Neurodevelopmental Disorders: From Genetics to Functional Pathways
Authors: Ilaria Parenti, Luis G. Rabaneda, Hanna Schoen, Gaia Novarino
Journal: Trends in Neurosciences (2020)

NDDs are caused by the disruption of essential neurodevelopmental processes. Many genes and mutations are associated with NDDs, pointing to a heterogeneous origin of these disorders.Genotype–phenotype correlations are difficult to establish due to the existence of multiple genetic as well as environmental factors that influence the phenotypical outcome. The two-hit model and the existence of multiple molecular diagnoses are important factors that should be taken into account when addressing NDDs.Most of the known NDDs genes belong to few common frequently affected molecular pathways. Functional and molecular studies elucidating how different mutations can disturb the converging pathways can lead to the identification of potential targets, thereby opening perspectives for future treatment. Neurodevelopmental disorders (NDDs) are a class of disorders affecting brain development and function and are characterized by wide genetic and clinical variability. In this review, we discuss the multiple factors that influence the clinical presentation of NDDs, with particular attention to gene vulnerability, mutational load, and the two-hit model. Despite the complex architecture of mutational events associated with NDDs, the various proteins involved appear to converge on common pathways, such as synaptic plasticity/function, chromatin remodelers and the mammalian target of rapamycin (mTOR) pathway. A thorough understanding of the mechanisms behind these pathways will hopefully lead to the identification of candidates that could be targeted for treatment approaches. Neurodevelopmental disorders (NDDs) are a class of disorders affecting brain development and function and are characterized by wide genetic and clinical variability. In this review, we discuss the multiple factors that influence the clinical presentation of NDDs, with particular attention to gene vulnerability, mutational load, and the two-hit model. Despite the complex architecture of mutational events associated with NDDs, the various proteins involved appear to converge on common pathways, such as synaptic plasticity/function, chromatin remodelers and the mammalian target of rapamycin (mTOR) pathway. A thorough understanding of the mechanisms behind these pathways will hopefully lead to the identification of candidates that could be targeted for treatment approaches. Neurodevelopmental disorders (NDDs) are characterized by an inability to reach cognitive, emotional, and motor developmental milestones. Typically, NDDs are associated with the disruption of the tightly coordinated events that lead to brain development. NDDs constitute a serious health problem in our society, affecting >3% of children worldwide [1.Gilissen C. et al.Genome sequencing identifies major causes of severe intellectual disability.Nature. 2014; 511: 344-347Crossref PubMed Scopus (573) Google Scholar]. They have a heterogeneous etiology and lead to impaired cognition, communication, adaptive behavior, and psychomotor skills. NDDs include autism spectrum disorder (ASD), intellectual disability (ID), attention deficit hyperactivity disorder, and epilepsy [2.Niemi M.E.K. et al.Common genetic variants contribute to risk of rare severe neurodevelopmental disorders.Nature. 2018; 562: 268-271Crossref PubMed Scopus (63) Google Scholar,3.Tărlungeanu D.C. Novarino G. Genomics in neurodevelopmental disorders: an avenue to personalized medicine.Exp. Mol. Med. 2018; 50: 1-7Crossref Scopus (5) Google Scholar]. Many studies have suggested that shared molecular pathways could account for the multiple clinical signs that characterize NDDs [4.Cristino A.S. et al.Neurodevelopmental and neuropsychiatric disorders represent an interconnected molecular system.Mol. Psychiatry. 2014; 19: 294-301Crossref PubMed Scopus (103) Google Scholar,5.Hormozdiari F. et al.The discovery of integrated gene networks for autism and related disorders.Genome Res. 2015; 25: 142-154Crossref PubMed Scopus (123) Google Scholar]. Accordingly, comorbidity (see Glossary) of two or more of these disorders is frequently observed. For instance, a combination of ID, ASD, and epilepsy is commonly reported in individual patients [6.van Bokhoven H. Genetic and epigenetic networks in intellectual disabilities.Annu. Rev. Genet. 2011; 45: 81-104Crossref PubMed Scopus (203) Google Scholar,7.Du X. et al.Genetic diagnostic evaluation of trio-based whole exome sequencing among children with diagnosed or suspected autism spectrum disorder.Front. Genet. 2018; 9: 594Crossref PubMed Google Scholar]. Identification of the shared pathogenic mechanisms of the different NDDs will help to explain the aforementioned comorbidity and eventually lead to effective treatment. In terms of genetics, different types of mutation have been associated with NDDs, including chromosomal rearrangements, copy number variations, small indels, and point mutations. Thus, the identification of a potential underlying mutational event, known as molecular diagnosis, is a challenging task that needs to overcome the heterogeneity of this complex array of genetic variations. Some of the technologies currently used for the molecular diagnosis of NDDs are summarized in Box 1.Box 1Evolution of the Diagnostic Flowchart of NDDsEarly molecular diagnosis of patients with NDD is essential for genetic counseling, patient management, and medical intervention.Previously, G banded karyotype and FMR1 trinucleotide repeat analysis were recommended as a first-tier test for patients with unexplained NDDs. However, the yield in patients was low [111.Blesson A. Cohen J.S. Genetic counseling in neurodevelopmental disorders.Cold Spring Harb. Perspect. Med. 2019; 10: a036533Google Scholar]. The breakthrough of next-generation sequencing technologies has led to significant advancements in the identification of the genetic causes of NDDs [1.Gilissen C. et al.Genome sequencing identifies major causes of severe intellectual disability.Nature. 2014; 511: 344-347Crossref PubMed Scopus (573) Google Scholar,7.Du X. et al.Genetic diagnostic evaluation of trio-based whole exome sequencing among children with diagnosed or suspected autism spectrum disorder.Front. Genet. 2018; 9: 594Crossref PubMed Google Scholar,112.Carneiro T.N. et al.Utility of trio-based exome sequencing in the elucidation of the genetic basis of isolated syndromic intellectual disability: illustrative cases.Appl. Clin. Genet. 2018; 11: 93-98Crossref PubMed Scopus (7) Google Scholar]. To date, >900 genes responsible for X-linked, autosomal dominant, or autosomal recessive NDDs have been reported [113.Chiurazzi P. Pirozzi F. Advances in understanding - genetic basis of intellectual disability.F1000Res. 2016; 5 (Faculty Rev-599): F1000Crossref PubMed Scopus (37) Google Scholar,114.Wright C.F. et al.Genetic diagnosis of developmental disorders in the DDD study: a scalable analysis of genome-wide research data.Lancet. 2015; 385: 1305-1314Abstract Full Text Full Text PDF PubMed Scopus (315) Google Scholar]. Due to the correlation of genetic disorders with mutations in protein-coding genes, the cheaper and quicker whole-exome sequencing (WES) is preferred as a diagnostic tool to the more informative whole-genome sequencing [115.Clark M.M. et al.Meta-analysis of the diagnostic and clinical utility of genome and exome sequencing and chromosomal microarray in children with suspected genetic diseases.NPJ Genom. Med. 2018; 3: 16Crossref PubMed Scopus (71) Google Scholar,116.Srivastava S. et al.Meta-analysis and multidisciplinary consensus statement: exome sequencing is a first-tier clinical diagnostic test for individuals with neurodevelopmental disorders.Genet. Med. 2019; 21: 2413-2421Abstract Full Text Full Text PDF PubMed Scopus (32) Google Scholar]. Different studies highlighted the efficiency of exome sequencing as a diagnostic tool, having a diagnostic yield up to >40% in patients with NDDs, especially when both biological parents are considered [111.Blesson A. Cohen J.S. Genetic counseling in neurodevelopmental disorders.Cold Spring Harb. Perspect. Med. 2019; 10: a036533Google Scholar] Still, mutations could also occur in noncoding regions, such as regulatory elements, and alter gene expression levels [111.Blesson A. Cohen J.S. Genetic counseling in neurodevelopmental disorders.Cold Spring Harb. Perspect. Med. 2019; 10: a036533Google Scholar]. DNA microarrays are also frequently used to detect gross chromosomal aberrations otherwise not detectable with conventional WES [117.Martin C.L. Ledbetter D.H. Chromosomal microarray testing for children with unexplained neurodevelopmental disorders.JAMA. 2017; 317: 2545-2546Crossref PubMed Scopus (5) Google Scholar,118.Bhattacharya S.K. et al.Chromosomal microarray analysis uncovers pathogenic copy number variations in unexplained neurodevelopmental disorders and congenital anomalies.J. Biomed. Sci. 2019; 8: 3Google Scholar]. The expected diagnostic yield of chromosomal microarray testing is estimated ~10–20% in patients with distinct NDDs [111.Blesson A. Cohen J.S. Genetic counseling in neurodevelopmental disorders.Cold Spring Harb. Perspect. Med. 2019; 10: a036533Google Scholar]. Epigenetic alterations, also escaping WES detection, are frequently observed in the presence of NDDs. Therefore, various additional methods can be used to detect epigenetic changes, such as PCR, tandem mass spectrometry, and southern blot. Early molecular diagnosis of patients with NDD is essential for genetic counseling, patient management, and medical intervention. Previously, G banded karyotype and FMR1 trinucleotide repeat analysis were recommended as a first-tier test for patients with unexplained NDDs. However, the yield in patients was low [111.Blesson A. Cohen J.S. Genetic counseling in neurodevelopmental disorders.Cold Spring Harb. Perspect. Med. 2019; 10: a036533Google Scholar]. The breakthrough of next-generation sequencing technologies has led to significant advancements in the identification of the genetic causes of NDDs [1.Gilissen C. et al.Genome sequencing identifies major causes of severe intellectual disability.Nature. 2014; 511: 344-347Crossref PubMed Scopus (573) Google Scholar,7.Du X. et al.Genetic diagnostic evaluation of trio-based whole exome sequencing among children with diagnosed or suspected autism spectrum disorder.Front. Genet. 2018; 9: 594Crossref PubMed Google Scholar,112.Carneiro T.N. et al.Utility of trio-based exome sequencing in the elucidation of the genetic basis of isolated syndromic intellectual disability: illustrative cases.Appl. Clin. Genet. 2018; 11: 93-98Crossref PubMed Scopus (7) Google Scholar]. To date, >900 genes responsible for X-linked, autosomal dominant, or autosomal recessive NDDs have been reported [113.Chiurazzi P. Pirozzi F. Advances in understanding - genetic basis of intellectual disability.F1000Res. 2016; 5 (Faculty Rev-599): F1000Crossref PubMed Scopus (37) Google Scholar,114.Wright C.F. et al.Genetic diagnosis of developmental disorders in the DDD study: a scalable analysis of genome-wide research data.Lancet. 2015; 385: 1305-1314Abstract Full Text Full Text PDF PubMed Scopus (315) Google Scholar]. Due to the correlation of genetic disorders with mutations in protein-coding genes, the cheaper and quicker whole-exome sequencing (WES) is preferred as a diagnostic tool to the more informative whole-genome sequencing [115.Clark M.M. et al.Meta-analysis of the diagnostic and clinical utility of genome and exome sequencing and chromosomal microarray in children with suspected genetic diseases.NPJ Genom. Med. 2018; 3: 16Crossref PubMed Scopus (71) Google Scholar,116.Srivastava S. et al.Meta-analysis and multidisciplinary consensus statement: exome sequencing is a first-tier clinical diagnostic test for individuals with neurodevelopmental disorders.Genet. Med. 2019; 21: 2413-2421Abstract Full Text Full Text PDF PubMed Scopus (32) Google Scholar]. Different studies highlighted the efficiency of exome sequencing as a diagnostic tool, having a diagnostic yield up to >40% in patients with NDDs, especially when both biological parents are considered [111.Blesson A. Cohen J.S. Genetic counseling in neurodevelopmental disorders.Cold Spring Harb. Perspect. Med. 2019; 10: a036533Google Scholar] Still, mutations could also occur in noncoding regions, such as regulatory elements, and alter gene expression levels [111.Blesson A. Cohen J.S. Genetic counseling in neurodevelopmental disorders.Cold Spring Harb. Perspect. Med. 2019; 10: a036533Google Scholar]. DNA microarrays are also frequently used to detect gross chromosomal aberrations otherwise not detectable with conventional WES [117.Martin C.L. Ledbetter D.H. Chromosomal microarray testing for children with unexplained neurodevelopmental disorders.JAMA. 2017; 317: 2545-2546Crossref PubMed Scopus (5) Google Scholar,118.Bhattacharya S.K. et al.Chromosomal microarray analysis uncovers pathogenic copy number variations in unexplained neurodevelopmental disorders and congenital anomalies.J. Biomed. Sci. 2019; 8: 3Google Scholar]. The expected diagnostic yield of chromosomal microarray testing is estimated ~10–20% in patients with distinct NDDs [111.Blesson A. Cohen J.S. Genetic counseling in neurodevelopmental disorders.Cold Spring Harb. Perspect. Med. 2019; 10: a036533Google Scholar]. Epigenetic alterations, also escaping WES detection, are frequently observed in the presence of NDDs. Therefore, various additional methods can be used to detect epigenetic changes, such as PCR, tandem mass spectrometry, and southern blot. These challenges notwithstanding, recognition of NDD-causing genes is crucial for accurate genetic counseling and patient management, and represents an essential first step toward a better understanding of the molecular pathways affected by these disorders. This review focuses on the molecular etiology of NDDs, starting from genetics and moving to the functional level. First, we discuss how the study of familial cases improved our understanding of the complex genetics of NDDs. Second, we consider the genetic factors that determine and influence the phenotype, such as gene vulnerability, mutational load, and multiple molecular diagnoses. We also highlight the relevance of the two-hit model in the context of understanding the genetics of NDDs. Finally, we debate whether the identification of frequently affected cellular pathways allows circumventing the issue of the wide genetic variability of NDDs and whether the identification of such pathways could open perspectives for future treatments. The identification of the potential genetic causes of NDDs is vital for understanding the molecular mechanisms responsible for the onset of these disorders and for the delineation of a genotype–phenotype correlation that could help to monitor the progress of the disorder and to foresee future complications. Despite the numerous NDD-causative genes identified, many individuals with NDDs still do not receive a molecular diagnosis. Additionally, phenotype–genotype correlation studies have brought to light that the number and severity of clinical signs can vary substantially among patients with overlapping genetic etiology [8.Li Y. et al.Genotype and phenotype correlations for SHANK3 de novo mutations in neurodevelopmental disorders.Am. J. Med. Genet. A. 2018; 176: 2668-2676PubMed Google Scholar,9.Casanova E.L. et al.Widespread genotype-phenotype correlations in intellectual disability.Front. Psychiatry. 2018; 9535–535Crossref Google Scholar]. Thus, missing heritability and phenotypical variability point to a multifactorial and/or polygenic nature of NDDs. Familial NDDs represent a useful paradigm for dissecting the contribution of genetic and nongenetic factors to the pathogenesis of these disorders in the presence of a shared genetic background. For this reason, numerous studies have been conducted on monozygotic twins with discordant phenotypes [10.Huang Y. et al.Identifying genomic variations in monozygotic twins discordant for autism spectrum disorder using whole-genome sequencing.Mol. Ther. Nucleic Acids. 2018; 14: 204-211Abstract Full Text Full Text PDF PubMed Scopus (4) Google Scholar, 11.Willfors C. et al.Medical history of discordant twins and environmental etiologies of autism.Transl. Psychiatry. 2017; 7e1014Crossref PubMed Scopus (10) Google Scholar, 12.Radley J.A. et al.Deep phenotyping of 14 new patients with IQSEC2 variants, including monozygotic twins of discordant phenotype.Clin. Genet. 2019; 95: 496-506Crossref PubMed Scopus (4) Google Scholar] or on pedigrees where incomplete penetrance and phenotypical variability are observed in the multiple affected offspring [13.Karaca E. et al.Phenotypic expansion illuminates multilocus pathogenic variation.Genet. Med. 2018; 20: 1528-1537Abstract Full Text Full Text PDF PubMed Scopus (33) Google Scholar]. This line of research has tremendous potential not only for the mere identification of the molecular causes of the disease, but also for the recognition of risk factors and protective factors. Furthermore, it has the potential for establishing more accurate genotype–phenotype correlations. Thanks to the study of inherited NDDs, it has emerged that the phenotypical outcome essentially revolves around two main principles: gene vulnerability and mutational load (Figure 1A ). Gene vulnerability can be defined as the capability of a given gene to tolerate disruptive variants: the lower the tolerance towards mutations, the higher the level of vulnerability. Some genes associated with NDDs are haploinsufficient genes characterized by a striking dosage sensitivity. These particular genes fall within the category of highly vulnerable genes, and mutations affecting these genes are associated with significant disease risk. Examples of highly vulnerable genes include DEPDC5, CACNA1A, and SCN8A, which are discussed later in this section. Disruption of one of these genes has a high probability of inducing the onset of a disease phenotype also in the absence of other causative events, thus resulting in monogenic forms of NDDs [14.Iossifov I. et al.Low load for disruptive mutations in autism genes and their biased transmission.Proc. Natl. Acad. Sci. U. S. A. 2015; 112: E5600-E5607Crossref PubMed Scopus (58) Google Scholar]. For this reason, mutations affecting these genes are normally subject to a strong negative selective pressure. Hence, population studies have recognized a reduced number of disruptive variants in vulnerable genes compared with other genomic loci [14.Iossifov I. et al.Low load for disruptive mutations in autism genes and their biased transmission.Proc. Natl. Acad. Sci. U. S. A. 2015; 112: E5600-E5607Crossref PubMed Scopus (58) Google Scholar]. In other words, mutations in highly vulnerable genes can be categorized as rare variants associated with significant disease risk and high penetrance. The other end of the vulnerability spectrum comprises those genes that are less sensitive to disruptive mutations. Variants in these genes are not under negative selective pressure and are frequently transmitted in families for generations [2.Niemi M.E.K. et al.Common genetic variants contribute to risk of rare severe neurodevelopmental disorders.Nature. 2018; 562: 268-271Crossref PubMed Scopus (63) Google Scholar,14.Iossifov I. et al.Low load for disruptive mutations in autism genes and their biased transmission.Proc. Natl. Acad. Sci. U. S. A. 2015; 112: E5600-E5607Crossref PubMed Scopus (58) Google Scholar]. Since single disruptive events affecting nonvulnerable genes are not disease causing per se, they fall within the category of common variants with low disease risk. Nonetheless, recent studies have demonstrated that a significant portion of NDDs with polygenic nature can be attributed to common genetic variants [2.Niemi M.E.K. et al.Common genetic variants contribute to risk of rare severe neurodevelopmental disorders.Nature. 2018; 562: 268-271Crossref PubMed Scopus (63) Google Scholar,15.Kurki M.I. et al.Contribution of rare and common variants to intellectual disability in a sub-isolate of Northern Finland.Nat. Commun. 2019; 10: 410Crossref PubMed Scopus (6) Google Scholar]. In fact, the additive effects of these mutational events could result in a disease phenotype [2.Niemi M.E.K. et al.Common genetic variants contribute to risk of rare severe neurodevelopmental disorders.Nature. 2018; 562: 268-271Crossref PubMed Scopus (63) Google Scholar,15.Kurki M.I. et al.Contribution of rare and common variants to intellectual disability in a sub-isolate of Northern Finland.Nat. Commun. 2019; 10: 410Crossref PubMed Scopus (6) Google Scholar,16.Pizzo L. et al.Rare variants in the genetic background modulate cognitive and developmental phenotypes in individuals carrying disease-associated variants.Genet. Med. 2019; 21: 816-825Abstract Full Text Full Text PDF PubMed Scopus (26) Google Scholar]. In these cases, however, the phenotypical outcome depends not only on the sum of the effects of the single mutations, but also the physical and/or functional interactions between the affected genes (i.e., epistasis) [17.Mitra I. et al.Reverse pathway genetic approach identifies epistasis in autism spectrum disorders.PLoS Genet. 2017; 13e1006516Crossref PubMed Scopus (19) Google Scholar,18.Iyer J. et al.Pervasive genetic interactions modulate neurodevelopmental defects of the autism-associated 16p11.2 deletion in Drosophila melanogaster.Nat. Commun. 2018; 9: 2548Crossref PubMed Scopus (13) Google Scholar]. Epistatic interactions and dosage sensitivity strongly correlate with the concept of mutational load, which argues that the penetrance and complexity of a disease phenotype are influenced by the number of disruptive events. For example, loss-of-function monoallelic mutations in the sodium channels CACNA1A and SCN8A are commonly associated with a variety of clinical features including movement disorder, ID, ASD, and benign familial infantile seizures (Figure 1B) [19.Reinson K. et al.Biallelic CACNA1A mutations cause early onset epileptic encephalopathy with progressive cerebral, cerebellar, and optic nerve atrophy.Am. J. Med. Genet. A. 2016; 170: 2173-2176Crossref PubMed Google Scholar,20.Wengert E.R. et al.Biallelic inherited SCN8A variants, a rare cause of SCN8A-related developmental and epileptic encephalopathy.Epilepsia. 2019; 60: 2277-2285Crossref PubMed Scopus (2) Google Scholar]. In accordance with the aforementioned criteria of dosage sensitivity and mutational load, inherited germline biallelic mutations of CACNA1A and SCN8A are associated with more severe phenotypes compared with monoallelic changes (Figure 1C) [19.Reinson K. et al.Biallelic CACNA1A mutations cause early onset epileptic encephalopathy with progressive cerebral, cerebellar, and optic nerve atrophy.Am. J. Med. Genet. A. 2016; 170: 2173-2176Crossref PubMed Google Scholar,20.Wengert E.R. et al.Biallelic inherited SCN8A variants, a rare cause of SCN8A-related developmental and epileptic encephalopathy.Epilepsia. 2019; 60: 2277-2285Crossref PubMed Scopus (2) Google Scholar]. The recently reported CACNA1A and SCN8A compound heterozygous probands are characterized by the presence of epileptic encephalopathy, while the heterozygous parents and siblings only exhibit mild cognitive impairment without seizure [19.Reinson K. et al.Biallelic CACNA1A mutations cause early onset epileptic encephalopathy with progressive cerebral, cerebellar, and optic nerve atrophy.Am. J. Med. Genet. A. 2016; 170: 2173-2176Crossref PubMed Google Scholar,20.Wengert E.R. et al.Biallelic inherited SCN8A variants, a rare cause of SCN8A-related developmental and epileptic encephalopathy.Epilepsia. 2019; 60: 2277-2285Crossref PubMed Scopus (2) Google Scholar]. In other cases, a higher mutational load might be determined by a combination of germline and somatic events, a mechanism known as the two-hit model. In the classic two-hit hypothesis, a constitutive inherited mutation generates a vulnerable genetic background. A subsequent somatic hit occurring later during development will then be responsible for the onset of a disease phenotype or the expansion of already present clinical features (Figure 1E). One example of a two-hit model comes from mutations in DEPDC5. Germline heterozygous loss-of-function mutations affecting DEPDC5 are a major cause of familial refractory focal epilepsies [21.Ribierre T. et al.Second-hit mosaic mutation in mTORC1 repressor DEPDC5 causes focal cortical dysplasia-associated epilepsy.J. Clin. Investig. 2018; 128: 2452-2458Crossref PubMed Scopus (0) Google Scholar]. A second somatic variant causing biallelic inactivation of DEPDC5 was found to be responsible for the additional development of focal cortical dysplasia in patients with a severe phenotype [21.Ribierre T. et al.Second-hit mosaic mutation in mTORC1 repressor DEPDC5 causes focal cortical dysplasia-associated epilepsy.J. Clin. Investig. 2018; 128: 2452-2458Crossref PubMed Scopus (0) Google Scholar,22.Lee W.S. et al.Second-hit DEPDC5 mutation is limited to dysmorphic neurons in cortical dysplasia type IIA.Ann. Clin. Transl. Neurol. 2019; 6: 1338-1344Crossref PubMed Scopus (1) Google Scholar]. Primary and secondary variants can also occur at genomic loci different from each other, thus expanding the classic two-hit hypothesis (Figure 1D). Several studies have unveiled the significant contribution of multiple molecular diagnoses in the context of NDDs [13.Karaca E. et al.Phenotypic expansion illuminates multilocus pathogenic variation.Genet. Med. 2018; 20: 1528-1537Abstract Full Text Full Text PDF PubMed Scopus (33) Google Scholar,23.Guo H. et al.Inherited and multiple de novo mutations in autism/developmental delay risk genes suggest a multifactorial model.Mol. Autism. 2018; 9: 64Crossref PubMed Scopus (16) Google Scholar, 24.Posey J.E. et al.Resolution of disease phenotypes resulting from multilocus genomic variation.N. Engl. J. Med. 2017; 376: 21-31Crossref PubMed Scopus (246) Google Scholar, 25.Liu P. et al.Reanalysis of clinical exome sequencing data.N. Engl. J. Med. 2019; 380: 2478-2480Crossref PubMed Scopus (16) Google Scholar]. In line with the notion of mutational load, genotype–phenotype correlation analyses have established that individuals with mutations in multiple genes are more likely to be affected [23.Guo H. et al.Inherited and multiple de novo mutations in autism/developmental delay risk genes suggest a multifactorial model.Mol. Autism. 2018; 9: 64Crossref PubMed Scopus (16) Google Scholar] and that the number of disrupting events positively correlates with the number and severity of the clinical signs observed [13.Karaca E. et al.Phenotypic expansion illuminates multilocus pathogenic variation.Genet. Med. 2018; 20: 1528-1537Abstract Full Text Full Text PDF PubMed Scopus (33) Google Scholar,24.Posey J.E. et al.Resolution of disease phenotypes resulting from multilocus genomic variation.N. Engl. J. Med. 2017; 376: 21-31Crossref PubMed Scopus (246) Google Scholar]. For instance, the contribution of different mutational events was recently dissected in two families characterized by intrafamilial clinical variability. In both families, the additional clinical features of the probands were explained by mutations at additional loci that were not present in the less severely affected siblings [13.Karaca E. et al.Phenotypic expansion illuminates multilocus pathogenic variation.Genet. Med. 2018; 20: 1528-1537Abstract Full Text Full Text PDF PubMed Scopus (33) Google Scholar]. The cumulative load of common genetic variants might also represent the first hit that makes the genetic background more vulnerable to subsequent pathological events (Figure 1F). In fact, it was recently reported that the burden resulting from the combination of common variants in families with a history of NDDs positively correlated with genetic predisposition to lower educational attainment and ID [2.Niemi M.E.K. et al.Common genetic variants contribute to risk of rare severe neurodevelopmental disorders.Nature. 2018; 562: 268-271Crossref PubMed Scopus (63) Google Scholar]. Thus, the data currently available in the literature suggest that purely monogenic forms of NDDs are an exception rather than the rule. Most NDDs cases most likely have a multifactorial and/or polygenic nature, hence confirming the broad heterogeneity of these disorders at both the clinical and molecular level. Importantly, the clinical outcome might also be influenced at various levels by nongenetic factors, although discussion of environmental factors is beyond the scope of the current review. The implementation of next-generation sequencing (NGS) technologies in the diagnostic flowchart of NDDs has dramatically increased the percentage of patients who receive a molecular diagnosis. The identification of the genetic etiology of the disease has important ramifications for genetic counseling and patient management, since it can lead to a better assessment of the recurrence risk and gives the possibility to foresee future medical complications. The advances in the field of genetics have also served as a roadmap for the development of functional genomic studies aimed at understanding the pathogenic mechanisms associated with the reported mutations. As discussed next, this line of research has elucidated some of the biological pathways important for the onset of NDDs. The recognition of these networks also offers an opportunity to overcome the complexities associated with the wide genetic variability, and to develop targeted therapeutic approaches. Functional studies performed during the past decade have shown that most rare and common variants associated with NDDs affect genes that have a role in a few conserved pathways [26.Sahin M. Sur M. Genes, circuits, and precision therapies for autism and related neurodevelopmental disorders.Science. 2015; 350aab3897Crossref PubMed Scopus (108) Google Scholar, 27.Parikshak N.N. et al.Integrative functional