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Isovaleric acidemia: an integrated approach toward predictive laboratory medicine

Dercksen, M.

Publication date 2014

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Citation for published version (APA): Dercksen, M. (2014). Isovaleric acidemia: an integrated approach toward predictive laboratory medicine.

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Download date:02 Oct 2021

Chapter 1

General introduction and outline of thesis

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1 Preface

Organic acidemias are an important group of inborn errors of metabolism (IEMs), which mainly involve defects in the catabolism and related intermediary pathways of carbohydrates, amino acids and fatty acids. Some organic acidemias can be treated with a relatively high success rate, but this may depend on rapid diagnosis and early treatment interventions. Treatment is in general aimed to reduce metabolic decompensation as well as to prevent neurological damage and developmental delay. The phenotypical presentation of the organic acidemias is broad.

Isovaleric acidemia (IVA), which is the result of the defective isovaleryl-CoA dehydrogenase (IVD) in the catabolism of , a branched chain amino acid (BCAA), was one of the first organic acidemias to be described, almost 50 years ago by Tanaka et al. (1966). Subsequently, Budd et al. (1967) clarified the primary clinical manifestations of the disease. A large number of case studies have progressively emphasized the clinical heterogeneity of IVA (reviewed by Ensenauer et al., 2004; Vockley and Ensenauer, 2006). These reviews indicate that the original notion of a one genotype, one phenotype relationship is probably the exception rather than the rule, because the disorder is accompanied by neurological aberrations in varying degrees (Budd et al., 1967; Grünert et al., 2012). The clinical variability, even in patients with the same genetic background, as well as novel diagnostic biochemical tools and expanding treatment possibilities for isovaleric acidemia, served as main motivation for this study.

A timely diagnosis of IVA, through (NBS) programs around the world has improved the clinical outcome of most patients by the early implementation of treatment. The development of mass spectrometry for NBS has led to the identification of IEM patients with an unexpectedly wide clinical presentation (Ensenauer et al., 2004; Dionisi-Vici et al., 2006). Recent investigations of IVA patients in Korea, Taiwan and Thailand have further emphasized the diversity of genotype-phenotype relationships in different populations and even within families (Lee et al., 2007; Lin et al., 2007; Vatanavicharn et al., 2011). IVA is periodically diagnosed in the Caucasian South African population (although its prevalence is still unknown). The molecular and biochemical characteristics, however, have been poorly documented thus far. Consequently, the characterization of IVA in the South African population was one of the main aims of this study. Nutritional and pathological aspects were also subjects of investigation.

A crucial additional factor in the conduct of the research reported in this thesis is the advent of metabolomics, which is a highly sensitive, data-driven technology responsible for novel multidisciplinary approaches (as will be described in section 6 of this chapter) that permit the interpretation of pathophysiological aspects of disease. The metabolomic approach has also irrefutably led to the first proof-of-concept studies in IEMs, namely

2 General introduction and outline of thesis

defects in the metabolism of propionate (Wikoff et al., 2007) and respiratory chain disorders (Smuts et al., 2012). The study of the metabolome and its changes in response to different physiological and genetic processes already shows promise in the identification of the mechanism of disease and of underlying problems associated with such disorders, for example pathological effects and nutritional deficiencies. A metabolomic analysis may ultimately be able to determine the choice of therapy, recognize susceptible patients and predict possible toxic effects of treatment (McCabe, 2010; Mamas et al., 2011). An exciting further spin-off may be the follow-up investigations of the disease which will ultimately lead towards predictive laboratory medicine. The recognition of the unique potential of metabolomics in the investigation of IEMs therefore became one of the aims of this investigation, as will be elaborated on in this chapter.

The following sections address topics that have a close bearing on the study reported in this thesis. The initial discussion will outline the metabolism of branched chain amino acids (BCAA) in general, and present an overview of IVA.

2 Metabolism of branched chain amino acids

The branched chain amino acids (BCAA) leucine, and , are essential biomolecules which play a vital role as building blocks in protein synthesis. These neutral aliphatic amino acids, containing methyl-branched side-chains are present in protein-containing food. BCAAs are metabolized predominantly in the skeletal muscle and the liver (>70%). Between 8 – 30% of the oxidation of BCAAs may also take place in kidney -, brain -, heart -, pancreatic -, intestinal - and adipose tissue (Suryawan et al., 1998). The degradation of these compounds results in the formation of important metabolites, which are vital in biochemical processes (e.g. in the biosynthesis of lipids), as well as in energy production (via the Krebs cycle and ketone body production).

The degradation of the BCAAs starts with their initial transportation into the cell via a distinct L-amino acid-specific transporter, most likely Na+-independent (Shotwell and Oxender, 1983). The initial transamination step, identical for all three BCAAs, takes place in the cytosol via branched chain aminotransferase. Alternatively, BCAAs can also be transported into the mitochondria (with a neutral amino acid carrier protein) and converted into the corresponding branched chain keto acids (BCKAs) via mitochondrial branched chain aminotransferase. Both aminotransferases are pyridoxal phosphate- dependent and simultaneous amination of 2-ketoglutarate takes place to form glutamate. The aminotransferase step for leucine, isoleucine and valine is not individually regulated; however, the catabolism of each of the BCAAs is highly regulated by both allosteric and covalent mechanisms (recently reviewed by Chuang et al., 2012).

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The branched chain keto acids will have to cross the mitochondrial membrane through the action of a keto acid transporter. Once inside the mitochondria, all three branched chain keto acids are oxidatively decarboxylated via the branched chain keto acid dehydrogenase (BCKAD) complex to form branched chain acyl-CoAs. BCKAD is a multi-enzyme complex consisting of three subunits, namely: E1, a thiamine pyrophosphate-dependent decarboxylase; E2, a lipoamide acyltransferase; and E3, a FAD- and NAD-containing dihydrolipoyl dehydrogenase (Chuang et al., 2012). The sequential metabolic steps for each branched chain acyl-CoA differ and are illustrated in Fig. 1. In view of the focus in this thesis on isovaleryl-CoA dehydrogenase deficiency, this overview will deal mainly with the leucine degradation pathway (Fig. 1).

Leucine is transaminated to 2-oxoisocaproic acid, which is subsequently converted to isovaleryl-CoA. Isovaleryl-CoA is resistant to β-oxidation, because of the methyl-group at the carbon-3 position and instead undergoes a carboxylation step catalyzed by - dependent 3-methylcrotonyl-CoA carboxylase (3-MCC) to form 3-methylglutaconyl-CoA. The latter is hydrated by 3-methylglutaconyl-CoA hydratase to form 3-methyl-3- hydroxyglutaryl-CoA, which is followed by a lyase step [3-hydroxy-3-methylglutaryl-CoA lyase (HMG-CoA lyase)], resulting in the formation of acetyl-CoA and acetoacetate. The ketone body acetoacetate can readily be converted into the other ketone body D-3- hydroxybutyric acid. Both ketone bodies are produced in the liver and can be transported to peripheral tissues as an alternative energy source. The catabolism of leucine and several defects in this pathway have been reassessed recently by Vockley et al. (2012). Isovaleryl-CoA dehydrogenase deficiency will be discussed in detail in this chapter. Some aspects of the BCAA metabolism do not fall within the scope of these investigations, but are mentioned in relevant sections of this thesis.

4 General introduction and outline of thesis

Fig 1: The catabolic pathways of BCAAs with special focus on the degradation of leucine (highlighted in blue) (Vockley et al., 2012). Numbers indicate the enzymatic steps within the catabolic pathways: 1) branched chain aminotransferase; 2) branched chain keto acid dehydrogenase complex; 3) isobutyryl-CoA dehydrogenase or Acad 9; 4) enoyl-CoA hydratase/crotonase; 5) 3-hydroxyisobutyryl-CoA hydrolase; 6) 3-hydroxyisobutyric acid dehydrogenase; 7) methylmalonic semialdehyde dehydrogenase; 8) propionyl-CoA carboxylase; 9) methylmalonyl-CoA racemase; 10) methylmalonyl-CoA mutase; 11) short/branched chain acyl-CoA dehydrogenase; 12) enoyl-CoA hydratase/crotonase; 13) 2-methyl-3-hydroxybutyryl-CoA dehydrogenase; 14) β-ketothiolase; 15) isovaleryl-CoA dehydrogenase; 16) 3-methylcrotonyl-CoA carboxylase; 17) 3-methylglutaconyl CoA hydratase; 18) 3-hydroxy-3-methylglutaryl-CoA lyase.

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2.1 The disorders of leucine degradation

Defects in the leucine pathway give rise to amino acidopathies and/or organic acidemias with multisystemic pathophysiological consequences, including neurological dysfunction. Disorders of the leucine metabolism include the BCKADH complex deficiency or Maple Syrup Urine Disease (which affects all three branched chain amino acids), isovaleryl-CoA dehydrogenase deficiency, 3-methylcrotonyl-CoA carboxylase deficiency, 3-methylglutaconyl-CoA hydratase deficiency and 3-hydroxy-3- methylglutaryl-CoA lyase deficiency.

Co-factors derived from several vitamins such as riboflavin, biotin, thiamine and pyridoxine are vital catalysts in the enzymatic steps of this pathway. Any deficiency in these cofactors may have an impact on several parts of the BCAA catabolic pathways. Good examples of such deficiencies are riboflavin-transporter deficiency, which affects the degradation of short-chain and short/branched chain acyl-CoAs, including isovaleryl- CoA and 2-methylbutyryl-CoA (Bosch et al., 2011) and the biotin-related disorder due to biotinidase deficiency (Bartlett et al., 1980) which affects 3-methylcrotonyl-CoA carboxylase. Many of the primary enzyme and/or cofactor-related disorders in the BCAA catabolic pathways are known to be partially or successfully treatable via timely diagnosis, early dietary intervention and the supplementation of relevant cofactors. (see reviews by Ogier de Baulny et al., 2012; Vockley et al., 2012). HMG-CoA lyase deficiency, a defect of the terminal leucine catabolic pathway, is associated with a complete inability to form ketones; correspondingly, affected patients are at risk of developing non-ketotic hypoglycemia which is often fatal. Avoidance of fasting is the only therapeutic option. Isovaleric acidemia (IVA), a defect located in the proximal part of the leucine catabolic pathway, is a good example of a treatable which requires dietary intervention as well as detoxifying agents.

2.2 Isovaleric acidemia

Isovaleric acidemia (IVA), an autosomal recessive disorder caused by isovaleryl-CoA dehydrogenase (IVD) deficiency (E.C.1.2.99.10), is a well-defined organic acidemia (Tanaka et al., 1966; Budd et al., 1967). This disorder has been described in consanguineous and non-consanguineous families, as well as in various ethnic groups. The incidence of IVA has been reported to be 1:62 500 in Germany, 1:250 000 in the USA and 1:365 000 in Taiwan (Ensenauer et al., 2004; Lin et al., 2007). These differences may possibly be attributed to founder effects in some populations. Currently, over 40 mutations in the IVD gene have been described. The nucleotide and amino acid variations, referred to in this thesis, are described in accordance with the Human Gene Mutation Database (HGMD) nomenclature, and have recently been renumbered and

6 General introduction and outline of thesis

based on cDNA sequence in accordance with the GenBank entries NM_002225.3 and NP_002216.2 (http://www.hgmd.org; Hertecant et al., 2012). The following sections will initially discuss the biochemical abnormalities of IVA. These anomalies in the catabolism of leucine result in a clinical spectrum of IVA and will be discussed at the end of section 2.2.

2.2.1 Abnormal metabolites and biochemical mechanisms

Isovaleric acid (Tanaka et al., 1966), N-isovalerylglycine (Tanaka and Isselbacher, 1967) 3-hydoxyisovaleric acid (3-HIVA) (Tanaka et al., 1968) and isovalerylcarnitine (Roe et al., 1984) have been identified as the primary metabolic indicators of IVA and are still reliable diagnostic markers for the disease with exception of free isovaleric acid which escapes most of the currently applied chromatographic analyses. The accumulating substrate isovaleryl-CoA and the subsequent formation of metabolites through secondary metabolic pathways result in various biochemical changes which may have a serious clinical impact.

Isovaleryl-CoA and subsequently isovaleric acid may increase several hundred fold during a metabolic crisis (Vockley et al., 2012). Both isovaleryl-CoA and isovaleric acid have been implicated in the inhibition or dysfunction of various enzymes and in biochemical mechanisms which consequently cause neurotoxicity and related clinical abnormalities. Early investigations have shown isovaleryl-CoA to inhibit the pyruvate dehydrogenase complex (in pig liver), resulting in elevated lactic acid levels during a metabolic crisis (Gregersen, 1981). The influence of isovaleryl-CoA on pyruvate carboxylase has been examined in several bacterial as well as mammalian species, but no effect on the activity of this enzyme was observed (Scrutton, 1974; Zeczycki et al., 2010).

Enzymes of the Krebs cycle are also influenced to some degree. The inhibition of succinyl-CoA ligase by isovaleryl-CoA in rat liver has been reported (Bergen et al., 1982). This is a serious potential side effect of isovaleryl-CoA, as it is known today that a complete absence of succinyl-CoA ligase results in mitochondrial DNA-depletion (Carrozzo et al., 2007). Furthermore, some studies suggest that the accumulation of acyl-CoAs (of various chain lengths) may affect the function of the 2-ketoglutarate dehydrogenase complex, isocitrate dehydrogenase, malate dehydrogenase and citrate synthase to varying degrees (Stumpf et al., 1985; Lai et al., 1991; Lai et al., 1994). However, the inhibition of these enzymes by isovaleryl-CoA has not been specifically confirmed in these investigations. Isovaleryl-CoA can further act as an inhibitor of N- acetylglutamate synthase, the first step in the , which thereby contributes to secondary observed in isovaleric acidemia (Coude et al., 1979;

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Lehnert, 1981b). A report by Lai et al. (1991) showed that an elevated ammonia level, which is present during a metabolic crisis, may amplify the inhibitory effect of acyl-CoAs (of different chain lengths) on mitochondrial enzymes (as described above).

Isovaleric acid has been implicated in cerebral dysfunction in addition to the primary disturbance of energy production in the mitochondria. It was found that the in vivo administration of isovaleric acid inhibits Na+,K+-ATPase activity. The latter enzyme is important in maintaining the basal membrane potential, which is vital for adequate neurotransmission and consequently for energy production in the brain (Dahl, 1968; Lai et al., 1991; Ribeiro et al., 2007). Furthermore, a report by Solano et al. (2008) suggested that elevated levels of isovaleric acid and N-isovalerylglycine may be involved in oxidative damage within the mitochondria and consequently be partially responsible for the neuropathological features of IVA. The involvement of N- isovalerylglycine is somewhat controversial, because no supportive evidence of N- isovalerylglycine and its relation to neurotoxicity has been put forward yet. In brief, the precise elucidation of the mechanism of neurotoxicity due to the accumulation of isovaleryl-CoA and/or isovaleric acid (and potentially N-isovalerylglycine), is still strongly debated.

Increased isovaleryl-CoA may also participate in acylation reactions, as well as ( ω-1)- hydroxylation and ω-oxidation reactions (Lehnert and Niederhoff, 1981; Lehnert, 1981b; Truscott et al., 1981; Millington et al., 1987; Tanaka et al., 1988; Loots et al., 2005). Fig. 2 depicts the secondary transformation of the accumulating isovaleryl-CoA in IVA. The formation of 3-hydroxyisovaleric acid has been attributed to several secondary pathways namely ( ω-1)-hydroxylation (Tanaka et al., 1968) and/or liver specific α- ketoisocaproate dioxygenase (Sabourin and Bieber, 1982; Van Kovering and Nissen, 1992). Recent findings of the inhibition of 3-methylcrotonyl-CoA carboxylase by isovaleryl-CoA may subsequently contribute to the further formation of 3- hydroxyisovaleric acid (3-HIVA) (Luís et al., 2012). The neurotoxicity of 3-HIVA is still being questioned. Indeed, 3-HIVA has been suggested to have neurotoxic properties by Duran et al. (1993). However, Ribeiro et al. (2007) and Van der Graaf et al. (2010) found no correlation between the neurological features and the extent to which 3-HIVA was elevated in these patients.

Due to the described aberrant effects in the mitochondria of IVA cells, we can only assume that energy production is severely compromised and that mitochondrial homeostasis is in disarray. The increased rate of fatty acid oxidation needed for energy production as well as elevated 3-ketothiolase activity using isovaleryl-CoA and acetyl- CoA as substrates potentially lead to mitochondrial CoA depletion (Lehnert 1981a; Vockley et al., 2012). The restricted availability of free CoA consequently limits the

8 General introduction and outline of thesis

function of the CoA- exchange mechanism, which further debilitates mitochondrial functioning (Mitchell et al., 2008).

The accumulation of isovaleryl-CoA may further influence fatty acid synthesis. Similar effects have been observed in the production of odd-numbered fatty acids from propionyl-CoA in patients with and (Lynen, 1961; Wendel et al., 1995). One short report indicated that isovaleryl-CoA, together with malonyl-CoA, can act as substrates in the production of branched odd-chain fatty acids but further investigation is needed to assess the influence on lipid biosynthesis (Malins et al., 1972). Loots (2009) reported that methylsuccinic acid, a homologue of succinate formed during ω-oxidation of isovaleryl-CoA, acts as a precursor substrate for the production of methylated tricarboxylic acid cycle intermediates and therefore contributes substantially to the disruption of energy production. Taken together, cellular homeostasis may be disrupted due to several biochemical aberrations as a result of the IVD deficiency.

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Fig 2: Schematic representation of important secondary metabolites formed via alternative pathways in the case of an IVD deficiency. Numbers indicate related enzymes or processes: 1: aminotransferase; 2: branched chain 2-keto dehydrogenase; 3: N- acylase/acylation; 4: N- acetylglutamate synthase; 5: carnitine acetyl-CoA transferase; 6: thiolase; 7: 3-hydroxy-3- methylglutaryl-CoA synthase; 8: 3-hydroxy-3-methylglutaryl-CoA lyase; 9: 3-hydoxybutyrate dehydrogenase; 10: glucuronidation; 11: thio-esterification; 12: ( ω-1)-hydroxylation and/or α- ketoisocaproate dioxygenase; 13: ω-oxidation; 14: succinate dehydrogenase. Abbreviations: R 1: α- aminobutyric acid, alanine, , asparagine, glycine, , leucine, , , serine, threonine, , , or valine (Van Kovering and Nissen, 1992; Loots et al., 2005; Vockley et al ., 2012).

The debilitating effect of isovaleryl-CoA during primary decompensation is mostly counteracted by the production of the metabolites indicated in Fig. 2. The body's natural

10 General introduction and outline of thesis

detoxification pathways which will effectively remove accumulating isovaleryl-CoA from the mitochondria are maximally activated. Isovaleryl-CoA may be conjugated with glycine via glycine-N-acylase to form N-isovalerylglycine, which is polar and water- soluble and can therefore be excreted via the kidneys (Krieger and Tanaka, 1976). Acylation with other amino acids such as alanine, sarcosine and serine has also been reported (Yudkoff et al., 1978; Lehnert, 1983; Loots et al., 2005). Further conjugation with glucuronic acid (Dorland et al., 1983; Hine and Tanaka, 1984) and L-carnitine (Roe et al., 1984) results in (partially) detoxified conjugates which are readily excreted in the urine. Investigation of the biochemical profile of these patients has revealed free carnitine depletion in plasma and urine, which suggested the formation of isovalerylcarnitine (Stanley et al., 1983; Roe et al., 1984).

The decrease in plasma glycine level during an oral leucine loading test was reported by Yudkoff et al. (1978), which suggested the enhanced production of N-isovalerylglycine. However, the latter study did not clearly reveal depletion of glycine, such as in the case of L-carnitine. Isovaleryl-CoA may further on enter the ketone body synthesis pathway via 3-ketothiolase which then enters the HMG-CoA cycle (Lehnert, 1981a). The subsequent formation of long-chain ketones, i.e. 3-hydroxyisoheptanoic acid and its related keto acid, are probably useless as alternative energy sources in the peripheral tissues. The detoxification of accumulating substrates and the therapeutic importance through conjugation of isovaleryl-CoA will be discussed further in section 4 of this chapter.

2.2.2 IVD enzyme characteristics

Human IVD is initially produced in the cytosol as a 45 kDa precursor molecule and imported into the mitochondria, after which it is proteolytically cleaved to form a 43 kDa monomer. The active 172 kDa homotetramer is assembled in the mitochondria and one mole of the cofactor, flavin adenine dinucleotide (FAD), is added to each subunit (Ikeda and Tanaka. 1983; Ikeda et al., 1984; Ikeda et al., 1987). FAD transfers electrons to the electron transfer flavoprotein (ETF) during the IVD reaction. These electrons are further transmitted to coenzyme Q in the respiratory chain via ETF dehydrogenase (McKean et al., 1983, Tiffany et al., 1997). Isovaleryl-CoA has been identified as by far the best substrate for IVD. Valeryl-CoA (46%), butyryl-CoA (21%) and hexanoyl-CoA (15%) showed some affinity for recombinant human IVD compared to isovaleryl-CoA set to 100% activity. Other branched/short-chain CoAs such as 2-methylbutyryl-CoA and isobutyryl-CoA showed virtually no activity with IVD (Ikeda and Tanaka, 1983; Mohsen and Vockley, 1995).

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IVD is one of at least eight defined mammalian acyl-CoA dehydrogenases which have been isolated from mitochondria, each with different substrate specificity. Four enzymes – IVD, short/branched chain acyl-CoA dehydrogenase, isobutyryl-CoA dehydrogenase and glutaryl-CoA dehydrogenase – are involved in amino acid catabolism. The other four acyl-CoA dehydrogenase enzymes have straight-chain substrate specificities – short- (SCAD), medium- (MCAD), long- (LCAD), and very long- (VLCAD) chain acyl- CoA dehydrogenase – and catalyze the first step of mitochondrial β-oxidation of fatty acids with various chain lengths. In addition to their sequence similarities, all acyl-CoA dehydrogenases exhibit similar biochemical properties and catalytic mechanisms (Tiffany et al., 1997; Battaile et al., 2004). The IVD proteins from different species share 85–90% amino acid sequence identity (Mohsen et al., 1998)

IVD protein identification using Western blot technology, as well as enzymatic analysis of IVD, have been well studied in the past, but not seen as necessary or as vital tools for diagnostic purposes. This was because IVA was believed to be associated with a distinct urine/plasma metabolite profile, namely grossly elevated N-isovalerylglycine and isovalerylcarnitine accompanied by 3-hydroxyisovaleric acid. The recent acknowledgement of heterogeneity within IVA, however, warrants the investigation of the IVD protein and its associated enzyme activity to conclusively identify and detail the anomaly at the biochemical level. Mutations described early on by Mohsen et al. (1998), associated with the "classical" presentation of IVD, in general, showed no expressed or active IVD protein, exemplified by the case of p.L45P. This is in contrast to mild IVA, which is associated with the amino acid change, p.A314V.

12 General introduction and outline of thesis

Fig 3: The three-dimensional molecular structure of IVD at 2.6 Å (MMDB: 49718 and 1IVH). The IVD homotetramer is shown in 4 different colours. The substrate (isovaleryl-CoA) and cofactor (FAD) are represented as "stick" components within the structure. [The image was generated using the Cn3D program (Wang et al ., 2000).]

Lee et al. (2007) observed a limited IVD protein signal and no residual IVD activity in Korean patients with various mutations in the IVD gene. The IVD protein due to the splice site mutation 153+1G > T showed the weakest signal on immunoblot analysis, compared to missense mutations which were also identified in this Asian population. The position of the mutation does not always explain the influence on the expression of the IVD protein. Some amino acid changes are directly responsible for a change in the binding pocket of substrates. As an example, p.Y403C affects the FAD binding to IVD (Lin et al., 2007). Other amino acid substitutions are not in close proximity to the substrate binding position, but may still be responsible for no or limited IVD expression or activity, probably due to the instability of the protein or faulty protein folding (Mohsen et al., 1998). Vockley and Ensenauer (2006) indicated that the activity of IVD could partly explain the clinical phenotype, although in a few patients only. Furthermore, they suggested that pharmaceutical "chaperones" may be used to optimize protein folding in certain mutated enzymes (discussed in section 4 of this chapter).

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Several enzyme assays have been set up and tested with variable success. The original methods involved the indirect measurement of IVD activity, which included the use of (1) the DCPIP dye reduction assay with artificial electron acceptors (Rhead et al., 1981; Okamura-Ikeda et al., 1985) or (2) the ETF fluorescence analysis, which was initially described by Frerman and Goodman (1985) and modified by Mohsen and Vockley (1995). These are still the methods of choice but have turned out to be inadequate in several respects. The DCPIP dye reduction assay results in a relatively high assay background and can only be performed in isolated mitochondria. The ETF fluorescence assay has to be performed under strict anaerobic conditions, and the commercial unavailability of ETF is a definite problem. The measurement of acyl-CoA dehydrogenase activities (ACADs), including IVD, was recently reviewed and optimized by Wanders et al. (2010). Direct measurement of the enzyme can be achieved through the use of ferricenium hexafluorophosphate, which is commercially available as a stable, albeit artificial electron acceptor and substitutes for ETF. The products of the ACAD reaction can be identified by HPLC coupled to UV detection or by UPLC coupled to tandem MS detection. This method has been chosen as the method of choice for the follow-up of neonates who are picked up in newborn screening programs with a suspicion of isovaleric acidemia.

2.2.3 Molecular basis of IVD

The IVD gene is located on chromosome 15, region q14 → qter (Kraus et al., 1987), and consists of 12 exons and 11 introns, spanning ~15 kb of genomic DNA (Parimoo and Tanaka, 1993). Analysis of the IVD gene in patients with symptomatic IVA led to the identification of numerous missense, nonsense, frameshift-, and splice-site mutations. The latter cause changes in the intron-exon boundaries of the IVD gene and abnormal processing of IVD mRNA. Most of these mutations consequently lead to the production of an inactive or unstable IVD protein (Vockley et al., 1991; Mohsen et al., 1998; Vockley et al., 2000; Ensenauer et al., 2004). Specific mutations have been prominent in various ethnic groups, suggesting a founder effect in some populations (Lee et al., 2007; Lin et al., 2007; Qui et al., 2008; Lee et al., 2010; Vatanavicharn et al., 2011; Hertecant et al., 2012; Kaya et al., 2012). An earlier proposal to classify IVD mutations was made by Vockley et al. (1991) in order to devise a genotype-phenotype relation in IVA, but no clear genotype-phenotype relation was found (Vockley and Ensenauer, 2006).

The absence of a clear genotype-phenotype relation in IVA has been noted in several subsequent studies. Ensenauer et al. (2004) reported on a mutation c.952A > C (p.A314V), typically identified via newborn screening. Patients, homozygous for this mutation, present with a benign to mild form of IVA. Lee et al. (2007) investigated IVA in

14 General introduction and outline of thesis

a Korean population and identified splice-site as well as missense mutations, all resulting in different phenotypes – 5 patients showed early onset of symptoms and 2 subjects presented with no symptoms that far. Lin et al. (2007) reported on the involvement of 6 missense mutations [the most common being the c.1208A > G (p.Y403C)] in the Taiwanese population, which resulted in both mild and severe phenotypes. The pathogenicity of certain mutations was recently explored with an in silico analysis of a cryptic splice-site deletion (c.1136_1138þ4delTTGGTGA) in exon 11 found in IVA patients from the United Arab Emirates (Hertecant et al., 2012).

The variation in IVA genotypes only partly explains the variation in the phenotypical presentation of the patients. Furthermore patients with the same genetic mutation may widely demonstrate different clinical signs and symptoms. Inappropriate dietary measures, delayed diagnosis (Vockley and Ensenauer, 2006), modifier genes (Dipple and Mcabe, 2000) or even epigenetic and polygenetic factors of unknown origin (Turan et al., 2010) may be responsible for these phenotypical variations.

2.2.4 Clinical aspects

IVA was first characterized by the odour of sweaty feet during periodic illness in the breath and biological fluids of patients which was attributed to isovaleric acid (Budd et al., 1967). The disorder was initially classified as having two phenotypic groups, based on the diverse clinical presentation of the disease. The first IVA group manifested with an acute neonatal presentation (usually in the first few weeks of life) and non-specific symptoms, including poor feeding, , , metabolic acidosis and a reduced level of consciousness (Tanaka et al., 1966; Budd et al., 1967). A second group of IVA patients presented with a chronic intermediate clinical profile, characterized by developmental problems of a variable degree and failure to thrive (Levy et al., 1973; Shih et al., 1984). Intermittent acute episodes of decompensation accompanied by mild illness are present in both groups. The patients' survival of the initial metabolic crisis makes these groups indistinguishable from each other as the disease progresses (Tanaka, 1990). In addition, a benign to mild IVA phenotype that has been described suggests that IVA patients may fall within a broad spectrum of clinical presentations (Ensenauer et al., 2004). Consequently, an updated metabolic classification has been put forward consisting of a "metabolically severe group" and a "metabolically mild or intermediate group" (Vockley and Ensenauer, 2006).

Various pathophysiological manifestations accompany IVA and are primarily associated with the accumulation of isovaleryl-CoA as well as isovaleric acid. The biochemical mechanisms of these pathological findings are discussed in this chapter in sections 2.2.1 and 4. Both hypoglycemia (due to physiological stress and fasting) as well as

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hyperglycemia (in some cases misdiagnosed as diabetic acidosis) have frequently been observed in IVA patients (Worthen et al., 1994; Erdem et al., 2010). In addition, hyperlactatemia as well as ketosis are frequently observed in patients during a metabolic crisis (Tanaka et al., 1966). Furthermore, an unexplained anion gap, secondary hyperammonemia (discussed in sections 2.2.2 and 5 of this chapter), hypocalcemia and immunological abnormalities, to varying extents, have been observed in IVA patients. The immunological features are linked to transient bone marrow suppression by isovaleryl-CoA, which may result in pancytopenia and isolated neutropenia and thrombocytopenia (Kelleher et al., 1980; Vockley et al., 2012).

Many patients have a tendency to avoid food rich in protein due to past medical experiences. IVA patients can also present with acute pancreatitis, myeloproliferative syndrome, , and cardiac arrhythmias (Arnold et al., 1986; Kahler et al., 1994; Gilbert-Barness and Barness, 1999). Isolated IVA patients with bilateral cataract, dwarfism and adrenoleukodystrophy have also been described in the literature (Duran et al., 1982; Bonilla Guerrero et al., 2008). Brain damage and neurological abnormalities are present in the severe forms of IVA, but the related biochemical mechanism is still poorly understood. Cerebral edema and/or hemorrhage may occur as a result of untimely or insufficient treatment (Fischer et al., 1981). In such cases, the IVA patient can progress into a and in some instances death (Vockley et al., 1991; Vockley et al., 2012). Consequently, the success of treatment determines the extent of the neurological aberrations and clinical features. The outcome may vary from normal psychomotor development to severe developmental handicaps.

3 Diagnosis of isovaleric acidemia

The routine diagnostic protocol for treatable IEMs has undergone extensive development in the past decades with sophisticated biotechnology increasingly available. The development of mass spectrometry as a paramount NBS tool enabled the timely identification of various organic acidemias, fatty acid oxidation disorders and aminoacidopathies in blood-spot samples of presymptomatic neonates. The identification of medically manageable IEMs, such as IVA, by means of a metabolite signature before clinical presentation and deterioration of the patient, consequently offers the possibility of well-timed therapeutic interventions (Dionisi-Vici et al., 2006). However, the introduction of NBS has also led to the identification of a group of IVA- patients with a benign clinical presentation and has forced clinicians and dieticians to assess each case carefully and to readdress and prescribe a subsequent personalized treatment regimen.

16 General introduction and outline of thesis

The identification of C5-carnitine, through acylcarnitine profiling in samples of newborns, heralds the initiation of follow-up specified metabolic screening, which includes organic acid profiling (Millington et al., 1990; Wilcken et al., 2003). C5-carnitine represents a mixture of isomers and their presence may be indicative of several conditions, namely, 2-methylbutyrylglycinuria, MADD or the presence of a medicinal artifact such as pivaloylcarnitine (Vockley et al., 2012). Consequently, the collection of additional samples (urine, blood card and plasma) should be requested to test specifically for a possible IEM which is associated with elevated C5-carnitine. Urine samples may have the odour of sweaty feet as described in section 2.2.4, but this is not the rule for all IVA patients. The presence of primary diagnostic markers (mostly found in urine), namely, N-isovalerylglycine and 3-hydroxyisovaleric acid, as well as secondary IVA markers depicted in Fig. 2 further points to the diagnosis and metabolic status of IVA patients (Tanaka and Isselbacher, 1967; Tanaka et al., 1968; Vockley et al., 2012). The identification of IVA at the metabolite level must also include elevated C5-carnitine (as a mixture of isomers) detected by MS/MS in the urine and blood of patients. The selective screening procedure should be followed by the measurement of the activity of IVD in fibroblasts and/or lymphocytes and mutation analysis for definitive diagnosis.

The identification of N-isovalerylglycine via GC-MS analyses (Hine et al., 1986) and/or isovalerylcarnitine with mass spectrometry (Shigematsu et al., 1996) in amniotic fluid has been shown to be a reliable tool in the prenatal diagnosis of IVA. Eventually, mutation analysis of the IVD gene is the best option for conclusive pre- and postnatal diagnosis. It is highly recommended that families undergo genetic counseling and be informed about all aspects of IVA including treatment. It is essential to know that an acute metabolic crisis in IVA patients increases the risk of long-term neurological abnormalities, as well as other secondary physiological effects, which lead to a poor quality of life and even death in some cases. However, the patient may also develop the benign variant of IVA, which may or may not present phenotypically. In any case, the follow-up and monitoring of patients are vital, and personalized therapeutic intervention is a particular challenge for each patient, as discussed in the subsequent section.

4 IVA treatment and therapeutic intervention with monitoring

Advances, and to a lesser extent challenges, in the treatment of branched chain amino acid disorders have emphasized the need for treatment strategies based on the clinical assessment of each patient and by acting accordingly. Indeed, the monitoring of biochemical parameters is essential and metabolomics may be a useful tool for the comprehensive assessment of both treated and untreated patients with branched chain amino acid disorders with diverse metabolic phenotypes (Knerr et al., 2012).

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4.1 Treatment through dietary intervention

The main strategy of dietary intervention and the design of nutritional regimens to treat organic acidemias, involves: 1) the restriction of one or more nutritional components from which toxic substances may be produced as a result of enzyme deficiency; 2) supplementation of potentially deficient nutritional compounds; 3) the elimination of toxic compounds via the intake of detoxifiers (glycine and L-carnitine are most commonly used); and 4) administration of pharmacological agents which alleviate the secondary aberrations of the disease, such as hyperammonemia (Giovannini et al., 1995; Daniotti et al., 2011).

IVA is one of the metabolic defects which respond well to dietary intervention, such as limiting the intake of leucine. The prevention or early intervention of a metabolic crisis is the main objective in the treatment of IVA. The secondary breakdown of endogenous leucine during metabolic decompensation is inevitable, and consequently leads to the accumulation of isovaleryl-CoA (as described in section 2.2 of this chapter). Stabilization of IVA patients is achieved through the intake of glucose, and subsequently limited ingestion of proteins, in particular those high in leucine.

Apart from these general guidelines in the treatment of IVA, some specific clinical actions are recommended to physicians faced with life-threatening events affecting IVA patients. Thus, patients suffering from metabolic decompensation normally require immediate hospitalization and a recommended glucose infusion of 8 mg/kg.min, when needed with the simultaneous use of intravenous insulin, under the primary supervision of a pediatrician. Depending on the clinical evaluation of the patient, the protein intake may be returned to the originally prescribed level after 24 hours. It is generally agreed that a low protein diet involves maximum protein intake of 1.5 g/kg body weight/day. The latter is essential for adequate growth and development (Vockley and Ensenauer, 2006).

To date, no biomarkers for the therapeutic monitoring of IVA patients are available (Vockley et al., 2012). However, we anticipate that future research will identify biomarkers to indicate the metabolic status of IVA patients and adapt their treatment. Consensus protocols for organic acidemias, including IVA, and urea cycle defects (UCDs) are currently being developed by the European Registry and Network for Intoxication-type Metabolic Disorders (E-IMD) (http://www.e-imd.org) in order to facilitate the development of strategies to evaluate and determine the metabolic status of patients. The E-IMD consortium, which was established in 2011, has made substantial progress in assessing the diagnosis, treatment and follow-up of patients with related diseases and will subsequently contribute to the design of comprehensive guidelines to deal with the corresponding metabolic defects.

18 General introduction and outline of thesis

4.2 Detoxification options for IVA patients

Most IVA patients respond positively to prescribed detoxifiers (glycine and L-carnitine), with optimal conjugation of isovaleryl-CoA, the accumulating primary metabolite of this condition. The clearance of grossly elevated isovaleryl-CoA is achieved through conjugation with glycine and the formation of N-isovalerylglycine, which is excreted by the kidneys. Several studies have shown the benefit of glycine treatment, without adverse implications for IVA patients (Cohn et al., 1978; Yudkoff et al., 1978; Naglak et al., 1988). In contrast, some reports emphasized the fact that the in vivo glycine-N- acetylating capacity may vary among individuals and that some patients are prone to have episodes of hyperglycinemia, resulting in encephalopathy during continuous glycine treatment (Duran et al., 1979; De Sousa et al., 1986). Subsequently, supplementation of 150–300 mg/glycine per kg body weight per day is the recommended dosage for IVA patients, but monitoring of plasma glycine levels (aim at levels of 200–400 μM) must be carried out to prevent unwanted side effects of the treatment (Wappner and Gibson, 2006).

L-carnitine is an essential cofactor in fatty acid oxidation where it acts as a carrier of acyl groups to transport fatty acids across the mitochondrial inner membrane and also functions as a modulator of the acyl-CoA/CoA ratio (Bremer, 1983). Because carnitine plays a vital role in normal CoA-homeostasis within the mitochondria, it is involved in the treatment of various organic acidemias. Its benefits in IVA include the prevention of systemic carnitine depletion as well as the formation of isovalerylcarnitine, which is safely excreted in the urine. No reports of secondary clinical complications in the administration of L-carnitine could be found (Stanley et al., 1983; Roe et al., 1984). A dose of 100 mg/kg per day has now been recommended to avoid depletion of free carnitine and to maximize isovalerylcarnitine formation (Wappner and Gibson, 2006).

The use of glycine and L-carnitine in combination improved the biochemical profile of IVA patients, for example, by reducing ketosis and acidosis during episodes of metabolic decompensation. The pros and cons of separate and combined use of supplementation have been widely debated. Various studies have been conducted to determine the appropriate dose of L-carnitine and glycine needed for effective treatment of IVA patients (Berry et al., 1988; De Sousa et al., 1986; Mayatepek et al., 1991; Van Hove et al., 1994). The conclusion in the majority of these studies was that an increase in L-carnitine dosage initially enhanced N-isovalerylglycine formation, which declined over a 24-hour period. More recent studies concluded that L-carnitine in combination with glycine results in the most appropriate long-term treatment of IVA patients (Itoh et al., 1996; Vockley and Ensenauer, 2006). The clinical presentations of the patients enrolled in these studies varied, which again emphasized the need of a personalized approach in L-carnitine and glycine treatment of individual patients. It is anticipated that

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the comprehensive investigation by the E-IMD consortium may shed light on the use of supplementation and its involvement in the phenotypical presentation of IVA.

4.3 Nutritional deficiencies

The restricted protein intake and high synthetic carbohydrate intake implies a diet with vegetarian-like properties. Dedicated dietary formulas (such as leucine-free amino acid mixtures) are available for IVA patients, but their use is limited wherever health economics restrict the use of expensive dietary substituents or supplements. The alternative, a restricted protein diet, results in amino acid deficiencies and a reduced intake of vitamins, minerals and polyunsaturated fatty acids (PUFAs) (Giovannini et al., 1995). Loots et al. (2007) also indicated that IVA patients may suffer from amino acid depletion due to acylation of these essential biomolecules. They proposed that the optimum benefits for the patients are a strict leucine-free diet with additional essential amino acids (including glycine) and added intake of L-carnitine. Patients with organic acidemias, including IVA, may develop antioxidant depletion and reduced intracellular glutathione. Therefore it was recommended that organic acidemia patients should receive antioxidant supplementation in their routine management (Atkuria et al., 2009). Further investigations of patients with protein-related deficiencies – for example , urea cycle deficiencies, maple syrup urine disease (MSUD), methylmalonic acidemia, and other amino acid-related disorders – demonstrated deficiencies in omega-6 and omega-3 polyunsaturated fatty acids and their related biological products, because of the restricted dietary intake of the fatty acids and their precursors in the form of linoleic acid and alpha-linolenic acid (Vlaardingerbroek et al., 2006, Fekete and Decsi, 2010).

4.4 Administration of pharmacological agents to alleviate secondary biochemical abnormalities

Various supplementation options have recently been proposed to alleviate secondary pathophysiological effects of IVA. The use of N-carbamylglutamate to activate carbamyl phosphate synthetase 1 and thereby reduce elevated ammonia levels was successfully demonstrated by Kasapkara et al. (2011). Furthermore, the administration of has been shown to act as a "neuroprotector" in various neurological diseases (Matthews et al., 1998). It has recently been shown that creatine prevents Na+,K+-ATPase inhibition caused by isovaleric acid resulting in normal neurological function in an animal model. Consequently, creatine may be beneficial as a "neuroprotector" and considered as a future therapeutic agent for IVA (Ribeiro et al., 2009). The optimal dosage of N- carbamylglutamate and creatine to treat pathophysiological effects and the development

20 General introduction and outline of thesis

of chaperones to improve IVD activity is still under investigation and will probably be part of personalized medicine of individual patients.

The biochemical stabilization of enzymes through the use of pharmaceutical chaperones is another promising treatment option for IEMs. These chaperones may restore the native configuration of IVD, thereby increasing their residual activity. Their use in organic acidemias such as IVA is currently being investigated (Gregersen, 2006). Finally, IVA patients affected by IVD gene mutations that give rise to a stop codon and hence a truncated enzyme protein may benefit in the near future from drugs which may result in an enhanced read-through. Currently a trial in this area on a Europe-wide basis is being carried out in a group of patients with methylmalonic aciduria (Sánchez-Alcudia et al., 2012).

5 Pathophysiological complications of IVA

Isovaleric acidemia is caused by the dysfunctioning of isovaleryl-CoA dehydrogenase. Various secondary pathophysiological events result from this primary lesion and have become characteristic of the disorder. Lactic acidosis, ketosis, hyperammonemia and immunological abnormalities are typical manifestations of the acute presentation of the disease. Most of these symptoms can be managed therapeutically via different treatment options, which in general limit the number as well as the severity of the episodes of metabolic decompensation (Vockley et al., 2012). Secondary hyperammonemia, which is a prominent biochemical feature of IVA, is also observed in other organic acidemias that may be accompanied by neurological dysfunction such as propionic acidemia and methylmalonic acidemia.

This biochemical aberration is presumed to be due to the inhibition of N-acetylglutamate synthase (NAGS) by accumulating isovaleryl-CoA (or other short-chain acyl-CoAs) and/or intracellular depletion of acetyl-CoA, which subsequently leads to reduced N- acetylglutamate synthesis and consequent impairment of the urea cycle (Coude et al., 1979; Stewart and Walser, 1980; Lehnert, 1981b). NAGS is responsible for the production of N-acetylglutamate (NAG), which activates the initial rate-limiting enzyme, carbamyl phosphate synthetase 1 (CPS), of the urea cycle. Prolonged secondary hyperammonemia can lead to irreversible neurological damage and account for some of the pathogenic occurrences in IVA (Cagnon and Braissant, 2007). Patients with a urea cycle defect usually have markedly increased levels of the amino acid , which supposedly contributes to the neurometabolic damage. Excessive formation of glutamine in IVA (and other classical organic acidemias) does not take place, probably as a consequence of a disturbed Krebs cycle that limits the availability of 2- ketoglutarate, the original precursor of glutamine (Meijer et al., 1990). Nevertheless, the

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prevention of hyperammonemia in IVA and other organic acidemias is of prime importance to improve the quality of life of affected patients.

The outcome of IVA patients who were diagnosed following an episode of metabolic decompensation is not entirely satisfactory. It is expected that the implication of large- scale newborn screening will improve this aspect of the disease. However, it is still too early to predict that subsequent episodes following the NBS-diagnosis will cease to occur, and many efforts will be needed to find the best personal treatment regimen for every patient.

6 Metabolomics: A multidisciplinary data-driven strategy to obtain information contained within a diverse biological system

All aspects of IVA discussed thus far dealt with well-established approaches used to investigate and characterize inborn errors of metabolism. Metabolomics, the third member of the initial "-omics" triplet (consisting of genomics and proteomics apart from metabolomics), became recognized as an important emerging field of scientific research about a decade ago (Goodacre, 2005; Goodacre, 2010). Wikoff et al. (2007) provided the first proof-of-concept that metabolomics could expand the range of metabolites associated with inborn errors of metabolism as shown for propionic acidemia (PA) and methylmalonic acidemia (MMA), and concluded that metabolomics might be useful in the diagnosis and evaluation of patients suffering from these diseases. It was therefore logical to include a metabolomics approach as part of an integrated investigation of South African cases of IVA. It is beyond the purpose of this thesis to present an in-depth review of metabolomics technology as it has already been well covered in several monographs (Lindon et al., 2007; Weckwerth, 2007; Griffith, 2008) and recent reviews (D'Alessandro et al., 2012; Beger and Colatsky 2012; Zhang et al., 2012; Bartel et al., 2013; Brennan, 2013). The focus here will be on the topicality of a metabolomics approach to investigate inborn errors of metabolism and its potential to contribute to the further development of predictive laboratory medicine.

6.1 A metabolomics approach in the study of IEMs

Clinical chemists anticipate that the application of metabolomics will improve researchers' and clinicians' knowledge of inborn errors of metabolism and their treatment (McCabe, 2010). The main purpose of metabolomics is to identify as many metabolites as possible that are altered due to a known perturbation within the biological system of interest, and which consequently leads to a greater understanding of the biochemical and clinical relevance of the metabolites in the altered state. The importance of a standardized metabolomic protocol has been emphasized by various

22 General introduction and outline of thesis

researchers in the field. This approach consists of 1) the careful selection of defined groups (e.g. patients versus controls); 2) the type of biological samples to be used (e.g. blood, urine, sputum or tissue); 3) the choice of methods, which include sample preparation and the selection of instrumentation – such as nuclear magnetic resonance spectrometry and hyphenated mass spectrometry (MS) – for data acquisition; 4) the procedures used for data processing via deconvolution and statistical analyses – for example, univariate analyses or multivariate analyses such as principal component analysis and partial least-squares-discriminant analysis (PLS-DA); and 5) the interpretation of the information derived from the data analysis in relation to the biological system being investigated (Goodacre et al., 2007).

This protocol includes several aspects which are familiar to biochemists involved in the study of IEMs. Those who study these disorders are normally comfortable with most of the steps in the standardized metabolomics protocol and are used to investigate disease in relation to genotype-phenotype correlations and the consequent clinical manifestations (McCabe, 2010). However, the analyses required to reveal the information in complex data sets are not typically part of traditional research in IEMs (Goodacre, 2005). The need for timely identification of novel and treatable metabolic disorders, however, has fast-tracked the development of sensitive acquisition and identification of biomolecules in specimens of medical interest. This became the core of NBS, as discussed above, and the use of tandem MS was designed for high-throughput application in the screening for various IEMs. The application of MS as a powerful tool for diagnostic purposes inadvertently laid the foundation for "targeted metabolomics" and the beginning of unique metabolic profiling for various types of deviations from normality related to age, gender and disease in different life forms (McCabe, 2010).

Already more than a century ago, Sir Archibald Garrod, a pioneer of IEM studies, postulated that individual IEMs were due to one faulty gene resulting in the production of a defective enzyme and consequently a specific metabolic disorder – in his case it was the description of alcaptonuria. Recent findings describe variations within the clinical and pathophysiological presentation of metabolic disorders and suggest multifactorial involvement in many IEMs, including IVA (see above). The comprehensive study of healthy subjects, MMA and PA, revealed significant differences in the presence and absence of metabolites among the three groups (Wikoff et al., 2007). The untargeted metabolomics approach established proof-of-concept and the potential benefits of metabolomics in the diagnosis of metabolic disorders, providing information on phenotypical diversity and the clinical monitoring of patients. The diagnosis of classical MMA and PA via biomolecular analyses is not difficult in the field of IEMs, but diagnosis of complex metabolic disorders, without invasive techniques and extensive genetic screening, is a great challenge to the clinical biochemist. The example of deficiencies in the respiratory chain defects (RCDs) will be discussed below to illustrate this point.

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Over 100 different RCDs – with an incidence of 1:5 000 to 1:10 000 among newborns – may manifest at any age (see reviews by Smeitink et al., 2006 and Haas et al., 2008). The multi-systemic involvement of different organs and non-specific symptoms limit the differential diagnosis and understanding of the pathophysiology involved. Inadequate knowledge of the consequences of the defects within the body results in poor therapeutic intervention and unpredictable quality of life for the sufferers (Suomalainen, 2011). These factors inspired researchers to search for the metabolic fingerprint for RCDs. Suomalainen (2011) recommended several approaches, including metabolomics, for the identification of suitable biomarkers. Reinecke et al. (2012) constructed a comprehensive metabolite profile of the carbohydrates, amino acids and fatty acids involved in the catabolism of 39 RCD patients, which emphasized the biochemical complexity of these disorders. Their study proposed that the identification of a biosignature via chemical pattern recognition, rather than one or a few specific biomarkers, holds the key to a potential non-invasive screening for RCDs. Smuts et al. (2012) investigated subsections of the metabolome of selected RCD patients using a differential analytical protocol, which included GC-MS, ESI-MS and NMR. They also focused on one subset of RCDs and consequently improved on the selection of certain patients. Specific medical procedures and treatment with the aid of a metabolomics- driven approach were also derived. The value of metabolomics to identify the biosignatures in RCDs in terms of metabolic markers was a further illustration of the proof-of-concept through this study of a complex set of IEMs (Smuts et al., 2012), which concurs with the view that metabolomics investigations of multifactorial diseases should focus on studying complex and dynamic biomarker patterns rather than on single biomarkers (Van der Greef and Smilde, 2005).

This brief overview of the first pioneering metabolomics studies of IEMs indicates its value for a further understanding of these diseases and may eventually contribute to the identification of biochemical mechanisms involved in these disorders, as well as their corresponding pathophysiological implications. These features are not yet well understood for autosomal recessive disorders, and subsections of this thesis will address some of these features through the metabolomics investigation of South African cases of IVA.

6.2 Metabolomics and laboratory medicine

The potential benefits of metabolomics are progressively being recognized as also affecting laboratory medicine which is defined as that part of medicine in which specimens of tissue, fluid or other body substances are examined outside of the patient's body (D’Alessandro et al.; 2012). This can be related to three innovative applications of metabolomics: 1) the generation of new knowledge and an increased

24 General introduction and outline of thesis

understanding of metabolism and its regulation; 2) improvement of important areas in contemporary laboratory medicine, such as patient risk assessment, prediction of disease development and the monitoring of treatment strategies; and 3) the introduction of personalized medicine based on individualized phenotyping.

6.2.1 New knowledge

The novel and useful features of metabolomics have been identified in various biochemical and clinical conditions as described above. The investigation and detection of biomarkers by metabolic profiling within the metabolome have been pursued with limited biological information, as well as with known biology, on the basis of targeted and untargeted analyses. Both approaches can result in the comprehensive identification of new biomarkers with the potential for the diagnosis of disease, and for evaluating its severity and treatment (Mamas et al., 2011). Metabolomics is thus expected to play a key role in 1) detecting patterns of metabolites that may be unexpected but important in explaining disorders, and reveal mechanisms of disease and consequently the phenotypes within various subject groups; 2) predicting the effects of drugs, their efficacy or toxicity and therefore how to customize treatment protocols; and 3) non-invasive to minimal invasive investigations of biological abnormalities through the study of biological fluids and which have already brought benefits in several fields, for example, paediatrics (Baraldi et al., 2009). At the Metabomeeting held in Manchester, UK, in 2012, Reinke and Broadhurst (2012) acknowledged that metabolomics may be used as a basis for various hypotheses to broaden scientific knowledge on several levels. Metabolomics may also reveal the importance of regulation of the metabolic steps within a biological system that are vital for cell organization and functionality (Vangala and Tonelli, 2007).

Furthermore, metabolomics offers various benefits which improve on genomics and proteomics in several ways. For example: 1) there are estimated to be ~3 000 metabolites that exist to be examined in metabolomics studies compared with the much larger number of variables present in other "-omics" data sets; 2) its likely application in clinical chemistry appears to be imminent due to progress in non-invasive sample collection; 3) the technology may be of use in animal models in which biomarkers of clinical relevance to a particular disease or toxicology are evaluated; and 4) the metabolic state of a biological system is reflected in changes in metabolite levels, and so mirrors alterations in the phenotype with the onset, for example, of disease, which is determined by the genotype in combination with external factors. Thus, metabolomics facilitates the elucidation of the clinical pathology of disease as in the case of IEMs, which results in the characterization of unique phenotypes. Timely and targeted treatment and medical intervention can proceed with the help of a customized

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metabolomics approach (Vangala and Tonelli, 2007; Shlomi et al., 2009). This was highlighted by Wikoff et al. (2007) and Reinecke et al. (2012), who reported that diverse phenotypes exist within simple as well as complex IEMs (discussed above). This phenomenon is still poorly understood, but the evidence from metabolomics is already contributing to a rethinking of the traditional concept of one phenotype, one genotype.

Future work should aim at extending the current metabolomics models to recreate a comprehensive metabolic network with leading researchers for example the Edinburgh Human Metabolic Network (Ma et al., 2007) – and subsequently identify all primary and secondary pathways of relevance to human health and disease. Predictive metabolic pathways and the corresponding biomarkers should reveal the real biological activity of activation or inhibition of selected pathways. Evidently, the need for complex computational methods for solving such an integrated metabolic network, which may further implicate alterations on the systems level (including genomic, proteonomic and metabolomic information) will most probably gain importance in the future (Van der Greef and Smilde, 2005; Shlomi et al., 2009).

6.2.2 Prediction of disease development and monitoring of treatment

Whitfield et al. (2004) and Grieger et al. (2008) assessed the value of metabolomics and its clinical application and indicated its benefits to medicine. The current rapid development in metabolomics has made it possible to describe the "metabotype" in relation to the genotype of individual subjects. Intermediate phenotypes and disease aetiology can be continuously assessed biochemically and may provide details on the pathways potentially affected. Grieger et al. (2008) described this process as a "fundamental read-out of the physiological state of the human body". Genotype variation does not affect a single step in the metabolism of lipids, carbohydrates or amino acids, but plays a more intricate role in a cascade of the metabolic conversions and modifications that consequently affect the molecular mechanisms that underlie disease. Once these factors that are fundamental to health and disease are properly addressed, we may use the technology of metabolomics for drug development and nutritional intervention to tackle different clinical problems. This in turn may offer the prospect of further developments in predictive laboratory medicine (Fig. 4) (Grieger et al., 2008).

A metabolomics approach has led to several applications in the field of clinical diagnosis and pharmacological research. It can be employed in pre-clinical trials to ascertain biomarkers related to toxicity and efficacy of pharmacological agents, which can be evaluated subsequently and monitored in clinical trials. Biomarkers are useful in locating a point(s) in a pathway which might be the cause or effect of a particular disease or abnormality. This knowledge may be useful in the development of a drug to correct or

26 General introduction and outline of thesis

treat this cause or effect and also lead to the identification of novel targets associated with drug intervention (Nörstrom and Lewensohn, 2010).

The broader and exciting aspect of a metabolomics approach, in the post-genomic era, is that it can produce not only metabolic profiles but also intricate metabolic maps which can be used in different fields of medicine, including nutrition, in health and disease (Fig. 4) (Watkins et al., 2001). The complex interaction between exogenous and endogenous nutrients and vital metabolic processes can be examined with this approach, which may help in the construction of the "dietary biosignature" observed in the biofluids of individual subjects (German et al., 2004). Go et al. (2003) and Milner (2003) reported that chronic diseases can have both a dietary and a genetic component. Metabolomics has been further applied to establish the relevance of metabolic control in relation to disturbances (deficiencies or excesses) of dietary components. The value of metabolomics in relation to nutrition has been demonstrated in several investigations on nutritional substances, such as the metabolism of ethyl glucoside (Teague et al., 2004) and isoflavones (Solanky et al., 2003), which are present in some diets.

Fig 4: Illustration of the effect of treatment intervention after diagnosis of treatable IEMs with emphasis on the development of an individualized approach (indicated by the dashed oval), made possible by a metabolomics investigation. (This representation is based on that of Nörstrom and Lewensohn, 2010).

The comprehensive analysis of different classes of metabolites has also led to specialized metabolomics approaches that are useful in different aspects of medicine. For example, lipidomics, a subcategory of metabolomics that focuses on lipid metabolism, is used as a means to understand the genome (e.g. polymorphisms), as well as post-genetic effects induced by pathogens, drugs, nutrition and toxins. This field of research consists of the analysis of various lipid classes which are responsible for cellular structure and the functionality of complex signal transduction systems.

27 Chapter 1

Furthermore, lipids play a vital role as a source of energy in biological systems (German et al., 2007). Several lipidomics studies indicate that disease, nutritional status and drug applications have an influence on the functionality (genetically and biochemically) of peroxisomes and mitochondria and consequently lead to altered levels of several types of lipids, including polyunsaturated fatty acids, glycolipids, phospholipids and triacylglycerols (Whitfield et al., 2004).

6.2.3 Personalized medicine

The arrival of the "-omics" research applications has shown promise in the development of personalized basic health assessment, in the prevention of disease and of health care. Many researchers believe that these "-omics" technologies, including metabolomics, will effectively address today's shortcomings in the clinical support of patients. However, gaps exist between the discovery and implementation of new knowledge in daily medical practice, and consequently in the understanding of genetic and metabolic differences among individuals. The development of these innovative and efficient technologies has resulted in a paradigm shift from classical clinical disciplines – which are based on reliable diagnostic information – to a broader scope of investigation, which consists of the assembly of biological maps (intricate metabolic pathways) which will ultimately result in the novel biomarker identification in health and disease (Plebani and Lippi, 2013).

The dynamic state of the metabolome, in contrast to the genome, has resulted in the recognition of common genotypes with multiple phenotypes due to external factors of unknown origin (Baraldi et al., 2009). Metabolomics can therefore contribute further to the evaluation of past and future perspectives and consequences of the metabolic status of the metabolome of all living organisms. Aspects of the relationship between metabolomics and personalized medicine will thus be highlighted in the thesis.

Ultimately, the insight and impact of contemporary metabolomics testify to the pioneering vision of Archibald Garrod on individuality in human health and in IEMs in particular (Garrod, 1909):

"To our chemical individualities are due our chemical merits as well as our chemical shortcomings, and it is very nearly true to say that the factors which confer upon us our predispositions to, or our immunities from, the various mishaps which are spoken of as disease, are inherent in our very structures, and even in the molecular groupings which confer upon us our individualities, and which went to the making of the chromosomes from which we sprang."

28 General introduction and outline of thesis

6.3 Challenges and opportunities in metabolomics investigations of IEMs

It should be noted that a metabolomics investigation of an IEM will present with several challenges as well as opportunities that are common to metabolomics investigations in general, but are also unique to investigations of these diseases. Three such challenges and opportunities are highlighted in this section, as they are of particular relevance to the present investigation of IVA.

In general, metabolomics is a field of research which, in its most simplified form, is linked to the traditional disciplines of biology, chemistry and statistics in which their respective experts actively collaborate to explore metabolic processes in biological systems (Fig. 7). An example is the interactions between, or the consequences of, stimuli (such as chemicals or disease) on metabolism as reflected by the resulting metabolite profiles.

Fig 5: A model to illustrate the transdisciplinary aspect of metabolomics research (reproduced with permission after personal communication with M. van Reenen).

Fig. 5 shows that the research questions addressed in metabolomics are predominantly formed from a biological or clinical point of view. The response to such questions often requires an untargeted metabolomics approach. For untargeted metabolomics investigations, inputs from two very different fields of specialization are essential: highly

29 Chapter 1

sophisticated analytical chemistry and equally highly specialized, statistically based bioinformatics and related information technologies. This is clearly emphasized in the definition used by Harrigan et al. (2005):

"Metabolomics involves the acquisition of a metabolome dataset of sufficient chromatographic and spectral richness and resolution for multivariate statistical analysis and for metabolite identification and quantification."

Katajamaa and Oresic (2007) more recently emphasized the biological aspect, defining metabolomics as

"a discipline dedicated to the global study of metabolites, their dynamics, composition, interactions, and responses to interventions or to changes in their environment, in cells, tissues, and biofluids."

As a consequence, information emerging from metabolomics is solution-driven and can only be achieved through transdisciplinary collaboration. This viewpoint opens the possibility of defining various challenges and opportunities to most metabolomics investigations, and specifically so in the field of IEMs.

• Some minimum requirements for experimental design and reporting of data and findings have been defined for metabolomics investigations (Goodacre et al ., 2007). In this regard, sample collection and preparation present with unique challenges not to produce biases due to the selection of experimental groups or to the choice of the metabolome to be analyzed (Dunn and Ellis, 2005). This is a particular challenge in metabolomics investigations of IEMs, given the limited number of cases which are typically available for these studies, as well as the special requirements to obtain reliable controls for these investigations (Barshop, 2004). Although the IVA patient group available for the investigation reported in this thesis was relatively small, it was nevertheless seen as an opportunity to embark on a metabolomics approach to understand this IEM further. • Transdisciplinary research generates exciting opportunities: metabolomics investigations not only present with complex challenges to the biological and clinical specialists in such studies, but also to the analytical chemists and statisticians. However, these challenges also open up opportunities to these experts for further new supporting approaches to generate and analyse the experimental data. This is clearly illustrated by the novel approaches to develop original models to assess analytical aspects such as repeatability in the generation of metabolomics data (Van Batenburg et al ., 2011) or the statistical analysis of metabolomics data (Smilde et al ., 2005). Although these challenges are beyond the expertise of the biologist or clinician, it can be anticipated that an investigation as presented here could contribute to such novel developments.

30 General introduction and outline of thesis

• Application: Metabolomics has recently been hailed as opening a new frontier in paediatric research, which inevitably includes the clinical assessment of infants suffering from an IEM (Carraro et al ., 2009). Such potential applications that could emanate from knowledge of metabolomics are generally referred to as examples of translational research. Such research has received focus with regard to research activities in medicine and seems to be gaining support on the evidence of the funding it generates (Woolf, 2008). The aim of translational research implies bringing "research into practice" (Woolf, 2008). The "bench-to-bedside" (Woolf, 2008) approach does, however, differ with regard to the composition of the research team. Translational research tends to remain multidisciplinary, whereas fields such as metabolomics require transdisciplinary teams. Although translational research is beyond the scope of the present investigation, the new knowledge gained through the metabolomics study of IVA holds the promise of being applied to the benefit of patients suffering from this disease.

7 Outline of this thesis

The main goal of this thesis was to develop an integrated approach to study IVA including genetic, enzymatic and metabolic assessments. This study therefore expanded on these objectives and included metabolomics as part of the integrated approach to improve our understanding of IVA. It was envisaged that this study would contribute to a change in the paradigm that metabolic defects should be considered as diverse, multifactorial diseases rather than deficiencies of the one enzyme, one phenotype kind. Fig. 8 outlines the integrated approach towards the investigation of IVA and indicates how information was obtained to develop predictive laboratory medicine for IVA that may be applicable to all treatable IEMs.

31 Chapter 1

Figure 6: A schematic representation of the study design and outcome of the integrated approach to predictive laboratory medicine.

In Chapter 2 IVA patients from South Africa were characterized via clinical and biomolecule profiling, IVD gene sequencing and determining the IVD enzyme activity with a novel approach. A single homozygous mutation (p.G123R) in all patients was identified which was found to result in an inactive protein, with no detectable residual IVD activity. The presence of a diverse phenotype within this genetically homogeneous group was confirmed, which may be attributed to differential treatment regimes, delayed diagnoses of patients and even epigenetic and polygenetic factors.

Chapters 3 and 4 discuss the use of metabolomics as an investigative tool in a homogeneous IVA population. Chapter 3 consists of the development of the CONCA (concurrent class analysis) model, a novel multivariate dimension-reducing technique in which biomarker differences between untreated IVA patients, treated IVA patients and control subjects were identified. Chapter 4 is an untargeted metabolomics investigation in which untreated IVA patients, treated IVA patients, obligatory heterozygotes, and children and adult control subjects, were compared with various multivariate statistical applications including CONCA, principal component analysis (PCA) and partial least- squares-discriminant analysis (PLS-DA) in order to determine variables important in discrimination (VIDs). Three univariate methods (ES, t-tests and Mann-Whitney tests) were also included to assess the significance of variation of components of the respective metabolite profiles in relation to the perturbation being considered. Major and minor metabolites associated with IVA as well as with secondary conditions of IVA, such as ketosis, could be clearly identified. Various biomarkers as a result of treatment of IVA were also identified, which established that the use of personalized therapeutic

32 General introduction and outline of thesis

intervention is needed for individual patients. The obligatory carriers could also be separated from adult control subjects due to minor excretion of IVA-related metabolites.

Organic acidemias have various secondary biochemical consequences, for example, lactic acidosis, ketosis, involvement of the liver and hyperammonemia. In Chapter 5 we report the occurrence of secondary hyperammonemia in IVA as well as other organic acidemias, where short-chain and short-branched chain acyl-CoAs accumulate. The urea cycle facilitates the elimination of NH3 via the formation of urea, a non-toxic metabolite, which is excreted in urine by the kidneys. The initial steps of this cycle are important in the primary regulation of this pathway. The formation of N-acetylglutamate via N-acetylglutamate synthase (NAGS) is needed for the activation of carbamyl- phosphate synthetase (the first and rate-limiting step of the urea cycle). We established that various short-chain acyl-CoAs act as inhibitors and/or substrates of purified NAGS, in vitro . The latter explains, and also raises the question of the involvement of these cumulative CoA esters in the occurrence of secondary hyperammonemia in different organic acidemias. An additional outcome was the development of a NAGS enzyme assay described in Chapter 6 . This validated assay was used to measure NAGS activity in mouse liver samples. NAGS knockout mouse liver samples showed no activity, consistent with NAGS deficiency.

The metabolomics investigation led to the identification of diet-related metabolites. These findings motivated the examination of some aspects of the nutrient status in treated IVA patients. Therapeutic intervention and the dietary regimen of IVA and of other amino acid-related organic acidemias consist primarily of a low protein, high carbohydrate diet. Various secondary effects of such a diet have been described in the literature for patients with amino acid-related disorders. Deficiencies in essential fatty acids, vitamin B12 and other vitamins and minerals have been observed (Robinson et al., 2000; Vlaardingerbroek et al., 2006; Fekete and Decsi, 2010). Chapter 7 addresses underlying of nutritional insufficiency in particular deficiencies in functional vitamin B12 and polyunsaturated fatty acids, in treated IVA patients. This chapter emphasizes the fact that additional monitoring is required in these patients where a protein-restricted diet is applied.

In the final chapter ( Chapter 8 ), a comprehensive discussion of the findings presented in this thesis is addressed, including proposals for further detailed investigations on IVA.

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