostic test for autism spectrum disorder: Big data meets metabolomics. The Canadian Journal of Chemical Engineering, 101(1), 9–17. https://doi.org/10.1002/cjce.24594
Rahmani, Z., et al. (2021). Genetic and molecular biology of autism spectrum disorder among Middle East population: A review. Human Genomics, 15(1), 17. https://doi.org/10.1186/s40246-021-00319-2
Round University Ranking (2023) World University Rankings. roundranking.com/ranking/world-university-rankings.html#world-2023 (Accessed: 3 August 2023).
Saad, K., et al. (2017). Frequency of dendritic cells and their expression of costimulatory molecules in children with autism spectrum disorders. Journal of Autism and Developmental Disorders, 47(9), 2671–2678. https://doi.org/10.1007/s10803-017-3190-5
Saad, K., et al. (2020). Polymorphism of interleukin-1β and interleukin-1 receptor antagonist genes in children with autism spectrum disorders. Prog Neuropsychopharmacol Biol Psychiatry, 20, 103.
Said, S., et al. (2021). ‘Role of glutathione-S-transferase M1 (GSTM1) and T1 (GSTT1) genes on aluminum concentration and oxidative markers among autistic children.’ Egyptian Journal of Chemistry, 64(12), 7591–7601. https://doi.org/10.21608/ejchem.2021.94656.4464
Salari, N., et al. (2022). The global prevalence of autism spectrum disorder: A comprehensive systematic review and meta-analysis. Italian Journal of Pediatrics, 48(1), 112. https://doi.org/10.1186/s13052-022-01310-w
Samadi, S. A. (2022). Overview of services for autism spectrum disorders (ASD) in low- and middle-Income countries (LMICs) and among immigrants and minority groups in high-income countries (HICs). Brain Sciences, 12(12), 1682. https://doi.org/10.3390/brainsci12121682
Shaffer, J. G., et al. (2019). Expanding research capacity in Sub-Saharan Africa through informatics, Bioinformatics, and data science training programs in Mali. Frontiers in Genetics, 10, 331. https://doi.org/10.3389/fgene.2019.00331
Sirugo, G., Williams, S. M., & Tishkoff, S. A. (2019). The missing diversity in human genetic studies. Cell, 177(1), 26–31. https://doi.org/10.1016/j.cell.2019.02.048
SJR (2022) Scimago journal & country rank. http://www.scimagojr.com/countryrank.php?area=2400®ion=Africa (Accessed: 3 August 2023).
Stathopoulos, S., et al. (2020). DNA methylation associated with mitochondrial dysfunction in a South African autism spectrum disorder cohort. Autism Research, 13(7), 1079–1093. https://doi.org/10.1002/aur.2310
The World Bank (2022) GDP per capita (current US$). data.worldbank.org/indicator/NY.GDP.PCAP.CD?view=chart (Accessed: 4 August 2023).
Tisato, V., et al. (2021). Genetics and epigenetics of one-carbon metabolism pathway in autism spectrum disorder: A sex-specific brain epigenome? Genes, 12(5), 782. https://doi.org/10.3390/genes12050782
Tishkoff, S. A., & Verrelli, B. C. (2003). Role of evolutionary history on haplotype block structure in the human genome: Implications for disease mapping. Current Opinion in Genetics & Development, 13(6), 569–575. https://doi.org/10.1016/j.gde.2003.10.010
UNESCO et al. (2021) UNESCO science report: The race against time for smarter development. unesdoc.unesco.org/ark:/48223/pf0000377433/PDF/377433eng.pdf.multi.
Wei, H., et al. (2021). Genetic risk factors for autism-spectrum disorders: A systematic review based on systematic reviews and meta-analysis. Journal of Neural Transmission, 128(6), 717–734. https://doi.org/10.1007/s00702-021-02360-w
Wenham, C., et al. (2021). Measuring health science research and development in Africa: Mapping the available data. Health Research Policy and Systems, 19, 142. https://doi.org/10.1186/s12961-021-00778-y
World Health Organisation (WHO) (2021) Mental health atlas 2020. http://www.who.int/teams/mental-health-and-substance-use/data-research/mental-health-atlas.
Yoo, H. (2015). Genetics of autism spectrum disorder: Current status and possible clinical applications. Experimental Neurobiology, 24(4), 257–272. https://doi.org/10.5607/en.2015.24.4.257
Zeidan, J., et al. (2022). Global prevalence of autism: A systematic review update. Autism Research, 15(5), 778–790. https://doi.org/10.1002/aur.2696
Zhang, H., et al. (2023). The use of data independent acquisition based proteomic analysis and machine learning to reveal potential biomarkers for autism spectrum disorder. Journal of Proteomics, 278, 104872. https://doi.org/10.1016/j.jprot.2023.104872
Acknowledgements
This work was supported by the University of Cape Town and the National Research Foundation, South Africa (Grant No.138010 and 118525).
Funding
Open access funding provided by University of Cape Town.
Author information
Authors and Affiliations
Contributions
Conceptualization: Colleen O’Ryan; Literature searches, screening and selection: Emma Frickel, Sophia Bam, Erin Buchanan, Caitlyn Mahony and Mignon van der Watt; Writing—original draft preparation: Emma Frickel, Caitlyn Mahony and Colleen O’Ryan; Writing—review and editing: Emma Frickel, Sophia Bam, Erin Buchanan, Caitlyn Mahony and Mignon van der Watt; Funding acquisition and supervision: Colleen O’Ryan.
Corresponding author
Ethics declarations
Conflict of Interest
On behalf of all authors, the corresponding author states that there is no conflict of interest.
Additional information
Publisher's Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Electronic supplementary material
Below is the link to the electronic supplementary material.
Rights and permissions
Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.
About this article
Cite this article
Frickel, E., Mahony, C., Bam, S. et al. Molecular Autism Research in Africa: Emerging Themes and Prevailing Disparities. Rev J Autism Dev Disord (2023). https://doi.org/10.1007/s40489-023-00415-0
Received:
Accepted:
Published:
DOI: https://doi.org/10.1007/s40489-023-00415-0